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SPE 161144
Black Oil, Heavy Oil and Tar in One Oil Column Understood by Simple Asphaltene Nanoscience Douglas J. Seifert, Saudi Aramco, Murat Zeybek, Chengli Dong, Julian Y. Zuo, Oliver C. Mullins, Schlumberger
Copyright 2012, Society of Petroleum Engineers This paper was prepared for presentation at the Abu Dhabi International Petroleum Exhibition & Conference held in Abu Dhabi, UAE, 11–14 November 2012. This paper was selected for presentation by an SPE program committee following review of information contained in an abstract submitted by the author(s). Contents of the paper have not been reviewed by the Society of Petroleum Engineers and are subject to correction by the author(s). The material does not necessarily reflect any position of the Society of Petroleum Engineers, its officers, or members. Electronic reproduction, distribution, or storage of any part of this paper without the written consent of the Society of Petroleum Engineers is prohibited. Permission to reproduce in print is restricted to an abstract of not more than 300 words; illustrations may not be copied. The abstract must contain conspicuous acknowledgment of SPE copyright.
Abstract A Jurrasic oilfield in Saudi Arabia is characterized by black oil in the crest and with mobile heavy oil underneath and all underlain by a tar mat at the oil-water contact. The viscosities in the black oil section of the column are fairly similar and are quite manageable from a production standpoint. In contrast, the mobile heavy oil section of the column contains a large continuous increase in asphaltene content with increasing depth extending to the tar mat. The tar shows very high asphaltene content but not monotonically increasing with depth. Because viscosity depends exponentially on asphaltene content in these oils, the observed viscosity varies from several to ~ 1000 centipoise in the mobile heavy oil and increases to far greater viscosities in the tar mat. Both the excessive viscosity of the heavy oil and the existence of the tar mat represent major, distinct challenges in oil production. Conventional PVT modeling of this oil column grossly fails to account for these observations. Indeed, the very large height in this oil column represents a stringent challenge for any corresponding fluid model. A simple new formalism to characterize the asphaltene nanoscience in crude oils, the Yen-Mullins model, has enabled the industry’s first predictive equation of state (EoS) for asphaltene gradients, the Flory-Huggins-Zuo (FHZ) EoS. For low GOR oils such as those in this field, the FHZ EoS reduces to the simple gravity term. Robust application of the FHZ EoS employing the Yen-Mullins model accounts for the major property variations in the oil column and by extension the tar mat as well. Moreover, as these crude oils are largely equilibrated throughout the field, reservoir connectivity is indicated in this field. This novel asphaltene science is dramatically improving understanding of important constraints on oil production in oil reservoirs. Introduction Huge viscosity gradients in oil columns have an enormous impact on production. Oil flow rate depends inversely on visosity. Water sweep efficiency is greatly reduced when the viscoity ratio between oil and water exceeds ~5 causing water fingering instead of sweep. Tar mats at the OWC can preclude any aquifer support and any effectiveness of water injection in the aquifer. In spite of this overriding impact of viscosity gradients in black oil, heavy oil and tar, there has been very little understanding of the origin and distribution of these gradients. The reason for this glaring deficiency in petroleum science and engineering is simple to understand. These viscosity gradients in black oil/heavy oil systems are dominated by asphaltene gradients. Until recently, there has been no proper theoretical framework for understanding the distribution of asphaltene gradients in oil reservoirs. For example, the ubiquitious use of the cubic equation of state in reservoir models traces back to the Van der Waals Equation, which was developed to treat gas-liquid equilibria and has no provisions for handling colloidal solids such as the asphaltenes. The reason for the inability to treat asphaltenes in thermodynamic models to give asphaltene gradients is quite clear; there has been long-standing, orders-of-magnitude debate in the asphaltene science literature about the size of asphaltene molecules (Mullins 2010). If the size is unknown, then the effects of gravity are indeterminate, thus precluding the ability to model or predict gradients. In short, this deficiency has been resolved; the molecular and colloidal sizes of asphaltenes in crude oil and in laboratory solvents has been resolved and codified in the Yen-Mullins model (Mullins, in Press). Indeed, with the resolution, the Flory-Huggins-Zuo Equation of State (FHZ EoS) has been developed (Freed 2010) and proven to give asphaltene gradients in heavy oils (Pastor 2012), black oils (Betancourt 2007) and condensates (Elshahawi 2012).
