The Petroleum System Blog

Making the best use of petroleum geochemistry in Top Down Petroleum Systems Analysis (TDPSA)

2024-07-15T14:18:00.000-07:00

By Andrew Murray

"Top Down" petroleum systems analysis (TDPSA) includes petroleum geochemistry and, specifically, the process known as “geochemical inversion”. Given even a small fluid sample, we can extract information on:

The organic matter type and depositional environment of the source rock
In some cases (and only in broad terms) the age of the source rock
Whether more than one source rock and/or kitchen area has contributed
What alteration processes have affected the fluid in or on the way to the trap

Other applications might include:

Estimating the average or integrated thermal “maturity" of the source rock at the time of expulsion
Identifying separate (distinct in time) fill events

There are problems, however, both conceptually and in practice, with the last two: See here:

http://petroleumsystem.blogspot.com/2014/10/measuring-maturity-of-hydrocarbon-fluid.html

http://petroleumsystem.blogspot.com/2020/12/does-complex-geochemistry-of-oil-mean.html

The most valuable information obtained from fluid geochemistry is the organic matter type/depositional environment of the source rock. This is the strongest determinant of yield and the gas to liquids ratio (GLR). We can measure the GLR of a fluid sample (if we have enough of it) but that doesn’t necessarily tell us the “system” GLR, i.e. what came out of the source rocks in the kitchen. We need that information to assess the chance of finding oil, gas and also as an input to the probabilistic prediction of migration. Does one need to be an expert geochemist to extract this information? Well, it helps – but there is a lot a non-expert can do, as we shall see. Firstly, though, it is necessary to recognise that a few things have hampered the integration of petroleum geochemistry into TDPSA:

A disconnect that commonly happens somewhere between the PVT lab and the geochemistry lab, leading to loss of spatial context and relation to fluid bulk properties such as GOR, API, saturation pressure etc: Most geochemical databases and many reports do not align PVT and geochemistry samples
Traditional analytical methods focusing on the trace, higher molecular weight biomarkers in the C₁₂+ fraction, leading to an intrinsic bias against the origin of the gas fraction when more than one source rock contributes (Murray and Peters, 2021). While analyses of the gases (C₁- C₅) and gasoline range (C₆ – C₉) hydrocarbons are often included, there is a fundamental trade-off: low molecular weight hydrocarbons are present in high concentration and thus likely representative of the bulk fluid, but offer low source discrimination. High molecular weight biomarkers are present in low (and variable) concentration but they provide more discrimination. This trade-off is summarised in the figure below.
Lack of quantitative data and use of compound ratios rather than absolute amounts in interpretation. This causes problems when more than one source rock/kitchen is contributing and/or when biodegradation, phase separation or migration contamination occur. All of these things can hide or distort the contribution of one source over another.
Interpretations placing too much (or too little) emphasis on individual geochemical features, without regard to their relative discriminating power.

In recent years, analytical methodology has improved to the point where it is no longer necessary to separate a crude oil or condensate into chemical classes (Saturates, Aromatics, Resins, Asphaltenes) before analysis by gas chromatography (GC) or gas-chromatography-mass-spectrometry (GCMS). This means the whole oil (C₆+) can be analysed in a single run. It also facilitates quantitative analysis which, when combined with the GOR, allows true whole reservoir-fluid concentrations to be calculated. GeoMark Research have always included concentrations in the C₁₂+ liquids in their standard protocols and they kindly allowed Ken Peters and I to use the data in their global database (https://www.geomarkresearch.com/rfdbase) to assess the impact of fluid mixing on geochemical interpretations. More recently, they have instituted a combined high-resolution GC (HRGC) and triple quadrupole GCMS (QQQ) protocol to provide quantitative data on whole oil samples for a very wide range of target compounds. Even more recently they have improved the GC part of this analysis, making it "Ultra High Resolution GC" (UHRGC) with up to 190 individual compounds identified:

The GeoMark database (also helps us to assess the relative discriminating power of different geochemical parameters, as regards source rock type. (Some years ago, from 10,000+ oils in the library, I made a subset of 2843 oils/condensates which met the following criteria (a) not biodegraded (b) not very high or low maturity (c) not contaminated (d) have a complete data set available (e) are from a well-understood petroleum systems with high confidence about the identity of the source rock. GeoMark use source rock type descriptors such as “Marine Carbonate”, “Distal Marine Shale”, Lacustrine Freshwater for algal OM type sources and “Paralic”, Coal-resinitic”, Paralic Deltaic” for land plant type. These correspond to the Pepper and Corvi (1995) organofacies, A, B, C and D/E respectively (there are no “F” oils because, in the standard formulation, an F type source rock expels no oil). The distribution for each source type is shown below.

The figures below show statistics (mean, +/- 1 SD and range) for five common geochemical source parameters; pristane/phytane ratio, % sulphur, the C₂₉ to C₃₀ regular hopane ratio, the % C₂₇ steranes among the C₂₇-C₂₈-C₂₉ total and the ratio of C₂₆ to C₂₅ tricyclic terpanes. It is apparent that some of these parameters, if used in isolation, offer only weak discrimination. This is why all good interpretations use multiple parameters visualised with cross-plots or via multi-parametric statistics.

These are only five of the numerous geochemical source parameters which geochemists can use and which are described in the Peters, Moldowan and Clifford text book “The Biomarker Guide” (https://www.amazon.com.au/Biomarker-Guide-K-Peters/dp/0521039983)

How can a non-expert know which parameter(s) to use? The table below gives the median values for each source rock type and ranks the parameters from most (1) to least (20) discriminating power:

We start with the “All” column and the first parameter (Pr/Ph) and find the source type with the median value closest to that of the sample in question. Then we do the same for the next parameter down the list (% sulphur) and so on until parameter six. By then, the source type should be clear but, if it’s not, we can continue down or look at the “B vs. C” column and note that the strongest parameter for distinguishing between a “B” and “C” type source rock is the C26/C25 tricyclic terpane ratio. The second strongest discriminator in that column is the ratio of total steranes/terpanes (some reports use steranes/hopanes). The same process applies if we are trying to choose between “A” and “B” or between “C” and “D/E” types. Note that values are given in the table for median carbon isotope ratios but these are not ranked for discriminating power. The parameter notation is based on the standard GeoMark summary sheets. If data from other laboratories are used, they will generally correspond and in most cases differences in analysis protocols etc will not make much difference to the process. Nevertheless, it is obviously better, if possible, to have your sample analysed by GeoMark. For those who subscribe to the OILS library, that will also allow a search for geochemical analogs, which can be illuminating. This is one of the benefits of subscribing to the GeoMark OILS library: it provides the perspective that is often absent from narrower regional studies but is essential for solid interpretations.

Of course, nature is a continuum and source rocks from transitional environments, as well as oils which are mixtures, may emerge from this process as “B/D/E” or “C/D/E” etc. The latter is common for deltaic petroleum systems where lacustrine and fluvio-deltaic source rocks occur in association, the Pearl River Mouth Basin in China being a good example.

The focus here has been on the typical parameters used by petroleum geochemists. However, the process should not be separated from geological and engineering data: If an oil types geochemically to a “C” type source rock but is a single-phase fluid with a GLR above 2000 scf/bbl it’s likely there is a separate source of gas. That might be a D/E (or F) source rock, biogenic gas, residual liquids cracking in the source rock or in-reservoir oil cracking. Gas geochemistry then comes into play. We find that the number and type of distinct source families can often be determined using just four parameters from the PVT report: GLR, API of the liquids, saturation pressure, whole reservoir fluid gas wetness - and one geochemical parameter: good old pristane/phytane. .

References cited:

Murray A.P and Peters K.E. (2021) Quantifying multiple source rock contributions to petroleum fluids: Bias in using compound ratios and neglecting the gas fraction: AAPG Bulletin, v. 105, no. 8 (August 2021), pp. 1661–1678

Pepper A.S. and Corvi P.J. (1995) Simple kinetic models of petroleum formation. Part I: Oil and gas generation from kerogen: Marine and Petroleum Geology, v. 12, no. 3, p. 291–319

Home Made Capillary Seal/Trap Experiment

2024-01-30T15:30:00.000-08:00

This is my first home made capillary seal experiment. The setup is a 1/2 in burette filled glass beads of different sizes. 4 mm diameter color less beads for reservoir, and 1.5 mm black beads for the seal. The blue beads (2 mm) are used to keep the small light black beads from falling down into the "reservoir" section and from being blown upwards by leaking air bubbles. Column is filled with water dyed with red food coloring. Air is injected slowly from bottom using a air bulb.

Figure 1. Setup of capillary experiment - burette tube filled with water colored red with food coloring, and different sized glass beads to represent reservoir, and seal facies (black).

An air column of about 3 cm is reached when addition air injected start to leak above the seal. The air water contact fluctuated by about up to ±0.5 cm depending on rate of air coming up due to variable injection rate. Injection may also be pushing on the water below in the closed system. However, the final air-water-contact did did not change for 3 hours after injection stopped.

Figure 2, final steady state trap - 3 hours after injection stopped.

Observations:

1) Capillary seal works even with a very porous rock - the sealing beads are 1.5 mm in diameter, and pore throats are probably at least 0.5 mm. I am guessing the porosity is 40% and peaceability is >100 Darcies. Yet, it is able to trap an finite air column below.

2) Leakage rate and injection rate are not quite same due to unsteady injection rate with the bulb. Injection may also be pushing the air-water-contact up in the closed system. This may have led to some fluctuation of the column height.

3) However, the column height did not change with time once injection stopped as expected of a capillary seal. The final column is about the average of the entire session. This disputes the idea that capillary seal capacity is reduced after initial leak.

4) Migrating air bubble/slugs often get trapped along the way (migration loss), and migration resumes when new air merges with trapped ones (Figure 2). As a result, the first bubble reached the trap after some volume has been injected. This is called "migration lag" (the time needed to fill these small accumulations / "saturate" the carrier). Continued migration requires continued supply.

Below is the video of one of the sessions. Sorry about the shaky video recording with my phone in one hand and the air bulb in the other.

I am doing this because I feel too many geologists think that seals are impermeable, and leaking means seal failure. Capillary seal mechanism is the physical interaction of interfacial tension and pore throat diameter, and has nothin to do with permeability! For a given pore throat size, a finite column is trapped, and additional gas (or oil) leaks to maintain the balance of buoyancy and capillary entry pressure of the seal. Simple as that!

This is my initial test experiment and I have ordered a precision pump to be able to inject very slowly and other materials to improve the setup. Stay tuned for my next post!

Does HC Generation Cause Over Pressure and Micro-Fracturing?

2023-12-29T21:15:00.000-08:00

First let’s estimate the maximum rate of oil generation in a geological setting. Lets take a very good source rock, with an S2 yield of 30 mg/gRock (5% TOC and 600 mg/g HI). That is 3% in weight of HC generation potential. Converting to volume, it becomes 6 to 10% of the rock volume, depending on HC density (eg. 0.06 to 0.1 m³ per cubic meter of rock). Lets take the high end, and assume a short oil window of 10 million years (most oil windows are longer), the rate of generation is 0.1m³ /10,000,000year, or 10^-8 m³/ year, or 0.01 cc per year. Since a typical liquid drop contains 0.05 cc, this means in one cubic meter of rock, the source rock generates one drop of oil every 5 years!

Now go on and think about how much pressure that generates, and whether this has any chance of making fractures in the source rock. Compare that one drop every 5 years rate with the 60 barrels per minute fluid injection rate we use to hydraulically frack the same rock.

Source rocks are quite "permeable" given geological time is 7 more more orders of magnitude longer than production time. Migration really does not require micro fractures. We have 10s of million years of time and a migration rate of only 0.0005 m/year is required to allow for the volume generated, creeping one pore space over a few years - at which rate, according to capillary number theory, it becomes a capillary dominated system, and viscosity (therefore permeability) does not even play a role.

Even during gas generation, the volume increase is still minimal. Typical good marine source rocks generate only 10 to 20% of its potential as gas, and less than 30% including cracking of oil retained in the source rock. In situ gas density is lower, and volume may be 3 to 5 times of that for oil. So we are still in the same rate range of less than 0.1 cc/year volume generated in 1 cubit meter of rock maximum.

I do not believe these rates can cause micro fracturing, and do not believe micro-fractures are necessary for primary migration. As HC generation happens almost uniformly everywhere in a mature source rock, fractures should be everywhere and in every mature source rock if they are required for expulsion/primary migration. We just don't see that, far from that.

Core photo of Upper (A) and Lower (B) Eagle ford formation (Emmanuel Martin, 2013). Of all the core photos of mature source rocks I have seen, and I have been looking hard, vast majority of them do not have fractures of any kind.

We do see micro-fractures in some source rocks, sometimes, most noticeable are those calcite filled "beef" like fractures are probably not caused by HC generation - but more likely formed during diagenesis before generation occurred. If they were caused by HC generation, they would be likely filled with bitumen/oil.

We also see fractures in some source rocks that are indeed filled with bitumen. These however could be formed in a way similar to large scale bitumen (gilsonite) dykes, and python like bitumen coming out of mine's roof in Italy, or growing out of California beaches. These are associated with very rich siliceous or limestone source rocks, such as the Monterey or the Tithonian in GoM, but at very low maturity. Instead of volume increase, which is minimal going from kerogen to bitumen, these are probably squeezed out of the source due to overburden no longer partially supported by solid kerogen.

Micro-fractures are not present, or not pervasive in most mature source rocks, especially clay rich lacustrine and marine source rocks. Occasionally we observe a few bitumen filled fractures but they tend to be a just a few, localized, not everywhere you would expect due to HC generation. Bitumen filled fractures are also not proof HC generation was the cause of the fractures. An simpler explanation of these is simply tectonic (especially shear) stress. Some "fractures" in lab pyrolysis experiments are typically along bedding and probably caused by the thermal expansion of the rock during the experiments - even if we ignore the 13 orders of magnitude in heating (generation) rate. Even at such high generation rate in the lab, Grohmann et al. (2021) shows that even 1 bar of vertical stress inhibits fracturing, as compared to the 100s of bars in geological conditions.

References:

R. Lenormand, E. Touboul and C. Zarcone, 1988, Numerical models and experiments on immiscible displacements in porous media, Journal of Fluid Mechanics 189(-1):165 - 187

S. Grohmann et al. Hyrous Pyrolysis of Source Rock Plugs: Geochemical and Visual Investigations and Implications for Primary Migration, 2021, IMOG conference paper.

Does Over-Pressure Affect Seal Capacities ?

2023-12-29T15:20:00.000-08:00

This may be the most controversial one I have ever posted. In this post I would like to challenge the widely accepted theory that over-pressure causes hydraulic fracturing in the seals and thus seal failure. I myself have taken this concept for granted during my entire career and have used it for basin modeling and petroleum system analysis for over 30 years.

The figure below shows the reservoir pressure and HC columns in the HPHT area of the central graben in the North Sea. It is one of the most over pressured basins in the world, with over-pressures as high as 9000 psi above hydrostatic. First, there seems no correlation between pressure and the column heights. Some very large gas columns exist in the very over-pressured deep section. Pressures at top of some of the large gas columns exceed the regional LOP gradient and are very close to lithostatic!

Figure 1. Pressure and HC column data from the HPHT area of Central Graben, North Sea. Modified from Nygaard et al., 2020. Some of the reservoir pressures at top of gas column are above the minimum leak off pressure trend, and some approaches the 1 psi/ft (typical lithostatic) line.

Many authors have mentioned hydraulic fracturing due to over-pressure may have caused some traps to have reduced columns, either not filled to spill, or have indications of a larger paleo-column, and some dry hole examples. But such observations are common place in not so over pressured systems as well, and there can by many reasons not unique to over pressured systems.

I have added the two dashed blue lines that connect several fields in what seems to be the centroid effects on several connected structures in a large fault block or compartment. This could explain the relatively lower pressure and large columns in the downdip parts of each centroid block. The centroid pressure transfer creates a condition that the seal has a higher pressure than the reservoir below. Several exceptionally large (>1000 m) columns in several basins can be attributed to centroid effects.

Figure 2. Central North Sea aquafer pressure (hydrocarbon column pressures are corrected to water leg pressures).Central North Sea HPHT Pressure Cell Study, by Zimmer and Farris, 2021, Oil & Gas Authority

The second part of my challenge has to do with rates again. We can fracture the rock through leak off tests (LOT), or hydraulic fracking in unconventional plays. In figure 2, which include only water leg pressures, we see many cases of reservoirs pressures close to or at lithostatic pressure (1 psi/ft) and above the regional LOT fracture curve.

