A method for profile control and oil displacement in high water cut reservoirs

Abstract

The application belongs to the technical field of petroleum engineering, and specifically provides a high water cut reservoir profile control and oil displacement method. The application adopts water passing multiple to describe fluid flow capacity, adopts permeability change value to describe reservoir physical property change, and adopts water saturation to describe reservoir fluid type change. The objective weight variation coefficient method is used to determine the weight coefficient of each parameter. Then, each parameter is weighted to obtain a comprehensive reservoir identification index to describe the development degree of the preferred flow channel. According to different dominant seepage channel categories, different concentrations and different injection amounts of profile control agents are injected to adjust the pressure gradient in different dominant seepage channels. Finally, a viscosity reducer is injected into the profile-controlled reservoir for displacement. The application quantitatively identifies the dominant seepage channel of the high water cut reservoir, realizes quantitative profile control and oil displacement of the reservoir, and greatly improves the recovery rate of the high water cut reservoir.

Description

Technical Field

[0001] This invention belongs to the field of petroleum engineering technology, specifically relating to a method for profile control and oil displacement in high water-cut reservoirs. Background Technology

[0002] my country's oil and gas fields are mainly distributed in terrestrial sedimentary basins, characterized by high viscosity and high wax content. The sandstone oil fields in the east have gradually entered the high water-cut stage (water cut ≥80%) after continuous water injection development, but the remaining reserves are still nearly 50%, which has great potential for further development.

[0003] Water injection development, as an important method for enhancing oil recovery, is widely used in various oilfields. During long-term water injection development, the scouring effect of water injection has had varying degrees of impact on the reservoir, producing significant physical and chemical effects that lead to changes in reservoir parameters. Water injection scouring erodes and strips the reservoir rock mineral particles and intergranular cement, smoothing pore throats or expanding throat spaces. This creates "dominant flow channels" with larger high-permeability areas in the throats, affecting further oilfield development. Therefore, clearly identifying the development level of dominant flow channels is extremely important. Furthermore, after long-term waterflooding in high-water-cut oilfields, the formation of high-permeability channels within the reservoir leads to inefficient or ineffective circulation of the injected medium, resulting in highly dispersed residual oil and severely restricting the overall recovery rate of the reservoir. Existing methods for identifying dominant flow channels can only qualitatively determine their location, and profile control and water shut-off methods cannot quantitatively adjust the profile according to the actual conditions of the reservoir to comprehensively and significantly improve the overall oil recovery rate.

[0004] Therefore, there is an urgent need to develop a profile control and oil displacement method for high water-cut reservoirs to increase the swept volume of the reservoir and thus improve the oil recovery rate. Summary of the Invention

[0005] The present invention aims to solve the technical problems in the aforementioned related technologies.

[0006] Therefore, the purpose of this invention is to provide a profile control and oil displacement method for water-drive reservoirs. Based on the changes in reservoir properties, this method quantitatively describes the development of dominant flow channels in water-drive reservoirs and quantitatively implements profile control to achieve rapid and accurate identification of dominant flow channels in water-drive reservoirs and significantly improve the overall oil recovery rate.

[0007] This invention provides a method for profile control and oil displacement in high water-cut reservoirs, comprising the following steps:

[0008] S1 uses natural cores with different permeabilities in the reservoir and water flooding at different ratios to obtain the permeability change values ​​of cores with different permeabilities under different water flooding ratios, and fits the curves of permeability change values ​​of cores with different permeabilities under different water flooding ratios.

[0009] S2 establishes a numerical simulation model of the reservoir. After historical fitting, it calculates the water permeability ratio, permeability change value, and water saturation of each grid in the reservoir, and uses them as parameters to describe the development degree of the dominant seepage channels in the reservoir.

[0010] S3 performs normalization calculations on the water permeability ratio, permeability change value, and water saturation obtained in step S2;

[0011] S4 uses the objectively weighted coefficient of variation method to calculate the weighting coefficients of permeability change, water flow ratio, and water saturation for each grid.

