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WO2021048760A1 - Effet de viscosité des biopolymères sur la saturation en huile résiduelle dans des réservoirs de carbonate - Google Patents

Effet de viscosité des biopolymères sur la saturation en huile résiduelle dans des réservoirs de carbonate Download PDF

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Publication number
WO2021048760A1
WO2021048760A1 PCT/IB2020/058382 IB2020058382W WO2021048760A1 WO 2021048760 A1 WO2021048760 A1 WO 2021048760A1 IB 2020058382 W IB2020058382 W IB 2020058382W WO 2021048760 A1 WO2021048760 A1 WO 2021048760A1
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Prior art keywords
reservoir
oil recovery
hydrocarbon
trapping number
substrate
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Emad Walid AL SHALABI
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Khalifa University of Science, Technology and Research (KUSTAR)
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Khalifa University of Science, Technology and Research (KUSTAR)
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Priority to US17/633,575 priority Critical patent/US20220290540A1/en
Publication of WO2021048760A1 publication Critical patent/WO2021048760A1/fr
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    • E—FIXED CONSTRUCTIONS
    • E21—EARTH OR ROCK DRILLING; MINING
    • E21B—EARTH OR ROCK DRILLING; OBTAINING OIL, GAS, WATER, SOLUBLE OR MELTABLE MATERIALS OR A SLURRY OF MINERALS FROM WELLS
    • E21B43/00—Methods or apparatus for obtaining oil, gas, water, soluble or meltable materials or a slurry of minerals from wells
    • E21B43/16—Enhanced recovery methods for obtaining hydrocarbons
    • E—FIXED CONSTRUCTIONS
    • E21—EARTH OR ROCK DRILLING; MINING
    • E21B—EARTH OR ROCK DRILLING; OBTAINING OIL, GAS, WATER, SOLUBLE OR MELTABLE MATERIALS OR A SLURRY OF MINERALS FROM WELLS
    • E21B2200/00—Special features related to earth drilling for obtaining oil, gas or water
    • E21B2200/20—Computer models or simulations, e.g. for reservoirs under production, drill bits

Definitions

  • Oil can be recovered from a reservoir using primary and secondary recovery mechanisms. However, even after these mechanisms have been employed, up to 60% of original oil-in-place (OOIP) can remain in the reservoir.
  • EOR Enhanced oil recovery
  • the composition of some reservoirs can reduce the efficiency of even the most effective EOR technique, for example, polymer flooding.
  • hydrocarbon reservoirs that can be characterized with carbonate lithology, high temperature, high salinity, high heterogeneity with low permeability, and mixed-to-oil wettability can results in low oil recovery when polymer flooding EOR techniques are used.
  • Models can be used to simulate the oil recovery using polymer flooding techniques, however, these models may not accurately predict the performance of the polymer flooding behavior in reservoirs with certain compositions, for example, carbonate reservoirs. It may be desirable to have a model that more accurately simulates oil recovery using polymer flooding techniques in carbonate reservoirs.
  • Embodiments described herein are directed to a method of generating a prediction of an oil recovery from a reservoir induced by accomplishing an enhanced oil recovery technique that comprises injection of one or more fluids into the reservoir.
  • the method can include simulating the reservoir in a computer simulation, simulating injection of a first fluid into the reservoir in the computer simulation, and simulating the oil recovery from the reservoir induced by accomplishing an enhanced oil recovery technique in the computer simulation so as to account for an estimated change in aqueous viscosity that would be induced by injection of the first fluid into the reservoir.
  • the reservoir can be simulated having various properties.
  • the method can include the computer simulation simulating the reservoir in three dimensions and multiphase flow within the reservoir.
  • the first fluid can include various types of fluid.
  • the first fluid can include a polymer.
  • the method includes simulating injection of a second fluid into the reservoir in the computer simulation.
  • the first fluid is injection into the reservoir after the second fluid is injected into the reservoir in the enhanced oil recovery technique.
  • the second fluid includes water.
  • the method includes calculating a trapping number (N T1 ) for the reservoir that accounts for the first fluid within the reservoir, wherein the trapping number is defined as where v is a Darcy velocity of a core sample comprising the same or similar material as the reservoir, m is an aqueous phase viscosity, and s ow is an interfacial tension between oil and water.