In a LOT, fluid is pumped into the well bore at a typically 0.5 barrels/min and fractures initiate when pressure exceeds the rocks tensile strength in the lateral direction (σ3). The rate of pressure increase is at about 10 psi/min. In comparison, the pressure increase in the most rapidly buried basins is on the order of 0.01 psi/year (take the nearly 10,000 psi over pressure in figure 1 and assume all that happened in one million years). To add the pressure from buoyancy, if a 500 m gas column formed over a million years, that is 0.0005 m/year and also about 0.0005 psi/year increase in buoyancy pressure. We are talking about rates different by 8 orders of magnitude! And observation tells us, there is very little lateral pressure gradient in natural systems. We know deformation in geological times scales are more ductile, especially with the typical lithologies of seals - shales.

In addition, LOT is performed in a drilled hole, which strongly affect the stress and fracture characteristic of the formation. Stress concentration factor (Kt) is about a factor of 3 based on Kirsch's solution (E.G. Kirsch, 1898) for a circular hole in an infinite plate. In nature such holes obviously do not exist, natural fractures (faults) are likely result of tectonic stress, and stress concentration is governed by structural geometry.

This also means basin models that assume some "fracture gradient" below lithostatic based on LOT observations to bleed pressure off cannot explain this observation in figure 2.

Note that the HC column has a higher pressure than water, and the difference is capillary pressure (P_hc-P_w). If the reservoir is water wet, as most reservoirs are, the non-wetting phase HC pressure does not transmit to the rock matrix. This perhaps is why some of the columns can extend all the way to the lithostatic line. However, when the water pressure itself does reach lithostatic - there is no room for a HC column (such as Juno in the figure). And it would be very hard do drill in this situation. This does not happen everywhere, perhaps only where large vertical relief structures drain from a deep depocenter. Centroid effect can cause the pressure in the shallowest structure on a connect trend to far exceed the background pressure. Structures down dip from such as high location may have a lower reservoir pressure than the overlying shale may trap larger columns than the capillary seal alone. Fields downdip from Juno, Shearwater, Elgin, and Franklin (Fulmar, and Pentland) seem to line up on the same water pressure gradient. The Jade (Joanne, Judy) and Jasmin trend seem to have a similar situation.

I am also not aware of any observed hydraulic fractures in seals in over pressured areas. And I would like to hear any additional evidence that seals fail due to over pressuring.

All petroleum accumulations are found below a seal, a layer of rock with tighter pore throats than the reservoir. This is true with tight reservoirs (unconventional) too (He and Xia, 2017). So the main mechanism of petroleum traps is capillary. The capillary force balance equation for column height , H = 2γcos(θ)[1/r-1/R]/g(ρ_o-ρ_w), has no pressure term (Purcell 1949, Berg 1975, Schowalter 1979). Any effect over pressure may have on capillary seal capacity would have to be indirectly on how it may affect pore throat size. We can assume over pressure can inhibit compaction, but it would be to a very minor degree compared to the range of pore throat sizes among the different seal rocks.

Selected References:

Kirsch, E.G., "Die Theorie der Elastizität und die Bedürfnisse der Festigkeitslehre," Zeitschrift des Vereines deutscher Ingenieure, Vol. 42, pp. 797-807, 1898. (no I can't read German).

J. NYGAARD et all, 2020, The Culzean Field, Block 22/25a, UK North Sea, Geological Society London Memoirs · October 2020

WINEFIELD, P., GILHAM, R. & ELSINGER, R. 2005. Plumbing the depths of the Central Graben: towards an integrated pressure, fluid and charge model for the Central North Sea HPHT play. In: DORÉ, A.G. & VINING, B.A. (eds) Petroleum Geology: North-West Europe and Global Perspectives: Proceedings of the 6th Conference. Geological Society, London, 1301–1315.

Ole Christian Engdal Sollie, University of Bergen Master's thesis, 2015, Controls on hydrocarbon column-heights in the north-eastern North Sea

T. T. Schowalter, 1979, Mechanics of Secondary Hydrocarbon Migration and Entrapment; AAPG Bulletin vol. 63 (5): 723–760.

Berg, R.R. (1975) Capillary Pressures in Stratigraphic Traps. AAPG Bulletin, 59, 939-956.

Purcell, W. R., 1949, Capillary pressure--their measurements using mercury and the calculation of permeability therefrom: AIME Petroleum Trans., v. 186, p. 39-48.

He, Z and D. Xia, 2017, Hydrocarbon Migration and Trapping in Unconventional Plays, Search and Discovery Article #10968 (2017), AAPG Annual Conference Presentation.

Eva Zimmer, Matt Farris, 2021, Central North Sea HPHT Pressure Cell Study, Oil & Gas Authority.

The Missing and Wrong Physics In The So-Called "Full Physics" Model

2023-11-19T07:35:00.000-08:00

First this paragraph from George Box on "All models are wrong", "Since all models are wrong the scientist cannot obtain a "correct" one by excessive elaboration. On the contrary following William of Occam he should seek an economical description of natural phenomena. Just as the ability to devise simple but evocative models is the signature of the great scientist so overelaboration and overparameterization is often the mark of mediocrity".

That does not prevent some scientists try to include every thing they believe they understand, then promote their models as "full physics", not knowing many things in nature are not well-understood, or understood at all. Not knowing what is importantly wrong, they selectively worry about minor things that has no implication to the problem at hand.

Are their models "full physics"? No, far from it. Basin modeling aims to model the physical/chemical/geological processes in hopes of better understanding these processes. However, we don't yet fully understand many of the processes, some important processes are obviously not accounted for in some basin models. Below I list some important physics that either are missing from current basin models, or are not correctly implemented. Hope this servers a reminder when you hear "full physics" marketing ploy again next time.

Migration modeling: Some Darcy flow migration models lack some well-known physics between saturation and capillary pressure, and as a result, oil accumulations occur in places without a trap (!!), or accumulations with unrealistic saturation distribution - Have you ever seen a 2km vertical HC water contact (??). Also note the total column of the trap is 3 km!! Has anyone ever seen it exist in nature?

Figure 1. Darcy migration model without proper physics between fluids and rock. Saturation distribution is very unrealistic, and geologically impossible.

Wrong rifting heat flow: Some so called full physics models still have the wrong idea about rifting and heat flow. Below is a heat flow model (red curve) of an area with a beta factor of 2. Notice the heat flow started at 32 mW/m2 (which is a unrealistically too low for any continent, especially where this basin is - Australia which has one of the hottest crust!), and at the end of rifting it doubled, and then over the next 100 million years it cooled off to 36 mW/m2. What's wrong you may ask? It is wrong because the model does not account for the fact that crust produces more than half of the heat - so attenuation of the crust by rifting will cause loss of heat production. Because of that, the heat flow at present day should be lower than before rifting! But this model shows the opposite!

Figure 2. Rift heat flow history from a certain "full physics" model that does not account for the loss of radiogenic heat production (RHP) by crust attenuation from rifting.

Compaction: The compaction model is an essential part of modeling burial history and over-pressuring. Current models assume a unique porosity-effective stress relationship that was first developed from soil mechanics. This is not appropriate as over geological time rocks are not elastic and continue to creep/lose porosity under the same load (effective stress), as evidenced by much lower porosity in older rocks, compaction curves correlate with formation age, etc. The immediate effect of not accounting for the effect of geological time is that it is very hard to maintain overpressure once loading stops, or with uplift and erosion. Almost all the unconventional plays have experienced uplift and still maintain significant overpressure.

HC expulsion fractionation: Some researchers attempt to use the composition of fluid generated by lab pyrolysis for the initial composition of fluid expelled from the source rock in basin models. This ignores the observation that fluids found in source rock extracts are VERY different from fluids produced from accumulations - many things are happening between generation and accumulation that are not accounted for in basin models. It is pretty obvious that heavier HC molecules are preferentially retained by source rock (perhaps due to preferential adsorption), so the expelled fluids are much lighter, and higher GOR. A good reference on this is this study by Sonnenfeld and Canter, 2016 Many of us recognize the problem, but we don't have the physics worked out.

Migration fractionation: At the typical depth petroleum fluid is generated, oil and/or gas are single phase. As migration of the fluid upward reaches bubble or dew point pressure, it separates into a vapor (gas) and liquid phase (oil). The two fluids now have very different composition - light liquid goes with the vapor phase, and the remaining liquid becomes lower GOR and lower gravity. In an oil dominated system - we find heavier, low GOR oil (than what was generated) in shallower reservoirs because of this. They are not what the source rock had generated. Same happens to gas systems. Migrating gas loses heaviest liquid first, so the remaining condensate gets lighter as the gas gets drier (higher GOR). See this post on observations. Loss of polar components along migration path due to adsorption on minerals has not been accounted for in models.

Even during early single phase migration, the effects of composition grading ( observed compositional gradient in accumulations) especially in near critical conditions, in a fill-spill trap is that the spilled fluid is lower GOR and lower gravity, that the total fluid in the trap.

This is not accounted for in basin models and it is not a good idea to think that basin models can predict fluid properties without accounting for this (thermodynamic) process.

Using Heat flow as boundary condition: Many modelers use heat flow as the boundary condition at the base of sediment for modeling the temperature history. This method ignores the effect of growing the sediment column has on heat flow itself. Adding sediment column moves the surface further away from the LAB (1300 °C). It lowers mantle heat flow by increasing dz in the equation Q = K*dT/dz. It also ignores the transient effect as the entire lithosphere now requires new equilibrium.

Figure 2. The effect of adding 1 km of sediment to the lithosphere column. The red arrows show temperature increase required for new equilibrium. It is often mentioned that the new sediments need to warm up. But we cannot ignore that the rest of the lithosphere (~100 times the rock volume of the new sediments) also needs to warm up, on average 15°C, for every 1000 m of new sediment. And that is going to take a much longer time. And you can see that the new profile is a lower thermal gradient and thus lower heat flow.

Full lithosphere models show that rapid burial can reduce heat flow by 30% in some cases, depending on burial rate. This is physics that can be modeled correctly, but not if we assume some "basal heat flow" through time independent of the physics. To account for this physics, a proper thermal model should use a boundary condition at the base of lithosphere.

Relationships: Many of the functions, relationships used in basin models are empirical - which is not physics. A simple example is the permeability-porosity relationship below. There is no direct relationship between the two physically. Permeability varies by several orders of magnitude at the same porosity - even for the same rock type, same formation etc. Empirical models can be useful in many ways, but the uncertainty cannot be ignored - but basin models often use these relationship to model fluid flow, pressure prediction and HC migration without addressing the huge uncertainty.

Relationship between porosity and permeability for porous rocks- modified from Ma and Morrow, 1996,

Upscaling: Due to limited computation power, cellular basin models use grid cells on the order of 10s to 100s of meters in thickness. If we take a look at 100 m worth of well-log, or outcrop, how often it is entirely homogeneous ? I think you can imagine petroleum migration thorough a homogeneous rock volume is entirely different from some sand-shale interbeds. I have not seen any published attempt at upscaling Sw-Pc curves of interbedded different rock types.

We simply don't' have enough data for migration modeling. A parallel problem is that seismic does not have the resolution for mapping the plumbing system to which the physics apply, for us to upscale from, not even close. We don't actually know the number of interbeds and their lateral distribution from the standard seismic interpretation - let alone all the properties of these rocks, such as the different Sw-Pc curves for each type. Well that is even if you model actually implemented a Sw-Pc relationship in the first place. If you are interested in this topic, you may want to look up the concepts of the Leverett-J function and FZI and HFU.

Biogenic gas: The formation of biogenic gas is not well understood - especially when it comes to quantifying the volume. That does not stop vendors from making up a model for you (and charge you a lot of money for it). The current model assumes that the process of biogenic gas generation consumes part of kerogen - and asks you to input some equivalent TOC and a convertible fraction that is the source for biogenic gas. Well - that is not physics - the volume you are getting from these models are based on assumptions, so it is no different than you are assuming you know how much gas is generated per volume of rock - it is not based on any real science!

Assumptions, assumptions: Many assumptions are made in the traditional basin modeling, often an assumption is made just because we don't know it well not because it is insignificant. Yet we will forget that assumption when we discuss the result of the model. I will add some examples later.

Conclusion: Don't be fooled by a fancy colorful 3D model, its usually not very useful. We actually don't need a full physics mode, we need something simple but when applied can answer important questions in exploration quickly.

Are Faults Necessary Migration Conduits? A Simple Migration Model Says No.

2023-11-17T13:03:00.000-08:00

We often observe petroleum accumulations in association with faults, especially in deltaic systems (Gulf coast, Niger delta, Mahakam delta, Nile delta ... and rift systems (Most basins in South East Asia, North Sea ...). Often in the literature the assumption is made that the faults act as path ways for migration up such systems. Here I make a simple argument that migration via faults is not necessary, or even possible in order to explain the distribution.

This cross section is from the Hindel field, in Mahakam delta, Indonesia. Some obviously active faults cut through the large number of stacked oil and gas reservoirs. This is very typical of deltaic systems. Question is, did the oil and gas migrate up the faults to charge these reservoirs?


Figure 1. Cross section through Handil Field, Mahakam delta, Indonesia, Antony Reynolds, 2016. There are some 500 stacked reservoirs vertically.

I have made a very simple model of the geology in Trinity (our popular 3D migration modeling software). There are only two (yes only 2) variables in this model. Capillary displacement pressure, Pd, and buoyancy. The faults are assumed to have a higher Pd than the shales, meaning NO migration along or across the faults. Oil is injected from below the field where the source is at. As the column of each accumulation grows and exceeds the capillary displacement pressure of the shale above, migration continues through the shale and into the next reservoir. It is amazing that such a simple model can explain the distribution of petroleum pools so well. So the first obvious conclusion is that the faults are NOT necessary to act as conduits for the filling of the reservoirs. In fact, if we allow migration along the faults, we could not form the accumulations.

Figure 2. Simple capillary model to explain the accumulations in stacked reservoirs in a deltaic system. The faults are sealing.

With the high net to gross in this field, it is very conceivable that juxtaposition of sand on sand may allow migration across the faults. Below I made some of the sand-on-sand locations low capillary pressure so migration across faults is allowed. The patterns are a bit more complex and the main difference is that the shallow reservoirs between the faults are charged in such a case, compared to figure 1.

Figure 3. Same as figure 2, except migration is allowed through some of the sand-on-sand juxtapositions. This is by lowering the capillary pressure of the faults at the juxtaposition locations.

The second one is more reasonable compared to the actual field. Also keep in mind this is only a 2D model. Vertical migration may happen in different locations, and lateral migration along structure strike is also possible.

An important observation I have made of similar fields in many basins that the sands in between large faults in these compressional flower structure are less frequently charged. I interpret this as indicating although cross fault migration is possible, but less frequent. The faults are acting as barriers and thus creating migration shallows for vertical migration.

I have paid attention to these observations to get a better understanding on migration. And I have always been able to explain them with a simple capillary model like this. This applies to stacked reservoirs in 3 ways against salt as well.

A lot of papers mention faults are migration conduits, without further elaboration. In discussions I have had with colleagues and friends, I find that more than 50 of us would invoke faults as migration conduits. Some go as far as to believe no charge of shallow reservoirs is possible without faults. But when asked how can the oil come up the faults and fill a reservoir, but not leak up the fault the same way it came (both sealing and leaking). The answer is usually more strenuous and unconvincing, and usually involves some exotic episodic behavior.

I think the main reasons geologists like to invoke faults for migration are 1) accumulations are often associated with faults, and 2) there have been a misconception that shales are "impermeable". The association argument works both ways, and the opposite is that faults act as seals so 3 way traps can be traps. The permeability is never zero for a shale, they are often quite permeable, and low-permeability is not the reason that oil is trapped below a shale, it is the entry pressure that is holding the column. Entry pressure is a finite pressure and can only hold a finite column. Additional oil will simply leak through.

Since the simple assumption that faults are seals (vertically and laterally) can explain the distribution of accumulations beautifully, I suggest we stick to an Occam's Razor model.

I am not ignorant of anecdotal evidence for oil migrating though faults, most obviously the seeps along faults at surface, bitumen filled faults, among others. But for forming large accumulations that we observe we should assume faults, in most cases are sealing. If we look at accumulations in basins across the global, we can hardly find any fields that don't have faults across the structure - if faults are leaking, and not leaking, we would have no predictive power. Some of these have been there for many millions of years.

There, I said it.