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In this paper, a brief review of a new asphaltene formalism is given, and it is shown that the formalism is extremely simple for low GOR fluids. This simple formalism is applied to a, double plunging anticlinal oil field (4 way closure) that has black oil in the crest, mobile heavy oil in the flank, and a tar mat at the oil-water contact (OWC). (For this work mobile heavy oil is defined to have viscosity less than ~1000 cP; in many fields such oil is produced conventionally.) It is shown that the simple precepts herein properly account for detailed observations. Chemical analysis of the oils and tar show that the simple model captures the primary features of the data. Indeed, the treatment of such important properties such as viscosity of such a large volume of oil over such great distances with a simple, effective model might be called stunning. Certain unresolved issues are discussed within the context of the new foundation of asphaltene science. Asphaltene Nanoscience The Yen-Mullins Model. After a lengthy literature debate, the centroid and distribution of asphaltene molecular weights and sizes has largely been resolved by many different experimental methods and by many different groups around the world (Mullins, in Press, 2007). In addition, there is now extensive consensus on the nanocolloidal picture of asphaltenes. Most importantly, there are two, not one nanocolloidal species of asphaltenes, and this fact has a major bearing on asphaltene and viscosity gradients in oil reservoirs. The dominant molecular and colloidal structures are represented in a model with prototypical structures, now called the Yen-Mullins model (Sabbah 2011). (Professor Teh Fu Yen founded modern asphaltene science.) A schematic of the model is shown in Figure 1.
Figure 1. The Yen-Mullins model of asphaltene science showing predominant molecular and colloidal structures of asphaltenes (Mullins 2010). Left: At low asphaltene concentrations such as in condensates, asphaltenes are dispersed as molecules. Center: At larger asphaltene concentrations such as in black oils, asphaltene molecules self assemble forming nanoaggregates with about 6 molecules per nanoaggregate. Right: At even higher asphaltene concentrations such as in (mobile) heavy oils, asphaltene nanoaggregates self assemble forming asphaltene clusters with about 8 nanoaggregates. Nominal sizes of molecules, nanoaggregates and clusters are shown in Figure 1. Generally different fields are seen to exhibit these sizes within 10% variability. It is not currently know whether there are actual size differences of asphaltene nanoaggregates from one oil to the next, or whether apparent differences are actually from errors in measurements. It is important to note that asphaltene molecular properties from many different crude oils are seen to be rather uniform and not dependent on the specific crude oil (Mullins 2007). The salient components of this nanoscience model are as follows: asphaltene molecular weights of asphaltenes are ~750 g/mole with a range of 500 g/mole to 1000 g/mole. The predominant molecular achitecture has a large central ring system with peripheral groups (Figure 1, Left). At low asphaltene concentrations, asphaltene molecules are not aggregated and asphaltenes are dispersed as molecules; this applies to condensates (Elshahawi 2012). At higher concentrations such as in black oils, asphaltene molecules self assemble into nanoaggregates (roughly six molecules) with a single, central, disordered stack of aromatic groups (Figure 1, Center). At yet higher asphaltene concentrations for exampe found in mobile heavy oil, asphaltene nanoaggregates self assemble into clusters of roughly eight nanoaggregates (Figure 1, Right). These structures figure prominently when determining the direct effect of gravity on asphaltene gradients. The Flory-Huggins-Zuo Equation of State. With the size known for these distinct asphaltene species, a 1st-principles model can be developed for describing asphaltene gradients. The Flory-Huggins equation has been used extensively to describe asphaltene solubility and asphaltene phase behavior (Buckley 2007). Adding the gravity term to the Flory-Huggins equation enables calcualtion of asphaltene gradients in reservoirs. This modification yields the powerful Flory-Huggins-Zuo Equation of State (Zuo 2010).
