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SPE 163291
Heavy Oil and Tar Mat Characterization Within a Single Oil Column Utilizing Novel Asphaltene Science Douglas J. Seifert (Saudi Aramco), Ahmed Qureshi, Murat Zeybek, Andrew E. Pomerantz, Julian Y. Zuo and Oliver C. Mullins (Schlumberger)
Copyright 2012, Society of Petroleum Engineers This paper was prepared for presentation at the SPE Kuwait International Petroleum Conference and Exhibition held in Kuwait City, Kuwait, 10-12 December 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 Jurassic oil field in Saudi Arabia is characterized by black oil in the crest, with heavy oil underneath and all underlain by a tar mat at the oil-water contact (OWC). The viscosities in the black oil section of the column are similar throughout the field 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. Both the excessive viscosity of the heavy oil and the existence of the tar mat represent major, distinct challenges in oil production. A simple new formalism, the Flory-Huggins-Zuo (FHZ) Equation of State (EoS) incorporating the Yen-Mullins model of asphaltene nanoscience, is shown to account for the asphaltene content variation in the mobile heavy oil section. Detailed analysis of the tar mat shows significant nonmonotonic content of asphaltenes with depth, differing from that of the heavy oil. While the general concept of asphaltene gravitational accumulation to form the tar mat does apply, other complexities preclude simple monotonic behavior. Indeed, within small vertical distances (5 ft) the asphaltene content can decrease by 20% absolute with depth. These complexities likely involve a phase transition when the asphaltene concentration exceeds 35%. Traditional thermodynamic models of heavy oils and asphaltene gradients are known to fail dramatically. Many have ascribed this failure to some sort of chemical variation of asphaltenes with depth; the idea being that if the models fail it must be due to the asphaltenes. Our new simple formalism shows that thermodynamic modeling of heavy oil and asphaltene gradients can be successful. Our simple model demands that the asphaltenes are the same, top to bottom. The analysis of the sulfur chemistry of these asphaltenes by X-ray spectroscopy at the synchrotron at the Argonne National Laboratory shows that there is almost no variation of the sulfur through the hydrocarbon column. Sulfur is one of the most sensitive elements in asphaltenes to demark variation. Likewise, saturates, araomatics, resins and asphaltenes (SARA); measurements also support the application of this new asphaltene formalism. Consequently, the asphaltenes are very similar, and our new FHZ EoS with the Yen- Mullins formalism properly accounts for heavy oil and asphaltene gradients. INTRODUCTION Previously there have been no proper thermodynamic models for treating asphaltene gradients in reservoirs. The reason of this deficiency is clear; nobody knew the size of asphaltene particles in oil. Without the size known (or mass, m), Newton’s gravitational force (F=ma where a is earth’s gravitational acceleration) acting on the asphaltenes is unknown. And without the ability to model the effect of gravity, one cannot model gradients in the oil reservoirs. This profound deficiency led to improper understanding of low gas-oil ratio (GOR) black oils and mobile heavy oils. It is widely acknowledged that condensates have large GOR gradients. That is, compressible reservoir fluids under the force of gravity exhibit density gradients due to the hydrostatic head pressure squeezing the base of the oil column to higher density. In turn, this density gradient of the compressible reservoir fluid provides the thermodynamic drive to yield a chemical compositional gradient and is accurately modeled by cubic equations of state (EoS). Conceptually, one might view this as the methane being squeezed out of the base of the compressible oil column. In contrast, low GOR black oils and heavy oils are incompressible. The cubic EoS correctly predicts that the GOR gradients for low GOR fluids are tiny. That is, the small methane fraction in these fluids is homogeneously distributed. The methane
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molecule is so small that thermal energy can lift it to great heights in the reservoir, in the same way that thermal energy can lift atmospheric molecules diatomic nitrogen (N2) and oxygen (O2) to great heights in the earth’s atmosphere. Likewise, the methane molecule is so small that Archimedes buoyancy forces are also very small precluding accumulation of dissolved methane near the top of the column. The cubic EoS also correctly predicts that the GOR of low GOR black oils and heavy oils is nearly homogeneous. Herein lays the source of the misunderstanding of black oils and heavy oils. The cubic EoS predicts that the GOR is homogeneous in low GOR black oils and in heavy oils. Consequently, the gross misinterpretation has been that low GOR black oils and heavy oils “should be” homogeneous (according to the cubic EoS); however, the cubic EoS, which is derived from the Van der Waals cubic EoS (developed in 1873) is designed to handle gas-liquid equilibria only. The cubic EoS is not designed to handle nanocolloidal solids of crude oil, the asphaltenes. (Nanocolloidal asphaltenes means that the asphaltene molecules aggregate into species that are nanometer length scale in crude oils.) The cubic EoS predictions for the asphaltenes are totally deficient. The reservoir engineering