Migration and Trap Filling Models

2023-11-17T12:17:00.000-08:00

This post compiles some of the images from my recent posts on LinkedIn, to show the important role capillary pressure plays in petroleum migration and trap filling. These models assume that migration rate is extremely slow, limited by supply rates from the source rock, and thus migration is always in equilibrium with the capillary pressure field of the geological system - the dynamic effects of viscosity (thus Darcy flow rates) can be safely ignored. In fact we have never observed any distribution patterns of petroleum pools that can not be explained by capillary pressure alone. All accumulations are constrained by a capillary system, except occasionally hydrodynamics and gravity (tar sands) play a role in part of the accumulation. The variation of pore throat sizes laterally due to facies change, and vertically due to different lithologies is the greatest force that controls the migration process and the distribution of petroleum pools - at all scales microscopic to 100 km+ scales, and tight reservoirs to the traditional traps.

These models use very simple geological models to demonstrate the useful physical principles, and real world geology is much more heterogenous and variable - we need to have in mind what we see in cores, on logs, and in outcrops when we make models. Models are useful because they help us understand the physics, and interpret observations, and make predictions, with the difference between nature and model in mind.

Figure 1. Capillary displacement pressure, and Sw-Pc (Sw-Height) curves are fundamentally what control the trap filling process, and the resulting saturation profiles, and the variable oil water contacts.

Figure 2. The saturation distribution in the model above. Saturation is a function of both height above FWL (ie. capillary pressure (Po-Pw), and the rock type. The low saturation occurs in tight rocks thus volume is reduced by both porosity and saturation.

Figure 3. An idealized model to show OWC can be tilted if a systematic change in pore size exist across the entire field. Observation of a tilted, or variable OWC is not always due to hydrodynamics. When studying tilted OWCs, we should investigate not only the pressure gradient, but also capillary data, which can be inferred from porosity/permeability data. The Tin Fouye Tabankort (TFT) field in Algeria may be such an example.

Figure 4. A model demonstrating the mechanism of stratigraphic traps after Tim Schowalter 1979. Note that capillary seals are relative - a trap is formed when a tighter rock is above or up dip of a less tight rock. So reservoir rock of one accumulation can be the seal for another accumulation. In nature these changes are more subtle and hard to draw the boundaries. The main observation of these mechanisms are the correlation between saturation and rock quality.

Figure 5. The purpose of this model is to demonstrate the effect of storage along migration pathway on the distance of migration for a given volume generated by the source rock. The poor reservoir (silty, or shalely) stores less along the carrier, and the result is that same volume of supply will travel further in the same time that volume is generated compared to a better quality carrier bed - everything else being equal. Effective carrier beds do not have to be very good quality.

Now a couple of real examples:

Figure 6. The Parshall field on the eastern side of the Williston basin. The middle Bakken reservoir gradually thins to the east with lower porosity and permeability. The field does not reach the actual pinch out of the middle Bakken. This model shows that the gradual change of the middle Bakken facies is responsible for the trap, rather than the pinch out. This is probably true with many of the subtle accumulations elsewhere in the Middle Bakken, and in other unconventional plays. The traps are subtle!

Figure 7. The Kraka field in the Danish North Sea has a tilted FWL. This is a quick model to show how it works based on data from this paper.

Please feel free to use these images in your research or teaching. You may reference the petroleum system blog, by Zhiyong He, founder of ZetaWare Inc.

Key references:

T. T. Schowalter, 1979, Mechanics of Secondary Hydrocarbon Migration and Entrapment; AAPG Bulletin vol. 63 (5): 723–760.

T. T. Schowalter and P. Hess, 1982, Interpretation of Subsurface Hydrocarbon Shows;

AAPG Bulletin, V66, No.9, pp. 1302-1327

P. Frykman et al., The history of hydrocarbon filling of Danish chalk fields, Geological Society London Petroleum Geology Conference series · January 2004

What Is Migration Lag & Why Timing of Generation Is Not Important

2023-11-06T08:38:00.015-08:00

As a source rock begins to generate oil and gas, the generated HC fluid cannot just leave the source right away, it will first need to saturate the kerogen's adsorption capacity, which depends on the total organic carbon (TOC). The volume retained by adsorption can be a significant of the generative potential - 20% for a good source rock, and 50% or more for a poor one. This can be estimated by the extract of petroleum/bitumen in the source rock. After that, additional volume generated may be trapped within the pore systems (especially if the source is heterogeneous - with interbeds of shales, limestone, marls, and silty interbeds) of the source rock as we see in shales that we produce from, and this can be very significant, also on the order of up to 50% of the generative potential of the source. There is no secondary migration up to the time until the saturation induced capillary pressure is high enough to allow primary migration out of the source rock.

Secondary migration first occurs in "first carrier beds", which are layers of more porous beds directly above, or below, or interbedded with the source. In the carrier beds, it forms accumulations in structure (3, 4 ways) and stratigraphic traps, large and small (down to pore scales), that need to be filled before migration continues, either leaking up wards, or spilling out side of the mature kitchen. Since this happens near the source rock, the lateral extent is as large as the kitchen/fetch area. This consumes a large volume, up to 100% of the generated volumes, and the time it took to generate this additional volume.

There can be additional carrier beds, and large and small traps that need to be filled before HC fluids finally reach our target trap. All of these cause the delay of charging the traps we want to drill. This delay/lag is a function of the volume of all of these traps (also called hotels, motels) between the source rock and the target trap. This lag explains in many basins where oil is found in traps that formed up to 10s of millions of years after oil generation occurred, such as the oil fields in the West of Shetlands basin:

Typical burial history of of the kitchen area for the Faroe-Shetlands basin. Despite oil generation from the Jurassic source rock (green start) occurring mainly in Cretaceous time, the lower Tertiary reservoirs (yellow start) are filled with low GOR black oils (eg. the Foinaven and Schiehallion fields). This was explained as migration delayed by first "moteling" in deeper traps, Scotchman et all 2006.

HC migration does not stop when the source rock is exhausted as we might expect. This is because the volume of HC fluids trapped in these deeper traps (hotels) continue to mature - cracking from larger molecules to smaller ones, and gas oil ratios (GOR) continue to increase. This volume increase can be larger the the volume generated by the source rock. Continued compaction, diagenesis also reduce the size of these hoteling traps, and cause additional migration. This is why we are seeing very young traps being filled very recently, long after the source rock is spent.

Schematic explanation of migration lag. Note that the present day condition of a basin/area could be at one of these stages. The target shallow trap has not been charged yet if the system is at stage 2 at present day, although the source rock is mature. It should be obvious that the hoteling traps directly above the source should be the main targets in all stages.

Some times, or should I say very often, the hoteling traps are so numerous, or large that generated volume is entirely consumed by them, and the traps above them we are targeting don't get charge at all. One very useful observation, globally, is that exploration targeting the hoteling traps (first carrier beds) are very successful - in fact - 80% of more of the world's petroleum reserves are found in these (Lower Cretaceous reservoirs of western Siberia, Jurassic/Cretaceous reservoirs in the Middle east, Middle Jurassic in the North Sea below the source rock, Wilcox play in deep water GoM ... ..., ). Success rate exponentially decreases for traps further up stratigraphy.

Unconventional plays are essentially the hotels that we are now and producing from. East Texas field, Giddings Field are conventional reservoirs and the oil was generated and migrated from the Eagle Ford. The Eagle Ford retained about 15 mmbls/km2 of oil, which would have to be filled first before migration toward the conventional fields happened. The Woodford, Meramec would have to be filled before oil could migrate northward to North Oklahoma and Kansas.

Note that the original notion of hoteling/moteling may imply that some tectonic movement is necessary for the hotels to spill at a later time. This can happen of course, but more generically it is not necessary. Generation and cracking to lighter fluids is continuous, and volume expansion of HC trapped near the source is continuous, once a hoteling trap is filled, it will continue to leak/spill, porosity loss in the hoteling traps continues, all as long as the burial continues. In rift basins like the FSB, the thermal subsidence and the associated tilting toward the basin center, therefore spilling up-dip, is continuous too.

More generally speaking, every trap is a hotel, while being filled, it causes a migration lag for the next trap in the chain of spilling or leaking. We can only drill and produce economically a limited number traps in a basin. The deeper, non-economical ones are then referred to as hotels, or migration losses. But they are all over the kitchen area and contain much more volumes. In some shallower basins we are drilling and producing from traps near the source and the source rock itself (unconventional). The Eagle Ford contains more oil and gas that ever been found in conventional traps sourced from it. Back in time, these conventional traps up dip had to wait until Eagle Ford itself was filled. The distribution of HC volumes in a basin is a pyramid stratigraphically speaking. The base is the source rock, and the bottom 1000 meters typically contains more than half the volume, and often > 90%.

Predicting Oil vs Gas in a Mixed Oil/Gas System

2023-09-23T13:22:00.011-07:00

Fluid phase (oil, gas, oil and gas) in traps are usually not what the source rock has made through maturation process, and often far different from it. This is because of expulsion fractionation, migration lag, mixing of fluids from different sources, and phase separation during migration and entrapment (leak, spill) etc. Typical BPSM modeling does not model most of these processes correctly, or at all.

In a D/E (deltaic coals as source rock), or a system with multiple source rocks, the most useful concept comes from Sales 1997 paper, that fluid phase often is controlled by trap closure and seal strength, as shown in this figure:

In a dual HC phase system (reservoir pressure < Psat), if a trap's closure is less than the maximum column of gas the seal can hold, it will spill the oil phase and contain only gas (class 1). If the seal strength is less than a full oil column, it will retain the oil column, and leak off the gas (class 3). If closure is greater than the maximum gas column but less than the maximum oil column, it will end up with both phases (class 2). After J, Sales, 1997.

Structure closure is often known at time of prospecting. Seal strength is not, nor is the fluid entering the trap, so the method we use is a Monte Carlo model that describes the unknow parameters, most importantly seal strength, GOR of incoming fluids (which depends on source rock type, maturation and migration process), and the saturation pressure of the fluids, with a distribution. The outcome of the modeling (Trinity software) is a probability of fluid type for each prospect/trap.

The classic examples are found in deltaic basins in South East Asia. The discovery of Kikeh field rekindled the talk on this concept. Not too far, in the Mahakam delta, Kutei basin, Indonesia, there are several large/giant fields that are perfectly explained by this model. The structure closures range from 10s of meters to greater than 500 meters. The source rock is deltaic and fields are a mix of oil, gas and oil/gas. The figure below shows the model prediction using the same assumptions on 4 different fields.

Trinity 3D phase risking results of four fields along the cross section (blue line) with same input parameters on charge (1000-10000 scf/bbl) and seal (25 to 120 psi seal Pc). Only variable is closure height among the traps. Map courtesy of Ramdhan and Goulty , 2018

It is important to note that the results are very good and not so dependent on the incoming fluid type. With the typical seal strength, the traps can be charged with 1500 scf/bbl black oil, or a 15,000 scf/bbl gas condensate, the end results is nearly the same. The high relief structures consistently yield oil phase or oil phase with a gas cap, and vise versa, that low relief structures are most often end up with a gas phase.

I make this post because It seems to me that the last 25 years since the paper was published, there have not been enough application of this simple and very useful concept. Now we have a map based risking tool for easily making such predictions. Hope this will get more application of this unbelievably useful concepts.

Discussions:

To be more generic, we can describe Sales classes mathematically between capillary entry pressure, fluid density and trap closure. For any given structure closure that is in the two-phase region (reservoir pressure below bubble or due point) of a petroleum system, the seal capacity dictates which phase ultimately remain in the trap, assuming charge volume is sufficient.

Where, P_c is the capillary seal capacity of the shale, H is the closure (crest to spill point) of the trap,

⍴_w, ⍴_o, and ⍴_g are the in-situ densities of the water, oil and gas columns, respectively.

Class 3 traps may often include a small gas column due to differences in interfacial tension between oil-water and gas water. Theoretically this may be 15 to 20% of the column see earlier post here. Some class 3 traps offshore Sabah (Kikeh and nearby fields) have variable small gas caps in stacked reservoirs.

In the real world, many factors can affect the contacts and phase proportions, faults are prevalent in deltaic systems and can complicate leak/spill/closure relationships greatly, especially 3 way traps. Column may be dynamic from both rate of charge/leakage and changing composition of charge where gas is often not equilibrated with the oil column below. There is rarely enough data to validate, let alone predict such details before drilling. However, for exploration purposes, Sales' concept, especially when combined with our probabilistic approach hold very well against observations. It is possible to include considerations of non-capillary seal, faults, and other factors in the input distributions.

References:

Sales, J.K., 1997, Seal strength vs. trap closure ----, fundamental control on the distribution of oil and gas, in R.C. Surdam, ed., Seals, traps, and the petroleum system: AAPG Memoir 67, p. 57-83

Ramdhan1, A. & N. R. Goulty, 2018, Two-step wireline log analysis of overpressure in the Bekapai Field, Lower Kutai Basin, Indonesia. Petroleum Geoscience online article.

Phase Behavior of Mixed Petroleum Fluids

2023-06-18T09:58:00.005-07:00

I came across this phase diagram recently and like to explain what I see. What is this fluid, what are the likely properties, and what geological processes may have created it? I posted on LinkedIn as a question and had many good suggestions that I have incorporated in the explanation below.

1) It is obviously a gas (vapor) reservoir by definition (reservoir temperature > critical temperature), and a retrograde one (reservoir temperature < cricondentherm), definitely not an oil. See definitions of fluid types in the blog post just below.

2) It is not a normal retrograde condensate. First, the critical point is at -92 °C, that is colder than pure methane (perhaps some nitrogen may be mixed in there)! So it is a lean gas. The actual C6+ is only about 2 mol% - so it is actually very dry.

3) The cricondentherm (the highest temperature on the curve) for a normal dry gas should be near 0 or negative, but this one is at 380 °C! That is a cricondentherm for a black oil. High cricondentherm means it takes very high temperature to vaporize the liquid in this fluid - so it must be fairly heavy hydrocarbons.

4) The dew point pressure is abnormally high at ~8000 psi. High Psat gas means either it has a lot of liquid (rich), and/or the liquid fraction in fluid is hard to dissolve in the gas.

5) We can rule out rich liquid case because the critical temperature is too low for that a rich condensate. 8000 psi is also too high for that too. So it is likely a mixture of a lean/dry gas with a liquid that is much heavier than normal condensate.

6) In this particular case, it is a dry gas sourced from a coal mixed with small amount of lacustrine oils. The "condensate" is around 35 API gravity!

7) Very high saturation pressure (some times > 12,000 psi) is a good indicator of a mixed fluid that came from very different sources. We see this in the GOM deep water, and the Mediterranean Sea, where we have mixes of biogenic gas and some normal oil. We also find these on both side of Atlantic margins, and some deep basins in China. It is one of the clues for some of the fluids offshore Guyana/Suriname.

8) This could also be a result of a dry gas with oil based mud contamination , as proposed by Brian Moffat in the LinkedIn comments section. So be careful.

The figure below explains the effects on phase diagram when a dry/lean gas is mixed with a normal oil.

Fig. 2. Effects of mixing dry gas with normal oil on phase diagram. Dry gas has a very low critical temperature and cricondentherm. Black oil has very high critical temperature and cricondentherm. The mixed fluid inherits the low critical temperature from the gas, but the high cricondentherm from the oil. The saturation pressure increases dramatically as the two fluids are not compatible. It takes higher pressure for them to dissolve each other.

Petroleum Reservoir Fluid Types

2023-06-15T15:32:00.040-07:00

The five main type of reservoir fluids, black oil, volatile oil, retrograde gas, wet gas and dry gas, are used mainly by engineers for designing production facilities based on what is expected to happen to the fluid during production. It is often confusing to geologists as we tend to focus on the range of properties of each fluid type, such as API gravity, GOR and color etc. offered in literature tables like this one:

However, the classification does not actually depend on these properties, instead it depends on the fluid's phase behavior and initial reservoir PT conditions. The same exact fluid can be a retrograde gas, or a volatile oil simply due to a few degrees difference in reservoir temperature. A fluid may be retrograde gas at a given reservoir temperature, but a wet gas if the reservoir temperature is higher. These typical ranges of properties are only a guide. In nature some gas fields have heavy condensates (<40 API gravity), whereas some black oils are colorless and very light (55 API). I hope this essay can help the PSA community in their petroleum system evaluation and communicate with engineers and managers better.

Fig. 1. The standard fluid types are determined by the position of the initial reservoir PT condition relative to the fluid's critical point, cricondentherm and separator conditions. The color circles on each line is the critical point. The large blue dot is the initial reservoir pressure and temperature. The blue line indicates how reservoir pressure decreases during production. Tc - critical temperature, Tct - cricondentherm, Pd -- dew point pressure, Pb -- bubble point pressure.