  • a method includes generating a model of a hydrocarbon reservoir having parameters, determining a critical trapping number for the hydrocarbon reservoir based in part on a substrate of the hydrocarbon reservoir, determining a trapping number of the substrate for a given injection volume, determining whether the trapping number has exceeded the critical trapping number, and modifying, based in part on the determination that the critical trapping number has been exceeded, one or more parameters of the model of the hydrocarbon reservoir.
  • generating the model of the hydrocarbon reservoir includes generating the hydrocarbon reservoir.
  • the hydrocarbon reservoir can be generated in three dimensions and modeling multiphase flow within the hydrocarbon reservoir.
  • hydrocarbon reservoir can include adjustable parameters.
  • the parameters of the hydrocarbon reservoir can include residual oil and relative permeability.
  • modifying one or more parameters of the model comprises modifying the residual oil and relative permeability parameters.
  • determining a trapping number of the substrate for a given injection volume includes simulating injection of a first fluid into the model of the hydrocarbon reservoir.
  • the first fluid includes a polymer.
  • the method further includes determining expected oil recovery for a reservoir having a substrate that is the same as or similar to the substrate of the model of the hydrocarbon reservoir. In some embodiments of the method, determining the expected oil recovery includes determining the expected oil recovery using an enhanced oil recovery technique.
  • a method of simulating oil recovery from a biopolymer injection cycle in a hydrocarbon carbonate reservoir includes: determining a critical trapping number representative of a simulated hydrocarbon carbonate reservoir based in part on a composition of a reservoir substrate; determining whether, for a given injection volume, a trapping number of a substrate of the hydrocarbon carbonate reservoir has exceeded a critical trapping number; and modifying the residual oil and relative permeability parameters of the simulated hydrocarbon carbonate reservoir based on the determination that the critical trapping number has been exceeded.
  • the method further comprises simulating the hydrocarbon carbonate reservoir.
  • the hydrocarbon reservoir can be simulated prior to determining the critical trapping number.
  • the hydrocarbon carbonate reservoir is simulated in three dimensions.
  • the hydrocarbon carbonate reservoir can include multiphase flow within the hydrocarbon carbonate reservoir.
  • the method prior to determining whether the trapping number of the substrate has exceeded the critical trapping number, the method further comprises determining the trapping number of the substrate for the given injection volume.
  • the trapping number (N T1 ) is defined as where v is a
  • determining the trapping number comprises simulating injection of a first fluid into the simulated hydrocarbon carbonate reservoir.
  • the first fluid comprises a polymer.
  • the method further includes determining expected oil recovery for a reservoir having a substrate that is the same as or similar to the substrate of the simulated hydrocarbon carbonate reservoir. In some embodiments of the method, determining the expected oil recovery includes determining the expected oil recovery using an enhanced oil recovery technique.
  • a computer system includes a processor and reconfigurable memory.
  • the processor and reconfigurable memory operable to: determine a critical trapping number representative of a simulated hydrocarbon reservoir based in part on a composition of a reservoir substrate; determine whether, for a given injection volume, a trapping number of the substrate has exceeded the critical trapping number; and modify residual oil and relative permeability parameters of the simulated hydrocarbon reservoir based on the determination that the critical trapping number has been exceeded.
  • the processor and reconfigurable memory are further operable to simulate the hydrocarbon reservoir.
  • the hydrocarbon reservoir is simulated in three dimensions and includes multiphase flow within the hydrocarbon reservoir.
  • the method further comprises determining the trapping number of the substrate for the given injection volume.
  • the trapping number (N T1 ) is defined where v is a Darcy velocity of a core sample comprising the same or similar material as the reservoir, m is an aqueous phase viscosity, and s ow is an interfacial tension between oil and water.
  • the processor and reconfigurable memory are further operable to, determine expected oil recovery for a reservoir having a substrate that is the same as or similar to the substrate of the simulated hydrocarbon reservoir. In some embodiments of the computer system, the expected oil recovery is determined for oil recovery using an enhanced oil recovery technique.