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1. where OD(hi) is the optical density or oil color typically measured by downhole fluid analysis at height hi in the oil column, a(hi) is the asphaltene concentration at height hi, va is the molar volume of the asphaltene species of interest, either molecule, nanoaggregate or cluster (cf. Figure 1), v is the molar volume of the crude oil, g is earth’s gravitational acceleration, is the density contrast between the asphaltene and the liquid crude oil, a is the solubility parameter of the asphaltene and is the solubility parameter of the crude oil, k is Boltzmann’s constant, and T is temperature. The color of the crude oil scales linearly with asphaltene content as has been shown in numerous case studies. The first term in the argument of the exponential is the gravity term. For low GOR black oils and heavy oils, the gravity term dominates. This gravity term contains Archimedes buoyancy that has had two millenia of validation, vag. The asphaltenes are negatively buoyant (more dense) than the liquid crude oil. Newton’s force (F=ma) is mass times acceleration. With Archimedes buoyancy, it is not the total mass of the asphaltene species that matters but rather the effective buoyant mass, va (volume times density is mass). This buoyant mass is multiplied by g to obtain the gravitational force on the asphaltene particle. Of course, with larger asphaltene species (with larger volume va) the force is greater. In effect, the energy required to lift an asphaltene particle off the base of the oil column to some height h equals the graviational force, vag, multiplied by that height h. If gravity were the only determinant for the asphaltene distribution, then all asphaltene would be at the base of the oil column. As Boltzmann showed over 100 years ago, available thermal energy can lift particles to higher energy states. In a gravitational field, this amounts to thermal energy lifting particles off the floor to some higher height. The Boltzmann distribution describes the population distribution of ground (E=0) and excited (E) states and has the very simple form: exp{- E/kT}; this applies to all systems. Most importantly, the Boltzmann distribution represents an equilibrated state. Having particles in an excited state is not a transient condition; it is an equilibrium condition that will not change with time. One system that clearly shows the Boltzmann distribution is the earth’s atmosphere. If gravity were the only determinant for the distribution of air molecules, then all air molecules would be pulled to the surface of the earth and everyone would sufficate. Thermal energy lifts air molecules to elevations above the earth’s surface. Because air molecules are small (two heavy atoms in N2, and O2), then available thermal energy lifts air molecules to great height. Here, the air molecules are suspended in a vaccum, so the Boltzmann distribution is simply exp{-mgh/kT} where m is the weighted molar mass of air molecules, 80% N2 and 20% O2, and this is what is plotted in Figure 2 with T=298
o Kelvin. Such a simple prediction (Figure 2) closely matches observation.
Figure 2. Calculated atmospheric pressure from the equation exp{-mgh/kT} using the weighted average of the molecular mass of air molecules (and 298oK) closely matches observations. The prediciton for Mount Everest is slightly high because of the assumption of constant room temperature. Virtually the same equation applies to mobile heavy oil gradients substituting the negative buoyancy of asphaltene particles for mass (Mullins 2012).
kT
v
v
v
v
v
kT
hhgv exp
h
h
hOD
hOD 2 ha
2 haa
h
a
h
a12a
1a
2a
1
2 12
12
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For asphaltenes, one replaces “m” by va, thereby using Archimedes buoyancy (essentially because the liquid is incompressible so buoyancy is used) and the rest of the Boltzmann distribution expression remains the same as for the atmosphere. For low GOR crude oils, the asphaltene gradient is predominatly just given by the gravity term with all variables defined above. 2. Asphaltene molecules contain ~70 heavy atoms, nanoaggregates contain ~400 heavy atoms and clusters contain 3000 carbon atoms. Consequently, the gravitation gradient of asphaltenes depends critically on the particular asphaltene species. For a fixed thermal energy (temperature), asphaltene molecules are suspended to considerable height (but much less than air molecules with only two heavy atoms), nanoaggregates less, and clusters with ~3000 heavy atoms, the least height. Figure 3 shows the gradients for asphaltenes presuming molecules, nanoaggregates and clusters in a crude oil of 0.90 g/cc liquid phase density and T= 393o Kelvin.