The standard fluid types are determined by the position of the initial reservoir PT condition relative to the fluid's critical point, cricondentherm and separator conditions (Fig. 1). If reservoir temperature is lower than the critical temperature of the fluid it is oil (liquid), and when pressure drops it will cross the bubble point and thus also called a bubble point fluid. If the reservoir temperature is higher than the critical temperature, it is a gas (vapor), and also called a dew point fluid. Black oil and volatile oils are separated by the shrinkage factor (FVF) ; Among the gas types, it is called retrograde gas if condensate can form in the reservoir (Tc < T < Tct). If condensate cannot form in the reservoir (T>Tcc), but can in the separator, it is called wet gas. It is dry gas if no liquid drops out at the separator or surface.

Black Oil is a bubble point fluid whose critical temperature is much higher than the reservoir temperature (Tc>>T). It is "low shrinkage" - with FVF (or Bo) less than 2 due to low GOR. It is usually black hence the name.

Volatile Oil is also a bubble point fluid (Tc>T). But the critical temperature is closer to reservoir temperature. It is high shrinkage (FVF > 2.0) due to higher GOR and volatile because it has higher content of C2-C6 hydrocarbons.

Retrograde Gas (or Gas Condensate) is a dew point with critical temperature less than reservoir temperature (Tc<T) but because cricondentherm is higher than reservoir temperature (Tct>T) condensate can form in reservoir when pressure drops below dew point and cause production problems. However, condensate volume decreases again (retrograde) when pressure is further reduced.

Wet Gas has a dew point as well, but because reservoir temperature is higher than the cricondentherm (T>Tct), condensate cannot form in the reservoir when pressure decreases. However, because the separator PT condition falls within the phase envelope, condensate will form in the separator and has to be dealt with.

Dry gas has so little C7+ that the condensate will not drop out in the separator or even at surface.

Exceptions and odd fluid properties

The properties of fluids within each type can be outside or typical ranges given in the table above. There can be a black oil with no color, and 55 API gravity. Some gases may have a low gravity and dark colored condensate.

The boundary between black oil and volatile oil is not so clear cut with parameters. GOR for volatile oils can be as low as 1000 scf/bbl, and black oil up to 2000 scf/bbl, depending to a large degree on the concentration of C2-C5 hydrocarbons vs methane. The solution gas for black oil stays in gas phase in the separator, and simple mass balance equations (black oil models) are adequate. Solution gas from volatile oils drops condensate in the separator, and requires more sophisticated EOS models.

Fig. 2. Normal relationship between API gravity and GOR. Fluids outside of the normal trend are likely formed under certain geological conditions, that may not happen to most fluids.

Certain geological processes can create unusual fluids. For example, when a gas condensate migrates into a low pressure reservoir, the light gravity condensate drops out and forms an "oil" rim. If the trap then leaks off the gas cap, or if the oil rim migrates into another trap, we can end up with a low GOR black oil but very light (something like 300 scf/bbl & 55 API). Water washing can cause a gas condensate to lose most of its gas and form a black oil as well. These “black” oils are light colored or colorless. The laminaria fields (fig.2) are black oils interpreted as formed by water washing of an originally gas condensate fluid.

The opposite can happen when mixing very different fluids. We are now drilling much deeper (higher pressure) than before. A migrating undersaturated gas may dissolves a small amount of normal or even heavy oil during migration, either from background organic matter, or small oil accumulations. The result can be a gas reservoir with a condensate API gravity in the black oil range. Such fluids have abnormally high dew point pressure and cricondentherm, so they likely fit the definition of retrograde condensate, but GOR can be in the dry gas range.

Abnormal fluid properties can be clues to the geological processes, and the interpretation can be useful in petroleum system analysis and prospect evaluation.

Other names

Gas condensate often has the same meaning as retrograde gas, but also a more generic term that include all gases because all natural gases have some amount of condensate, however little it may be. Sometimes is is also called condensate gas.

Rich gas condensate is one that contains more condensate. At a GOR of 5000 scf/bbl, a million cubic feet of gas yields 200 barrels of oil (condensate from the gas). The mass fraction of the two are about same (50% each), but both dollar and calorific/BTU value of the condensate are more than that of the gas. Even at the GOR of 20,000 scf/bbl, the 50 barrels of condensate at $70/bbl, is worth more than 1 mmcf of gas at $3/mcf. For us geologists, we need to be aware that rich gas condensate can only be found at deep enough reservoirs.

Super critical fluid, is gas condensate (but typically refer to liquid rich ones) when reservoir pressure and temperature are higher than critical point. These have properties between gas and oil and some times called dense fluid. Near critical fluid can also include volatile oil.

References:

William McCain, The Properties of Petroleum Fluids, 2nd Ed., 1990

Petroleum Migration Rates and Distances

2022-04-22T09:46:00.035-07:00

In my training classes, I am often asked about the rate and distances of oil and gas migration. There seems to be much confusion in understanding how petroleum migrates, and the controlling factors.

Migration Distance

Long distance migration are observed in many basins. Here is a list of basins I am familiar with:

Athabasca field, Alberta basin, Canada > 700 km from the kitchen
Orinoco oil field, Venezuela, > 100 km
East Texas field, Texas, USA, > 100 km
Wolfcamp accumulations near outcrop in central Texas, Permian basin, > 200 km.
Rubiales field, Llanos basin, Colombia > 100 km
Mississippi oil trend in Kansas, Anadarko basin, > 500 km
Ghawar field, Saudi Arabia, > 200 km.
Oil fields in Saskatchewan ( Viewfield, Cactus Lake ...) and Manitoba (Sinclair), Canada migrated from the Williston basin, North Dakota, >100 km.
Illinois basin, oil pools > 200 km away from the mature New Albany source rock.
Hangjinqi gas field, Erdos basin, 130 km based on maturity analysis.

Most of these are from Foreland basins or continental sags which have marine depositional systems with good vertical seals, and the structure relief is too low to allow vertical migration. Another requirement for long distance migration seems to be the source rock - enough petroleum needs to be available to feed the migration chain.

Below are two figures from the Anadarko basin in Oklahoma and Kansas.

Figure 1. oil and gas wells in the Anadarko basin. The accumulations in Kansas are 100s of kilometers north of the Woodford kitchen in southern Oklahoma. The oil production trend (a giant "river" of oil migration) continues further north into Nebraska.

Figure 2. Map location of wells in the Anadarko basin, showing patterns of migration into Kansas and beyond. The orange outline is the mature kitchen of the Woodford shale, which is the main source rock for the oil in the basin. There is also production in Nebraska, Colorado that are not indicated here.

Large vertical distances are associated with very good source rock potential and the geological controls that limit lateral migration (such as high structure relief, faults, and salt), and may be then limited by the thickness of the sediment column. In the GoM basin discussed above, sea bottom seeps are very common, the source rock is 10 km below surface.

Migration Rate

Below is a typical burial history diagram from deep water of Gulf of Mexico basin. It shows that the "oil window" is roughly 10 million years. The Tithonian source rock is excellent (~ 100 m thickness, TOC ~6%, HI ~600mg/g ) with an UEP of about 10 m³ of oil per m². Assuming a porosity of ~10%, this converts to a flux of 1 m³ per million years, and a flow rate of about 0.00001 m/year for primary migration. Imagine it taking a year to move from one clay sized pore to the next! The capillary number Ca, is about 10^-15, ten orders of magnitude too low for viscosity to have any effect, so no Darcy flow! Note that the GoM has one of the fastest burial rates in the world, and most basins will have rates 10 times slower.

Figure 2. Typical burial history from deep water of Gulf of Mexico basin. The main generation window occurs over about 10 million years.

Similarly we can infer rate of secondary migration or charging, again with an example of a large accumulation and fast generation rate. A one billion barrel field filled over 10 million years equates to 100 barrels (16 m³) per year. Even if the charge is occurring over a 1 square meter area (which is unrealistically too small), the rate is still slower than typical glacier, and 4 orders of magnitude too slow for Darcy flow.

A related question is whether oil generation is fast enough to create micro-fractures. If we take the 1 m³/my rate generated, and calculate how much volume is generated per unit rock volume, we come to 1/100/1000000 = 1e-8 m³/year per m³, or 0.01 cc/m³/year. A drop is 005 cc, so one drop every 5 years. You see where I am going.

Flow Mechanism

On a related subject, some authors have suggested that Darcy flow be used to explain/model the higher saturation in some source rocks. I think it is just a misunderstanding of Darcy behavior. If we examine the geology of these source rocks, such as the Eagle Ford shale, the higher saturation in these source rocks is a result of the source rock being sandwiched in between tight limestones which act as seals. The source rock needs to build up saturation (higher local capillary pressure) to exceed the seal capillary entry pressure for primary migration. In areas where the seals are not present, the saturation is very low. The Eagle Ford is underlain by the Woodbine sandstone in East Texas, where the Eagle ford is not a good unconventional target. The oil expelled downward into the Woodbine and migrated up dip to accumulate in the giant East Texas field. Vast majority of source rocks in the world, such as the well known CT & A source rocks in the Atlantic margins, the Kimmeridge clay formation in the North Sea, and the lacustrine source rocks in the Bohai basins are also excellent source rocks but have very low saturations shown by the fact that S1 Rock Eval extract correlates very well with TOC. It indicates that the residual oil is mostly adsorbed by the organic matter.

Another argument against using Darcy model for unconventional settings, is that if Darcy (viscous, transient) flow is the mechanism, we would expect high saturation in source rocks in younger basins. On the contrary, most unconventional plays are in old basins, and some of which have had no deposition (and therefore HC generation) for over 100 million years.

Source rocks are not homogeneous, and there are always some inter-bedded capillary contrasts over the thickness of the source rock, so some saturation is often necessary for primary migration, and often higher in the middle due to having to overcome addition capillary barriers to reach the edge. Migration will be from high saturation toward low saturation, so both up and down from the middle of the source rock. It is not a viscosity (Darcy) effect as the capillary number is just orders of magnitudes too low. The capillary contrast within a source rock are much, much higher than buoyancy - so downward migration is pretty common. See this post on that.

Simple experiment/Analog for Migration

Here is something you can try or imagine. Take a bottle of water, walk outside and pore it on the street. It will flow down the street, may be for a few feet. Then it will stop. Right? Then take another bottle and pore it at the same spot, the water on the street will start moving again, a few feet further, and stops again. The distance of migration is related to the amount of water you have (UEP of the source rock), and the rate is related to how fast you can pore it (rate of generation). If there is a big pot hole, it will not continue further down until it is filled. This is how I think of migration, the roughness of the street surface mimics a capillary system, with small pools and barriers between them, when additional water is added, it allows the small pools to connect and flow continues, and then when you stop adding water, the barriers between the pools will hold the water in place, and flow stops.

Phase Separation & Implications in HC Migration

2021-11-20T07:58:00.009-08:00

Here are two videos of CCE (constant composition expansion) PVT test videos kindly provided to us by Murray Macleod at Core Labs Perth. These tests are used by engineers to determine bubble or dew point pressure (pressure at which the single reservoir fluid becomes two phase). In this blog I would like to talk about the implication of this in HC migration process. I hope this helps those geoscientists not so familiar with PVT/phase behavior. I wish I had learnt this earlier in my career as a petroleum geologist.

In the CCE tool, the rotating cylinder moves away to expand the volume of the chamber thus lowering the pressure. The first video shows what happens to a single phase volatile oil when pressure is decreased from 8000 to about 1000 psi. At about 3300 psi (which in a basin would be at about 2200 meters depth), vapor (gas) bubble begins to form (hence the term bubble point pressure).

As pressure is further reduced, more and more gas comes out of the solution and takes up the upper part of the chamber and the volume of the liquid decreases significantly (by a factor of more than 2 in this case). What is not obvious (and important for exploration) is that along with that the gas oil ratio (GOR) in the liquid also decreases.

The following figure shows the path of the process in a geological setting. Following the 3 green circles from deep to shallow, the starting volatile oil (deepest green circle) has a GOR of about 2300 scf/bbl. During upward migration, phase separation starts when it reaches about 2200 meters. As the oil continues to migrate to shallower depth, it loses more and more gas. At the shallow depth, the GOR becomes 300 scf/bbl (a black oil).

The lost gas may get trapped in small traps along the way, so we end up with an low GOR oil accumulation. Or if enough of the gas makes to the final trap, we may have a gas cap. If the trap is not able to support the column of oil and gas to spill point, it may leak the gas and retain only the low GOR oil. Or if the seal is very good but the trap is small, all of the oil may spill, and we end up with a gas accumulation.

Again, let me be clear, although the source rock may have supplied a high GOR oil, the final trap may be a low GOR oil accumulation, or a gas accumulation, or an oil accumulation with gas cap. It is determined by the seal and the reservoir pressure!

A similar process applies to gas condensate fluid. Below is a CCE video for gas condensate. As the pressure decreases to dew point, a liquid phase forms at the bottom. The liquid volume increases as pressure decreases and more liquid comes out solution from the vapor phase. The GOR of the vapor increases (CGR decreases). Like the oil case, you may deduct what can happen at the final trap following the red circles in the figure above. Depending on if it leaks or spills, the trap may end up with a higher GOR gas, or a low GOR oil, or both. Check out the AAPG paper by John Sales (1997).

If the starting fluid has a GOR between 3000 and 4000 scf/bbl, whether it is called oil or gas depends on what engineers find in the CCE test. If bubbles form at the top, it is called an oil, and if liquid forms at the bottom, it is called a gas condensate. This is how engineers decide if a field is called oil field or a gas condensate field. Note that even at 4000 scf/bbl, there is still more what geochemists call oil (C6+) in the fluid than gas (C1-5) in weight.

Please let me know what you think by commenting, thanks!

Zhiyong He,

ZetaWare, Inc.

Is Uplift/Erosion A Significant Risk for Petroleum Systems?

2021-11-06T08:01:00.013-07:00

When the basin experiences uplift and erosion, the source rock may cease to generate hydrocarbons, and structures formed afterwards may not receive charge; existing oil accumulations may form gas caps, and gas caps may expand and cause oil to spill; reservoirs may get too shallow and oil may get biodegraded; seals may become ineffective and the accumulation may be completely destroyed. Given these reasons, you would think it would be hard to find oil and gas in such basins?

Lets first look at it not from the tradition process driven perspective but from a statistical one. More than 80% of the world's petroleum reserves are found in basins with uplift and erosion (well, I did not calculate the precise percentage, but just thinking of North America, Venezuela, Russia, the middle East, North Africa, etc.). So if had all the knowledge we have before any petroleum had been found yet, we would have had a much higher chance to find oil and gas fields in an uplifted basin, than one that is not.

The petroleum industry began in the 19th century in Pennsylvania/Ohio, in the Appalachian basin, and the first well found oil at just 20 meters below surface. The basin has been uplifted since 200 my and between 3 to 5 km of sediments have been removed, which is why the oil was found at such shallow depths in the first place. The petroliferous basins in North Africa have experienced two significant erosion events, on in Hercynian, and then more recently during the Alpine orogeny (figure 1). Yet some of the biggest fields are found here, such as the Hassi Messaoud and El Borma. In the US, the giant East Texas oil field (10 billion OOIP), and giant Hugoton gas field (80 TCF) are both very shallow due to uplifting since Cretaceous time; and the list can go on and on. It seems to be a rule, rather than exception with so many cases. It leads me to conclude that perceived risks of seal and timing in uplifted basins are probably unfounded.

Fig. 1. Burial history in the Ghadames basin, where giant fields like the El Borma, and the famous Hassi Messaoud field are located.

Perhaps the most extreme cases are found in the San Juaquin basin in California, where several billion barrel fields are found literally at surface, due to reservoirs outcropping at surface. The Midway-Sunset oil field shown in figure 2 below, and the Kern River oil field are just a couple of examples.

Fig. 2. Midway-sunset oil field in the San Juaquin basin (John Borkovich, 2019 CA State Water Resources Control Board). More than 3 billion barrels of oil had been produced by 2006. Gusher image from Wikipedia.

For my 35 years as a basin modeler and later a practical petroleum system analyst, what I have seen is that the experts who conduct research and write papers tend to study the problems from a scientific/process perspective, focusing on the details, but tend to not look from the perspective of analogs and statistics that may contradict their research. In the past 10 years or so, I have been paying more attention and finding contradicting evidence from analogs and large dataset against some of our common wisdoms or misconceptions, such as my earlier posts on gas risk due to high maturity, timing risk, biodegradation risk, etc. This post is just another example.

Downward Migration: Observation and Mechanisms

2021-10-10T09:33:00.033-07:00

by Zhiyong He, ZetaWare, Inc.

Observation:

I have been asked often in my training classes about downward migration. Is downward migration limited, or does it present a higher risk? What is the mechanism for large scale downward migration/charge? Is there a way to estimate the volumes for upward vs downward migration?