  • FIG. 1 illustrates an example computer system for generating and modifying a hydrocarbon reservoir model
  • FIG. 2 is a flowchart illustrating a process for modifying a simulated hydrocarbon reservoir for use with the computer system of FIG. 1;
  • FIG. 3 is a flowchart illustrating a process for modifying a simulated hydrocarbon reservoir for use with the computer system of FIG. 1;
  • FIG. 4 is an example simulated hydrocarbon reservoir for use with the computer system of FIG. 1;
  • FIG. 5 is a graph showing history matched cumulative oil recovery for waterflooding followed by polymer flooding cycles
  • FIG. 6 is a graph showing the effect of inaccessible pore volume (IPV) on tertiary oil recovery by polymer flooding
  • FIG. 7 is a graph showing the effect of polymer adsorption on tertiary oil recovery by polymer flooding
  • FIG. 8 is a graph showing the effect of permeability reduction on tertiary oil recovery by polymer flooding
  • FIG. 9 is a graph showing the effect of shear rate coefficient on tertiary oil recovery by polymer flooding
  • FIG. 10 is a graph showing the effect of makeup water hardness on tertiary oil recovery by polymer flooding;
  • FIG. 11 is a graph showing the remaining oil saturation as a function of capillary number;
  • FIG. 12 is a graph showing a modeled capillary desaturation curve (CDC) for both sandstone and carbonate rocks;
  • FIG. 13 is a graph showing relative permeability curves before and after exceeding the critical trapping number
  • FIG. 14 is a graph showing the effect of trapping number on tertiary oil recovery by polymer flooding.
  • FIG. 15 is a graph showing history matched cumulative oil recovery for waterflooding followed by polymer flooding cycles.
  • Oil recovery techniques can be used to extract oil from oil reservoirs. However, primary and secondary oil recovery methods can still leave a large amount of oil remaining in a reservoir. For example, up to 60% of original oil-in-place (OOIP) can remain in a reservoir.
  • Tertiary recovery techniques e.g., enhanced oil recovery (EOR)
  • EOR enhanced oil recovery
  • EOR techniques can be used to extract some of the OOIP, for example, by targeting unswept oil and/or capillary trapped oil saturations.
  • EOR techniques can be or include solvent, thermal, chemical, and/or any suitable technique.
  • Polymer flooding is an EOR technique that can increase oil sweep efficiency, for example, by targeting by-passed oil and/or recover residual capillary-trapped oil.
  • Polymer flooding is often used in sandstone reservoirs that can have properties including temperatures below 60° C, low formation salinity ( ⁇ 100 g/L), and/or moderate to high permeability (>40mD).
  • certain reservoirs can have properties that reduce the effectiveness of polymer flooding.
  • hydrocarbon reservoirs can have properties including carbonate lithology, high temperature, high salinity, high heterogeneity with low permeability, and mixed-to-oil wettability.
  • Modeling of polymer behavior in carbonate reservoirs can be used improve the efficiency of polymer flooding in real world situations.
  • polymer flooding models for sandstone reservoirs may not include the trapping number effect on residual oil saturation.
  • modeling the trapping number effect on residual oil can increase the accuracy of the model.
  • a polymer flooding model that includes the trapping number effect on residual oil saturation can be developed.
  • the polymer flooding model can be validated, for example, by history matching biopolymer corefloods with the model.
  • FIG. 1 an example computer system 100 for generating and modifying a hydrocarbon reservoir model is shown.
  • the example embodiment includes a model generating module 102, a determining module 104, a comparing module 106 and a model modifying module 108.
  • Computer system 100 may represent a single component, multiple components located at a central location, or multiple components distributed throughout multiple locations.
  • computer system 100 may represent components of interconnected computer systems that are capable of communicating information between one another.
  • computer system 100 may include any appropriate combination of hardware and/or software suitable to provide the described functionality.
  • Processor 110 is operable to execute instructions associated with the functionality provided by computer system 100.
  • Processor 110 may comprise one or more general purpose computers, dedicated microprocessors, or other processing devices capable of communicating electronic information.
  • Examples of processor 110 include one or more application-specific integrated circuits (ASICs), field programmable gate arrays (FPGAs), digital signal processors (DSPs) and any other suitable specific or general purpose processors.
  • ASICs application-specific integrated circuits
  • FPGAs field programmable gate arrays
  • DSPs digital signal processors
  • Memory 112 stores processor instructions, inventory requests, reservation information, state information for the various components of inventory sorting system 100 and/or any other appropriate values, parameters, or information utilized by computer system 100 during operation.