Figure 3. The asphaltene gradient from the gravity term alone for the three asphaltene species from Figure 1 in the Yen-Mullins model. The large clusters (5.0 nm) show a rapid decline of % asphaltene with height, while the intermediate nanoaggregates (2.0 nm) and the small molecules (1.5 nm) show a very gradual decline. For low GOR crude oils, the gravity term tends to dominate the asphaltene gradient, while for large GOR crude oils, the solubility term in the FHZ EoS can dominate the asphaltene gradient (cf. Equation 1). In Equation 1, the second and third terms in the argument of the exponential incorporate the effects of entropy. This term tends to be small so can largely be ignored. The effect of entropy is to randomize or equally disperse the asphaltenes. The last term in the argument of the expontial of Equation 1 is the solubility term. In chemistry, “like dissolves like” and this chemical heristic is formalized in the solubility term. For example, water and alcohol are mututally soluble, both have OH groups. In contrast, oil with its CH groups is dissimilar to water with OH groups; oil and water are not mutually soluble. Here, being interested in gradients, it is the variation of the solubility term with height in the oil column that is important in establishing asphaltene gradients. The asphaltene solubility parameter is determined by asphaltene chemical properties and is invariant aside from a slight temperature dependence (Zuo 2010). If the composition of the liquid oil does not change in an oil column, then there is no variation of the solubility parameter or solubility term in Equation 1 versus height in the oil column, the gravity term still dominates. The primary factor which determines whether or not there is a variation of the liquid oil solubility parameter (for equilibrated oil columns) is the solution gas content. Solution gas is a colorless gas, asphaltenes are a dark brown solid – they are chemically very different and don’t dissolve in each other. Asphaltene does not partition to gas making gas colorless. Asphaltene does not dissolve well in crude oil with high solution gas. If there is a significant solution gas variation in an oil column, then there will be a large variation of the liquid oil solubility parameter with height, and this can dominate creation of an asphaltene gradient. Crude oils with low solution gas have largely homogeneous solution gas. For these crude oils the gravity term dominates. For crude oils with high solution gas (>700 scf/bbl) then there is a signifcant solution gas variation and the solubility parameter then becomes dominant creating the asphaltene gradient. The GOR variation is largely traceable
kT
hhgv exp
h
h
hOD
hOD 12a
1a
2a
1
2
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to compressibility. Crude oils with high solution gas are compressible. The hydrostatic head pressure of the oil column increases density at the base of the column; the light components get “squeezed out” of the base creating a solution gas variation. Low solution gas crude oils are incompressible. For these oils, the hydrostatic head pressure does not increase the oil density at the base of the column, thus there is no density gradient to drive a compositional gradient. Black Oil, Heavy Oil and Tar in a Single Reservoir Mobile Heavy Oil. A large anitclinal structure contains a black oil reservoir of low GOR (Mullins 2012). The asphaltenes underwent some instability forming a mobile heavy oil section of the oil column and a tar mat at the oil-water contact. Here, the focus is on the mobile heavy oil and tar mat in the field. A small fraction of the asphaltenes in the black oil were destabilized possibly by a gas or condensate charge. The destabilized asphaltenes formed clusters, which then accumulated at the base of the oil column. In a local section of the field spanning roughly 8 kilometers, the asphaltenes are in clusters and are equilibrated as shown in Figure 4, in total agreement with the reservoir scenario just discussed (Mullins 2012).
Figure 4. A local section of a large anticline with fluid data from three wells. (Top) The asphaltene content versus height agrees exactly with a simple equilibrium model with only one tightly constrained parameter, the size of the asphaltene cluster, here determined to be 5.2 nm, closely matching the nominal 5.0 nm clusters size in Figure 1. (Bottom) the viscosity matches a simple Pal-Rhodes model showing that viscosity is largely exponentially dependent on asphaltene content. Figure 4 shows that the simple gravity term of the FHZ EoS fits a huge increase in asphaltene content in a height of 120 feet. Such a large height in the oil column, and the corresponding 6 fold increase in the asphaltene content from top to bottom represents a stringent test of any model. The gravity term has only one tightly constrained parameter, the size of the asphaltene cluster. The fitted data gives 5.2 nm which is a very close match to the nominal 5.0 nm cluster size shown in Figure 1. Moreover, traditional modeling finds almost no asphaltene gradient because of the lack of any GOR gradient. That is, traditionally fluid modeling of the mobile heavy oil fails miserably and here is all but useless. Asphaltene data from eight wells around the entire circumference of the field is shown in Figure 5 (and includes the data from Figure 4). The fit is very good indicating that the simple Boltzmann distribution of asphaltene clusters accounts for the huge increase in asphaltene content in the height of the mobile heavy oil section for the entire circumference of the anticline. The FHZ EoS with the Yen-Mullins model represents a dramatic improvement of understanding mobile heavy oil columns. Moreover, the measured size of the asphaltene cluster closely matches that found in an Ecuador heavy oil column (5.0 nm) (Pastor 2012) and in a Gulf of Mexico heavy oil column (5.2 nm) (Nagarajan 2012).