I want to start with observations. Many large accumulations have been discovered in reservoirs stratigraphically older than the source rock in many basins. Here are some examples that I am familiar with:

North Sea, Middle Jurassic and older reservoirs below the KCF
North Africa, the Cambrian, Ordovician sandstone reservoirs in Ghadames, Illizi and Murzuq basins, below the Silurian hot shale source cock. The giant Hassi Messaoud field produces from Cambrian, some distance below the source rock.
Bohai, Oil fields in Paleozoic basement, “Buried Hills”, karst tomography, between and under the Tertiary grabens that contain the Oligocene source rock.
Similarly, the Bach Ho (White Tiger) oilfield in fractured granite basement underlying Oligocene source rocks in Vietnam.
The biggest oil fiend in the United States lower 48 is the East Texas Field (> 10 billion barrels) that produces from the Woodbine sandstone directly below the Eagle Ford source rock.
The biggest oil field in Anadarko basin is the Oklahoma City Field which produces from the Ordovician Wilcox formation, charged from the Devonian Woodford source rock above.
In California, the giant Midway-Sunset oil field also produces from the Temblor formation below the Monterey source rock.
Muddy/Dakota reservoirs underlying the Mowry shale in Powder River basin.
Cambrian and Ordovician oil and gas fields charged from the Utica source rock above in Ohio and Indiana, of the Appalachian basin.
Three forks reservoirs and the Bakken source rock above in Williston basin.
The Norphlet plays in onshore Mississippi, Alabama and more recently the Eastern GoM deep water where the Smackover is the source and the seal.
The Tuscaloosa sands below the Tuscaloosa Marine Shale (TMS)
La Paz field, Maracaibo basin, Venezuela. Reservoirs are Cretaceous limestone and fractured granite basement, below the La Luna source rock.
The Augila-Naafora field, Sirte basin, Libya. Cretaceous source rock above and onlapping onto basement reservoir and provides the seal.
Suban gas field, South Sumatra, Indonesia and Adang Utara oil field in Malay basin, producing from basement.

Some other observed characteristics are:

The source rock is often also the seal
Reservoirs can be separated by one ore more shales/sands from the overlying source (eg. North Sea and Williston basin).
In some cases, lateral juxtaposition across faults may help explain accumulations, and some are harder to explain.
Check out this paper on basement fields around the world.

Downward Migration Mechanism

I would explain downward migration as driven by the natural capillary process. The figure on the left below shows the typical capillary curves of a reservoir and a shale (source rock). The shale has a very steep curve and pressure increases quickly with HC saturation. The center and right figures show the theoretical capillary pressure (difference between the HC phase pressure and water pressure, Pc = Po-Pw), profiles before and during HC generation.

Fig. 1, Capillary drive mechanism for primary migration. Pressure in the non-wetting phase HC is higher due to saturation increase cased by HC generation.

During generation, as oil saturation increases in the shale, so does capillary pressure and the oil near the sand is pushed into the sand due to capillary pressure difference: energy/potential for the non-wetting phase HC fluid is much lower in the sand than in the shale.

Oil saturation and therefore capillary pressure in the center of the shale is higher as it is further away from the sand. Pc can be several hundred psi even at 20% oil saturation.
Saturation at the boundary stays low as it is easier to expel due to the sharp gradient in Pc.
Buoyancy gradient for oil (~0.1 psi/ft) or gas (~0.3 psi/ft) is much smaller compared to capillary gradients ( which can easily reach several hundred psi over the half thickness of the source rock)
Capillary pressure is in addition to any pressure increase due to hydrocarbon generation, or compaction. And it is a higher in magnitude force than both over the source rock thickness.

Additional Controls

The above assumes a homogeneous layer of source rock. In nature, the source rock may vary vertically in pore sizes. If the source formation is deposited as a fining upwards sequence, the capillary pressure is higher at the top with smaller pores. This will cause more volumes to migration downward.

If the source rock is overlain by a tighter formation, and underlain by a good reservoir, nearly all the volume will migrate downward. This may be the case with the biggest oil field in the lower 48 of US, the East Texas field. The Woodbine sandstone reservoir sits directly below the Eagle Ford source. The tight Austin chalk is above the Eagle Ford.

If the source interval has inter-bedded silty zones, hydrocarbon saturation in the more porous zones will be higher in order for the Pc to exceed the sealing capacity of the tighter zones. This essentially creates the favorable condition for a unconventional play. Check out this post for more on this.

Overpressure and the "centroid" effects of carrier beds may further enhance downward migration. The figure below is after the North Sea, and the Norphlet examples. The water pressure in the source rock is expected to follow the regional compaction driven over pressure. The sand below has limited vertical extent, which causes the classic centroid pressure effect. The pressure in the sand will follow the line parallel to the hydrostatic pressure, but higher. At the deeper end, usually the HC kitchen, the shale is more over pressured than the sand below, and the resulting hydrodynamic force will help downward migration.

Fig. 2, Effects of over pressure on primary migration. Downdip area of the carrier beds are under pressured relative to the source rock. At the crest, the opposite is true, which may limit column heights of accumulations.

Accumulations usually occur at the shallow end, and some volumes migrated below the source rock may leak up to younger reservoirs. Note that Both capillary force and centroid pressure drive help upward expulsion as well, if the sand is above the source.

Discussions:

Human intuition is that we want to quantify the volumes that migrate upwards vs downwards, especially as a basin modeler. The uncertainty is large. I would simply assume that roughly 50% of the volumes should migrate downwards if the reservoir is directly below the source rock, plus/minus the uncertainty, more if there is a tight formation above the source rock. If the reservoir is further down stratigraphy, the risk goes higher, as it may need to rely on juxtaposition, or coarsening downward stratigraphy, etc. No, the modeling software cannot tell you this (whatever the vendor may claim their software can do), you have to make such arguments, or assumptions, like most things with basin modeling.

Limited columns in Northpet traps:

Some have observed that Norphlet play seems to have limited column heights compared to structure closure, and have suspected that it could be due to the limited efficiency perceived of downward migration. Steve Walkinshaw observed that the Norphlet sand only has a oil column if the overlying Smackover porosity is filled, or where the Smackover is tight (http://www.visionexploration.com/norphlet.htm), implying that it may be volume limited.
My own interpretation, based on concepts given this presentation and my other presentations on seals/column height and charge limitation, is that these could be seal capacity limited. Where the Smackover is tight, it is simply a better seal. In my observations and estimates, where column height is less than the trap closure, it is often are often limited by the seal capacity, rather that charge volumes. We may find stacked pays with similar columns. In some cases, we may find an empirical correlation between column heights and effective stress.
In general, volume can be limited if the fetch areas are small or the source rock is very weak. However, in majority of cases, trap sizes are typically much smaller than the estimated change volumes.
We may never know the reason for sure in a particular case. So we should use any empirical rule of thumb we can find if it helps to reduce risk. Meanwhile, we should continue to look for evidence, correlations and new explanations.

Conclusions:

Downward migration should be very effective as large scale forces exist to drive downward migration.
If the reservoir/carrier is directly below source rock, chance of charge should be high as evidenced by the examples of several prolific basins.
Lateral juxtaposition across faults may be helpful, especially for migration into reservoirs further down stratigraphy, but it is not required for sands directly below the source rock.

Where Did All The Gas Go?

2021-02-13T12:57:00.024-08:00

This is my summary of the same titled LinkedIn post, where I asked for analogs of known gas fields that are interpreted as sourced from an oil prone source rock due to high maturity. We have received more than 130 comments, and 13,000 views at the time of this post. I want to thank all who participated in this crowd wisdom experiment.

The background is that we have all come to use to burial histories and maturity maps from basin models showing oil and gas windows. Particularly, gas windows colored in red are giving exploration managers a heartburn. In recent years as we started to look at petroleum systems from the top down, the large dataset of basins and fields globally show that the organo-facies dominantly control what fluid type we find in the basin. The second most significant factor we find is the reservoir pressure (pvt control), in conjunction with seals that determine oil vs gas in traps in a mixed source environment. The effect of thermal maturity, which the original schematic diagram from Tissot et all were meant to show, plays only a minor role.

Figure 1. Traditional concept of oil/gas windows may have led to over-emphasis on maturity in our industry. Cumulative expelled products from Pepper and Corvi 1995 organo-facies give more appropriate basin wide GORs, that are strongly a function of organo-facies, rather than maturity.

As the figure above shows, cumulative fluids expelled from the different organo-facies (Pepper and Corvi, 1995) differ greatly, and the proportions of oil and gas are very consistent with observations of accumulated fluids in basins regardless of maturity of the source rock. In short, we find that basins with very oil prone source rocks, such as the Tithonian of the GoM deep water, KCF of the West of Shetland, SHJ of the Bohai basins, have little or no gas discoveries although the source rock were over mature before the reservoirs were even deposited. On the other hand, basins with only gas prone source rocks have essentially no oil discoveries such as the Southern North Sea, areas of South China Sea, Rovuma Basin of Mozambique, and the Nile delta of Egypt. In basins with mixed oil and gas accumulations, as in many South East Asia basins. we find that the type of fluids and their properties are more controlled by the pvt conditions of the reservoirs, rather than maturity.

Figure 2. The contracts among three different petroleum systems. The Nile delta has almost no oil fields, and the Gulf of Suez has almost no gas fields. The Western Desert has mixed oil and gas fields. Of course all three basins have part of the source rock in "oil window" and part in "gas window". The fluid types seem independent of that.

The commenters provided quite a few potential examples, that I have tried to further look into and continue to learn about. Here I will attempt to group them in my proposed explanation to limit the length of this post. They fall into the following categories:

1) Some of the examples are from basins with mixed source rocks, such as the North Sea, which has the well-known oil prone KCF, but also the gas prone Heather, and potentially Paleozoic coals. The Western Desert of Egypt falls into this category (left side of figure 2). These are basins with mixed oil and gas fields, and as I will discuss below, PVT conditions may be an important control.

2) Some very large gas fields at shallow depth may be formed by phase separation. The Hassi R'Mel in Algeria may be explained as a Sales 1997 class I trap where significant solution gas in oil was released as oil migrated to shallow depth and displaced the oil. Similar large gas fields include the Hugoton field (largest gas field in North America), and the Troll field in the North Sea. These fields are less than 1500 m deep, and all have an oil rim. Based on standard PVT diagrams, at about 2000 psi in reservoir, any charge between 400 scf/bbl and 60,000 scf/bbl will result in a dual phase reservoir. Although in these examples, a partial contribution from a more gas prone facies may not be ruled out, the shallow depth (low pressure) have made fluid phase almost independent of the charge from source. Some of the shallow Eastern Siberia oil and gas fields, many of which are dual phase, may fall in to this category.

Figure 3. Phase diagram. Green curve is the Glaso (1980) bubble point and red dew point curve of England (2002). At reservoir pressure of 2000 psi, any incoming fluid between 400 scf/bbl and 60,000 scf/bbl will form a dual phase trap. Whether the gas phase, or the oil/condensate phase is preserved depends on the seal capacity and trap closure. Chance of both preserved is very high due to the density differences.

3) Some of the gas fields, such as the North field in Qatar (largest in the world) and the Astrakhan in Russia, the Rimbey gas field at the deep end of the Leduc reef trend in Alberta, the Norphlet trend in Alabama and the Sichuan gas fields. The commonality of these are they are associated with carbonates, in which thermal cracking of oil can be greatly accelerated by TSR. These fields are all sour (high H2S and CO2). Cracking to gas at oil window temperatures make it likely to happen during migration. In the case of the North field and the Permo-Triassic gas fields in southern Iran and the UAE, there is also evidence that they may have been generated by a low quality Qusaiba facies.

Figure 4. Effect of TSR on thermal cracking of oil to gas. Gas condensate can be formed at much lower temperatures compared to normal cracking kinetic models. Data from Zhibin Wei et al. 2011.

4) As usual, these are not the only possible explanations, and often several factors contribute. The main point of this post is that it is relatively rare to find conventional gas accumulations due to a very good oil prone source rock being over mature. The exception being when we started drilling very close to the source kitchen, maturity does come into play. The deeper sub salt fields in the Campos basin offshore Brazil, such as the Pão de Açucar, the Austin Chalk play near the Eagle Ford gas window, and the Elgin-Franklin fields in the North Sea, are examples. These tend to be condensate rich (100-200 bbl/mmscf) as supposed to dry gas. Of course if our target is the source rock itself, we would expect to find gas in the gas window.

The WoS Application

Here I would like to use the example of the West of Shetland basin to demonstrate how to analyze a petroleum system from the top down when traditional PBSM modeling does not provide the answers. The WoS is a Jurassic rift basin in the north Atlantic, and the Kimmeridge Clay formation is an excellent marine source rock. Much modeling work has been focused on the complex thermal history, with rifting, and Eocene volcanism, the source kinetics, the suppressed vitrinite reflectance ..., but have not explained the fluids in the basin.

Figure 5. Basin modeling results of the WoS. Timing of oil generation predates the deposition of reservoirs. Present day thermal stress is at ~240 C. Note the source rock is not present in the green area. Burial history and maturity map courtesy of Julian Moore.

The models predicted that the source rock was in the oil window near the end of Cretaceous, and very post mature today. Yet the basin contain mainly oil fields. And the system GOR (adding all gas and oil reserves) is less than 2000 scf/bbl, consistent with the Pepper and Corvi 1995, class B organo-facies.

Figure 6. The basin hosts several large oil fields, some of which have small gas caps, and some scattered small gas condensate fields. The GOR of these fields plot on a simple phase diagram. PVT data courtesy of APT UK/Julian Moore

The top down method as applied here is this. Since the source rock is a very oil prone one, with hydrogen index up to 1000 mg/gTOC. The bulk of the accumulations should be oil, regardless of maturity or timing. The GOR and API gravity of the oils should increase with depth due to various reasons, such as migration lag effects, gravity fractionation, and bubble point controls, as shown in figure 6, on the right. The small gas fields are likely result of phase separation, rather than maturity, and the GOR for those are higher at shallow depth due to dew point control. J. Sales 1997 concept may be at work here, that small traps on spill path will have phase separated gas, whereas large relief structures should contain oil. That is what has been observed here.

Zhiyong He,

ZetaWare, Inc.

References:

He Z. and Murray A. (2019) Top Down Petroleum System Analysis: Exploiting Geospatial Patterns of Petroleum Phase and Properties. AAPG Search and Discovery, #42421

Pepper A. and P. Corvi, 1995, Simple kinetic models of petroleum formation. Part III: Modelling an open system. December 1995 Marine and Petroleum Geology 12(4):417-452

Sales, J.K., 1997, Seal strength vs. trap closure—a fundamental control on the distribution of oil and gas, in R.C. Surdam, ed., Seals, traps, and the petroleum system: AAPG Memoir 67, p. 57–83.

Oistein Glaso, 1980 "Generalized Pressure-Volume-Temperature Correlations," Journal of Petroleum Technology.

England, W.A., 2002, Empirical correlations to predict gas/gas condensate phase behavior in sedimentary basins, Org Chem 2002, 33(6):665-73

Wei, Z. et al., 2012 Thiadiamondoids as proxies for the extent of thermochemical sulfate reduction, Organic Geochemistry, 44 (2012) 53-70

Does complex geochemistry of an oil mean a multi-stage filling history?

2020-12-22T06:07:00.008-08:00

In the last few years Zhiyong and I have talked a lot about “top down” petroleum systems, analysis (e.g. He and Murray, 2019), one aspect of which is “geochemical inversion”. Petroleum is a natural material containing 100’s of thousands of individual compounds, mostly hydrocarbons. Although the composition is complex it is not random: it encodes signals inherited from the original organic matter as well some related to thermal or biological processes during or after formation. Geochemists interpret this to provide information on the origin and history of a reservoir fluid.

However, I get nervous when the results of geochemical inversion suggest complicated charge histories which are not matched by an equally complicated geological/tectonic history. Recently I reviewed a paper which suggested eight discrete charge events had contributed to the fill for a cluster of fields. The corresponding burial history looked fairly simple so it was hard to imagine how charge could be anything but smooth and continuous in the area. I have a feeling that interpretations like this arise from a lack of recognition of how heterogeneous fluid compositions can be, even in well-connected reservoirs, charged slowly and continuously by a single source rock.

In an AAPG talk last year (Murray and He, 2020) we noted that it is quite common for the oil underlying a gas cap to be undersaturated with gas. This shouldn’t be surprising, given that the rate of filling – which is limited by the rate of kerogen maturation during burial - is of the same order of magnitude as the rate of diffusion driven mixing. If the kerogen organofacies is not uniform (normal for fluvio-deltaic and fluvio-lacustrine source rocks in particular), and fluids are not fully mixed, we would not expect the fluids in the reservoir to be uniform either. Furthermore, since fluids are expelled over a source rock maturity range from ~ 0.7 to 1.3% Ro (vitrinite reflectance), we would not expect to find a uniform “maturity” signal in most oils either, whether it is based on methylphenanthrene isomer ratios or gasoline range ratios or whatever.