  • Memory 112 may represent any collection and arrangement of volatile or nonvolatile, local or remote devices suitable for storing data. Examples of memory 112 include, but are not limited to, random access memory (RAM) devices, read only memory (ROM) devices, magnetic storage devices, optical storage devices or any other suitable data storage devices.
  • the model generating module 102 can generate a 3D model of an oil reservoir based on data collected during oil recovery techniques.
  • the model can be used to simulate the process of removing the oil from the oil reservoir using primary, secondary, and/or EOR techniques.
  • the model can be used to simulate waterflooding and/or polymer flooding of an oil reservoir.
  • the model may also be used to predict the amount of oil recovery using secondary and/or EOR techniques.
  • the model can be or include a 3D multiphase-flow, transport, and chemical-flooding simulator and/or a carbonate core model.
  • Determining module 104 can determine one or more parameters for the reservoir model generated by model generating module 102. In various embodiments, the determining module 104 can determine a critical trapping number based on material properties of the modeled reservoir. For example, a critical trapping number can be determined for a carbonate reservoir model and/or a sandstone reservoir model. In further embodiments, the determining module 104 can determine a trapping number for a given injection volume of polymer.
  • Comparing module 106 can compare the critical trapping number with the determined trapping number. For example, the comparing module 106 can compare the critical trapping number with the determined trapping number to determine whether the critical trapping number has been exceed. Based on the comparing, one or more parameters of the model can be adjusted to more accurately reflect the real world behavior of the reservoir.
  • the modifying module 108 can modify one or more parameters of the model based on the comparing of the critical trapping number with the determined trapping number. For example, if the comparing module 106 determines the trapping number has exceeded the critical trapping number, the residual oil and relative permeability parameters of the model can be modified to more accurately reflect the real world behavior of the reservoir. The modifying of the model can be used to increase the accuracy of the model.
  • the computer system 100 can include a communication interface module 114 that facilitates communication between modules and/or components of the computer system 100.
  • communication interface module 114 may be responsible for facilitating either or both of wired and wireless communication between the modules and/or components of the computer system 100.
  • the computer system 100 may communicate using communication protocols such as 802.11, Bluetooth, or Infrared Data Association (IrDA) standards.
  • generating module 102, determining module 104, comparing module 106, modifying module 108, and/or communication interface module 114 may each represent any appropriate hardware and/or software suitable to provide the described functionality.
  • computer system 100 may, in particular embodiments, represent multiple different discrete components and any or all of resource generating module 102, determining module 104, comparing module 106, modifying module 108, and/or communication interface module 114 may represent components physically separate from the remaining elements of computer system 100.
  • any two or more of generating module 102, determining module 104, comparing module 106, modifying module 108, and/or communication interface module 114 may share common components.
  • generating module 102, determining module 104, comparing module 106, and/or modifying module 108 represent computer processes executing on processor 110 and communication interface module 114 comprises a wireless transmitter, a wireless receiver, and a related computer process executing on processor 110.
  • FIG. 2 a flowchart illustrating a process for modifying a simulated hydrocarbon reservoir for use with the computer system of FIG. 1 is shown.
  • the process 200 at block 202 can include simulating a reservoir in a computer simulation.
  • the simulated reservoir can be the same as or similar to the carbonate core model 400 shown in FIG. 4.
  • the computer simulation can be generating using computer system 100.
  • the hydrocarbon reservoir can be simulated in three dimension and/or with multiphase flow within the reservoir.
  • the process 200 at block 204 can include simulating injection of a first fluid into the reservoir in the computer simulation.
  • the first fluid simulation can be or include a polymer.
  • a second fluid simulation e.g., water
  • the second fluid can be injected into the reservoir prior to the first fluid being injected into the reservoir.
  • the first fluid can be injected into the reservoir prior to the second fluid being injection into the reservoir.
  • the process 200 at block 206 can include simulating oil recovery from the reservoir induced by accomplishing an enhanced oil recovery technique in the computer simulation, for example, to account for an estimated change in aqueous viscosity that would be induced by injection of the first fluid into the reservoir.
  • the enhanced oil recovery technique can be or include polymer flooding.