[0012] S5 calculates a comprehensive identification index based on the permeability change, water flow ratio, water saturation, and their respective weighting coefficients, and identifies dominant seepage channels based on the comprehensive identification index; dominant seepage channels are then classified into: strongly dominant seepage channels, weakly dominant seepage channels, and non-dominant seepage channels.

[0013] S6 calculates the optimal profile control agent injection concentration and injection volume based on the dominant seepage channels identified in step S5, and adjusts the pressure gradient within different dominant seepage channels.

[0014] S7 adjusts the profile of the actual reservoir based on the optimal injection concentration and injection volume of the profile control agent calculated in step S6, and then injects a viscosity reducer for displacement to improve reservoir recovery.

[0015] Preferably, the formula for calculating the water dilution ratio is:

[0016]

[0017] In the formula:

[0018] M represents the time step from 0 to t, the grid water passage multiple, and is dimensionless;

[0019] Q x,t Let m be the water flow rate in the x-direction grid at time step t. 3 ;

[0020] Q y,t Let m be the water flow rate in the x-direction grid at time step t. 3 ;

[0021] Q z,t Let m be the water flow rate in the z-direction at time step t. 3 ;

[0022] PORV is the mesh pore volume, in meters. 3 .

[0023] Preferably, the normalized calculation is as follows:

[0024]

[0025] In the formula:

[0026] X' m,kij - Normalized value of the original parameter m in the i-th row and j-th column of the k-th layer of the reservoir; X m,kij - Original data of the m-th parameter of the reservoir in the i-th row and j-th column of the k-th layer in the reservoir; X m,max - The maximum value of the original grid dataset for the m-th parameter in the reservoir;

[0027] X m,min - The minimum value of the original grid dataset for the m-th parameter in the reservoir.

[0028] Preferably, the coefficient of variation method for objective weighting is calculated as follows:

[0029]

[0030] In the formula:

[0031] - The mean of the grid-normalized data of the m-th parameter in the reservoir;

[0032] u m,i - Normalized grid data of the m-th parameter in the reservoir;

[0033] σ m -Standard deviation of the grid-normalized data for the m-th parameter in the reservoir;

[0034] V m - The coefficient of variation of the m-th parameter grid-normalized data in the reservoir;

[0035] ω m - The weighting coefficient of the grid-normalized data of the m-th parameter in the reservoir.

[0036] Preferably, the comprehensive identification index is calculated as follows:

[0037]

[0038] In the formula:

[0039] E k,ij - The comprehensive recognition index of the grid in the i-th row and j-th column of the k-th grid layer.

[0040] - The weight coefficient of the m-th parameter of the i-th row and j-th column of the k-th grid layer.

[0041] X' m,k,ij - The normalized value of the m-th parameter of the i-th row and j-th column of the k-th grid layer.

[0042] Preferably, the comprehensive identification index of each grid of the strong dominant seepage channel ranges from 0.45 to 0.68, the comprehensive identification index of each grid of the weak dominant seepage channel ranges from 0.23 to 0.45, and the comprehensive identification index of each grid of the non-dominant seepage channel ranges from 0 to 0.23.

[0043] Preferably, the profile control agent is a gel-type profile control agent, a gel-type profile control agent, a polymer microsphere profile control agent, or a foam-type water-blocking profile control agent.

[0044] Preferably, the injection concentration range of the profile control agent for strong dominant seepage channels is 1000 mg / L-2500 mg / L, and the injection concentration range of the profile control agent for weak dominant seepage channels is 100 mg / L-1000 mg / L.

[0045] Preferably, the injection volume of the profile control agent for strong dominant seepage channels is 0.15-0.3 PV; the injection volume of the profile control agent for weak dominant seepage channels is 0.01-0.15 PV.

[0046] Preferably, the viscosity reducer is CO2, a surfactant, or a nanofluid.

[0047] Preferably, the surfactant is sodium dodecyl sulfate, dodecyl dimethyl betaine, hexadecyl trimethylammonium bromide, or dodecyl glycoside.

[0048] Preferably, the nanofluid is: silica nanofluid, molybdenum disulfide nanofluid, zirconium dioxide nanofluid, nano-iron oxide fluid, or nano-graphite fluid.