My experience of reservoir geochemistry studies, where samples from multiple depths, units and wells within a single field are examined, mostly confirms these expectations: A lot of fields I have looked at do not contain well-mixed fluids, independently of any physical compartmentalisation that may exist. This is hardly a new observation: England (1990) commented on it in relation to the Forties field for example. Indeed, it is more surprising when reservoir fluids are found to be well mixed. I have seen examples of this too though and it seems to be when (a) geometric factors in migration homogenise fluids before or during their arrival at the trap or (b) thermal disequilibrium accelerates density overturn via convection and therefore mixing. My colleagues and I described the latter process in respect of the remarkably well mixed fluids in the Sunrise gas-condensate field (James et al., 2010). Well-mixed fluids are also quite common in fractured carbonate reservoirs where mixing pathways are short due to polygonal fracturing. My point in mentioning the unmixed fluids is that geochemical inversion studies frequently base their conclusions only one sample from each particular field or reservoir, without taking this into account.

A specific example of geochemical inversion is the interpretation of patterns of biodegradation in terms of reservoir temperature vs. charge history. Biodegradation, which occurs at temperatures lower than about 80 °C, has easily recognisable effects on oil. The most characteristic feature is the complete or partial loss of the n-alkanes (also called n-paraffins). These straight-chain compounds are easily assimilated by bacteria and gas-chromatograms of biodegraded oils show their depletion relative to the “unresolved complex mixture (UCM)” hump. Note that no new material is formed here – bacteria do not convert straight chain hydrocarbons into the branched and cyclic hydrocarbons comprising the UCM – the latter are just more resistant to attack. A chromatogram of a crude oil with complete loss of n-alkanes is shown in figure 1.

Fig. 1 Gas chromatogram of a severely biodegraded oil from the Vincent Field, Australia (Murray et al., 2013)

A so-called “polyphase” or “hybrid” oil is one in which it is suggested that more than one discrete charge/biodegradation event occurred. This is usually based on the simultaneous presence of very easily degraded and very resistant compound. An example is the co-occurrence in an oil of n-alkanes and the 25-norhopanes, a group of pentacyclic terpane biomarkers associated with a severe level of biodegradation (Peters et al. 2005 and references cited therein). The n-alkanes are attributed to a component of the charge arriving after the reservoir temperature exceeded 80 °C when biodegradation stopped. A similar conclusion is sometimes drawn when the gas chromatogram shows prominent n-alkanes on top of a large UCM, as shown here in figure 2.

Fig. 2 Gas chromatogram of a “polyphase” biodegraded oil from the Lady Nora Field, Australia. MCH is methyl cyclohexane, a cyclic alkane which is relatively resistant to degradation

Back in 2005 I worked on a heavily biodegraded oil field in the Middle East. Being onshore and shallow it had been pattern drilled and there were a lot of samples to play with. Gas chromatograms showed the usual UCM with n-alkanes and resolved peaks from other simple compounds present to variable degree. There was a good correlation between API gravity and the area of GC-resolved peaks relative to the UCM, as shown in figure 3.

Fig. 3 Correlation between the total area of resolved peaks (relative to the UCM) and API gravity of oils from a large oil field in the Middle East region

This correlation was useful in estimating the API and the viscosity (by another correlation) of fluids for which there was insufficient sample for direct measurements. However, in order to predict bulk properties away from well control, we needed to understand the factors controlling the extent of degradation. Because there were spatially coherent differences in the degree to which light vs. heavy “fresh” charge overprinted the UCM, I concluded, at the time, that there were multiple stages of charge and degradation. The problem was that the burial history was simple and charge should have concluded more than 100 Ma before present. At the time, I thought there must have been things in the charge history – perhaps to do with “motelling” or some other migration-related process - that were not captured in the charge model. However, I revisited the report recently and realised there is another possibility. It goes like this…

Several studies have shown that heating of the asphaltene fraction of a heavily biodegraded oil can release fresh oil, complete with the original complement of n-alkanes (Snowdon et al. 2016 and references therein). Asphaltenes are macromolecules with a composition and molecular structure similar to that of the kerogen from which they were derived (Snowdon et al. , 2016). Laboratory pyrolysis of asphaltenes is thus akin to the artificial maturation of kerogens. Figure 4 shows gas chromatograms (and density, viscosity) of a heavily biodegraded oil from a field in the Middle East region, before and after heating at 300 °C for 12 days and at 350 °C for 10 days. The thermal stress from these two heating regimes is equivalent to a vitrinite reflectance of 0.8 and 1.3% respectively.

Fig. 4 Gas chromatograms for the original oil from a large oil field in the Middle East region and after heating as shown. I.S. is the “internal standard” added to assist quantitative analysis

If we can do this in the laboratory, why would it not also happen in nature as a reservoir containing biodegraded oils is buried deeper? Let’s consider such a reservoir which is continuously buried so that the temperature increases from 80 °C to ~ 120 °C over a period of about 20 Ma. Using the kinetics of asphaltene conversion from laboratory studies, we can estimate that about half of the mass of asphaltenes would be converted to “fresh” oil. The chromatogram, perhaps like that in Fig. 4B, would show a “polyphase” character, without the requirement of any new charge arriving from the source rock after biodegradation ceased.

What if the reservoir is not heated as high as 120 °C? Could we still get an apparently polyphase oil? I believe so: Some studies (see Snowdon et al., 2016 and references cited therein) have shown that the source of fresh oil in asphaltene heating studies is not only pyrolysis (i.e. the breaking of high-energy covalent bonds). Rather, the cage-like molecular structure of asphaltenes appears capable of encapsulating some of the original oil and preventing it from being biodegraded in the first place. This oil can be released by thermal disruption of the asphaltene clusters at temperatures lower than those required for pyrolysis. Figure 5 shows before and after heating chromatograms for a crude oil which had been severely biodegraded at the surface (following an oil spill). The conditions used, 320 °C for 2 days, create a level of thermal stress similar to that applied to the oil in figure 4B. However, in this case the post-heating oil has lots of n-alkanes and only a very small UCM. I wonder how much of the fresh oil here has been released prior to pyrolysis temperatures being reached.


Fig. 5 Gas chromatograms for the original, biodegraded oil collected after a spill at sea and after heating at 320 °C for two days (from Oudot and Chaillan, 2009)

In almost all cases where complex charge histories are invoked to explain geochemical anomalies, I can (at least in principle) explain them by things that happen during, normal continuous burial and supply of hydrocarbons. This doesn’t mean that the simple explanation is necessarily true - just that, in the absence of evidence for a complex burial/thermal history, we need not be as puzzled as I was back in 2005.

As with all these blog posts, I invite and indeed welcome push back/comments/clarification. They are not peer-reviewed papers, just some observations and thoughts from one individual.

Cheers,

Andrew Murray,

References:

England W. (1990) The organic geochemistry of petroleum reservoirs. Org. Geochem., 16, 415-425

He Z. and Murray A. (2019) Top Down Petroleum System Analysis: Exploiting Geospatial Patterns of Petroleum Phase and Properties. AAPG Search and Discovery, #42421

James B., Bailey W, Murray A., Pelechaty S., Kaiko A. and J. Li (2010) Unusual reservoir connectivity revealed by data integration at the Sunrise Field. APPEA J. 50th Anniversary issue, 349-370, Australian petroleum production and exploration association (A PDF is available from the author on request)

Murray A. and He. Z. (2020) Oil vs. Gas: What are the Limits to Prospect-Level Hydrocarbon Phase Prediction? AAPG Search and Discovery, #42513

Murray A., Dawson D.A., Carruthers D. and Larter S. (2013) Reservoir Fluid Property Variation at the Metre-scale: Origin, Impact and Mapping in the Vincent Oil Field, Exmouth Sub-basin. Proceedings of the Western Australian Basins Symposium, Petroleum Exploration Society of Australia, Perth, August 2013 (A PDF is available from the author on request).

Oudot J. and Chaillan F. (2009) Pyrolysis of asphaltenes and biomarkers for the fingerprinting of the Amoco Cadiz oil spill after 23 years. Nature Precedings. 4. 10.1038/npre.2009.2975.1

Peters K. E., C. C. Walters and J. M. Moldowan, 2005, The Biomarker Guide: Cambridge University 479 Press, Cambridge, U.K., 1155 p.

Snowdon L., Volkman J.K., Zhang Z., Tao, G. and Liu, P. (2016). The organic geochemistry of asphaltenes and occluded biomarkers. Org Geochem., 91, 3-15.

Composition Fractionation During Petroleum Migration

2020-10-16T12:24:00.021-07:00

By Zhiyong He, ZetaWare, Inc.

One of the goals of petroleum system modeling and analysis is to predict fluid composition and properties (GOR, API gravity etc.). However, most of the work in the past has been focused on the generation process, with compositional kinetics, etc. Below I will try to show that the petroleum under goes significant changes in composition and properties along the migration pathways due a number of secondary processes not well understood yet. Most people are familiar with the Gussow (1954) migration model in the figure below. The trap closest to the kitchen would receive the latest, and most mature and therefore lighter fluid, which displaces less mature fluid to traps up dip.

Fig. 1. Differential entrapment of petroleum along migration path (Gussow, 1954). Late forming gas displaces oil to up dip traps.

Even without forming gas caps, the later fluid tends to reach the crest of the trap because it is lighter and more buoyant. This pattern is generally true in most basins. Oils with lower gas oil ratios, and lower API gravities are found further away from the generation kitchen. Closer to the kitchen, lighter fluids, sometimes gas condensates are found.

There are a couple of other factors not obvious from the Gussow model. When the migrating fluid reaches bubble point, a separate gas (vapor) phase starts to form, as shown in the trap in the middle. The gas in the gas cap selectively dissolves the lightest fraction of the liquid as condensate. The remaining oil in the leg retains the heavier part of the incoming fluid. The physical properties in a dual phase trap would over time equilibrate to profiles shown in the figure below.

Fig. 2. Properties of fluid in a dual phase trap under thermodynamic equilibrium. Red and green lines are reservoir pressure of the gas phase, and oil phase respectively. The blue dashed lines show both phases are undersaturated away from the gas oil contact. GOR and API gravity both decrease with depth, in both phases.

The dashed lines are bubble point pressure (Pb) and dew point (Pd) pressures. The oil near the oil water contact is always the least saturated with gas, lowest in GOR and heaviest in gravity, as is the the oil that spills from the trap to the next. If the trap is leaking from the crest, the next trap above will receive a gas with lowest condensate content.

Phase separation happens due to pressure drop below saturation pressure, so it happens along the migration path as well as in traps. If it happens along the migration path, the gas would gradually "bubble" out from the migrating oil phase and either get stuck along the migration pathway as residual saturation (migration losses), because relative permeability for the minor phase is much lower or zero, or trapped in small traps below seismic resolution, along with the light ends of the oil fraction (condensate) dissolved in the lost gas. The remaining oil will have less solution gas, and become heavier, gradually.

Even in single phase traps, not only the late arriving lighter fluid goes to the top and displaces the heaver fluid to the flank due to gravity (charge disequilibrium). Gravity segregation and thermal equilibrium may enhance or alter the composition profiles. The figure below shows some observed GOR and API gravity profiles in single phase reservoirs in different basins.

Fig. 3. Fluid property (API gravity and GOR) profiles in single phase reservoirs, plotted against depth below crest of the trap. Both API gravity and GOR decreases toward the oil water contact.

Significant grading occurs in near critical fluids, as show in figure (c) on the right. These profiles are controlled by complex migration and filling process and PT history and some not well understood thermodynamic processes. Therefore we do not yet have the ability to predict the composition and properties of the fluids quantitatively during the migration process. There are also other secondary processes such as mixing, methane diffusion, water washing, stripping by non-HC gases, biodegradation that can significantly alter the fluid properties.

In the previous post below. I discussed an alternative "top down" approach to provide a probabilistic estimate of the fluid type and properties in a given prospect.

Select references:

Gussow, W.C., 1954. Differential entrapment of oil and gas - a fundamental principle. American Association of Petroleum Geologists, Bulletin 38, 816-853

Zhiyong He, and Andrew Murray, 2020. Migration loss, Lag and fractionation: Implications for fluid property prediction and charge risk. AAPG annual conference, Houston Texas, Sept 28-30, 2020.

Gas Oil Ratio Trends In Sedimentary Basins & PVT Behavior

2020-10-04T13:20:00.009-07:00

By: Zhiyong He, ZetaWare, Inc.

Gas oil ratios of oil and gas fields plotted against depth show interesting trends as shown below. The figure on the left is from large global datasets, and the one on the right is from an area in the North Sea. What are the reasons we may ask?

We have recently talked about this in several presentations (see references below). We concluded that this is a result of PVT behavior during migration. At shallower depth, the pressure is lower, and oil cannot dissolve as much solution gas as it can at a deeper depth. Likewise, gas can not dissolve much liquid at shallow depth.

This is supported by the relationship between saturation pressure (Psat) and GOR relationship based on some large PVT databases.

In this figure above, the blue shaded area are based on thousands of saturation pressure (bubble point on the left and dew point on the right) measurements. As HC generation windows are typically deeper than the blue band, migrating fluid toward shallow depth will reach saturation pressure at different depth depending on initial GOR of the fluid coming from the source rock. But once the Psat is reached, GOR will be limited by Psat, and follow the trend of the Psat-GOR relationship, resulting the distribution in figure 1.

This process not only changes GOR significantly from the initial fluid expelled from the source rock, it will also change the composition and API gravity. Below is a local example from a gas condensate system.

The initial fluid is found in a deeper reservoir (1) close to the kitchen, it is undersaturated as reservoir pressure is higher than initial Psat. In shallow trap along the migration path, the fluid is separated as a gas cap and an oil leg (2) and (3), with very different GOR and liquid API gravity. The fluid can further fractionate depending on whether migration is vertical or lateral, (4) and (5). Please also note that the saturation pressure itself is also modified by the same process, and becomes lower at shallow depths.

The same happens without a trap, or in between traps, along the migration pathway. In a gas condensate system like the above, the liquid phase that drops out is a) the heaviest fraction of the liquid first, and b) as droplets that are unable to form a continuous phase to migration along with the main gas phase.

Similarly, if the generated fluid is mainly oil, the GOR of the oil will follow the bubble point side of figure 2. Gas bubbles gradually drop out, or trapped in small traps that spill the liquid, reducing GOR along the way. As the gas phase that was dropped out retains the lightest ends extracted from the oil, the API gravity of the remaining oil decreases approaching shallower traps.

In any given trap, the HC fluid composition and therefore properties are not only a function of the initial generated fluid, but also on the pressure history and the complexity of the migration paths. The self regulating process of changing composition and in turn Psat itself, is much too complex to model at this time. Attempt to predict reservoir fluid properties solely based on source rock kinetics, as you may find in recent basin modeling literature, is misdirected in our opinion. A top down approach based on analyzing observed fluid properties in traps and trends in the geological context (Top Down PSA) is recommended.

Select References:

He, Zhiyong, and Andrew Murray, 2019, Top Down Petroleum Systems Analysis and Geospatial Patterns of Petroleum Phase and Properties. Celebrating the life of Chris Cornford (1948-2017): Petroleum Systems Analysis ‘Science or Art?’ The Geological Society, 24 - 25 April 2019

He, Zhiyong, and Andrew Murray, 2019, Top Down Petroleum System Analysis, Exploiting Geospatial Patterns of Petroleum Phase and Properties. AAPG Annual Convention, San Antonio, May 19-21, 2019 Download pdf from search and discovery

Murray, Andrew, and Zhiyong He, 2019, Oil vs. Gas: What are the Limits to Prospect-Level Hydrocarbon Phase Prediction? AAPG Hedberg Conference, The Evolution of Petroleum Systems Analysis, Houston, Texas, March 4-6, 2019 Download pdf from search and discovery

Zhiyong He, and Andrew Murray, 2020. Migration loss, Lag and fractionation: Implications for fluid property prediction and charge risk. AAPG annual conference, Houston Texas, Sept 28-30, 2020.

Biodegradation Much? Common Wisdom vs Statistics

2020-10-04T09:43:00.012-07:00

By: Zhiyong He, ZetaWare, Inc.

Many studies have shown that biodegradation can have significant impact on oil quality (eg. Larter et al, 2006, Yu et al 2002, Wilhelms, et al 2001). Peak degradation rates are around 30-40 degrees Celsius, which is roughly at about 1000 meters below mudline on average. How much is the risk (% probability) of finding heavy oil if we have a prospect at this depth? For practical purposes, lets say heavy oil means an API gravity lower than 20 API. This question was posted on LinkedIn as a poll, and the answers are anywhere between 10 to 90%, and the mode is around 70%. See the original post here and many thanks for all who participated.