  • the process 200 at block 206 can include calculating a trapping number for the reservoir that accounts for the first fluid within the reservoir. The trapping number can be calculated, for example, using where v is Darcy velocity in the core, m is the aqueous phase viscosity, and s ow is the interfacial tension between oil and water.
  • FIG. 3 another flowchart illustrating a process 300 for generating and modifying a hydrocarbon reservoir model for use with the computer system 100 of FIG. 1 is shown.
  • the process 300 at block 302 can include generating a hydrocarbon reservoir model, for example, the carbonate core model 400 shown in FIG. 4.
  • the reservoir model can be generated using model generating module 102.
  • the hydrocarbon reservoir model can include various adjustable parameters to more accurately model the effect of oil recovery techniques on the reservoir.
  • the sensitivity of various input parameters, the inaccessibility of pore volumes, polymer absorption, permeability reduction, equivalent shear rate, the hardness of makeup water, and/or the trapping number can be adjusted to better match the performance of the model reservoir with historical data of how a real world reservoir would function.
  • generating a model that includes the effect of the trapping number on residual oil saturation can result in a model that more accurately predicts the polymer flooding effect on oil recovery.
  • the process 300 at block 304 can include determining a critical trapping number for the model (e.g., a critical capillary number).
  • a critical trapping number can be determined based at least in part on a composition of a substrate of the reservoir.
  • the a critical trapping number can be determined for a sandstone reservoir and/or for a carbonate reservoir.
  • the critical trapping number can be determined based on the properties of the reservoir and/or can be determined based on the capillary desaturation curve (CDC).
  • CDC capillary desaturation curve
  • the critical trapping number of a sandstone reservoir can be determined to be about 10 -6 and the critical trapping number for carbonates can be lower than the critical trapping number of sandstone (e.g., about 10 -8 ).
  • the critical trapping number for carbonate can be more difficult to determine because the carbonate rocks that make up the carbonate reservoir are heterogeneous.
  • the CDC be determined based on measurements made in a lab. For example, the true residual oil, initial plateau of the CDC can be determined. The injection rate, viscosity of fluid, and/or a decrease of interfacial tension (IFT) can then be adjusted and the shape of further residual oil saturation reduction with increasing trapping number can be determined.
  • IFT interfacial tension
  • the process 300 at block 306 can include determining whether a trapping number for a given injection volume has exceeded the critical trapping number.
  • a trapping number (N Tl ) for a given injection volume can be determined using the equation
  • the trapping number can be determine using the capillary number and bond number.
  • Equations can be used to determine the trapping number, where l' is the displacing phase (aqueous phase including polymer), l is the displaced phase (oil phase), is the flow potential gradient of the displacing phase, k is the permeability, g is the gravitational force constant, q is the angle measured from the horizontal level or the contact angle, and s ll' is the interfacial tension between the displacing and displaced phases.
  • the determined trapping number can be compared with the critical trapping number to determine whether the trapping number has exceeded the critical trapping number.
  • the process 300 at block 308 can include modifying parameters of the hydrocarbon reservoir model. For example, if the trapping number exceeds the critical trapping number the residual oil and/or relative permeability parameters of the model can be modified. Modifying the parameters can improve the accuracy of the model, for example, by more accurately predicting the amount of OOIP that can be recovered during polymer flooding. Increasing the accuracy of the model can additionally or alternatively allow the model to more closely match data collected using scientific or real world techniques.
  • Polymer flooding is a process that can include a water-soluble chemical (polymer) being dissolved into water to increase the injected water viscosity. Additionally and/or alternatively, the water mobility may be reduced and/or the oil sweep efficiency may increase. Polymer flooding is a well-established enhanced oil recovery (EOR) technique that increases oil sweep efficiency by targeting by-passed oil and/or recover residual capillary- trapped oil. Standnes, D. C. and Skjevrak, I, 2014. Literature Review of Implemented Polymer Field Projects. Journal of Petroleum Science and Engineering, 122: 761-775, hereinafter, “Standnes and Skjevrak (2014)” reported over 40 successful polymer flooding projects worldwide, most of them in the United States, Canada, and China.
  • EOR enhanced oil recovery
  • Quadri (2015) presented a screening study for Schizophyllan biopolymer to be used in Middle Eastern carbonate reservoirs with high temperature and high salinity conditions.