community has depended on the chemical engineering community for a proper EoS for reservoir fluids. The cubic EoS works so well for gas-liquid equilibria that its deficiency for solids has largely been ignored. In fact, it is not the gas content that defines black oils and heavy oils, it is the asphaltene content, but this fact has been obscured due to the inability to model asphaltenes. The chemical engineering community might have probed thermodynamic models for asphaltene gradients; except that the literature of the chemistry community describing specific chemical properties of asphaltenes had been in disarray. Incredibly, even so basic a property such as molecular weight of asphaltene has been the subject of recent debate, where it has varied over six orders of magnitude (Mullins 2010; Mullins 2011; Mullins et al., 2012a). Fortunately, asphaltene science has undergone a renaissance in recent years (Mullins 2010; Mullins 2011; Mullins et al., 2012a; Mullins et al., 2007). The molecular and colloidal sizes of asphaltenes have been resolved, and the industry’s first predictive EoS for asphaltene gradients has been developed and is discussed. Asphaltene Nanoscience and Equation of State In recent years, many of the molecular properties of asphaltenes, especially the distribution of asphaltene molecular weight, have been resolved (Mullins 2010; Mullins 2011; Mullins et al., 2012a, Mullins et al., 2007). In addition, the aggregate structures first found for asphaltenes in laboratory solvents are found to also apply to crude oils. In 2010, a simple representation of the molecular and colloidal structures of asphaltenes in crude oils and laboratory solvents was first published under the name “the modified Yen model.” Professor Teh Fu Yen was the founder of modern asphaltene science. This published model has been renamed the Yen-Mullins model (Ruiz-Morales 2009; Sabbah et al., 2011) and is shown in Fig. 1.
Fig. 1. The Yen-Mullins model of asphaltene science showing predominant molecular and colloidal structures of asphaltenes (Mullins, 2010). At low concentrations as in condensates, asphaltenes are dispersed as a true molecular solution (left); for black oils, asphaltenes are dispersed as nanoaggregates of molecules (center); for heavy oils, asphaltenes are dispersed as clusters of nanoaggregates (right).
With the size known, the effect of gravity can be determined. For the asphaltene EoS, the gravity term is given by Archimedes buoyancy in the Boltzmann distribution. That is, the asphaltene particles are negatively buoyant in the crude oil as described by Archimedes buoyancy. Combining the gravity term, with a chemical solubility term and an entropy term we have the EoS for asphaltene gradients, the Flory-Huggins-Zuo (FHZ) EoS. The Flory-Huggins theory has long been used to describe polymer solubility, here we use this theory, but we also include a gravity term to treat asphaltene gradients.
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Where OD(hi) is the optical density (color) measured by downhole fluid analysis (DFA) of the fluids at height hi in the oil column, a(hi) is the asphaltene fraction at that height, a is the molar volume of the relevant asphaltene species (cf. Fig. 1),
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is the molar volume of the oil, R is the ideal gas constant, T is temperature, a is the solubility parameter of the asphaltene, is the solubility parameter of the oil, g is earth’s gravitational acceleration, a is the asphaltene density (~1.2g/cc), is the oil density. The solubility parameter of the asphaltene can be obtained from literature values, and, in an oil column, the solubility parameter variation of the oil is primarily due to GOR variations. In the FHZ EoS, the first exponential factor is the solubility term, the second is the gravity term and the third is the Flory-Huggins entropy term. For low GOR oils, the gravity term dominates. For moderate GOR oils (1,000 scf/bbl), typically both the solubility term and the gravity term contribute to the asphaltene gradient. With this foundation, the understanding of many reservoirs is dramatically improved. The FHZ EoS has now been validated on light condensates to heavy black oil in many case studies. A review and expansion of the FHZ EoS for reservoir fluids of all types is given by Zuo, et al., (in progress). The primary work flow is to measure the fluid gradient accurately, especially within the solid, liquid and gas fractions of the reservoir fluids. This measurement is best performed with downhole presssure measurements and DFA (Mullins, 2008). DFA is a relative new product line in the petroleum industry. Once the gradients are accurately measured, the cubic EoS for gas-liquid gradients and the FHZ EoS for asphaltene gradients are employed to understand the nature of the fluid column. By this means, a variety of issues can be addressed including reservoir connectivity, viscosity profiles, and tar mat character. One system that clearly shows the Boltzmann distribution is the pressure gradient of 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 suffocate. Thermal energy lifts air molecules to elevations above the earth’s surface. Because air molecules are small (two heavy atoms in N2 and in O2), then available thermal energy lifts air molecules to great heights. Here, the air molecules are suspended in a vacuum, 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 Fig. 2 with T=298° Kelvin. Such a simple prediction (Fig. 2) closely matches observation.