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Figure 5. Data from 8 wells shows that the mobile heavy oil column around the entire circumference of the field matches the simple gravity term of the FHZ EoS with one tighly constrained parameter, the asphaltene cluster size (here 5.2 nm versus the nominal 5.0 nm in Figure 1). Moreover, the large height of the column yields a factor of 6 variation of asphaltene content. This field represents an extreme test of our simple model for mobile heavy oil – and represents the best data set there is (to the knowledge of the authors) to test thermodynamic modeling of mobile heavy oil. Figure 5 provides dramatic confirmation that asphaltene clusters are in thermodynamic equilibrium as given by the FHZ EoS. This fact indicates that this reservoir is in flow communication, that is, it is a connected reservoir (Pfeiffer 2011) Gross differences in asphaltene concentration in crude oil versus height at different reservoir locations could trigger convection which would then rapidly smooth out these differences. In additioin, it is plausible that distal parts of the field underwent similar gravitation accumulations of asphaltene to arrive at current observations of substantial uniformity around the flank. Asphaltene migration through reservoirs is a subject of current research, and the consequence of this migration is seen repeatedly. Above the mobile heavy oil section there is less data. Figure 5 shows that the asphaltene content of the highest samples shown here is a few percent asphaltene. It is known that the oil in the crest at a much great height in the column is a black oil. At the asphaltene concentration of a few percent (in this oil) is the point of transition from asphaltene cluster to asphaltene nanoaggregate. At lower concentrations than a few percent asphaltene, the asphaltenes are dispersed as nanoaggregates. Figure 3 shows that the gradient of nanoaggrgeates is not so great. Even at much greater heights in this oil column the oil remains a black oil. If asphaltenes were still within clusters even at low concentrations, then, the huge reduction of asphaltene concentration with height would continue until there would be almost no asphaltenes, as shown in Figure 3. In other words, if the huge gradient of asphaltene concentration with height for clusters continued throughout the entire height of the oil column, then there would be a condensate (no asphaltenes) practically on top of the mobile heavy oil section. This is not correct and is avoided by asphaltenes being present as nanoaggregates at lower concentrations – thus yielding much small gradients (cf. Figure 3). A critical component of the model of gravitation accumulation of asphaltenes is that the ratio of other SARA components are not changing or changing a rate an order of magnitude slower than the asphaltenes. Figure 6 shows lab data testing this idea.
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Figure 6. For the mobile heavy oils plotted in Figure 5, the primary variation is the asphaltene content. The variation of the other SARA fractions is a factor of 5 to 10 smaller. This data shows consistency with the finding of a simple gravitational equilibration of asphaltene clusters throught the height and circumference of the field. There is signifcant scatter in the SARA data, which is not that unusual. Nevertheless, the trends are clear; the primary variation in the mobile heavy oil samples is their asphaltene content. The variations of ratios of other SARA fractions are five to ten times smaller. Indeed, if any other fraction were to associate with asphaltenes, one would expect that to be resins. Clearly, bulk resins are not accompanying asphaltenes. This limits an age old model showing strong asphaltene-resin association. Figure 6 shows that bulk resins do not associate with asphaltenes. Indeed, very similar results were obtained in a lab centrifugation experiment of a live black oil.
Figure 7. Live, black oil centrifugation shows a similar result to that found in Figure 6.(Indo 2009) A giant asphaltene gradient (10x) was formed by centrifuging a live black oil with moderate GOR so both the gravity term and the solubility term contribute to the asphaltene gradient. Due to the lower asphaltene fracrtion in this black oil, the asphaltenes are present as nanoaggregates.