  • the latter polymer showed shear thinning behavior with excellent thermal stability (at 120°
  • a coreflood can include a process in which a core (e.g., rock) is included in a displacement experiment.
  • a displacement experiment can include saturating the core with a first fluid (e.g., oil) and displacing the core using a second fluid (e.g., water and/or water combined with polymer). Moreover, a polymer concentration of 200 ppm was used to enhance oil recovery from these cores.
  • a first fluid e.g., oil
  • a second fluid e.g., water and/or water combined with polymer
  • a polymer concentration of 200 ppm was used to enhance oil recovery from these cores.
  • the current study utilizes polymer solution properties through the screening studies conducted by Quadri (2015) as well as rock and fluid properties through corefloods conducted by Li (2015).
  • the selected coreflood includes a secondary formation waterflooding followed by a tertiary biopolymer flooding.
  • the core was saturated with dead reservoir oil at irreducible water saturation, and then, formation water was injected at reservoir conditions (248° F and 3000 psig). Afterwards, polymer flooding was used to further enhance oil recovery from that core.
  • the core plug used has an average porosity of 13.12% and an average liquid permeability of 30.5 mD.
  • Table 1 A summary of the parameters used in sensitivity analysis of tertiary polymer flooding using the UTCHEM simulator “*” refers to the value used in the base simulation run.
  • IPV Inaccessible Pore Volumes
  • IPV inaccessible pore volume
  • Table 6 and FIG. 10 show that there is a slight decrease in oil recovery with increasing the water hardness as expected. However, this effect is not well pronounced. The latter is supported by the negligible absolute different in (%) OOIP (Table 6) and the almost overlapping curves 1000 in FIG. 10. It should be noted that in this analysis, the overall water salinity was kept constant and only the hardness factor was adjusted.
  • the capillary desaturation curve (CDC) model was applied in this work, where is assumed zero as usual, is 0.251 which is the residual oil saturation value obtained during waterflooding cycle, t is assumed as 0.8 which is a typical value in the literature for carbonates, and T l is a matching parameter with a value of 100,000. This latter parameter was obtained through tuning the relation to capture the residual oil saturation (S orp ) during the application of high trapping number during polymer flooding cycle.
  • Polymer Viscosity is important in mobility control of the injected polymer solution. Polymer viscosity increases with increasing polymer concentration whereas it decreases with increasing the solution salinity. The dependence of polymer solution viscosity at zero shear rate on both polymer concentration and salinity are modeled in UTCHEM using the Flory-Huggins equation as follows (Flory, P. J, 1953. Principles of Polymer Chemistry. Georgia University Press, hereinafter, “Flory, 1953”): where m w is the water viscosity in cP, C p is the polymer concentration in water, A p1 , A p2 ,
  • C sep is the effective polymer salinity. It should be noted that the units for the parameters inside the parentheses must be dimensionless so that the unit for the same asm w .
  • C sep captures the dependency of polymer viscosity on both salinity and hardness, and is defined as: where C 51 and C 61 are the anion and the divalent concentration in the aqueous solution in meq/mL, respectively.
  • C 11 is the water concentrations in the aqueous phase and it is expressed as water volume fraction in the aqueous phase.
  • b p is measured in the laboratory, with typical value of about 10.
  • P a is an empirical parameter that is obtained by matching laboratory-measured viscosity data, the limiting viscosity at low shear limit (approaching zero), m w is the water viscosity which is the limiting viscosity at high shear limit (approaching infinity), and is the shear rate at which polymer viscosity is the average of the and m w .
  • the equivalent shear rate is defined using Cannella equation as follows (Cannella, W. J.,
  • Polymer Adsorption Polymer retention could be either dynamic (mechanical trapping and hydrodynamic trapping) or static (adsorption). Mechanical trapping occurs due to the use of polymers with sizes greater than the pores of the porous medium and it happens during polymer flow. The latter could be controlled by using polymers in high permeability medium or pre-shearing of polymer solution. Hydrodynamic trapping occurs also during polymer flow in the medium where the polymer retention depends on the flow rate. Usually, this effect is negligible especially at field-applications. Adsorption is the most important mechanism, which occurs due to the interaction between polymer molecules and the solid surface. Adsorption depends on the surface area exposed to the polymer solution.