[0049] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0050] In describing the dynamic and static spatiotemporal aspects of reservoirs, this invention uses the water-to-flow ratio to describe fluid flow capacity, permeability variation to describe reservoir property changes, and water saturation to describe changes in reservoir fluid type. The weighting coefficients of each parameter are determined using the objective-weighted coefficient of variation method. Then, the parameters are weighted to obtain a comprehensive reservoir identification index to describe the development degree of preferred flow channels. Based on different dominant flow channel categories, profile control agents of varying concentrations and injection volumes are injected to adjust the pressure gradient within different dominant flow channels. Finally, viscosity reducers are injected into the profiled reservoir for displacement. This invention quantitatively identifies dominant flow channels in high water-cut reservoirs and achieves quantitative profile control, significantly improving reservoir recovery.

[0051] Additional aspects and advantages of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description

[0052] Figure 1This is a flowchart illustrating the process of profile modification and oil displacement in high water-cut reservoirs according to the present invention.

[0053] Figure 2 This is a schematic diagram of the grid orientation disclosed in an embodiment of the present invention;

[0054] Figure 3 This is a field diagram showing the water flow ratio of the grid in the X direction during the water injection process in an embodiment of the present invention.

[0055] Figure 4 This is a surface plot of permeability variation after water flooding with different water displacement ratios, as disclosed in the embodiments of the present invention.

[0056] Figure 5 This is a water saturation field diagram during the water injection process disclosed in an embodiment of the present invention;

[0057] Figure 6 This is a comprehensive identification index field diagram during the water injection process disclosed in this embodiment of the invention;

[0058] Figure 7 This is a field diagram of the dominant seepage channels during the water injection process disclosed in an embodiment of the present invention;

[0059] Figure 8 This is a diagram (a) showing the tracer concentration monitoring curve disclosed in an embodiment of the present invention;

[0060] Figure 9 The image shown is plot (b) of the tracer concentration monitoring curve disclosed in this embodiment of the invention. Detailed Implementation

[0061] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0062] The embodiments of the present invention will be described in detail below with reference to the accompanying drawings and specific examples and application scenarios.

[0063] For some embodiments of the present invention, please refer to Figure 1 As shown, a profile control and oil displacement method for high water-cut reservoirs is provided. Starting from describing the dynamic and static spatiotemporal aspects of the reservoir, the selected parameters, while focusing on changes in reservoir physical properties and fluid flow capacity, also have the screening principles of accumulability, quantifiability, independence, and optimality. The water permeability ratio describing the sweepability of injected fluids in the reservoir, the permeability change value describing changes in internal reservoir physical properties, and the water saturation value describing changes in internal reservoir fluids are selected as parameters to describe the development degree of dominant seepage channels in the reservoir.

[0064] The specific implementation steps are as follows:

[0065] S1 uses natural cores with different permeabilities in the reservoir and water flooding at different ratios to obtain the permeability change values ​​of cores with different permeabilities under different water flooding ratios, and fits the curves of permeability change values ​​of cores with different permeabilities under different water flooding ratios.

[0066] S2 establishes a numerical simulation model of the reservoir. After historical fitting, it calculates the water permeability ratio, permeability change value, and water saturation of each grid in the reservoir as parameters to describe the development degree of the dominant seepage channels in the reservoir.

[0067] S3 performs normalization calculations based on the water dilution ratio, permeability change value, and water saturation in step S2;

[0068] S4 uses the objectively weighted coefficient of variation method to calculate the weighting coefficients of permeability change, water flow ratio, and water saturation of each grid in S3.

[0069] Based on the weighting coefficients of permeability change, water flow ratio, and water saturation in step S4, S5 calculates a comprehensive identification index to classify dominant seepage channels into: strong dominant seepage channels, weak dominant seepage channels, and non-dominant seepage channels.

[0070] S6 calculates and optimizes the injection concentration and volume of the profile control agent based on the dominant seepage channels in step S5, and adjusts the pressure gradient within different dominant seepage channels.