Fig. 2. Calculated atmospheric pressure from the equation exp{-mgh/kT} using the weighted average of the molecular mass of air molecules (and 298 °K) closely matches observations. The prediction for Mount Everest is slightly high because of the assumption of constant temperature. Virtually the same equation applies to mobile heavy oil gradients substituting the negative buoyancy of asphaltene particles for mass. 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 atmospheric pressure. For low GOR crude oils, the asphaltene gradient is predominantly 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 ~3,000 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 ~3,000 heavy atoms, the least height. We are discussing equilibrium distributions; this means the distribution doesn’t change with time (like the atmospheric pressure gradient of the Earth), and the distribution does not change dramatically with a small change in applied conditions.
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CASE STUDIES Asphaltene Nanoaggregates. The first case study to prove the utility of Eq. 2 and ushered in the Yen-Mullins model and the FHZ EoS was a reservoir depicted in Fig. 3 (Mullins et al., 2007). This field is tilted due to differential uplift from buoyant salt, Fig. 3 left, and the reservoir contains a low GOR black oil. In the structuring process the reservoir was faulted and the largest uncertainty in the reservoir is whether these faults are sealing or transmissive. The asphaltene gradient was measured by DFA in the two primary stacked sands, the red and the blue sands and additionally in a section of the field with a different sand, the green sand. Equation 2 (the gravity term only from the FHZ EoS) was used to fit the asphaltene gradient in each sand. All data conformed to the asphaltenes being in the form of nanoaggregates (~2 nm particle size), the middle of the three species shown in Fig. 1. Since the asphaltene nanoaggregates have a very small diffusion constant, the asphaltenes are equilibrated (that is, they obey Eq. 2), then the conclusion is that reservoir must be connected in the sense of a production time frame. Barriers that impede fluid flow would also impede equilibration of the reservoir fluids (Pfieffer et al., 2011). Each sand, the red, blue and the green, contain equilibrated asphaltenes. Consequently, each of the sands are laterally connected, but not connected to each other; this has been shown correct with production data (Mullins et al., 2012c). Other case studies establish the existence of asphaltene nanoaggregates in black oils (Mullins et al., 2012c; Dong et al., 2012).
Fig. 3. Upper and lower horizons are depicted for a deepwater reservoir (Mullins et al., 2007). The stacked sands, the red and blue, are not in pressure equilibration, therefore are not connected. Each sand (including the green sand) contains equilibrated asphaltenes; they obey Eq. 2 for asphaltene nanoaggregates. Consequently, each sand is connected laterally and vertically, which has been proven in production (Dong et al., 2012). This case study proved that the asphaltene nanoscience and thermodynamic modeling presented herein are correct. Asphaltene Clusters. The first study to prove the existence of asphaltene clusters in oil reservoirs was in Ecuador (Pastor et al., 2012). Asphaltene clusters form at high concentration and therefore occur in heavy oils, Fig. 4. The clusters are large and settle preferentially lower in the oil column, thereby yielding gigantic gradients.
Fig. 4. The asphaltene concentration gradient is about a factor of 2 in ~50 ft for samples from a single well in a field in Ecuador (Pastor et al., 2012). Clusters form at high asphaltene concentration, here 10% to 20%. The relatively large cluster size, 5 nm, causes preferential accumulation of these asphaltenes towards the base of the column in accord with predictions of Eq. 2. Here, vertical connectivity is established and consistent production data.
