An injection-production structure adjustment method based on flow field characterization for offshore high-water-cut oilfields

Abstract

The application provides a kind of offshore high water cut oilfield injection-production structure adjustment method based on flow field characterization, belongs to the technical field of reservoir engineering, including the following steps: S1: fine history matching of reservoir numerical model and calculation of flow field basic attribute parameters;S2: taking the grid in the numerical model as a unit, calculate the dynamic efficiency coefficient in each grid and carry out normalization processing;S3: dynamic efficiency coefficient field grading evaluation, divide injection-production structure adjustment potential unit;S4: calculate the reserve abundance coefficient of each grid unit and carry out normalization processing;S5: combine the normalized dynamic efficiency coefficient and reserve abundance coefficient of grid unit, calculate and output dynamic splitting coefficient;S6: based on dynamic splitting coefficient, carry out flow field grading evaluation, and then guide injection-production structure adjustment.The application realizes real-time quantitative description of reservoir oil-water seepage law and remaining oil enrichment law, improves the accuracy and reliability of injection-production structure adjustment of offshore high water cut oilfield.

Description

Technical Field

[0001] This invention belongs to the field of reservoir engineering technology, and in particular relates to a method for adjusting the injection and production structure based on flow field characterization in offshore high water-cut oilfields. Background Technology

[0002] Offshore oilfields, constrained by limited production platform slots, are characterized by a low oil-to-water well ratio, high single-well input, and high fluid production intensity. After a long period of water injection development, most of my country's major offshore oilfields have entered a "dual-high" stage of high water cut and high recovery rate, making water control and oil stabilization increasingly difficult. In the high water cut stage, injection-production regulation is the most effective means to improve recovery rate and reduce water cut rise rate. Therefore, researching methods for adjusting the injection-production structure in offshore high water cut oilfields is of great significance for the efficient development of offshore oilfields.

[0003] Currently, the main methods for adjusting the injection-production structure in offshore oilfields include dynamic methods, residual oil methods, and water injection splitting calculation methods. However, offshore oilfield testing data is limited, and the understanding of water flooding patterns is unclear. The above reservoir engineering methods are still based on static data and cannot achieve real-time evaluation and quantitative characterization of the injection-production structure during reservoir development. Furthermore, in the high water-cut stage, the residual oil enrichment pattern becomes increasingly complex, and the injection-production contradictions, such as dominant channels, become more prominent. Traditional injection-production structure adjustment methods are no longer sufficient to solve the injection-production adjustment problems in the high water-cut stage. Therefore, there is an urgent need to establish a method for adjusting the injection-production structure in offshore high water-cut oilfields to guide the injection-production adjustment in the high water-cut stage. To this end, we have invented an injection-production structure adjustment method for offshore high water-cut oilfields based on flow field characterization to solve the above technical problems. Summary of the Invention

[0004] In view of this, the present invention aims to propose a method for adjusting the injection-production structure of offshore high water-cut oilfields based on flow field characterization. The method uses fine reservoir numerical simulation technology to conduct flow field evaluation, proposes to use the dynamic effect coefficient as an indicator to screen potential units for adjusting the injection-production structure, proposes a dynamic splitting coefficient, and determines the injection-production adjustment multiple to achieve optimized adjustment of the injection volume of water injection wells in the oilfield.

[0005] To achieve the above objectives, the technical solution of this invention is as follows: a method for adjusting the injection-production structure in offshore high water-cut oilfields based on flow field characterization, comprising the following steps:

[0006] S1: Fine history fitting of reservoir numerical model and calculation of basic property parameters of flow field. In the field application, the basic parameters are first output by the simulator, and the basic property parameters are processed by the Petrel-Re calculator and finally used for real-time utilization status judgment.

[0007] S2: Using the grid in the numerical model as the unit, calculate and output the dynamic effect coefficient in each grid, and perform normalization processing;

[0008] S3: Dynamic effect coefficient field classification evaluation, dividing the potential units for injection-production structure adjustment;

[0009] S4: Calculate and output the abundance coefficient of each grid cell and normalize it;

[0010] S5: Combine the normalized dynamic efficiency coefficient and the abundance coefficient of the grid cell to calculate and output the dynamic splitting coefficient;

[0011] S6: Conduct flow field classification evaluation based on dynamic splitting coefficient, and then guide the adjustment of injection and production structure.

