Wettability Alteration and Its Effects on Production in Water Flooding

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1 Petroleum Science and Technology, 30: , 2012 Copyright Taylor & Francis Group, LLC ISSN: print/ online DOI: / Wettability Alteration and Its Effects on Production in Water Flooding B. JU 1;2 AND T. FAN 1 1 School of Energy Resources, China University of Geosciences, Beijing, China 2 Key Laboratory of Marine Reservoir Evolution and Hydrocarbon Accumulation Mechanism, Ministry of Education Abstract The experiments validate that the wettability of reservoir rocks changes from weak water wetness to strong water wetness during secondary oil recovery. The relative permeabilities of the oil and water show that the increase in water wetness results in an obvious decrease in the water permeability. A numerical simulator considering wettability alteration was developed to predict oil production. The simulation indicates the wettability alteration during water flooding has strong effects on the water cut and oil recovery. It is found that the increase in water wetness during water flooding leads to a higher oil recovery and less accumulated production water at a water cut. Keywords mathematical model, oil recovery, percolation, wettability alteration, water flooding 1. Introduction The wettability governs not only the distribution of reservoir fluids in porous media, but also the flow behavior of oil, gas, and water in a reservoir (Morrow and McCaffery, 1978; Anderson, 1987a, 1987b; Ju et al., 2002; Guo and Abbas, 2003; Ju et al., 2006). Wettability alteration in oil reservoirs is caused by many factors such as solubility of fluids, chemical adsorption, and temperature change. Wettability alteration in oil reservoirs caused by the previous factors has been reported by other authors (Dixit et al., 1999; Graue and Bognø, 1999; Guo and Anthony, 2000; Li and Abbas, 2000; Amroun and Tiab, 2001), and most reservoir engineers have accepted their opinions. However, wettability alteration caused by the injected water without chemicals (e.g., alkaline, surfactant) used in enhanced oil recovery (EOR) has not been paid full attention by reservoir engineers. Recently, studies (Guo et al., 2001; Wang and Jiang, 2004; Ju, 2006; Zhao, 2008; Chinedu et al., 2009) have indicated that wettability of oil formation may change during water flooding. Because wettability may change, relative permeabilities and capillarities will also change. In turn, it may influence the oil production. Therefore, reservoir engineers should realize the importance of the effects of wettability alteration on multiphase flow when predicting oil production by a numerical simulation. Unfortunately, there is little consideration of the effects of wettability alteration in the present multiphase-flow Address correspondence to B. Ju, School of Energy Resources, China University of Geosciences, Beijing, Xueyuan Road No.29, Haidian district, Beijing, , China. jubs2936@ 163.com 1692

2 Wettability Alteration and Water Flooding 1693 mathematical model. Thus, the oil production predicted by the present reservoir simulator may lead to obvious deviation for neglecting wettability alteration. In this work, the wettabilities and relative permeabilities of these cores with different wettabilities were studied in a lab, and an oil reservoir simulator considering wettability alteration was developed to study the effects of wettability alteration on oil production. 2. Theoretical Aspects for Wettability Alteration and Its Effects on Fluid Flow Behaviors The wettability of reservoir rocks is influenced by the factors such as rock minerals and the materials coating on pore surfaces. In a water flood, water flushing can change the wettabilities of pore surfaces. Particularly, the water stream can detach the organics such as asphaltene coating on the pore surfaces, which lead to wettability alteration. Donaldson and Thomas (1971) studied the effects of wettabilities on oil displacement performances in lab. They found that strongly water-wetting systems produce more oil and have higher displacement efficiency than oil-wetting systems. 3. Experiments of Wettability Alteration and Its Effects on the Relative Permeability 3.1. Core Sampling In this study, the rock cores are sampled from the formations of G. D. oilfield in East China. Pressure coring technology was used to obtain representative cores of in situ conditions. The 19 cores used in the experiments have different water saturations from 37.6% to 86.2% Experiments for Measuring Wettability Some methods such as wetting-angle measurement only give quantitative descriptions such as preferential water wetness, oil wetness, and neutral wettability. The wettability may continuously change during water flood, so a quantitative description for wettability is urgently needed for predicting oil production. Amott index (AI) can be calculated by spontaneous imbibition and centrifugal displacement experiments. According to the definition of AI (Bae and Petrick, 1986), AI varies from 1 for a strongly oil-wetting rock to C1 for a strongly water-wetting rock. AI gives a quantitative evaluation of wettability. According to Figure 1, an approximate linear correlation between AI and water saturations can be obtained as: AI D 0:99S w 0:0948 (1) Equation (1) indicates that AI strongly depends on water saturation Experiments for Measuring Relative Permeability Two cores were obtained from the same pay zone. One was obtained at the water-free production stage. The other one was obtained at the high water-cut stage. The procedure to measure relative permeability is (a) to saturate the core with the water, and then displace the water to its irreducible saturation by injection oil; and (b) water is continuously