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Recently, a similar heavy oil gradient was observed in deepwater Gulf of Mexico (Nagarajan et al., 2012) confirming the observations from Ecuador that heavy oils can contain asphaltene clusters equilibrated according to Eq. 2. In addition, there is a study that has shown the coexistence of nanoaggregates and clusters in a destabilized black oil (Mishra et al., 2012). Nevertheless, the case study on asphaltene clusters with by far the most comprehensive data has been obtained in Saudi Arabia (Seifert et al., 2012; Mullins et al., 2012b). The case study is important both from the vantage of understanding reservoirs containing mobile heavy oil but also from the vantage of advancing petroleum science in many ways. RESULTS AND DISCUSSION The subject of this study is a Saudi Arabian oil field that is a doublely plunging anticlinal structure (4 way closure) of Jurassic age that has black oil in the crest, mobile heavy oil along the peripheral flanks, and a tar mat at the oil-water contact (OWC) (Seifert et al., 2012; Mullins et al., 2012b). Figure 5 is an illustration of the field and a plausible time evolution of the fluid processes in the field to arrive at today’s observations. The sequence of events consistent with this scenario is: Initially the reservoir was filled with black oil, then (1) Some asphaltene instability occurred in the crest possible due to a late gas or condensate charge, (2) This instability event caused a fraction of the asphaltene nanoaggregates to form the 5 nm clusters. The clusters, large compared to nanoaggregates, fell in the gravitational field yielding an asphaltic oil at the base of the crest, (3) This heavy oil then underwent convective flow to the base of the oil column around the rim of the field, and (4) Diffusion of clusters then enabled equilibrium of the asphaltenes to be attained, in particular, in the heavy oil rim of the field. It is very important to note that this field has been shown to be connected through extensive production and well testing. Connectivity is a requirement for true reservoir fluid equilibrium (Pfieffer et al., 2011).
Fig. 5. A large anticline has black oil in the crest, a large gradient of heavy oil in the rim underlain by a tar mat. A time sequence of events consistent with this scenario is given. Figure 5 presents a simple time sequence to account for the many varied observations in this field. One of the most important observations is the equilibration of asphaltene clusters in the heavy oil rim of this field (cf. Fig. 1). In local sections of the field, Fig. 6 shows the asphaltene content vs. height in the heavy oil section exactly matches expectations from the Boltzmann distribution (Eq. 2).
Fig. 6. Two local regions of this giant field. Many fluid samples from three wells in the South (blue) exactly match the Boltzmann distribution for asphaltene clusters with only one tightly constrained parameter, the cluster size, here 5.2 nm. Data from two wells farther to the North (burgundy) show a consistent gradient but with less asphaltene than in the South. The crest of the field is toward the South accounting for greater asphaltene accumulation in the Southern rim.
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Figure 6 shows excellent agreement of the asphaltene content with the simple Boltzmann distribution in spite of frequent uncertainties in lab determinations of asphaltene content. The enormous gradient of a factor of six variation of asphaltene content in 200 ft of height matches the cluster model exactly. Traditional equations of state purport that there is no asphaltene gradient with height, therefore failing dramatically, with what is a routine occurrence in heavy oil. This cluster distribution in Fig. 6 (and Fig. 4) is equilibrated. That is, it is not changing with time; gravity pulls the asphaltene particles down but thermal energy lifts them up, the Boltzmann distribution of Eq. 2 gives the balance. The asphaltene clusters of Fig. 6 are seen to yield a much bigger gradient (2x in asphaltene concentration in 50 ft) vs. the gradient of Fig. 3 due to asphaltene nanoaggregates (2x in 3,000 ft). For black oils and heavy oils, the viscosity depends exponentially on asphaltene content, so these asphaltene gradients for heavy oils are very important for production considerations. Plotting the asphaltene content vs. height for fluid samples from eight wells around the perimeter of the field, Fig. 7, one finds that the entire heavy oil rim is equilibrated matching the Boltzmann distribution, although there is some localized scatter in the data. That is, when using all field data from this giant field there is not total equilibrium, as shown in Fig. 6. Nevertheless, the deviations are small from the equilibration curve depicted in Fig. 7. This may be due to a “recent” geological structuring event.