  • a p is dimensionless and defined as: where a p1 and a p2 are fitting parameters, C sep is the effective salinity, k is the formation permeability, and k ref is the reference permeability of the rock used in the laboratory measurement for adsorption. It must be noted that Langmuir model assumes equilibrium conditions, instantaneous polymer adsorption as well as reversible adsorption in terms of polymer concentration. Polymer adsorption depends on polymer type, salinity, and rock surface.
  • the permeability reduction factor (F kr ) is defined as: where k eff,w is the rock effective permeability when rock is flooded by water and k eff,p is the rock effective permeability when the rock is flooded with polymer solution.
  • This factor is modeled in UTCHEM using the following equations: where b kr and C kr are input parameters derived from data matching, A p1 is the constant in Equation (1) and C sep is calculated using Equation (2). It should be noted that the term b kr C p must be dimensionless, similarly is the case for F kr,max , which has an assumed empirical value of 10.
  • the residual resistance factor (F rr ) was introduced.
  • the latter parameter is defined as the ratio of water mobility before polymer flow to water mobility after polymer flow.
  • F rr does not take into account the increase in viscosity caused by polymer flooding.
  • the resistance factor term (F r ) was introduced, which is defined as the ratio of water mobility during water flow to polymer mobility during polymer flow. It should be noted that in UTCHEM, viscosity increase and permeability reduction due to polymer flooding is only applicable to the water phase by modifying the polymer viscosity by F kr .
  • IPV Inaccessible Pore Volume
  • It refers to the fraction of pore volume where the radii of the pores are smaller than the size of polymer particles, especially when polymers with high molecular weight are used. These pores are usually filled with irreducible or connate water. IPV has a positive effect on sweep efficiency of polymer solutions and hence, better oil recovery due to boosting the advancement of the polymer solution front. Moreover, the IPV is useful from an economical point of view where it results in less contact between rock surface and polymer solution and hence, less polymer adsorption/retention. The only disadvantage of IPV is when these inaccessible pores have movable oil droplets.
  • IPV is modeled using UTCHEM by multiplying the porosity in the conservation equation for polymer by an input parameter (EPHI4) defined as the effective porosity.
  • EPHI4 is 1 - IPV. Trapping Number
  • Trapping number in Equation (11) can be expressed as a function of both capillary number and bond number.
  • Capillary number (N cl ) is defined as the ratio of viscous forces to capillary forces.
  • Bond number ( N Bl ) is defined as the ratio of gravity forces to capillary forces.
  • trapping number can also be expressed as follows: where l' is the displacing phase (aqueous phase including polymer), l is the displaced phase (oil phase), is the flow potential gradient of the displacing phase, k is the permeability, g is the gravitational force constant, q is the angle measured from the horizontal level in Equation (12) and the contact angle in Equations (13) and (14), and s ll' is the interfacial tension between the displacing and displaced phases.
  • Disjunctive language such as the phrase “at least one of X, Y, or Z,” unless specifically stated otherwise, is intended to be understood within the context as used in general to present that an item, term, etc., may be either X, Y, or Z, or any combination thereof (e.g., X, Y, and/or Z). Thus, such disjunctive language is not generally intended to, and should not, imply that certain embodiments require at least one of X, at least one of Y, or at least one of Z to each be present. [0107] Preferred embodiments of this disclosure are described herein, including the best mode known to the inventors for carrying out the disclosure.

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Abstract

Selon la présente invention, des modèles d'injection de polymères pour des réservoirs de carbonate et des procédés associés comprennent l'effet de nombre de piégeage sur la saturation en huile résiduelle. Un procédé de prédiction de récupération d'huile à partir d'un réservoir à l'aide de techniques de récupération d'huile assistée peut comprendre la simulation du réservoir dans une simulation informatique (202). L'injection d'un fluide (204) peut être simulée dans la simulation informatique et une technique de récupération d'huile assistée peut être simulée pour simuler la récupération d'huile à partir du réservoir (206).
PCT/IB2020/058382 2019-09-11 2020-09-09 Effet de viscosité des biopolymères sur la saturation en huile résiduelle dans des réservoirs de carbonate Ceased WO2021048760A1 (fr)

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