3 1694 B. Ju and T. Fan Figure 1. The relation between Amott Index and water saturation (the square legends are experimental data). (color figure available online) injected into the core. This process is intended to measure the relative permeabilities. Figure 2 shows that oil relative permeability for a strong water-wetness (AI D 0.80) is higher than that for a weak water wetness (AI D 0.24) at specified water saturation, and vice versa for water relative permeability. It indicates that the stronger the water wetness is, the higher the mobility of oil phase is Construction of the Relative Permeabilities for Actual Reservoirs Comparing the flooding time in oil reservoirs, the water flooding time in a lab is too short to fully reflect the wettability alteration. Therefore, the relative permeabilities obtained experimentally are different from those in an actual reservoir. Because the wettability alteration has strong effects on relative permeability (Figure 2), it is necessary to construct relative permeability curves for an actual reservoir numerical simulation. The key factors Figure 2. The comparison of relative permeability for different Amott Index (AI; 0.24, reflecting initial condition of the reservoir with connate water; AI D 0.80 reflecting the condition of residual oil). The dotted lines are the relative permeability at reservoir condition during the flooding history of decades. (color figure available online)

4 Wettability Alteration and Water Flooding 1695 affecting oil and water relative permeabilities are water saturation and wettability, so the relative permeabilities can be stated as a function of water saturation and AI. K ri D f.s w ; AmottI/ (2) Because the flooding time for measuring the relative permeability is too short to reflect wettability alteration, relative permeabilities may be approximately looked as the function of water saturation. K ri D f.s w.core/ / (3) The wettability changes continually during water flood in actual oil reservoirs, so AI does not keep a constant during the production of decades of years. It is difficult to describe quantitatively the relationship between AI and the property of pore surfaces. Fortunately, we found that the correlation between AI and water saturation at reservoir conditions is approximate linear. AmottI D F.S w.reservoir/ /: (4) Combining the experimental results of relative permeabilities of the cores with different wettabilities, the relative permeabilities of two-phase flow in actual reservoirs can be described as K ri.reservoir conditions/ D f.s w.cores/ ; AmottI/ D f.s w.cores/ ; F.S w.reservoir/ //: (5) S w.cores/ is the water saturation in water flooding experiments. S w.reservoir/ is the water saturation in a real reservoir during water flooding. The relative permeabilities (the dotted lines of Figure 2) for an actual reservoir can be calculated by using the relative permeabilities obtained experimentally. 4. Mathematical Model 4.1. Assumptions The assumptions considered were the following: (a) black oil system, (b) isothermal and three-dimensional multiphase flow, (c) compressible rock and fluids, (d) Darcy s law, (e) Newtonian fluid, (f) capillary and gravity forces, and (g) wettability alteration Mathematical Model of Multiphase Flow in Porous Media The mass conservation equation can be written as Z Z F nd n C q D d Z M dv n (6) n V n dt V n The integration is over an arbitrary subdomain V n of the flow system, which is bounded by the closed surface n. The quantity M represents the mass of a fluid per unit volume, with D w; o; g. F denotes mass flux, and q denotes sinks or sources, and n is a normal

5 1696 B. Ju and T. Fan vector on surface element d n, which points inward in to V n. The mass conservation equations can be written as K Krw div gradˆw C q w B w S w=b w / (7) K Kro div gradˆo C q o B o S o=b o / (8) K Krg div gradˆg C K K ro R s gradˆo B g g B o o C q S g=b g C S o R s =B o / For the flow of the three phases of oil, water, and gas, we can define (9) S o C S w C S g D 1 (10) ˆo D p o C o z; (11) ˆw D p w C w z D p o C p cwo C w z; (12) ˆg D p g C g z D p o C p cgo C g z; (13) where is porosity. S,, and p are saturation, viscosity, and pressure, respectively. K and K r are absolute and relative permeabilities, respectively. B is the volume factor and q is a production or injection rate. R s is the solution gas-oil ratio. is the specific gravity, and z is the distance from reference level. p c is the capillarity. 5. Numerical Solution The mathematical model is a nonlinear system that includes a set of nonlinear equations, which includes the mass conservation equations of oil, water, and gas, and a series of auxiliary equations. The finite-difference method is used to discretize the equations, and implicit-pressure, explicit-saturation, and self-adaptive iterative techniques were used to solve the pressure-saturation equation. 6. Applications in Oil Field Simulation and Discussions 6.1. The Production History The oil reservoir covers 6: m 2, and its pay zones are at depths of 1,034.8 to 1,390.5 m. The first well was drilled in 1966 and there are presently 32 wells. For the lack of nature energy, water injection started in The oil recovery was up to 37.5% by The Grid and Reserve of the Reservoir A grid mesh is set in the X-Y plane, and 6 layers are separated by impermeable beds. The oil reserves in the six layers from top to bottom are , , 0.012, , , , and million tons, respectively. The sixth layer (bottom layer) has the largest reserve among the six layers, which has 41.60% of the total oil reserve.