Fig. 7. A large, Jurassic anticline oilfield in Saudi Arabia has black oil in most of the field, has a mobile heavy oil rim, which is underlain by a tar mat (Seifert et al., 2012; Mullins et al., 2012b).The mobile heavy oil rim exhibits a gigantic asphaltene gradient (10x) as shown. The asphaltene gradient fits the gravity term of the FHZ EoS, with one tightly constrained adjustable parameter, the asphaltene cluster size, therefore the asphaltenes are equilibrated throughout this huge volume. The fitted data (above) gives a cluster size of 5.2 nm, very close to the published nominal size of 5.0 nm (cf. Fig. 1). This Jurassic field of Fig. 5 has experienced some asphaltene instability, most likely in the crest, but not too much instability as substantial asphaltene remains in the crude oil in the crestal portion of the field. The destabilized asphaltene accumulated in the flanks. The asphaltenes in the mobile heavy oil section equilibrated laterally over the entire circumference of the field and in a height of approximately 150 ft. Equilibration ultimately does have a diffusive component; the simple diffusion relation is Dt = x2 where D is the diffusion constant (which is very small for clusters), t is time, and x is mean distance of displacement. This field has a large value of x, consequently there is no way this field could equilibrate simply by diffusion. For example, it would take a trillion years for diffusion to equilibrate asphaltene clusters over 50 km! Figure 5 shows that convective flow can transport asphaltenes laterally, which is by far the longest distance that must be traveled. Vertically the asphaltenes need to diffuse hundreds of ft, which can be accomplished in the age of the reservoir. As noted above, convection must also play a large role in equilibrating this field. The field is Jurassic, and being equilibrated, this field identifies what a “long time” is for such reservoir process, that is ~200 million years. Asphaltene Chemical Identity Because of the former inability of petroleum models to treat asphaltene gradients, it has been claimed that large asphaltene gradients originate from some as-yet ill-defined, large chemical variation of the asphaltenes from the top to the bottom of the hydrocarbon column. In contrast, the model presented in the nanoscience section mandates that the chemical composition of the asphaltenes is the same throughout the column; it is only the concentration of the asphaltenes that changes. That is, in this
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model, the asphaltenes are equilibrated according to Eq. 2; which stipulates a concentration variation without a chemical compositional variation. This is in stark contrast to the expectation for the asphaltenes given the traditional view (with no corresponding specifics to give the massive heavy oil gradients) vs. the approach using the Yen-Mullins model coupled with the FHZ EoS that naturally gives large gradients. One of the best ways to determine differences in asphaltene chemical identity is to characterize the sulfur chemical speciation. Sulfur in asphaltenes, and in carbonaceous materials in general, can assume several different chemical forms. In particular, asphaltene sulfur can be in the form sulfide, thiophene and sulfoxide. Other organic forms of sulfur can occur but have not been observed in asphaltenes, these include sulfones and sulfonates. K-edge X-ray spectroscopy has been used in the characterization of sulfur in carbonaceous materials (George and Gorbaty, 1989). Figure 8 shows the sulfur K-edge spectra of several sulfur model compounds. The large single peak in each spectrum corresponds to the sulfur 1s-3p electronic transition; the energy of this peak depends significantly on the formal oxidation state of sulfur (George and Gorbaty 1989; Wiltfong, 2005).
Fig. 8. Sulfur X-ray spectra of various sulfur model compounds showing large and simple spectral differences for different types of sulfur (George and Gorbaty, 1989).
Fig. 9. Typical sulfur X-ray spectra for three asphaltenes showing very different chemical speciation of sulfur among the three chemical sulfur groups, sulfide, thiophene, and sulfoxide (Waldo et al., 1992). Typical sulfur X-ray absorption near edge structure (XANES) spectra for asphaltenes are shown in Fig. 9. To perform these measurements, it is required to have very high resolution data, such as that provided by synchrotrons. Sulfur is present in relatively low mass percent in the asphaltenes, typically a few mass percent. The sulfur chemistry can be variable while not impacting the asphaltene chemistry too much. For example, the Yen-Mullins model applies independent of the sulfur speciation (Mullins, 2010; Mullins, 2011; Mullins et al., 2012). Figure 9 shows three different asphaltenes that exhibit different sulfur speciation: Cal asphaltene; sulfide 16%, thiophene, 36%, sulfoxide 44%, Fr2 asphaltene; sulfide 20%, thiophene, 67%, sulfoxide 11%, and Tex asphaltene, sulfide 38%, thiophene, 54%, sulfoxide 4% (Waldo et al., 1992). Other
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sulfur oxides contribute small amounts. If the asphaltenes from the Saudi Arabian field are chemically variable, as the old view has claimed, then the sulfur XANES spectra could show this. Several asphaltene samples from the heavy oil section of the Saudi Arabian reservoir were taken to the Advanced Photon Source at the Argonne National Laboratory shown in Fig. 10 (left). The samples were mounted in the vacuum beamline shown in Fig. 10 (right) (Pomerantz et al., 2012).