[0012] Furthermore, in step 2, the kinetic coefficient refers to the product of the normalized oil phase output velocity and the oil content, and its expression is shown in equations (1) and (2):

[0013]

[0014]

[0015] Where: E—dynamic effect coefficient, dimensionless;

[0016] f o —Oil content, dimensionless;

[0017] —Normalized oil phase output rate;

[0018] —Normalized oil phase output velocities in all directions;

[0019] E t —Normalized kinetic coefficients, dimensionless;

[0020] E max —Maximum dynamic effect coefficient, dimensionless;

[0021] E min —Minimum dynamic coefficient, dimensionless.

[0022] Furthermore, in step 3, the kinetic coefficient field is quantitatively graded and evaluated using the characteristic curve method; the normalized oil phase output velocity is sequentially set to 0, 0.001, 0.002...1, and the kinetic coefficient data distribution map of all grids is plotted. By plotting the relationship curve between the kinetic coefficient and the oil content, the theoretical range of the data distribution of the reserve kinetic coefficient is obtained; the kinetic coefficient is distributed as a whole within an isosceles triangular area in the figure, and this range is the theoretical distribution range of the kinetic coefficient parameter values.

[0023] Based on the composite characteristics of the parameters, the current value of the dynamic efficiency coefficient parameter can intuitively show the effectiveness of the driving energy in different regions, i.e. the efficiency of water-driven driving. Within the theoretical distribution triangle, with the help of the water content index, the dynamic efficiency coefficient field is divided into six levels from low to high, namely ineffective, extremely inefficient, inefficient, medium efficient, high efficient, and strong efficient, using the maximum dynamic efficiency coefficient value corresponding to different water content critical values ​​as the critical point.

[0024] Furthermore, in step 4, the reserve abundance coefficient refers to the volume of crude oil per unit area. The reserve abundance coefficient can characterize the size of the crude oil reserve potential of the reservoir, and its expression is shown in equation (3):

[0025] Ω=hφS o (3)

[0026] Where: Ω—reserve abundance coefficient, m;

[0027] h—thickness, m;

[0028] φ—Porosity, dimensionless;

[0029] S o —Oil saturation, dimensionless.

[0030] Furthermore, in step 5, the dynamic splitting coefficient refers to the difference between the normalized dynamic efficiency coefficient and the normalized reserve abundance coefficient, and its expression is shown in equation (4):

[0031] M = E t -Ω t (4)

[0032] in, In the formula: M—dynamic splitting coefficient, dimensionless

[0033] Ω—Reserve abundance coefficient, m;

[0034] Ω t —Normalized reserves abundance coefficient, dimensionless;

[0035] Ω max —Maximum reserves abundance coefficient, m;

[0036] Ω min —Minimum abundance coefficient of reserves, m.

[0037] Furthermore, in step 6, the injection-production structure adjustment based on the dynamic splitting coefficient field can clearly show the injection-production balance of the target area through the dynamic splitting coefficient contour map. When the dynamic splitting coefficient is greater than 1 and the larger the value, it indicates that the reserves are relatively high, but the regional flow field intensity is relatively insufficient. It is generally recommended to carry out fluid lifting operations on the regional injection-production wells to enhance the flow field intensity. When the dynamic splitting coefficient is less than 1 and the smaller the value, it indicates that the flow field intensity is relatively high. It is necessary to carry out fluid limiting operations on the area to reduce inefficient water flushing. The splitting coefficient can be used to assist the dynamic efficiency coefficient to better evaluate and control the water drive status at the current time.

[0038] Compared to existing technologies, the injection-production structure adjustment method for offshore high water-cut oilfields described in this invention has the following advantages: This invention utilizes refined reservoir numerical simulation technology to conduct flow field evaluation, proposes using the dynamic efficiency coefficient as an indicator to screen potential units for injection-production structure adjustment, proposes a dynamic splitting coefficient, and determines the injection-production adjustment multiple to optimize the injection volume of water injection wells in the oilfield. This invention overcomes the shortcomings of traditional injection-production structure adjustment methods, which are based on static data and cannot achieve real-time evaluation and quantitative characterization of the injection-production structure during reservoir development. Based on refined reservoir numerical simulation technology, it achieves real-time quantitative characterization of reservoir oil-water seepage patterns and residual oil enrichment patterns, improving the accuracy and reliability of injection-production structure adjustment in offshore high water-cut oilfields. Attached Figure Description

[0039] The accompanying drawings, which form part of this invention, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an undue limitation of the invention. In the drawings:

[0040] Figure 1 This is a flowchart of a method for adjusting the injection-production structure of offshore high water-cut oilfields based on flow field characterization, as described in an embodiment of the present invention.