[0071] S7 adjusts the profile of the actual reservoir based on the optimal injection concentration and injection volume of the profile control agent calculated in step S6, and then injects a viscosity reducer for displacement to improve reservoir recovery.

[0072] Preferably, the formula for calculating the water dilution ratio is:

[0073]

[0074] In the formula:

[0075] M represents the time step from 0 to t, the grid water passage multiple, and is dimensionless;

[0076] Q x,t Let m be the water flow rate in the x-direction grid at time step t. 3 ;

[0077] Q y,t Let m be the water flow rate in the x-direction grid at time step t. 3 ;

[0078] Q z,t Let m be the water flow rate in the z-direction at time step t. 3 ;

[0079] PORV is the mesh pore volume, in meters. 3 .

[0080] The normalization calculation is as follows:

[0081]

[0082] In the formula:

[0083] X' m,kij - Normalized value of the original parameter m in the i-th row and j-th column of the k-th layer of the reservoir; X m,kij - Original data of the m-th parameter of the reservoir in the i-th row and j-th column of the k-th layer in the reservoir; X m,max - The maximum value of the original grid dataset for the m-th parameter in the reservoir;

[0084] X m,min - The minimum value of the original grid dataset for the m-th parameter in the reservoir.

[0085] The coefficient of variation method for objective weighting is calculated as follows:

[0086]

[0087] In the formula:

[0088] - The mean of the grid-normalized data of the m-th parameter in the reservoir;

[0089] u m,i - Normalized grid data of the m-th parameter in the reservoir;

[0090] σ m -Standard deviation of the grid-normalized data for the m-th parameter in the reservoir;

[0091] V m - The coefficient of variation of the m-th parameter grid-normalized data in the reservoir;

[0092] ω m - The weighting coefficient of the grid-normalized data of the m-th parameter in the reservoir.

[0093] The comprehensive recognition index is calculated as follows:

[0094]

[0095] In the formula:

[0096] E k,ij - The comprehensive recognition index of the grid in the i-th row and j-th column of the k-th grid layer.

[0097] - The weight coefficient of the m-th parameter of the i-th row and j-th column of the k-th grid layer.

[0098] X' m,k,ij - The normalized value of the m-th parameter of the i-th row and j-th column of the k-th grid layer.

[0099] The comprehensive identification index of each grid in the strong dominant seepage channel ranges from 0.45 to 0.68, the comprehensive identification index of each grid in the weak dominant seepage channel ranges from 0.23 to 0.45, and the comprehensive identification index of each grid in the non-dominant seepage channel ranges from 0 to 0.23.

[0100] The profile control agent can be a gel-type profile control agent, a gel-type profile control agent, a polymer microsphere profile control agent, or a foam-type water-blocking profile control agent.

[0101] The injection concentration range of the profile control agent for strong dominant seepage channels is 1000 mg / L-2500 mg / L, and the injection concentration range of the profile control agent for weak dominant seepage channels is 100 mg / L-1000 mg / L.

[0102] The injection volume of profile control agent for strong dominant seepage channels is 0.15-0.3 PV; the injection volume of profile control agent for weak dominant seepage channels is 0.01-0.15 PV.

[0103] Viscosity reducers can be CO2, surfactants, or nanofluids.

[0104] The surfactants are: sodium dodecyl sulfate, dodecyl dimethyl betaine, hexadecyl trimethylammonium bromide, or dodecyl glycoside.

[0105] The nanofluids are: silica nanofluids, molybdenum disulfide nanofluids, zirconium dioxide nanofluids, nano-iron oxide, or nano-graphite.

[0106] The following analysis examines the variation patterns of the parameters. To investigate the variations in water permeability, water saturation, and flow rate, an ideal model of a 5-point well network (including 1 injection well and 4 production wells) was established, incorporating both water and oil phases. Under a constant production regime, the continuous injection rate of the injection well is 56 m³ / s. 3 / d, the simulation lasted for 10 years. 0.20PV, 0.35PV, 0.50PV, and 0.65PV were injected respectively. Other basic parameters of the ideal model are shown in Table 1.