Fig. 10. Left, the Advanced Photon Source Synchrotron where sulfur X-ray spectra were acquired for the Saudi Arabian samples. Right, the sample chamber, vacuum beamline and electronics utilized for acquisition of the sulfur X-ray spectral measurements (Pomerantz et al., 2012). Asphaltenes that were selected spanned almost the entire asphaltene concentration range in the heavy oil section, from ~2% to ~35% asphaltene. The spectra are shown in Fig. 11 (left), and the analysis (right).
Fig. 11. Left, Sulfur X-ray spectra of the Saudi Arabian asphaltenes. Right, analyses showing that the sulfur speciation is almost identical within error (of a few %). In all samples the thiophene sulfur dominates and with little chemical variation even though these samples have highly variable asphaltene concentration, 5%-35%. There is no evidence that the sulfur speciation is changing among the different asphaltene samples shown in Fig. 11. These results support the simple model presented herein, that the gradients observed in the heavy oil rim of this field are due to the concentration profile of asphaltene clusters as given by Eq. 2 and the Boltzmann distribution, and are not due to some heretofore unidentified, unknown chemical variation of asphaltenes in the oil column. Further chemical analysis of these samples is planned. We note that nitrogen XANES spectroscopy (Mitra-Kirtley et al., 1993) and carbon X-ray Raman spectroscopy (Bergmann et al., 2003) on asphaltene samples are known to show less chemical variation than sulfur, so sulfur is the element of choice for elucidating chemical variation of asphaltenes. SARA Analysis Heavy Oil. According to the simple model of the Boltzmann distribution, along with the simple description of events
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presented in Fig. 5, the heavy oil in the reservoir should simply be the black oil plus added asphaltene, where this addition took place due to asphaltene instability forming clusters that then end up at the base of the reservoir. We can check the heavy oil composition in terms of the SARA components: saturates, araomatics, resins and asphaltenes, shown in Fig. 12.
Fig. 12. For the heavy oil samples, on the Y-axis, the SARA ratios (aromatics vs. saturates, resins vs. saturates and asphaltenes vs. saturates) are plotted vs. the %asphaltene of the sample on the X-axis. For the heavy oils, the only ratio that changes with the %asphaltene is the asphaltene vs. saturate ratio, the other SARA ratios remain fixed. This means that the heavy oils are comprised of oil+asphaltene without any additional aromatics or resins. This is exactly the expectation for our simple model of the formation of heavy oil by asphaltene cluster addition to the black oil. Figure 12 shows the analysis of the SARA data of the heavy oils from this field. The asphaltene content increases dramatically in the heavy oil column from 2% to 35%. It is not sufficient to plot the different individual SARA percentages against the asphaltene fraction because as the asphaltene fraction increases greatly the other SARA fractions must decrease, thereby disguising dependencies. To illustrate dependencies of SARA fraction variation with asphaltene content, the ratios of SARA fractions vs. the saturate fraction are plotted. The only significant variation of the SARA ratios vs. asphaltene content is the only ratio involving the asphaltenes, the other ratios remained fixed. Consequently, the heavy oils do indeed appear to be composed of black oil plus asphaltene. This is consistent with the simple model indicated in Fig. 5 where the heavy oil is formed by accumulation of asphaltene clusters into black oil. Tar Mat. When the asphaltene content exceeds 35%, the oil forms a tar mat. Unlike the mobile heavy oil, the asphaltene content in the tar mat in this field is not even slightly equilibrated. The asphaltene content in the tar mat ranges from ~35% to ~60%, with large variations up and down in concentration within a few feet within individual wells, Fig. 13. The explanation put forth is that the tar mat represents a phase transition; that the asphaltene is not soluble in crude oil in all proportions.
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Fig. 13. %Asphaltene vs. relative depth for both the mobile heavy oil (top) and tar mat (bottom). The blue arrows identify the same depth in the two plots. The heavy oil shows a monotonic increase of asphaltene with depth around the entire periphery of the field, while in the tar mat, the %asphaltene is not monotonic in individual wells (specific plot markers). As the asphaltene continues to enter low points in the reservoir by accumulation of 5 nm asphaltene clusters, the crude oil can become supersaturated in asphaltene content. The asphaltenes deposit out onto the grain surfaces, essentially as heterogeneous nucleation. As this process continues, the pore throats become occluded and no further fluid exchange can take place. That is, tar mats are not equilibrated in a couple of feet (vertical) because the carbonaceous grain coating in the tar mat blocking the pore throats precludes any mass exchange necessary for equilibration, whereas the heavy oil is equilibrated over many tens of km (lateral). Precepts in this explanation are under study.