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Figure 7 shows the results from centrifugation of a live black oil (Indo 2009). This oil had a GOR of 800 scf/bbl so both the solubility term and the gravity term contribute to establishing the asphaltene and resin gradients. It took one month without seal loss to achieve equilibrium in this spin. The asphaltene gradient is ~10x while the resin gradient is 25% relative. Thus, bulk resins are not migrating with the asphaltenes. Analysis of the centrifugation results did conclude that a fraction of the heaviest resins do associate with the asphaltenes. The picture that emerges is that there is a molecular continuum in going from resins to asphaltenes. The criterion of n-heptane insolublity to define the asphaltenes captures most but not all of the crude oil fraction that self-assembles into aggregates (cf. Figure 1) (Indo 2009). The field data presented in Figs. 5 & 6 is consistent with the centrifugation data of Figure 7. The asphaltenes by far dominate the fraction of crude oil that self- assembles. Moreover, mobile heavy oils such as those found in this study have large asphaltene fractions that are all in asphaltene clusters. These clusters equilibrate in the gravitational field yeilding large gradient (cf. Figure 5). Tar Mat. At the base of the mobile heavy oil section, Figure 5 indicates that a tar mat is found. Several wells were drilled in order to interesect this tar mat for characterization. The organics were extracted from core sections at different depths in the tar mat and characterized in terms of SARA fractions. Figure 8 shows an example of the asphaltene content in the extracted tar versus depth for two separate wells on the same depth scale.
Figure 8. Asphaltene content versus depth for tar wells below the mobile heavy oil section in two wells (cf. Figure 5). The asphaltene content does not vary monotonically in even a single well. In addition, there is no lateral correlation of asphaltene content in contrast to the mobile heavy oil sections. In the tar mat, there are large increases and decreases of asphaltene with very small intervals of height. Figure 8 shows that there is a nearly random variation of tar with height in each of the two “tar” wells. The asphaltenes are not equilibrated versus height even in a single well, in huge contrast to the heavy oil sections where the asphaltene content is (or appears) largely equilibrated over the circumference of the mobile heavy oil flank. Figure 8 shows that there is no correlation of asphaltene concentration laterally for these two wells. The asphaltene content shows large increases and decreases over very short vertical distances. The mobile heavy oil section was shown to be characteized by a simple gravitational accumulation and equilibration of asphaltene versus depth. Figure 8 shows that the asphaltene content of the tar is not even monotonic with depth, not even approximating any equilibration. It is important to check whether the tar is simply an accumulation of asphaltene in oil or whether other SARA fractions show large variations in the tar as well. Figure 8 shows that there is huge variation of asphaltene content in the tar. Since the asphaltene content shows large variations, the other SARA fractions must also show variations; the sum of all SARA fractions must add to 1. Thus, it is the ratio of the other SARA fractions that is of interest. Figure 9 shows the ratio of asphaltenes to paraffins, aromatics to paraffins and resins to paraffins. By far the largest change is in the asphaltene to paraffin ratio. That is, the tar is primarily an addition of a variable amount of asphaltene to an oil with fixed ratios of paraffins (=saturates), aromatics and resins.
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Figure 9. The SARA fractions divided by paraffins versus asphaltene content for samples from two “tar” wells (saturates = paraffins). By far the largest variation is in the asphaltene/paraffin ratio, the aromatic/paraffin ratio and the resin/paraffin ratio exhibit much smaller changes. Consequently, the tar can largely be described as having a large, variable asphaltene content in an oil of fixed composition. Figure 9 shows that the tar is dominated by a change in asphaltene content in an oil of fixed SARA components. Indeed, the variation of the asphaltene content is enormous, in one well changing from ~30% to 65%. This picture is consistent with the origin of tar in this field being due to the gravitational accumulation of asphaltene at the base of the oil column and is consistent with the same conlcusion drawn for the origin of the mobile heavy oil column immediately above the tar column. The primary differences between the tar and the mobile heavy oil is that 1) the mobile heavy oils have asphaltene content less than ~30% (cf. Figure 8) while the tar has asphaltene content greater than ~30% and 2) the mobile heavy oil is vertically and laterally equilibrated while the tar is not equilibrated even over short vertical distances let alone large lateral distances. Two factors play an important role in equilibration; distance and viscosity. Figure 10 shows the viscosity as a function of asphaltene content in an oil phase of fixed composition (Lin 1995) This viscosity profile is not for that of the oil and tar presented in this paper but nevertheless shows the dependence of viscosity on asphaltene content.
Figure 10. Viscosity is shown to depend exponentially (or more) on asphaltene content for several different carbonaceous systems (Lin 1995). For the range of %asphaltene relevant to the mobile heavy oil and tar sections of the hydrocarbon column, the viscosity in this figure increases by a factor of 100,000,000. Note the hydrocarbon system is not the crude oil and tar from this field, but the dependence of viscosity on asphaltene is similar. Figure 10 illustrates a plausible reason why the tar is not equilibrated while the mobile heavy oil directly above the tar is equilibrated. “Equilibrated” here means that the asphaltene content is varying monotonically versus depth according to Equation 2. Figure 10 shows that the viscosity is high at 30% asphaltene content and that every 5% increase in asphaltene content is associated with another huge increase in viscosity. In short, the viscosity in sections of the tar mat are extraordinairly high precluding equilibration.