[0107] Table 1 Basic Parameters of the Ideal Model

[0108]

[0109] (1) The variation law of water dilution ratio

[0110] During the water injection process, the calculated water injection volume is positive when water is injected along the x, y, and z directions; and negative when water is injected in the opposite x, y, and z directions. Figure 2 Therefore, in calculating the water permeability ratio, it is necessary to take the absolute value of the water injection volume of the grid, then sum the absolute values ​​of the water injection volume in each direction at each time step, and finally divide by the pore volume of each grid to obtain the actual grid water permeability ratio. As the water injection volume increases, the water permeability ratio around water wells and oil wells increases significantly, with a faster increase along the main flow lines of water wells and oil wells. Between injection wells and production wells, as the injection volume increases, the affected area of ​​the injected water gradually expands, and the water permeability ratio gradually increases, as shown in [see figure]. Figure 3 .

[0111] (2) The changing pattern of permeability values

[0112] Through different permeability rates (100-2500×10) -3 μm 2 In the core sample waterflooding experiment, the rate of change in permeability before and after waterflooding showed a logarithmic relationship with the original permeability. This logarithmic relationship revealed that after long-term waterflooding, the original permeability of the core sample was less than 920 × 10⁻⁶. -3 μm 2 The core permeability decreased, and the original permeability was greater than 920×10. -3 μm 2 The permeability of the core samples showed an increasing trend before and after waterflooding, ranging from 0.5% to 10%. By fitting the data, surface plots of permeability changes after waterflooding with different flow ratios were obtained, as shown in the figure. Figure 4 .

[0113] (3) The variation law of water saturation

[0114] As the injection volume increases, the water saturation around the water well increases significantly, with a faster increase in water saturation along the main flow line between the water and oil wells. Between the injection and production wells, as the injection volume increases, the affected area of ​​the injected water gradually expands, increasing the degree of crude oil recovery. This leads to a decrease in oil saturation and a gradual increase in water saturation within the reservoir. Figure 5 .

[0115] Based on the above analysis of the parameters for identifying dominant seepage channels in oil reservoirs, it can be seen that the parameters of water flow ratio, permeability change, and water saturation at different times in oil reservoirs have the characteristics of time accumulation and quantification, while also fully taking into account the changes in reservoir physical properties and fluid flow. Thus, the development degree of dominant seepage channels in oil reservoirs can be comprehensively described in terms of dynamic and static time and space.

[0116] The method for identifying dominant flow channels was applied to a field example, and the accuracy of the identified dominant flow channels was verified using the monitoring results of field isotope tracers. To ensure the reliability of the verification, the reservoir properties should be similar to those of the core used in the water drive permeability variation experiment. Therefore, reservoir D, a typical terrestrial sedimentary type, was selected. This reservoir exhibits strong heterogeneity in plan view and has undergone 60 years of water injection development. Due to the high intensity of water injection, dominant flow channels are easily formed between the injection wells and production wells. This reservoir has 6 water wells and 6 production wells. A corresponding corner-type gridded black oil numerical model was established, with the grid planar specifications being: length × width = 20 × 20 m. 2 The model's storage fit was 97.7%, and the moisture content fit was 82.0% (with a monthly time node, moisture content error = (actual moisture content - calculated moisture content) / actual moisture content; when the moisture content error value is less than or equal to 1.0%, it is considered a moisture content time node that meets the standard; moisture content fit = moisture content time node that meets the standard / all moisture content time nodes).

[0117] In the process of quantitatively characterizing the development degree of dominant seepage channels in an oil reservoir, the ranges of parameters such as water permeability ratio, permeability variation, and water saturation in the target study area are first normalized. Then, weighting coefficients are calculated. The ranges of variation for each parameter are shown in Table 2.

[0118] Table 2. Calculation of water saturation ratio, permeability change, water saturation standardization, and weighting coefficient.

