Sunday, October 10, 2021

Downward Migration: Observation and Mechanisms

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:

  1. North Sea, Middle Jurassic and older reservoirs below the KCF 
  2. North Africa, the Ordovician sandstone reservoirs in Ghadames, Illizi and Murzuq basins, below the Silurian hot shale source cock
  3. Bohai, Oil fields in Paleozoic basement, “Buried Hills”, karst tomography, between and under the Tertiary grabens that contain the Oligocene source rock.
  4. Similarly, the Bach Ho (White Tiger) oilfield in fractured granite basement underlying Oligocene source rocks in Vietnam. 
  5. Woodbine (giant East Texas field) underlying the Eagle Ford source rock. 
  6. Muddy/Lakota reservoirs underlying the Mowry shale in Powder River basin. 
  7. Cambrian and Ordovician oil and gas fields charged from the Utica source rock above in Ohio and Indiana, of the Appalachian basin. 
  8. Hunton reservoirs charged from the Woodford above in the Anadarko basin. 
  9. Three forks reservoirs and the Bakken source rock above in Williston basin.
  10. The Norphlet plays in onshore Mississippi, Alabama and more recently the Eastern GoM deep water where the Smackover is the source and the seal.  
  11. The Tuscaloosa sands below the Tuscaloosa Marine Shale (TMS)
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. 

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.
  1. 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.
  2. Saturation at the boundary stays low as it is easier to expel due to the sharp gradient in Pc.
  3. 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)
  4. 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. 





Saturday, February 13, 2021

Where Did All The Gas Go?

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

Tuesday, December 22, 2020

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

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.

Friday, October 16, 2020

Composition Fractionation During Petroleum Migration

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.

Sunday, October 4, 2020

Gas Oil Ratio Trends In Sedimentary Basins & PVT Behavior

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

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. 

Wednesday, June 27, 2018

Maximum Seal Limited Hydrocarbon Columns

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 γothe 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· (ρwg) + Ho· g· (ρwo)

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

          Pco = 2· γo · cos(θ)/r = Ho· g· (ρwo)

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.

Friday, April 29, 2016

Using Hydrogen Index as Maturity Indicator

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.