Many of you know Andrew Murray and I have been working on examples and methods for Top Down PSA for the last few years. While looking for field/fluid data, I came across a paper titled "Properties of crude oils in Eastern Hemisphere" by Kraemer and Lane 1937. Having read the papers on biodegradation and developed a tool for modeling biodegradation in Trinity a while back, my first thought was that by 1930s the wells were probably very shallow and that many of them would be heavy oils. I was only right about the depths. It was very surprising that out of the 142 fields, less than 10% (13) had an API gravity of less than 20, as shown in the figure below.

The next paper I found was McKinney et al. 1966, which included fluid properties of 546 oil fields in the United States. The API gravity depth plot on the left shows the typical trend, that API in general decrease to shallower depth (Similar to figure 2, Larter et al, 2006). The figure on the right is the 359 fields shallower than 2000 meters. Only 18 (5%) of those are below 20. You can see most of the heavy oils are from California. Most of them are probably sourced by the well known Monterey Fm, which belongs to organo-facies A, perhaps that is (at least partly) the reason for the low gravity (and often high sulfur). Texas and Louisianan have a lot of shallow fields but have no oils below 20. Reservoirs formation of some of these outcrop at surface not too far from the fields.

Next I plotted a global data set of ~16,000 fields that are less than 2000 meters deep. 14% of the top 1000 meters are less than 20 API, and only 7% of those between 1000 to 2000 meters. The figure on the right include the deeper fields as well.

So what does this all mean? Globally the base rate of heavy oil at shallow depth where biodegradation is a concern is only 10%. If we were to only rely on a basin model that includes the biodegradation process, we are much more likely to predict a heavy oil at these depths.

It is possible that such field databases may not include some discoveries where oil is too heavy to be produced (therefore not counted). But I don't believe that is a significant enough number to change the statistics because this is such a large dataset, and if it is a prevalent problem there would have been a lot of literature on it. Note that some of the large heavy oil pools are included such as the Athabaska, Orinoco, Rubiales and Kern River.

We are aware of other factors that may prevent biodegradation - such as OWC configuration, nutrient supply, paleo-pasteurization, and timing of charge (duration of oil in reservoir), etc. Most of these are very hard to determine. The statistics above would imply the possibility that one or some of these factors are very prevalent in most basins. My own suspicion is that in in vast majority of cases/basins charging of shallow reservoirs are active at present day, due to migration lag regardless of when generation occurred.

The most important take away from this is that we should always check base rate (Bayesian analogs) when using basin modeling (bottom up) to predict fluid properties in prospects. Our models only include a small fraction of physical/chemical processes that happen in nature and much of the input of these models are assumptions due to lack of data, and lack of understanding.

Select references:

Wilhelms, A., S. R. Larter, I. Head, P. Farrimond, R. di Primio, and C. Zwach, 2001, Biodegradation of oil in uplifted basins prevented by deep-burial sterilization: Nature (London), v. 411, p. 1034– 1037.

Yu, A., G. Cole, G. Grubitz, and F. Peel, 2002, How to predict biodegradation risk and reservoir fluid quality: World Oil, April, p. 1– 5.

Larter, S. R. et al. 2006, The controls on the composition of biodegraded oils in the deep subsurface: Part II-Geological controls on subsurface biodegradation fluxes and constraints on reservoir-fluid property prediction. AAPG Bulletin, v. 90, no. 6 (June 2006), pp. 921–938.

Kraemer A. J. and E. C. Lane, 1937, Properties of typical crude oils from the fields of the eastern hemisphere. Department of the Interior. United States Government Printing Office.

McKinney C. M. E. P. Ferrero, and W. J. Wenger, 1966. Analysis of crude oils from 546 oilfields in the United States. Bureau of Mines. Untied States Department of the Interior.

Maximum Seal Limited Hydrocarbon Columns

2018-06-27T15:50:00.004-07:00

If a trap has a large enough closure height, the capillary top seal becomes the limit of the oil column height trapped when available charge is sufficient. The maximum column height, Ho, is given by the capillary equation:

where ρw and ρo are densities of water and oil respectively. γo is the interfacial tension between water and oil, θ the contact angle, g the acceleration of gravity and r the pore throat radius of the seal. In the case of a gas only column, one can simply substitute the subscript o with g, replacing the density and interfacial tension for gas. Since subsurface gas density is typically 1/3 to 1/2 of oil density, and γg is 1.5 to 2 times γo, the maximum gas column is about 20% to 30% smaller than for an oil column.

Under dual phase (gas cap over an oil leg) conditions, because γg is higher than γo, the capillary force against gas at the crest is stronger than that against the oil column at the GOC for the same pore throat radius at base of the seal. This leads to a combined maximum column larger than the maximum oil only column, as the gas cap cannot be completely leaked off.

At equilibrium, the capillary force, Pcg, at the crest is balanced by the buoyancy of the combined column:

Pcg = 2· γg · cos(θ)/r = Hg· g· (ρw-ρg) + Ho· g· (ρw-ρo)

while at the GOC, the capillary force, Pco, is balanced by the oil column:

Pco = 2· γo · cos(θ)/r = Ho· g· (ρw-ρo)

Combine the two equations and canceling out r and cos(θ), we have:

Under typical reservoir conditions, this results in a gas cap that is about 1/6 to 1/5 of the oil column.

The implication of this is that small gas caps may occur more frequently in large structures than we expect otherwise, as long as it is a dual phase system. This can also explain stacked pays that have gas caps at more than just the top reservoir. The Kikeh field in deep water Malaysia may be such a case. The "gas chimney" above the field, as well as the multiple pays indicate top seal control of the columns. Several of the stacked reservoirs have a small gas cap.

Even if the seal can support an oil column larger than the trap closure, gas cap over oil leg can still be the case as long as it cannot also support a full gas column, as described by my earlier post.

Using Hydrogen Index as Maturity Indicator

2016-04-29T20:54:00.002-07:00

The common practice in the oil industry is to make source rock maturity maps in terms of vitrinite reflectance (%Ro). However, vitrinite reflectance does not actually tell us to what degree the source rock has converted its generation potential to hydrocarbons. VR is merely a thermal stress (the combined effects of temperature and time) indicator, and a very poor one at that. To know how much of the kerogen has converted to hydrocarbons we not only need to know thermal stress, but also the kinetic behavior of the source rock, which depends on the organo-facies (Pepper and Corvi, 1995).

This figure shows the fractional conversion (transformation ratio) of kerogen of different organo facies as a function of vitrinite reflectance (thermal stress). We see at 0.8%Ro, each of the standard kerogen facies has experienced very different degree of conversion, 70%, 60%, 40%, 20% and 0% respectively.

Vitrinite Ro measurements are also not reliable and affected by many things, insufficient readings, suppression due to deposition/diagenetic environments (arguable by pressure as well), subjectivity and experience of the lab personnel, recycled sediments, samples from cavings, etc. In some marine environment, vitrinite macerals are very rare, and in older basins it simply does not exist.

I would like to recommend that we take a good look at one of the most commonly available measurements, hydrogen index (HI), as a maturity indicator. HI decreases from its initial immature value gradually to zero as the kerogen is converted to hydrocarbons. It is a direct measure of how much of the potential of the kerogen has left yet to be converted. Obviously initial values can vary from source rock to source rock, and even within a single source rock facies, but most of that can be filtered out by removing samples with low TOC, and by removing the lower values at each depth/location, as we typically have abundance of samples. This works very well in case of good marine source rocks, (most of the unconventional areas in the US), and especially at higher maturities.

Below is an example of mapping maturity using hydrogen index. This is the Bakken formation in the Williston basin. The color variation based on hydrogen index clearly shows the decrease of HI toward the deeper part of the basin. But the shape of the maturity window do not conform exactly to depth contours as the two more mature areas are also affected by thermal anomalies.

There are several advantages of using HI as a maturity indicator. Most importantly, it is a direct measure of conversion, so it accounts for the effect of kinetics. Two different source rocks may require different thermal stress to get to the same transformation, but we know exactly how much is left. Most good marine source rocks starts off with an initial HI of about 600 mg/gTOC, so we we see 300, the conversion is about 50%, and when we measure 50, we have over 90% conversion. Secondly, it works well where Ro data is poor or absent - in very rich source rocks, in carbonate source rocks, and old source rocks. It is abundant, inexpensive. The instruments are very accurate and consistent. There is no subjectivity involved.

The limits of oil vs gas prediction and the relationship to migration range and charge risk

2016-01-10T07:21:00.018-08:00

The description of a forthcoming specialist conference on basin modeling includes the text:

BPSM (Basin and Petroleum System Modeling) has become an indispensable tool in frontier basins to identify risk, reduce uncertainty, and identify new potential areas. This technology has become more important over time as a result of increased understanding of processes and the rapid development of computing power. Both the hardware and the software are evolving to quantify more complex processes. See here

One could only assess the veracity of the first part of this statement by carrying out a survey of companies to see how many use basin modeling as part of their evaluation process and how many consider it "indispensable". What I think can be said is that, if basin models are "identifying risk and reducing uncertainty", then that isn't showing up in exploration success rates. Industry surveys show that frontier basin success rates have not changed much over the last 20 years, remaining less than 10% for a commercial discovery. I would also dispute whether the ability to "quantify more complex processes" has made a difference - increasing the complexity of a model does not mean increased predictive power. In fact, often the reverse is true because of a greater tendency to fit the "noise" in the system rather than the "signal" (see Nate Silver's excellent book "The Signal and the Noise: The art and science of prediction")

Some of us think that the lack of improvement in the predictive power of basin models is because they only partly address the two things most affecting the chance of a prospect receiving charge: The kitchen yield in relation to the volume of the migration pathway to the trap and the interaction of trap closure height and seal capacity (it doesn't matter whether we are speaking of fault seal or top seal). This is a topic that will be taken up elsewhere but of note are the presentations and papers of Richard Bishop (e.g. Bishop et al., 2015) and two other entries in this blog on traps being filled/not filled and traps leaking and spilling at the same time (in relation to the latter, see also the paper by Sales et al. 1997).

I would like to highlight one other aspect of this discussion: the controls on the occurrence of oil or gas in a trap and our ability (or lack thereof !) to predict it. The intrinsic link between trap fill and phase has already been discussed by Bishop (2015) and Sales et al. (1997). However, in Sales et al. (1997) excess supply of both oil and gas is assumed as precursor to the discussion. Bishop (2015) considers that such excess is implied by the observation that nearly all traps are filled to their spill or leak point. I would argue that not only the total amounts of gas and oil are important here but their relative amounts, i.e, the gas to liquids ratio of the incoming fluid. This, together with the pressure and temperature of the trap and the mutual miscibility of the gas and oil (dependent on their compositions), determines whether the fill of any individual trap is single or dual phase.

Firstly, let's look at the relative masses of oil and gas expelled from the standard Pepper and Corvi (1995) source rock types (cumulative):

Although maturity is often thought of as the strongest control on the amounts of oil and gas expelled by a kitchen, source rock type is a stronger control within most of the maturity range. Furthermore, the amounts of oil and gas retained in the source rock vs. expelled has a major impact on expelled fluid gas to liquids ratio (GLR):

With the default P&C (1995) retained oil and gas amount settings (100 mg/g/TOC and 20 mg/g/TOC respectively) a marine clastic (B) kerogen expels a fluid with GLR of ~ 1100 scfs/bbl at 50% kerogen conversion and ~ 2200 scfs/bbls at full conversion. The GLR for fluvio-deltaic source rocks is very sensitive to the hydrogen index input chosen but for the standard kerogen is ~ 4400 scfs/bbl at 50% and 8800 scfs/bbl at full conversion (as a point of reference, the system-wide GLR for the Taranaki Basin of New Zealand is ~ 10,000 scfs/bbl).

Note that source rock type and expulsion/retention settings are INPUTS to basin models not OUTPUTS, so we can already see that basin modelling per se may not be good at predicting GLR

What happens when we put these fluids into a migration system (the culmination of which is our target trap) ? First lets look at how the mass/volume of oil vs. gas translates into phase and for this we need to use some standard bubble point and dew point curves: the ones in the diagram below are for UK North Sea oils and gases based on empirical observations (Glaso, 1980, England et al. 2002). There are many factors which affect the position and shape of these curves but that is a topic for another day and they are reasonable for our present purposes. The figure shows how the GLR at 50% kerogen conversion sits in relation to these curves for the P&C (1995) kerogen types:

The symbols here show the phase state of fluids in traps at different depths (assumes hydrostatic pressure) and the black bars highlight the intersection with the dew point/bubble point curves.

If we charge our system from a standard "B" type source (50%) conversion and all those fluids arrive in a trap, we can expect it to contain monophase oil if deeper than about 3100m and dual phase oil and gas if shallower than that. On the other hand, if our charge is from a standard "D/E" source all traps shallower than about 5100m would contain dual phase fluids. If we have a very gas prone type F (upper flood plain or paleozoic coals for example) we will hardly ever encounter anything other than gas. Similarly, if the source is a very oil prone lacustrine "C" or marine carbonate "A" (not shown in the figure) we will find mostly oil filled traps. Once again there are factors such as migration lag and in-trap alteration which will modify these conclusions in specific circumstances. However, their generality is borne out by the relative frequency of oil vs. gas discoveries in petroleum systems driven by one of the end-member source types. As examples one may cite the oil dominance in offshore Angola or the Bohai Basin of China (C type source) and the gas dominance on the outer Exmouth Plateau of Australia (F type source).

Now let's see how this plays out in a migration plumbing system. The diagram below shows a stylised series of three stacked reservoir/seal pairs with the top seal capacity varying both vertically and laterally for reservoirs 2 and 3 as shown. The actual values are not important here - it is the closure height to seal capacity ratio which matters - but the seal capacity does increase with depth as we might expect as the rocks compact. We are going to inject fluids with varying GLR into the base of the system (this whole exercise is done in Zetaware Trinity).

For example, if we inject enough of a fluid with a GLR of 3000 scfs/bbl it will begin to migrate vertically at the second trap up-dip and then laterally within reservoir 2 where it leaks again at the most up-dip trap to reach reservoir 3:

Here are the patterns of oil and gas obtained with varying input GLRs (nb: input GLR varies from chart to chart but is held constant during the migration fill process):

Note that we change from expressing GLR as a GOR (scfs/bbl) to a CGR (bbls/MMscf) once it exceeds 3000 scfs/bbl.

We can note several things from this:

1. At low input GLR gas does not displace oil up-dip: it can't do so if the system remains single phase
2. At very high input GLR we do not drop out an oil rim at any realistic depth. However for gas condensates with CGR of about 50 bbls/MMscf or higher oil rims do begin to drop out and may even lead to oil filled traps (the oil found here would be saturated with gas). Commercial oil pools can be (and are) found in dew point systems - although they may also sometimes be present as "nuisance" oil rims to commercial gas pools. The distribution of oil and gas in traps can be complex in all but the most oil or gas dominated systems
4. Discovering an oil or gas pool or even several does not necessarily define the system as "oil prone" or "gas prone". Compare the patterns of oil and gas occurrence for the 3000 scfs/bbl and 50 bbls/MMscf (= 20,000 scfs/bbl) input cases in the figure. This has not stopped some frontier basins with one or two oil or gas discoveries being labelled as "gassy" or "oily". In reality, a close look at the fluid properties and geochemistry is needed to make this call.

Next let's see what happens when we have a more realistic charge scenario, with the input GLR increasing as maturity of the source increases:

This is for a standard P&C type D/E source rock varying in maturity from a vitrinite reflectance equivalent of 0.85% to 1.6% Ro. At low to moderate maturity the trap fill is dominated by oil but volumes are also low so that only the first few traps in the migration system receive charge (in many cases we will never find these pools because they are deep and with low gas content will not have associated seismic DHIs).

There is naturally more gas in the migration pathway as the source matures. However, notice that even at maturities above 1.3% Ro (the conventional "top gas window") it is possible to find oil. We might, for example, drill the middle trap, find that it contains gas or oil+gas and then deepen the well to find oil. Again, the decision about what to do should hinge on what the fluid property and geochemistry data for the first discovered fluid tell us about the petroleum system. The highest proportion of oil containing traps occur when the source is low mature but this also means fewer trap overall have received charge. If only oil is commercial in our area of interest, we trade off reduced phase risk against an increased risk of finding nothing at all.