[0119]

[0120] By calculating the standardized values ​​of parameters such as water permeability ratio, permeability variation, and water saturation of each grid in the reservoir at the current stage, and multiplying each standardized value by its corresponding weighting coefficient, the comprehensive identification index of each grid in the reservoir at the current stage is obtained. Based on the calculated comprehensive identification index, the index is divided into three average ranges, thereby classifying the development degree of the dominant seepage channels in the reservoir at the current stage into three different levels, such as... Figure 3 As shown.

[0121] Table 3. Ranges and standardization of each parameter.

[0122]

[0123] After calculating the comprehensive identification index for all grids, the data file is output using visualization software. The calculated comprehensive identification index field of dominant seepage channels in reservoir D at this stage is shown in [link to documentation]. Figure 6The calculation results show that there is a strong dominant seepage channel between WAT3 water well and PRO4 oil well, and a weak dominant seepage channel between WAT3 water well and PRO5 oil well; there is a strong dominant seepage channel between WAT2 water well and PRO1 oil well, and a weak dominant seepage channel between WAT2 water well and PRO2 oil well.

[0124] Inter-well tracer interpretation and verification:

[0125] Inter-well tracer technology is considered one of the most direct and accurate methods for identifying dominant flow channels. By monitoring the results of trace element tracer analysis, the water drive velocity from injected water to the oil well can be calculated, thereby determining the dominant flow channels in the reservoir. In reservoir D, 0.4 kg of tracer Pr was injected from the WAT3 water well. The PRO4 oil well initially encountered tracer Pr after 35 days, with an initial tracer concentration of 0.79 μg / L. The calculated water drive velocity was 5.6 m / d. Figure 8 The PRO5 well first encountered tracer Pr after 55 days, with an initial tracer concentration of 0.56 μg / L. The calculated water drive rate was 3.4 m / d. Figure 9 A strong dominant flow channel exists between the WAT3 water well and the PRO4 oil well, while a weak dominant flow channel exists between them. The results of the two dominant flow channels interpreted by the inter-well tracer are consistent with the results calculated by the new method.

[0126] Numerical simulation software was used to simulate reservoir D. 0.15PV profile modifier was injected into each injection well and then water-driven to a water cut of 98%. Ultimately, the recovery rate only increased by 15%.

[0127] Numerical simulation software was used to simulate the injection of profile control agents in reservoir D, followed by the injection of sodium dodecyl sulfate (NDS) viscosity reducer. After optimization through numerical simulation, the injection concentration of profile control agent in the strong dominant flow channels was 1800 mg / L, with an injection volume of 0.2 PV. The injection concentration of profile control agent in the weak dominant flow channels was 600 mg / L, with an injection volume of 0.1 PV, followed by the injection of 0.2 PV of viscosity reducer. Ultimately, waterflooding was achieved to a water cut of 98%, increasing the oil recovery rate by 27%.

[0128] The parts of this invention not described in detail are techniques known to those skilled in the art.

[0129] The embodiments of the present invention have been described above with reference to the accompanying drawings. However, the present invention is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms under the guidance of the present invention without departing from the spirit and scope of the claims, and all of these forms are within the protection scope of the present invention.

Claims

1. A method for profile control and oil displacement in a high water cut reservoir, characterized in that, The method includes the following steps: S1: using natural cores with different permeabilities in the oil reservoir to be watered in different multiples to obtain the permeability change values of the cores with different permeabilities under different water passing multiples, and fitting to obtain the permeability change value curve of the cores with different permeabilities under different water passing multiples; S2: establishing an oil reservoir numerical simulation model, calculating the water passing multiple, permeability change value and water saturation of each grid in the oil reservoir after history matching, and taking them as parameters for describing the development degree of the dominant seepage channel in the oil reservoir; S3: performing normalization calculation and processing on the water passing multiple, permeability change value and water saturation obtained in step S2; S4: using the objective weighting coefficient of variation method to calculate the weight coefficients of the permeability change value, water passing multiple and water saturation of each grid respectively; S5: calculating the comprehensive identification index according to the permeability change value, water passing multiple, water saturation and their respective weight coefficients, and identifying the dominant seepage channel according to the comprehensive identification index; the dominant seepage channel is divided into a strong dominant seepage channel, a weak dominant seepage channel and a non-dominant seepage channel; S6: calculating the injection concentration and injection amount of the profile control agent according to the dominant seepage channel identified in step S5, and adjusting the pressure gradient in different dominant seepage channels; S7: performing profile control on the actual oil reservoir according to the best injection concentration and injection amount of the profile control agent calculated in step S6, and then injecting a viscosity reducer for displacement to improve the oil recovery of the oil reservoir. The objective weighting coefficient of variation method is calculated as follows: （3） （4） （5） （6） In the formula: - the grid normalized data mean of the mth parameter in the reservoir; - mth parameter grid normalized data in the reservoir; - the standard deviation of the grid normalized data of the mth parameter in the reservoir; - the coefficient of variation of the normalized data of the mth parameter grid in the reservoir; - weight coefficient of the grid normalized data of the mth parameter in the reservoir; The comprehensive identification index is calculated as follows: （7） In the formula: - the global identification index of the grid of the i-th row and j-th column of the k-th grid layer, - a weight coefficient of an mth entry parameter of an ith row jth column grid of a kth grid layer, - the normalized value of the m-th parameter of the j-th column of the i-th row of the k-th grid layer.