[0041] Figure 2 This is the kinetic effect coefficient classification characteristic curve upon which this invention is based;

[0042] Figure 3 This invention is based on the graded flow field diagram of the dynamic coefficient of the SZ oilfield.

[0043] Figure 4 This invention is based on the dynamic splitting coefficient graded flow field diagram of the SZ oilfield. Detailed Implementation

[0044] It should be noted that, unless otherwise specified, the embodiments and features described in the present invention can be combined with each other.

[0045] The present invention will now be described in detail with reference to the accompanying drawings and embodiments.

[0046] like Figure 1 As shown, reservoir numerical simulation technology is an important means for understanding the oil-water seepage patterns and remaining oil enrichment patterns in offshore oilfields. Furthermore, with the development of numerical simulation technology, current offshore oilfield reservoir numerical models can achieve very high simulation accuracy. This invention presents a method for adjusting the injection-production structure in offshore high water-cut oilfields based on flow field characterization. This invention utilizes refined reservoir numerical simulation technology to conduct flow field evaluation, proposes using the dynamic effect coefficient as an indicator to screen potential units for injection-production structure adjustment, proposes a dynamic splitting coefficient, and determines the injection-production adjustment multiple to optimize the injection volume of water injection wells in the oilfield.

[0047] This approach involves evaluating the reservoir flow field based on numerical simulation, proposing dynamic efficiency coefficients to screen potential units for adjusting the injection-production structure, and using dynamic splitting coefficients to guide quantitative adjustments to injection and production rates. Specifically, it includes the following steps:

[0048] S1: Fine history fitting of reservoir numerical model and calculation of basic property parameters of flow field. In the field application, the basic parameters are first output by the simulator, and the basic property parameters are processed by the Petrel-Re calculator and finally used for real-time utilization status judgment.

[0049] S2: Using the grid in the numerical model as the unit, calculate and output the dynamic effect coefficient in each grid, and perform normalization processing;

[0050] The kinetic coefficient refers to the product of the normalized oil phase output velocity and the oil content, and its expression is shown in equations (1) and (2):

[0051]

[0052]

[0053] Where: E—dynamic effect coefficient, dimensionless;

[0054] f o —Oil content, dimensionless;

[0055] —Normalized oil phase output rate;

[0056] —Normalized oil phase output velocities in all directions;

[0057] E t —Normalized kinetic coefficients, dimensionless;

[0058] E max —Maximum dynamic effect coefficient, dimensionless;

[0059] E min —Minimum dynamic coefficient, dimensionless.

[0060] The dynamic efficiency coefficient is used to characterize the timeliness of reservoir waterflooding development. This parameter introduces oil cut to represent the "current dimension theoretical upper limit of the dynamic capacity" of the reservoir grid unit's reserves, and uses normalized oil phase output velocity to represent the "current objective driving energy" used to drive the reserves within the grid. The product of these parameters represents the effective driving energy under the dynamic capacity limit, i.e., the energy value that can be effectively applied to drive the dynamic reserves within each unit under the current driving energy distribution state. In flow field characterization applications, this parameter can effectively characterize the real-time operational status of reservoir units with different physical characteristics.

[0061] The driving and carrying effects of water injection on regional reserves vary at different time points and in different areas during water-drive development. This can lead to insufficient oil phase mobility in high-drive energy areas and insufficient drive energy in high-mobility areas, resulting in uneven distribution of water-drive capacity and reduced development efficiency. A reserve dynamic efficiency coefficient is used to characterize the instantaneous driving effect of water-drive at various time points. This parameter field can display the development status under different water-drive scouring conditions within the target block in real time, thereby identifying areas with low water-drive control and insufficient energy.

[0062] S3: Dynamic effect coefficient field classification evaluation, dividing the potential units for injection-production structure adjustment;

[0063] The method of characteristic curves is used to achieve quantitative classification and evaluation of the dynamic effect coefficient field. Normalized oil phase output velocities are set to 0, 0.001, 0.002...1 in sequence, and dynamic effect coefficient data distribution maps of all grids are plotted. By plotting the relationship curve between dynamic effect coefficient and oil content, the theoretical range of dynamic effect coefficient data distribution of reserves is obtained. The dynamic effect coefficient is distributed in an isosceles triangular area in the figure, and this range is the theoretical distribution range of dynamic effect coefficient parameter values.