Fig. 14. SARA ratios vs. %asphaltene for samples from two separate tar mat wells. As with heavy oils, the SARA ratios show that the tar equals black oil plus asphaltene, exactly as expected for the simple scenario presented in Fig. 5. The tar mat is similar to the mobile heavy oil in that it evidently equals asphaltene plus black oil as shown in Fig. 14. The tar mat SARA analyses show that only the %asphaltene is variable, the other SARA fractions exhibit invariant ratios. This is consistent with tar mat forming from the addition of asphaltenes in the form of clusters to the base of the oil column. The mechanism shown in Fig. 5 is the most plausible scenario for this process. CONCLUSIONS Extensive fluid data from a Jurassic age Saudi Arabian oil field has been examined. The reservoir consists of a black oil in the crest with a heavy oil rim around the entire periphery of the field and underlain by a tar mat. Live fluid data from multiple depths in eight wells in the heavy oil section were analyzed along with fluid data from the tar mats in seven wells. The
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asphaltene gradient in the heavy oil column was found to be a factor of 10 in percentage content in 150 ft of height and largely invariant laterally. The nanoscience model of asphaltenes, the Yen-Mullins model, coupled with the FHZ EoS for asphaltene gradients accounts for this large asphaltene gradient with only one tightly constrained variable, the cluster size; found here to be 5.2 nm vs. the nominal 5.0 nm. This case study is perhaps the most stringent test case imaginable, encompassing an entire oil field, and the new nanoscience model and theory work very well. In addition, this equilibrium model predicts that the asphaltene chemical composition to be the same throughout the reservoir. A detailed test of this prediction was performed by examining the asphaltene sulfur chemical structures using X-ray spectra acquired at the APS synchrotron at the Argonne National Labs. Sulfur chemistry, a known sensitive test, confirmed the asphaltene compositional uniformity, that only the asphaltene concentration is variable, not its composition. Analyses of the SARA results also confirm primary precepts of this new asphaltene formalism. The tar mat was also explored; corresponding data from the tar mat is consistent with a simple asphaltene instability model to account for its basic measured properties. The confluence of new asphaltene science and new understanding of reservoirs is advancing each discipline and presents new opportunities of cross fertilization. REFERENCES Bergmann, U., Groenzin, H., Mullins, O.C., Glatzel, P., Fetzer, J. and Cramer, S.P. 2003. Carbon K-edge X-ray Raman Spectroscopy Supports Simple yet Powerful Description of Aromatic Hydrocarbons and Asphaltenes. Chemical Physical Letters, 369, 184-191. Dong, C., Petro, D., Latifzai, A.S., Zuo, J.Y., Pomerantz, A.E. and Mullins, O.C. 2012. Evaluation of Reservoir Connectivity from Downhole Fluid Analysis, Asphaltene Equation of State Model and Advanced Laboratory Fluid Analyses. Paper SPE 158838 presented at the SPE-ATCE, San Antonio, TX, 8-10 October. George, G.N. and Gorbaty, M.L.J. 1989. K-edge X-ray Absorption Spectroscopy of Petroleum Asphaltenes and Model Compounds. American Chemical Society, 111, 3182-3186. Mishra, V., Hammou, N., Skinner, C., MacDonald, D., Lehne, E., Wu, J.L., Zuo, J.Y., Dong, C. and Mullins, O.C. 2012. Downhole Fluid Analysis and Asphaltene Nanoscience Coupled with VIT for Risk Reduction in Black Oil Production. Paper SPE 159857 presented at the SPE-ATCE, San Antonio, TX, 8-10 October. Mitra-Kirtley, S., Mullins, O.C., Chen, J., van Elp, J., George, S.J. and Cramer, S.P. 