2. The method for profile control and oil displacement in high water cut reservoirs according to claim 1, characterized in that, The calculation formula of the water passing multiple is as follows: （1） In the formula: Grid overwater multiple, dimensionless, for time steps 0 to t Qx,t = discharge in x direction at time step t, m 3 ; Let m be the water flow rate in the x-direction grid at time step t. 3 ; Qz(t) = Qz(t - 1) + Qz(t - 1) * (1 - t) for t time steps z-direction grid overland flow, m 3 ; Vp is the pore volume, m3 3 .

3. The method for profile control and oil displacement in high water cut reservoirs according to claim 1, characterized in that, The normalization calculation is as follows: （2） In the formula: - normalized value of the mth parameter of the grid of the ith row and jth column of the kth layer in the reservoir - the original data of the mth parameter of the reservoir in the ith row and jth column grid of the kth layer in the reservoir; X m,max - maximum value of the grid raw data set of the mth parameter in the reservoir; X m,min - Minimum value of the grid original data set of the mth parameter in the reservoir.

4. The method for profile control and oil displacement in high water cut reservoirs according to claim 1, characterized in that, The range of the comprehensive identification index of each grid of the strong dominant seepage channel is 0.45-0.68, the range of the comprehensive identification index of each grid of the weak dominant seepage channel is 0.23-0.45, and the range of the comprehensive identification index of each grid of the non-dominant seepage channel is 0-0.

23.

5. The method for profile control and oil displacement in high water cut reservoirs according to claim 1, characterized in that, The profile control agent is a gel type profile control agent, a gel type profile control agent, a polymer microsphere profile control agent or a foam type water plugging profile control agent.

6. The method for profile control and oil displacement in high water cut reservoirs according to claim 1, characterized in that, The injection concentration of the profile control agent of the strong dominant seepage channel ranges from 1000 mg / L to 2500 mg / L, and the injection concentration of the profile control agent of the weak dominant seepage channel ranges from 100 mg / L to 1000 mg / L.

7. The method for profile control and oil displacement in high water cut reservoirs according to claim 1, characterized in that, The injection amount of the profile control agent of the strong dominant seepage channel is 0.15-0.3 PV, and the injection amount of the profile control agent of the weak dominant seepage channel is 0.01-0.15 PV.

8. The method for profile control and oil displacement in high water cut reservoirs according to claim 1, characterized in that, The viscosity reducer is CO2, a surfactant or a nanofluid.

9. The method of claim 8, wherein the water content of the oil reservoir is 70% or more. The surfactant is sodium dodecyl sulfate, dodecyl dimethyl betaine, cetyltrimethylammonium bromide or dodecyl glycoside.

10. The method of claim 8, wherein the water content of the oil reservoir is 70% or more. The nanofluid is a silicon dioxide nanofluid, a molybdenum disulfide nanofluid, a zirconium dioxide nanofluid, a nanometer ferroferric oxide fluid or a nanometer graphite fluid.

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