[0064] The graded evaluation of the real-time operational status of oil reservoirs needs to consider both the data rationality and practical applicability of the evaluation results. The variation characteristics of the reservoir kinetic efficiency coefficient index, used for dynamic characterization of the flow field in the current dimension, were analyzed. The analysis yielded a triangle representing the theoretical distribution range of the reservoir kinetic efficiency coefficient parameters. Furthermore, the analysis showed that this parameter can achieve a high kinetic efficiency characterization effect in low-water-cut zones when characterizing the kinetic efficiency of units with the same kinetic energy but different water cut levels.

[0065] Based on the composite characteristics of the parameters, the current value of the dynamic efficiency coefficient parameter can intuitively show the effectiveness of the driving energy in different regions, i.e. the efficiency of water-driven driving. Within the theoretical distribution triangle, with the help of the water content index, the dynamic efficiency coefficient field is divided into six levels from low to high, namely ineffective, extremely inefficient, inefficient, medium efficient, high efficient, and strong efficient, using the maximum dynamic efficiency coefficient value corresponding to different water content critical values ​​as the critical point.

[0066] S4: Calculate and output the abundance coefficient of each grid cell and normalize it;

[0067] Among them, the reserve abundance coefficient refers to the volume of crude oil per unit area. The reserve abundance coefficient can characterize the size of the crude oil reserve potential of the reservoir, and its expression is shown in equation (3):

[0068] Ω=hφS o (3)

[0069] Where: Ω—reserve abundance coefficient, m;

[0070] h—thickness, m;

[0071] φ—Porosity, dimensionless;

[0072] S o —Oil saturation, dimensionless.

[0073] S5: Combine the normalized dynamic efficiency coefficient and the abundance coefficient of the grid cell to calculate and output the dynamic splitting coefficient;

[0074] The dynamic splitting coefficient refers to the difference between the normalized dynamic efficiency coefficient and the normalized reserve abundance coefficient, and its expression is shown in equation (4):

[0075] M = E t -Ω t (4)

[0076] in, In the formula: M—dynamic splitting coefficient, dimensionless

[0077] Ω—Reserve abundance coefficient, m;

[0078] Ω t —Normalized reserves abundance coefficient, dimensionless;

[0079] Ω max —Maximum reserves abundance coefficient, m;

[0080] Ω min —Minimum abundance coefficient of reserves, m.

[0081] The dynamic splitting coefficient is composed of a dynamic efficiency coefficient representing the dimensionless effective energy of the grid, and a reserve abundance representing the dimensionless reserves of the grid. The physical meaning of this parameter is the sufficiency of the effective driving energy corresponding to regional water-drive scour relative to the regional reserves. This parameter comprehensively considers three factors: water-drive energy, oil phase flow capacity, and unit reserves, and is used to characterize the suitability of regional water injection / oil production intensity; quantitative analysis based on numerical modeling methods provides a reference for balanced injection-production control.

[0082] S6: Conduct flow field classification evaluation based on dynamic splitting coefficient, and then guide the adjustment of injection and production structure.

[0083] Among them, the injection-production structure adjustment based on the dynamic splitting coefficient field can clearly show the degree of injection-production balance in the target area through the dynamic splitting coefficient contour map. When the dynamic splitting coefficient is greater than 1 and the larger the value, the reserves are relatively high, but the flow field intensity is relatively insufficient. It is generally recommended to perform fluid lifting operations on the injection-production wells in the area to enhance the flow field intensity. When the dynamic splitting coefficient is greater than 1 and the larger the value, the flow field intensity is relatively high, and fluid limiting operations are needed in the area to reduce inefficient water flushing. Using the splitting coefficient to assist the dynamic effect coefficient can better evaluate and control the current water drive status.

[0084] The following explanation uses the Bohai SZ oilfield as an example.

[0085] S1: Fine-grained history fitting of reservoir numerical model and calculation of basic flow field property parameters;

[0086] In the field application, the simulator is first used to output basic parameters, and the Petrel-Re calculator is used to process and output basic attribute parameters. Finally, it is used for real-time utilization status judgment. Based on the numerical model of the Bohai SZ oilfield reservoir, flow field evaluation is carried out to complete the injection and production structure adjustment and other work.