1993. Determination of the Nitrogen Chemical Structures in Petroleum Asphaltenes using XANES Spectroscopy. Journal American Chemical Society, Vol. 115, 252. Mullins O.C., Betancourt, S.S., Cribbs, M.E., Creek, J.L., Andrews, B.A., Dubost, F. and Venkataramanan, L. 2007. The Colloidal Structure of Crude Oil and the Structure of Reservoirs. Energy & Fuels, 21, 2785-2794. Mullins, O.C., Sheu, E.Y., Hammami, A. and Marshall, A.G. ed. 2007. Asphaltenes, Heavy Oils and Petroleomics. New York, New York: Springer. Mullins, O.C. 2008. The Physics of Reservoir Fluids; Discovery through Downhole Fluid Analysis. Schlumberger Press, Houston. Mullins, O.C. 2010. The Modified Yen Model, Energy & Fuels, 24, 2179-2207. Mullins, O.C. 2011. “The Asphaltenes.” Annual Review of Analytical Chemistry, Vol. 4, 393-418. Mullins, O.C., Sabbah, H., Eyssautier, J., Pomerantz, A.E., Barré, L., Andrews, A.B., Ruiz-Morales, Y., et al. 2012. Advances in Asphaltene Science and the Yen-Mullins Model. Energy & Fuels, 26, 3986-4003. 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., Zuo, J.Y., Dong, C., Andrews, A.B., Elshahawi, H., Pfeiffer, T., Cribbs, M.E., Pomerantz, A.E. 2012. Downhole Fluid Analysis Coupled with Asphaltene Nanoscience for Reservoir Evaluation. Paper SPWLA-CCC presented at the 53rd Annual Logging Symposium, Cartagena, Colombia, 16-20 June.
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Nagarajan, N.R., Dong, C., Mullins, O.C. and Honarpour, M.M. 2012. Challenges of Heavy Oil Fluid Sampling and Characterization. Paper SPE-158450 presented at the SPE-ATCE, San Antonio, TX, 8-10 October. Pastor, W., Garcia, G., Zuo, J.Y., Hulme, R., Goddyn, X. and Mullins, O.M., 2012. Measurement and EoS Modeling of Large Compositional Gradients in Heavy Oils, Cartagena, Colombia. SPWLA Paper T presented at the 53rd Annual Logging Symposium, Cartagena, Colombia, 16-20 June. Pfeiffer, T., Reza, Z., McCain, W.D., Schechter, D.S. and Mullins, O.C. 2011. Determination of Fluid Composition Equilibrium – a Substantially Superior Way to Assess Reservoir Connectivity than Formation Pressure Surveys. Paper SPWLA-EEE presented at the 52nd Annual Logging Symposium, Colorado Springs, Colorado, 14-18 May. Pomerantz, A.E., Seifert, D.J., Qureshi, A., Bake, K., Craddock, P., Zeybek, M., Zuo, J.Y., Mitra-Kirtley, S., Kodalen, B., Bolin, T. and Mullins, O.C. Sulfur Speciation in Asphaltenes from a Compositionally Graded Oil Column. Manuscript in preparation. Ruiz-Morales, Y. 2009. Aromaticity in Pericondensed Cyclopenta-Fused Polycyclic Aromatic Hydrocarbons Determined by Density Functional Theory Nucleus-Independent Chemical Shifts and the Y-rule; Implications in Oil Asphaltene Stability. Canadian Journal of Chemistry, Vol. 87, 1280-1295. 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, Vol. 25, 1597-1604. Seifert, D.J., Zeybek, M., Dong, C., Zuo, J.Y. and Mullins, O.C. 2012. “Black Oil, Heavy Oil and Tar in One Oil Column Understood by Simple Asphaltene Nanoscience,” Paper SPE 158838 presented at the Abu Dhabi International Petroleum Exhibition & Conference, Abu Dhabi, U.A.E., 11-14 November. Waldo, G.S., Mullins, O.C., Penner-Hahn, J.E. and Cramer, S.P., 1992. “Determination of the Chemical Environment of Sulphur in Petroleum Asphaltenes by X-Ray Absorption Spectroscopy,” Fuel, Vol. 71, 53-57. Wiltfong, R., Mitra-Kirtley, S., Mullins, O.C., Andrews, B.A., Fujisawa, G., Larsen, J.W. 2005. “Sulfur Speciation in Different Kerogens by XNES Spectroscopy,” Energy & Fuels, Vol. 19, No. 5, 1971-1976. Zuo, J.Y., Mullins, O.C., Freed, D.E., Elshahawi, H., Dong, C. and Seifert, D.J. “Advances in the Flory-Huggins-Zuo Equation of State for Asphaltene Gradients and Reservoir Evaluation,” Submitted to Energy & Fuels.