6 6.3. The Major Parameters Wettability Alteration and Water Flooding 1697 The parameters are initial average pressure MPa; bubble pressure MPa; oil viscosity at reservoir condition mpa.sec; volume factor of oil 1.099; ratio of dissolved gas to crude oil 36.00; water viscosity in reservoir mpa.sec; and volume factor of water The oil formation thickness, porosity, permeability, and oil saturation were obtained by well logging approach. The parameters of the 6th layer are shown in Figure The Discussion on the Results of Numerical Simulation The relative permeabilities (Figure 2) K ro (AI D 0.24) and K ro (AI D 0.24) are oil and water relative permeabilities, respectively, reflecting the initial wettability of the reservoir. K ro (AI D 0.80) and K rw (AI D 0.80) are oil and water relative permeabilities, respectively, reflecting the wettability at the high water-cut stage. K ro and K rw at the reservoir condition are calculated by the method presented in this work, which reflects the wettability alteration during water flood. Figure 4 indicates that the water cuts considering wettability alteration has a better match than that the other two cases. At the same water cut, the recovery simulated by using K r (AI D 0.24) is much less than real recovery from oil production data. The predicted oil recoveries are 11.3% (K r [AI D 0.24]), 21.1% (K r [AI D 0.80]), 17.4% (considering wettability alteration), and 17.7% (production data) at the water cut of 80%. When the recovery arrives at 25%, the water cuts are 94.4% (K r [AI D 0.24]), 74.1% (K r [AI D 0.80]), 89.2% (wettability alteration), and 91.1% (production data). It shows that the results of the numerical simulation considering wettability alteration are very closed to production data. Figure 5 indicates that the deviations of accumulated production water are too large to be accepted if wettability alteration is ignored in numerical simulations. To evaluate how much oil is displaced by water flood, we define oil recovery efficiency as.x; y; z/ D S oi.x; y; z/ S ot.x; y; z/ : (14) S oi.x; y; z/ where S ot.x; y; z/ is the oil saturation at time t, and S oi.x; y; z/ is the initial oil saturation at a location.x; y; z/. Figure 6 gives the distribution of the recovery efficiency of the sixth layer when average water cuts of all production wells arrive at 80% and 98%, respectively. At a water cut, the recovery efficiency obtained by numerical simulation using K r (AI D 0.80) is higher, and vice versa using K r (AI D 0.24). Neither the K r (AI D 0.24) nor the K r (AI D 0.80) reflects wettability alteration from weak water wetness to strong water wetness during the production history. Therefore, they result in the unacceptable error when they are used in the oil reservoir numerical simulation. 7. Conclusions 1. The experimental results indicate that the wettability of the oil reservoir rocks of G.D. oil field has changed from the weak water wetness to the strong water wetness during the water flooding. 2. The regression correlation between AI and water saturations is approximately linear. 3. The shapes of relative permeability curves obtained by experiments change during a water flood.

7 1698 B. Ju and T. Fan (A) (B) Figure 3. The distributions of main parameters of the sixth layer. (A) The contour map of oil formation thickness (m); (B) contour map of porosity; (C) contour map of permeability (10 12 m2 ); (D) contour map of initial oil saturation. (color figure available online) (continued)

8 Wettability Alteration and Water Flooding (C) (D) Figure 3. (Continued). 1699

9 1700 B. Ju and T. Fan Figure 4. The comparisons of water cuts and recovery obtained by numerical simulation and production data from the oil field. Figure 5. The comparisons of accumulated production water and oil recovery. (color figure available online) 4. Wettability alteration induced by water flooding was considered by reconstructing wettability-dependent relative permeability in the developed multiphase flow mathematical model. 5. The numerical results indicate that the water cut, recovery, and accumulated water have good matches with actual production data when wettability alteration is considered in the history match. 6. We verified the necessity to considerate wettability alteration during water flood simulation.