This raises the question of charge sufficiency: Bishop (2015) observes that charge is not the limiting factor for trap fill even in systems apparently charged by lean source rocks. I suspect that the source rock quality and yield has been underestimated in many of these "lean" source rock cases because the true source - often deep in the kitchen - has never been drilled. This would explain why some of the data of Sluijk and Nederlof (1984) represent instances where more hydrocarbons were found in traps than were generated in the corresponding kitchen.

Studies such as those of Sluijk and Nederlof (1984), Biteau et al. (2010) and others cited by Bishop (2015) suggest that the supply of HCs to a trap may commonly be 1 - 2 orders of magnitude higher than the amount needed to fill it. However, we cannot conclude from this that charge sufficiency for an individual trap is never a problem: The next figure shows the distribution of oil and gas in our artifical migration pathway for scenarios in which the kitchen expels 28, 57 and 115 mmbboe/km2. For the purposes of this example we assume no migration losses other than those required to fill each trap in the pathway. In reality, some hydrocarbons will also be lost in reaching the critical saturation threshold in the rocks around the source interval itself and in sub-seismic waste zones

In the low yield case many traps, including those we would be most likely to drill, never receive charge. Although basins without sufficient charge may be rare, for every basin there must be a point at which hydrocarbons run out - equivalent to the maximum migration "range". It might be further from the kitchen than we expect but it must exist. This should be thought of not as a sharp line (even though it is sometimes drawn that way on play chance maps) but rather as a zone of increased probability of drilling a dry hole (nb: this means drilling into an empty trap, not a partly filled trap, since this is statistically unlikely - see http://petroleumsystem.blogspot.com/2012/08/probability-of-trap-not-filled-to.html).

It is also interesting to consider the impact of phase separation and where it occurs along the pathway: If vertical migration happens early in the sequence phase separation also occurs earlier and the volumetric expansion of gas with reducing pressure means that the same mass of hydrocarbons equates to a much larger volume. This in turn means a greater lateral migration range compared to situations in which most migration happens in deeper carrier beds.

Thus, source rock UEP can be thought of as a kind of "master variable" which controls not only the chance of finding a hydrocarbon filled trap but also - for mixed oil and gas systems particularly - the phase of hydrocarbons found in that trap. Furthermore, and again as discussed in other posts in this blog, UEP is a major control on charge timing. Hence, we see that many things we traditionally expect a basin model to tell us - the chance of a trap receiving charge, the timing of charge relative to trap formation, the phase state of the trapped HCs - are highly dependent on the inputs we choose for the source rock.

We can see also that the pattern of migration depends on top and fault seal capacity of each intermediate trap along the migration pathway: whether it leaks at the crest, leaks through fault juxtaposition or through a non-sealing fault plane. Have we any realistic chance of estimating this for a whole, three dimensional migration pathway (four dimensional if you also expect fault seal capacity to change over time )? In his recent paper, Bishop (2015) discusses the inherent difficulty in determining whether a single trap is fill to the leak point, whether this is set by top or fault seal or by stratigraphic pinchout. I would add to this the observation that there have been many cases where the extent of compartmentalisation of discovered fields has been badly misread, even after extensive appraisal drilling. If we have trouble working out the plumbing of discovered and multiply drilled fields, what chance have we got of doing it for a whole migration pathway, especially since much of it will have, at best, coverage by 2D seismic ?

We can, I think, deal with this issue in several ways. Firstly, we can run multiple scenarios sampling the input space probabalistically or deterministically (or a combination as suggested by Bishop 2015). Secondly we can use our knowledge of compartmentalisation of discovered fields: There are several extant schemes or algorithms relating reservoir continuity to geological characteristics such as structural type, depositional environment, fault throw vs. net to gross, propensity for shale gauge etc. Nature is fractal so the same logic should apply to migration pathways: perhaps we can use such schemes to assign at least a relative efficiency to a migration pathway. Demaison and Huizinga (1994) referred to this with their low and high "impedance" systems but we can probably address the issue in a more detailed manner now, especially when we have 3D seismic attributes over some or all of the pathway. I do not believe we can do it deterministically in basin models because we cannot provide such models with inputs of sufficient detail to define specific migration pathways.

Finally, it must be said that the migration "cartoons" used in this post to illustrate concepts take no account of the lack of mixing in many hydrocarbon pools. Calculations of in-reservoir mixing times (see Smalley et al. 2004 for example) suggest that they are often longer than the typical filling time. This was supported by the observations of Stainforth (2004) who argued that compositional grading of petroleum pools is the norm rather than the exception. My own experience includes fields which are clearly unmixed, as reported for the Forties Field (England, 1990) but also some that show remarkable homogeneity over large inter-well distances. The latter cases can arise when a trap has access to charge from multiple directions so that a natural "averaging" process occurs: different migration paths have different lengths and volumes. If we apply the same logic to the intermediate traps along a migration pathway it follows that the migration lag effect on fluid properties and phase - though a fundamental aspect of the migration process - may not always be significant in practice.

With this post I hope to have made the point that the prediction of phase at the trap level is (a) fundamentally linked to the overall charge risk and therefore subject to similar uncertainties (b) inherently difficult in any mixed oil and gas charged petroleum system. I do not think this is a reason for pessimism or for not attempting to assign a phase risk to our prospects. Rather, given that it is hard to enough to find hydrocarbons in the first place - witness the low success rates in frontier basins - we should not worry about hydrocarbon phase at the trap level. If only one phase is likely to be economic we need to explore in basins where a dominance of that phase is likely, e.g. those likely to host very oil prone or very gas prone source rocks. Migration scenario testing can then help us home in on areas with the best chance of traps filled with the desired phase.

Once we are in a play or basin however, any hydrocarbon discovery is valuable, regardless of the phase: Examination of the fluids will tell us if we are in a fundamentally oil prone, gas prone or mixed system and guide our decision about what to do next - drill up-dip, down-dip, farm down or exit the play. Petroleum geochemistry has a major role to play here as compositional and isotope signatures exist for source type, relative maturity of expulsion, evaporative fractionation and secondary alteration by in-reservoir cracking, biodegradation and water-washing. All of these affect the GLR of trapped fluids.

All comments/criticisms etc. are welcome,

Rgds,
AM

References:

Bishop R.S. (2015). Implications of source overcharge for prospect assessment. Interpretation, 3, 93-107, AAPG

Biteau et al. (2010). The why and wherefores of the SPI-PSY method for calculating the world hydrocarbon yet-to-find figures. EAGE First Break, 28, 53-64

Demaison G. and Huizinga B. (1991). Genetic classification of petroleum systems. AAPG. Bull., 75, 1626-1643

England W.A. (1990). The organic geochemistry of petroleum reservoirs. Org. Geochem., 16, 415-425

England W.A. (2002) Empirical correlations to predict gas/gas-condensate phase behaviour in sedimentary basins. Org. Geochem., 33, 665-673

Glaso O. (1980) Generalised pressure-volume-temperature correlations. SPE 8016, 785-795

Pepper A.S. and Corvi P.J. (1995) Simple kinetic models of petroleum formation: Part 1: oil and gas generation from kerogen. Marine and Petroleum Geology, 12, 291-319 (see also part II and III of this series of papers)

Sales J.K. (1997) Seal strength vs. trap closure - a fundamental control on the distribution of oil and gas. In: Seals, traps and the petroleum system, AAPG memoir 67, 57-83

Sluijk D. and Nederlof M.H. (1984). Worldwide geological experienceas as as systematic basis for prospect appraisal. In: Demaison G and Murris R.J. eds. Petroleum geochemistry and basin evaluation. AAPG Memoir, 35, 15-26.

Smalley et al. (2004). Rates of reservoir fluid mixing: implications for interpretation of fluid data. In: Cubitt J.M., England W.A. and Larter S. (eds.) Understanding petroleum reservoirs: towards an integrated reservoir engineering and geochemical approach. Geol. Soc. Lon. Spec. Pub. 237, 99-113

Stainforth J.G. (2004). New insights into reservoir filling and mixing processes. In: Cubitt J.M., England W.A. and Larter S. (eds.) Understanding petroleum reservoirs: towards an integrated reservoir engineering and geochemical approach. Geol. Soc. Lon. Spec. Pub. 237, 115-132

See also the blog posts:
http://petroleumsystem.blogspot.com/2012/08/probability-of-trap-not-filled-to.html

http://petroleumsystem.blogspot.com/2012/07/can-trap-spill-and-leak-at-same-time.html

Shale Plays Need Seals Too

2015-06-07T07:05:00.001-07:00

In an earlier post, I argued that there may be significant lateral migration within shale reservoirs that can lead to higher maturity fluids produced from lower maturity areas, and even occasionally dry gas production in the oil window. In this post, I would like to propose that shale reservoirs also need seals to work.

Sedimentary rocks have a wide range of pore sizes. In a conventional reservoir, HC saturation builds up due to higher capillary pressure caused by the buoyancy of the column (Schowalter, 1979). Saturation is highest at the crest of the reservoir.

In a shale reservoir, there may not be an effective column. The increase in saturation and capillary pressure is caused by generation of hydrocarbons. However, it will also require the presence of tight rock facies (above, below and laterally) to prevent migration out of the shale due to the increased capillary pressure. From MICP studies on shales, we see that shales have a wide range of displacement pressures (Pd), from 200 psi to >10,000 psi. The typical tight facies may have a Pd of ~6,000 psi mercury-air (~320 psi oil-water). After saturating the adsorptive kerogen, the generated HC fluid begins to fill the zones with larger pores (the reservoirs with low Pd) first. As saturation in the reservoirs builds up due to continued generation, capillary pressure increases, as hydrocarbons invade progressively smaller pores. Saturation may reach >50% when the capillary pressure exceeds the Pd of the seal and migration out of the shale begins. Obviously, without the sealing facies, a homogeneous rock cannot retain high saturation.

HC wet or partially HC wet pores may initially build up saturation without increasing capillary pressure.

From the above reasoning, higher Pd for the seals inter-bedded with the more porous zones at various scales ( millimeters, inches, to feet ) leads to higher saturation in reservoir intervals. Some shale plays may not work due to the lack of seals rather than the lack of porosity. Most studies on shale plays to date have focused on the porosity of the reservoirs, which ranges between 5 and 15% typically. If you agree with the above argument, perhaps it is also important to look at the seals (with less than 5% porosity) inter-bedded with, above and below the reservoir zones.

Zhiyong He, ZetaWare, Inc.

Dry Gas, Wet Gas, Condensate and Condensables

2015-06-02T08:30:00.000-07:00

At a recent industry conference a poster summarised aspects of the petroleum systems in a particular basin. The authors noted that some reservoirs contained "dry gas" while others contained "wet gas". The boundary between the two was not defined but it was clear from the context that the distinction reflected the condensate content: gases having more than about 20 bbls/MMscf of condensate were classified as "wet".

Wet vs. dry gas definitions and terminology can be confusing so I thought it might be worth posting a summary here. Firstly, let's look at the composition of a typical gas condensate:

This one is from the textbook on the phase behaviour of reservoir fluids by Pedersen and Christensen (2007). We can define four groups of compounds: Methane (C1) being the only member of the first group then ethane (C2), propane (C3) and the butanes (normal and iso) making up the remaining "permanent" gases, the "condensate" range with compounds having from 5 to 14 carbon atoms and the "oil" range consisting of compounds with 15 or more carbon atoms. The "condensate" and "oil" ranges are labelled that way because fluids with most of their liquid mass in those carbon number ranges tend to be gas-condensates and oils in the sub-surface respectively. The "permanent" gases are in the gas state at standard surface conditions of 1 atm pressure and 15 C (60 F)

The ideal condensate-gas ratio or "CGR" of a fluid is the ratio of the liquids to the gas species, usually expressed as their respective volumes under standard surface conditions. In the US, "oil field" units are used so that CGR is barrels of condensate per million standard cubic feet of gas (bbls/MMscf). In Europe the units are more commonly cubic metre gas per cubic metre liquids (M3/M3).

When speaking of wet vs. dry gas in the conventional E and P realm, mostly we are referring to the CGR. What is a "significant" CGR depends on the context, particularly the value it may add to a gas development. For example, for an LNG development based on a 5 trillion cubic feet (TCF) resource, a CGR of 10 bbls/MMscf would yield 50 million barrels of condensate (in ideal circumstances).

There are few standard definitions in the literature but (a) the state of New Mexico defines a "gas" well as one producing a fluid with less than 10 bbls/MMscf of liquids (see http://164.64.110.239/nmac/parts/title19/19.015.0002.htm. item G6) and (b) the Encylcopedia Brittanica on-line defines a wet gas as anything containing more than 2.5 bbls/MMscf.

The standard reservoir engineering definition of a "dry gas" is one that yields ZERO liquids at surface temperature and pressure. On the phase (P vs T) diagram for such a gas, the isotherm of surface temperature does not intersect the phase curve at any point. Another way of saying this is that the cricondotherm for this fluid is lower than surface temperature. The corresponding definition of a "wet gas" is one that will yield some liquids at surface temperature and pressure but there is no pressure at which liquids will begin to condense at reservoir temperature. For a wet gas, the cricondotherm lies somewhere between the surface and reservoir temperature. A gas-condensate is a fluid for which a reduction in pressure at reservoir temperature will, at some point between initial reservoir and surface pressure, cause liquids to drop out.

In the realm of unconventionals, a somewhat different terminology - one used by the natural gas industry - is prevalent. Gas wetness refers to the content of C2+, i.e. everything except methane is the "wet" stuff. These are called the "natural gas liquids" or "NGL" even though ethane through to the butanes (C2 - C4) are not liquids under standard surface conditions. The condensate fraction (C5+) is a sub-fraction of the NGL and, just to be extra confusing, the NGL are also called the "condensables". This comes about because during natural gas processing methane - the ultimate "dry gas" - is separated from all other compounds by either cryogenic cooling or by absorption. The condensate fraction of the condensables (the C5+ bit remember !) can also be called "plant condensate" or "natural gasoline". Just for completeness, let me add that the "liquefied petroleum gas (LPG)" that we use in our barbequeue, car or for cooking at the vacation house is propane, butane or a mixture of the two.

Confused yet ? Now enter the geochemists: Gas wetness to a geochemist is defined as the molar ratio or percentage of the "wet" gases to the total of C1 to C5 gases with no consideration of the condensate species at all. . Errr...except that the pentanes - liquids in a cool room but gas in a hot room (37 C/97 F) - are generally included. Thus, we calculate the wetness of mud gas (gas while drilling) as the sum of C2-C5/ the sum of C1-C5 and express it as a percentage.

The wetness of a gas (geochemical definition) and condensate-gas ratio are clearly related. However, the relationship is specific to a particular petroleum system and also to processes which may have altered the fluid during movement from source to trap and/or in the reservoir. The figure below shows how gas wetness relates to CGR for several different gas-condensate fields, each hosting stacked accumulations. It is obvious that the gases in field 3 have a very different character to those in the other fields. In particular there is almost no change in gas wetness for fluids varying in CGR from ~ 30 to ~ 75 bbls/MMscf. This implies a decoupling of the gas and liquid fractions of the charge with, for example, a fixed amount of liquids being diluted to variable extent by a near fixed composition gas. This in turn might imply different source kitchens and migration routes or some migration fractionation process.

Finally, it is worth noting that the phase behaviour of a gas-condensate system also depends on the composition of the gas and liquids fractions. The figure below shows gas chromatograms for several condensates with different compositions and corresponding to fluids with different CGRs (nb: no chromatogram is available for fluid "F")

Note that condensate E is slightly contaminated with an olefin based synthetic drilling mud.

The pressure at which a gas condensate begins to separate into oil and gas in the subsurface is called the "dew point" or "saturation pressure (Psat)". This pressure is a function of the CGR but also of the mutual miscibility of the liquid and gas components. The most important factor is the composition of the liquids (condensate). If they are very light, they will more easily enter the vapour phase so that we have a higher CGR for a given dew point. Conversely, the heavier the liquids, the lower will be the CGR for the same saturation pressure. The dew point pressure vs. CGR data for the condensates A - G above are shown in this figure (along with some data from the UK North Sea petroleum system and a published emprical correlation for the same area. (nB; gas-liquid ratio - GLR - is displayed - CGR = 1/GLR *1,000,000)

Note the wide variation related to condensate composition. In particular, note that the very light condensates B and C (yellow dots) show low dew point pressures even though they have a high CGR (~ 95 bbls/MMscf, or GLR ~ 10,000). This reflects the high mutual miscibility of the liquids and gases for these fluids. It is often assumed that finding a high CGR gas in a shallow reservoir increases the likelihood of a finding oil in the system. In fact, the reverse is true: If the liquids are light enough to remain in the vapour phase even in high concentration, there are few oil range molecules present. Condensates of type "G" (43 bbls/MMscf) are much more likely to be found in association with oil.