[0087] S2: Using the grid in the numerical model as the unit, calculate and output the dynamic effect coefficient in each grid, and perform normalization processing;

[0088] The driving and carrying effects of water injection on regional reserves vary at different time points and in different areas during water-drive development. This can lead to insufficient oil phase mobility in high-drive energy areas and insufficient drive energy in high-mobility areas, resulting in uneven distribution of water-drive capacity and reduced development efficiency. A reserve dynamic efficiency coefficient is used to characterize the instantaneous driving effect of water-drive at various time points. This parameter field can display the development status under different water-drive scouring conditions within the target block in real time, thereby identifying areas with low water-drive control and insufficient energy.

[0089] S3: Dynamic effect coefficient field classification evaluation, dividing the potential units for injection-production structure adjustment;

[0090] Taking into account both moisture content and dynamic efficiency coefficient parameters, a joint classification method based on these two parameters is proposed. For example... Figure 2As shown in the figure, within the theoretical distribution range of the dynamic effect coefficient, "energy grading and state zoning" are carried out, and the flow fields with different water contents and different dynamic effects are subdivided into "6 levels and 12 zones": the low water content area within the range of 0 < E < 1 is subdivided into four levels: extra-low, low, medium, and high; the extra-high water content area is always divided into the state of extra-low effective production; the area with E = 0 is divided into the ineffective production area; the area with E = 1 is divided into the highly effective production area. Through this method, the reasonable differentiation of the real-time production state of different oil-bearing areas can be achieved, as well as the accurate identification of high oil-bearing and low dynamic effect areas, so as to achieve clear guidance and precise measures in field practice.

[0091] Based on the composite characteristics of parameters, the effective degree of driving energy in different regions can be intuitively displayed through the current numerical value of the reserve dynamic effect coefficient parameter, that is, the efficiency of water flooding; within the theoretical distribution triangle, with the help of the water cut index, taking the maximum dynamic effect coefficient value corresponding to different water cut critical values as the critical point, the dynamic effect coefficient field is divided into 6 levels from low to high: ineffective, extra-low effective, low effective, medium effective, high effective, and highly effective, as Figure 3 shown. Generally, it is considered to preferentially carry out measures to tap potential in high oil-bearing areas, while for areas with high water cut and serious water flooding, water control measures such as profile control and water plugging need to be carried out to block the ineffective water circulation channels with low oil content and high water flow rate, so that the injected water preferentially passes through the remaining oil enrichment areas with low water content and low production, thereby achieving production increase and extraction improvement and efficient development.

[0092] S4: Calculate and output the reserve abundance coefficient of each grid unit, and perform normalization processing;

[0093] S5: Combine the normalized dynamic effect coefficient and reserve abundance coefficient of the grid unit, calculate and output the dynamic splitting coefficient; the parameter composition of the dynamic splitting coefficient is that the dynamic effect coefficient represents the dimensionless effective energy of the grid, and the reserve abundance represents the dimensionless reserve of the grid.

[0094] S6: Carry out flow field grading evaluation based on the dynamic splitting coefficient, and then guide the adjustment of the injection-production structure.

[0095] Through the dynamic splitting coefficient contour map, as Figure 4 shown, the injection-production balance degree of the target area can be seen more clearly. When the dynamic splitting coefficient is greater than 1 and the value is larger, it means that the reserve is relatively high, while the flow field strength in the area is relatively insufficient. Generally, it is recommended to carry out liquid-lifting operations on the injection-production wells in the area to enhance the flow field strength; when the dynamic splitting coefficient is greater than 1 and the value is larger, it means that the flow field strength is relatively high, and it is necessary to carry out liquid-limiting operations on the area to reduce the ineffective water scouring. The specific adjustment multiples of the injection-production liquid volume are shown in Table 1. With the help of the splitting coefficient and the dynamic effect coefficient, the water flooding state in the current period can be better evaluated and regulated.

[0096] Table 1 Injection-production adjustment multiple table for different levels of dynamic splitting coefficient

[0097]

[0098]

[0099] Guided by the dynamic splitting coefficient classification field map, injection and production adjustments were carried out for well group A in SZ oilfield. Based on the dynamic splitting coefficient level of the location of the injection well, the injection volume adjustment multiple was determined to achieve quantitative optimization of the injection volume, as shown in Table 2.