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Plausible Geoscenarios Matching field Overservation. This Jurrasic reservoir initially contained a black oil. A subsequent charge of a lighter hydrocarbon could have occured; in a normal burial sequence, the kerogen generates lighter hydrocarbon with longer times and greater temperature. The lighter hydrocarbon often goes to the top of the reservoir without good mixing (Stainforth 2004). This lighter hydrocarbon (could even be gas) can diffuse into the oil column and causing instability of the asphaltene (Elshahawi 2011; Zuo 2011). If the instability is not too great, the asphaltenes can migrate great distances in the reservoir in some cases going to the base of the reservoir. High concentrations of asphaltenes at or near the oil-water contact (OWC) can thus occur. One can imagine separate destablizing events yielding pulses of asphaltenes snowing down towards the OWC. At high asphaltene concentrations, the viscosity increases, and if the viscosity increase is also associated with a permeability restriction in the reservoir, then low viscosity tar can become trapped or “perched” below high viscosity tar. At some high asphaltene concentration, there might also be a phase transition yielding a phase very rich in asphaltene phase that might block pore throats. This is under investigation. If this occurs, this represents a second mechanism that can cause trapped lower viscosity tar underneath higher viscosity tar. For asphaltene concentrations below 30%, the viscosity is suffciently low that diffusion enables equilibration of the asphaltene in the mobile heavy oil section. Conclusions Traditional equation of state modeling of heavy oils has failed miserably due to 1) the former lack of knowledge about asphaltene colloidal sizes and 2) the lack of a proper model to treat colloidal solids in crude oil. The Yen-Mullins model of asphaltene nanoscience specifices the size of three distinct species of asphaltenes: molecules, nanoaagregates, and clusters. This nanoscience model enables accounting for the effects of gravity which has been incorporated into the Flory-Huggins- Zuo EoS for asphaltene gradients. Moreover, for mobile heavy oils, only the gravity term contrinbutes significantly to asphaltene gradients. In a field in Saudi Arabia, a mobile heavy oil rim has been fit using a simple exponential equation (the Boltzmann distribution) where the asphaltene content varies by a factor of 6 in the column. The simple Boltzmann distribution of asphaltene clusters accounts for this entire volume of mobile heavy oil. SARA analysis of the crude oil confirms that the mobile heavy oil column simply has added asphaltene into a crude oil of fixed composition. A tar mat below the mobile heavy oil does not show monotonic increase of asphaltenes towards the base. This is linked to the extraordinailry high viscosities within the tar mat. SARA analysis of the tar establishes that, similar to the mobile heavy oil, there is variable asphaltene added to a crude oil of fixed composition. Gravitational accumulation of asphaltenes at the low points of the reservoir is consistent with all observations. The application of new asphaltene science to heavy oils is seen to greatly improve understanding and prediction of reservoir observations. Refereneces Betancourt, S.S., Dubost, F.X., Mullins, O.C., Cribbs, M.E., Creek, J.L., and Mathews, S.G. 2007. Predicting Downhole Fluid Analysis Logs to Investigate Reservoir Connectivity. Paper IPTC 11488 presented at the IPTC Conference, Dubai, UAE, 4-6 December. Buckley, J.S. Wang, X., and Creek, J.L. 2007. Solubility of the least-soluble asphaltenes. In Asphaltenes, Heavy Oils and Petroleomics, ed. O.C. Mullins, E.Y. Sheu, A. Hammami, and A.G. Marshall, New