10 Wettability Alteration and Water Flooding 1701 Figure 6. The comparisons of water displacement efficiency. (color figure available online) Acknowledgments Part of the work was supported by the Fundamental Research Funds for the Central Universities and the National Science and Technology Major Projects (2011ZX , 2011ZX ), the project sponsored by SRF for ROCS, SEM, of which support is appreciated. The authors would like to thank Ms. Lixin Meng, Research Institute of Exploration and Development, Dagang Oil Field, CNPC, for the partial experimental and production data.

11 1702 B. Ju and T. Fan References Agbalaka, C. C., Dandekar, A. Y., Patil, S. L., Khataniar, S., and Hemsath, J. R. (2009). Coreflooding studies to evaluate the impact of salinity and wettability on oil recovery efficiency. Trans. Porous Med. 76: Amroun, H., and Tiab, D. (2001). Alteration of reservoir wettability due to asphaltene deposition in Rhourd-Nouss Sud Est Field, Algeria. SPE 71060, SPE Rocky Mountain Petroleum Technology Conference, Keystone, Colorado, May Anderson, W. W. (1987a). Wettability literature survey: Part 5 The effects of wettability on relative permeability. J. Pet. Technol. 39: Anderson, W. W. (1987b). Wettability literature survey: Part 6 The effects of wettability on waterflooding. J. Pet. Technol. 39: Bae, J. H., and Petrick, C. B. (1986). Glenn pool surfactant flood pilot test: Comparison of laboratory and observation-well data. SPE Res. Eng. 1: Dixit, A. B., McDougall, S. R., Sorbie, K. S., Heriot-Watt, U., and Buckley, J. S. (1999). Pore-scale modeling of wettability effects and their influence on oil recovery. SPE Reservoir Eval. Eng. 2: Donaldson, E. C., and Thomas, R. D. (1971). Microscopic observations of oil displacement in waterwet and oil-wet systems. SPE 3555, 46th Annual Fall Meeting of the Society of Petroleum Engineers of AIME, New Orleans, Louisiana, October 3 6. Graue, A., and Bognø, T. (1999). Wettability effects on oil recovery mechanisms in fractured reservoirs. SPE 56672, 1999 SPE Annual Technical Conference and Exhibition, Houston, Texas, October 3 6. Guo, L., Dou, S. J., and Wang, W. L. (2001). Reservoir structural changes after water flooding in Gangdong Development Area. J. Jianghan Pet. Inst. 23: Guo, Q. T., and Abbas, F. (2003). Wettability alteration to intermediate gas-wetting in porous media at elevated temperatures. Trans. Porous Med. 52: Guo, Q. T., and Anthony, R. K. (2000). Wettability alteration of diatomite induced by hot-fluid injection. SPE 77461, SPE Annual Technical Conference and Exhibition, San Antonio, Texas, September 29 October 2. Ju, B. S. (2006). Study on mechanism and mathematical simulation on the changes in physical properties of flow system in oil reservoirs. Ph.D. Thesis, China University of Geosciences. Ju, B. S., Dai, S. G., Luan, Z. A., Zhu, T. G., Su, X. T., and Qiu, X. F. (2002). A study of wettability and permeability change caused by adsorption of nanometer structured polysilicon on the surface of porous media. SPE 77938, SPE Asia Pacific Oil and Gas Conference and Exhibition, Melbourne, Australia, October Ju, B. S., Fan, T. L., and Ma, M. X. (2006). Enhanced oil recovery by flooding with hydrophilic nanoparticles. China Particuol. 4: Li, K., and Abbas, F. (2000). Experimental study of wettability alteration to preferential gas-wetting in porous media and its effects. SPE Reservoir Eval. Eng. 3: Morrow, N. R., and McCaffery, F. G. (1978). Displacement studies in uniformly wetted porous media. New York: Academic Press. Wang, H. G., and Jiang, M. (2004). Simulation on variation of physical properties in high water-cut reservoir. Acta Petrolei Sinica 26: Zhao, Y. F. (2008). Changes and characteristics of rock wettability of various types of reservoir in Lamadian oil field. J. Daqing Pet. Inst. 32: Nomenclature AI Amott index B volume factor of fluid F mass flux (m 2 /s) K transient absolute permeability of a porous media (m 2 )

12 Wettability Alteration and Water Flooding 1703 K r M p p c q R s S t V n v x z n g r o w 1 cm D m 1 MPa D Pa 1 mpa D Pa relative permeability of a porous media mass of a fluid per unit volume pressure (Pa) capillary force (Pa) sink/ source term (m 3 /s) solution gas-oil ratio saturation time (s) arbitrary subdomain of the flow system fluid flow rate (m/s) distance (m) distance from reference level (m) porosity of the porous media specific gravity of fluids. closed surface of an arbitrary subdomain viscosity of fluid (Pas) gas relative oil water