[0100] Table 2. Adjustment Table of Injection Volume in Water Injection Wells

[0101]

[0102] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for adjusting the injection-production structure in offshore high water-cut oilfields based on flow field characterization, characterized in that, Includes the following steps: S1: Fine history fitting of reservoir numerical model and calculation of basic flow field property parameters. First, the basic flow field property parameters are output by the simulator. Then, the basic flow field property parameters are processed by the Petrel-Re calculator and finally used for real-time dynamic state judgment. S2: Using the grid in the reservoir numerical model as the unit, calculate and output the dynamic effect coefficient in each grid, and perform normalization processing; The kinetic efficiency coefficient is the product of the normalized oil phase output velocity and the oil content, and its expression is shown in equations (1) and (2): （1） （2） In the formula: --Dynamic effect coefficient, dimensionless; --Oil content, dimensionless; --Normalized oil phase output rate; , , --Normalized oil phase output speeds in all directions; --Normalized kinetic coefficients, dimensionless; --Maximum dynamic effect coefficient, dimensionless; --Minimum dynamic effect coefficient, dimensionless; S3: Dynamic effect coefficient field classification evaluation, dividing the potential units for injection-production structure adjustment; S4: Calculate and output the abundance coefficient of each grid cell and normalize it; S5: Combine the normalized dynamic efficiency coefficient and the abundance coefficient of the grid cell to calculate and output the dynamic splitting coefficient; The dynamic splitting coefficient refers to the difference between the normalized dynamic efficiency coefficient and the normalized reserve abundance coefficient, and its expression is shown in equation (4): （4） in, (5) Where: M -- dynamic splitting coefficient, dimensionless; --Reserve abundance coefficient, m; --Normalized reserve abundance coefficient, dimensionless; --Maximum reserves abundance coefficient, m; --Minimum abundance coefficient, m; S6: Conduct flow field classification evaluation based on dynamic splitting coefficient, and then guide the adjustment of injection and production structure.

2. The method for adjusting the injection-production structure of offshore high water-cut oilfields based on flow field characterization according to claim 1, characterized in that: In step S3, the characteristic curve method is used to achieve quantitative classification and evaluation of the dynamic effect coefficient field. The normalized oil phase output velocity is set to 0, 0.001, 0.002...1 in sequence, and the dynamic effect coefficient data distribution map of all grids is plotted. By plotting the relationship curve between dynamic effect coefficient and oil content, the theoretical range of the dynamic effect coefficient data distribution of reserves is obtained. The dynamic effect coefficient is distributed in an isosceles triangular area in the figure, and this range is the theoretical distribution range of the dynamic effect coefficient parameter values. Based on the composite characteristics of the parameters, the effective level of driving energy in different regions, i.e. the efficiency of water-driven driving, can be intuitively displayed by the current value of the reservoir dynamic efficiency coefficient parameter. Within the theoretical distribution triangle, using the moisture content index, and taking the maximum dynamic efficiency coefficient value corresponding to different moisture content critical values ​​as the critical point, the dynamic efficiency coefficient field is divided into six levels from low to high: ineffective, extremely inefficient, inefficient, medium efficient, high efficient, and highly efficient.

3. The method for adjusting the injection-production structure of offshore high water-cut oilfields based on flow field characterization according to claim 2, characterized in that: In S4, the abundance coefficient refers to the volume of crude oil per unit area. The abundance coefficient can characterize the potential of crude oil reserves in an oil reservoir, and its expression is shown in equation (3): （3） In the formula: --Reserve abundance coefficient, m; --Thickness, m; --Porosity, dimensionless; --Oil saturation, dimensionless.

4. The injection-production structure adjustment method based on flow field characterization for offshore high water-cut oilfields according to claim 1, characterized in that: In S6, the injection-production structure is adjusted based on the dynamic splitting coefficient field. The injection-production balance of the target area can be clearly seen through the dynamic splitting coefficient contour map. When the dynamic splitting coefficient is greater than 1 and the larger the value, it indicates that the reserves are relatively high, but the regional flow field intensity is relatively insufficient. It is recommended to carry out fluid lifting operation on the regional injection-production wells to enhance the flow field intensity. When the dynamic splitting coefficient is less than 1 and the smaller the value, the higher the flow field intensity, the more necessary it is to limit the liquid flow in the region to reduce inefficient water scouring. The splitting coefficient can be used to assist the dynamic efficiency coefficient in evaluating and controlling the current water drive status.

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