York, New York, Springer. Elshahawi, H. Latifzai, A.S., Dong, C., Zuo, J.Y. and Mullins, O.C. 2011. Understanding Reservoir Architecture Using Downhole Fluid Analysis and Asphaltene Science. Paper SPWLA-FF presented at the 52nd Annual Logging Symposium, Colorado Springs, Colorado, 14-18 May. Elshahawi, H., Shyamalan, R., Zuo, J.Y., Dong, C., Mullins, O.C., Zhang, D. and Ruiz-Morales, Y. 2012. Advanced Reservoir Evaluation Using Downhole Fluid Analysis and Asphaltene Flory-Huggins-Zuo Equation of State. Paper prepared for the 53rd Annual Logging Symposium, Cartagena, Colombia, 16-20 June. Freed, D., Mullins, O.C., and Zuo, J. 2010. Asphaltene Gradients in the Presence of GOR gradients. Energy & Fuels 24 (7), 3942-3949. Indo, K., Ratulowski, J., Dindoruk, B., Gao, J., Zuo, J.Y., and Mullins, O.C. 2009. Asphaltene Nanoaggregates Measured in a Live Crude Oil by Centrifugation. Energy & Fuels 23, 4460–4469. Lin, M.S., Lumsford, K.M., Glover, C.J., Davison, R.R., and Bullin, J.A. 1995. The Effects of Asphaltenes on the Chemical and Physical Characteristics of Asphalt. In Asphaltenes: Fundamentals and Applications, ed. E.Y. Sheu and O.C. Mullins, pp. 155–76. New York: Plenum Press. Mullins, O.C., Sheu, E.Y., Hammami, A., and Marshall, A.G. ed. 2007. Asphaltenes, Heavy Oils and Petroleomics. New
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York, New York: Springer. Mullins, O.C. 2010. The Modified Yen Model, Energy & Fuels 24, 2179–2207. Mullins, O.C., Seifert, D.J., Zuo, J.Y., Zeybek, M., Zhang, D. and Pomerantz, A.E. 2012. Asphaltene Gradients and Tar Mat Formation in Oil Reservoirs. Paper WHOC12-182 presented at World Heavy Oil Conference, Aberdeen, Scotland, 10-13 September. Mullins, O.C., Sabbah, H., Eyssautier, J., Pomerantz, A.E., Barré, L., Andrews, A.B., Ruiz-Morales, Y., Mostowfi, F., McFarlane, R., Goual, L., Lepkowicz, R., Cooper, T., Orbulescu, J., Leblanc, R.M., Edwards, J., and Zare, R.N.. Advances in Asphaltene Science and the Yen-Mullins Model. Energy & Fuels, in Press. Nagarajan, N.R., Dong, C., Mullins, O.C. and Honarpour, M.M., Challenges of Heavy Oil Fluid Sampling and Characterization, Paper SPE 158450 presentented at the SPE ATCE, San Antonio, Texas, 8-10 October. Pastor, W., Garcia, G., Zuo, J.Y., Hulme, R., Goddyn, X., and Mullins, O.C. 2012. Measurement and EoS Modeling of Large Compositional Gradients in Heavy Oils, , Paper SPWLA-T presented at the 53rd Annual Logging Symposium, Cartagena, Colombia, 16-20 June. Pfeiffer, T., Reza, Z., Schechter, D.S., McCain, W.D. and Mullins, O.C. 2011. Fluid Composition Equilibrium; a Proxy for Reservoir Connectivity. Paper SPE 145703 presented at the SPE Offshore Europe Oil and Gas Conference and Exhibition, Aberdeen, UK, 6-8 September. Sabbah, H., Morrow, A.L., Pomerantz, A.E., and Zare, R.N. 2011. Evidence for Island Structures as the Dominant Architecture of Asphaltenes. Energy & Fuels 25, 1597-1604, {This paper, among others, introduced the name Yen-Mullins model after finding confirmation of a major component of the model.} Stainforth, J.G. 2004. New Insights into Reservoir Filling and Mixing Processes. In Understanding Petroleum Reservoirs: Toward and Integrated Reservoir Engineering and Geochemical Approach, ed. J.M. Cubit, W.A. England, and S. Larter, Special Publication, Geological Society, London. Zuo, J.Y., Mullins, O.C., Freed, D., and Zhang, D. 2010. A Simple Correlation for Solubility Parameters and Densities of Live Reservoir Fluids. J. Chem. Eng. Data 55 (9), 2964-2969. Zuo, J.Y., Elshahawi, H., Dong, C., Latifzai, A.S., Zhang, D., and Mullins, O.C. 2011. DFA Assessment of Connectivity for Active Gas Charging Reservoirs Using DFA Asphaltene Gradients. Paper SPE 145438 presented at the SPE ATCE, Denver, Colorado, 30 October – 2 November.
