Method and device for evaluating oil reservoir water-gas alternate development effect

Abstract

The invention provides an oil reservoir water-gas alternate development effect evaluation method and device. The method comprises the steps of obtaining well group data of each group of production wells and injection wells in an oil reservoir water-gas alternate development well group; calculating the variation coefficient of the well group data based on an entropy weight method, and calculating the information entropy of the well group data according to the variation coefficient of the well group data; determining information entropy weights of the production well and the injection well according to the information entropy of the well group data; based on an analytic hierarchy process, analytic hierarchy weights of the production well and the injection well are determined; the comprehensive weight of the production well and the injection well is obtained according to the information entropy weight and the analytic hierarchy process weight of the production well and the injection well; according to the comprehensive weight of each group of production wells and injection wells in the oil reservoir water-gas alternation development well group, the development effect score of each group of production wells and injection wells in the oil reservoir water-gas alternation development well group is determined; according to the method, multi-dimensional comprehensive evaluation on the well group development effect is realized, the evaluation accuracy can be effectively improved, and a theoretical basis can be provided for development and adjustment of an oil reservoir.

Description

Technical Field

[0001] This invention belongs to the field of oilfield development technology, specifically relating to a method and apparatus for evaluating the effect of alternating water and gas development in oil reservoirs. Background Technology

[0002] Water-gas alternation technology is a widely used production enhancement technology in the secondary and tertiary oil recovery processes of oil and gas fields. It improves crude oil recovery by alternately injecting water and gas, utilizing the displacement effect of water and the expansion effect of gas. This technology has significant advantages in reducing fluid cross-flow, delaying reservoir pressure decay, improving reservoir sweep efficiency, and utilizing residual oil.

[0003] However, the water-gas alternation development process involves complex multi-physics coupling phenomena, which affect the reservoir development effect. Therefore, how to scientifically and systematically evaluate the effect of water-gas alternation development has become a key technical challenge to improve the efficiency of oil and gas reservoir development. There are few existing evaluation methods specifically for the effect of water-gas alternation development, and they are still in the research and exploration stage. Traditional development effect evaluation methods mainly rely on single or a few indicators and depend to a large extent on the experience judgment of field personnel, which often leads to one-sided evaluation results and difficulty in reflecting complex underground conditions and dynamic changes. This limits the accuracy and reliability of the evaluation effect and can also easily lead to unreasonable development decisions, ultimately affecting the production efficiency and economic benefits of the oilfield.

[0004] Therefore, a new method is urgently needed to solve the problems existing in the current technology. Summary of the Invention

[0005] This invention provides a method for evaluating the effectiveness of water-gas alternating development in oil reservoirs. This method enables a multi-dimensional comprehensive evaluation of well group development effectiveness, effectively improving evaluation accuracy and providing a theoretical basis for reservoir development adjustments. The method includes:

[0006] Acquire well group data for each production well and injection well within the well group for alternating development of oil, water and gas in the reservoir;

[0007] Based on the well group data of each production well and injection well in the alternating development of oil, water and gas in the reservoir, the coefficient of variation of the well group data is calculated based on the entropy weight method, and the information entropy of the well group data is calculated based on the coefficient of variation of the well group data.

[0008] Based on the information entropy of the well group data, determine the information entropy weights of each production well and injection well in the well group for alternating development of oil, water and gas in the reservoir;

[0009] Based on the analytic hierarchy process (AHP), the weights of production wells and injection wells in each group of wells for alternating water and gas development in the reservoir are determined.

[0010] The information entropy weights and analytic hierarchy process weights of each production well and injection well in the alternating water-gas development well group of the reservoir are linearly combined using the game theory combination weighting method to obtain the comprehensive weights of each production well and injection well in the alternating water-gas development well group of the reservoir.

[0011] The development effect score of each group of production wells and injection wells in the reservoir water-gas alternating development well group is determined based on the comprehensive weight of each group of production wells and injection wells.

[0012] This invention provides a reservoir water-gas alternating development effect evaluation device, which realizes a multi-dimensional comprehensive evaluation of the development effect of well groups, effectively improves the evaluation accuracy, and provides a theoretical basis for reservoir development adjustment. The reservoir water-gas alternating development effect evaluation device includes:

[0013] The data acquisition module is used to acquire well group data for each production well and injection well within the well group for alternating development of oil, water and gas in the reservoir;

[0014] The information entropy calculation module is used to calculate the coefficient of variation of well group data based on the entropy weight method, and then calculate the information entropy of the well group data based on the coefficient of variation of well group data.

[0015] The information entropy weight determination module is used to determine the information entropy weight of each production well and injection well in the reservoir water-gas alternating development well group based on the information entropy of the well group data.

[0016] The analytic hierarchy process (AHP) weight determination module is used to determine the AHP weights of each production well and injection well in a well group for alternating water and gas development of an oil reservoir, based on the analytic hierarchy process (AHP).

[0017] The comprehensive weight determination module is used to linearly combine the information entropy weights and analytic hierarchy process weights of each production well and injection well in the alternating development well group of the reservoir based on the game theory combination weighting method, so as to obtain the comprehensive weight of each production well and injection well in the alternating development well group of the reservoir.

[0018] The development effect score determination module is used to determine the development effect score of each group of production wells and injection wells in the reservoir water-gas alternating development well group based on the comprehensive weight of each group of production wells and injection wells.

[0019] This invention also provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the above-mentioned method for evaluating the effects of alternating oil reservoir water-gas development.

[0020] This invention also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method for evaluating the effects of alternating oil reservoir water-gas development.

[0021] This invention also provides a computer program product, which includes a computer program that, when executed by a processor, implements the above-mentioned method for evaluating the effects of alternating oil reservoir water-gas development.

[0022] In this embodiment of the invention, well group data of each production well and injection well in the alternating development well group of the reservoir water and gas are obtained;

[0023] Based on the well group data of each production well and injection well within the alternating water-gas development well group in the reservoir, the coefficient of variation of the well group data is calculated using the entropy weight method. Based on the coefficient of variation, the information entropy of the well group data is calculated. Based on the information entropy of the well group data, the information entropy weights of each production well and injection well within the alternating water-gas development well group are determined. Based on the analytic hierarchy process (AHP), the AHP weights of each production well and injection well within the alternating water-gas development well group are determined. The information entropy weights and AHP weights of each production well and injection well within the alternating water-gas development well group are linearly combined using a game-theoretic combination weighting method to obtain the comprehensive weights of each production well and injection well within the alternating water-gas development well group. Based on the comprehensive weights of each production well and injection well within the alternating water-gas development well group, the development effect score of each production well and injection well within the alternating water-gas development well group is determined. This embodiment of the invention achieves a multi-dimensional comprehensive evaluation of the development effect of well groups, effectively improving the accuracy of the evaluation and providing a theoretical basis for reservoir development adjustments. Attached Figure Description

[0024] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. In the drawings:

[0025] Figure 1 This is an example diagram of the method for evaluating the effect of alternating oil reservoir water-gas development in an embodiment of the present invention;

[0026] Figure 2 This is a schematic diagram showing the location distribution of each well in the well group developed in this embodiment of the invention;

[0027] Figure 3 This is a specific example diagram illustrating the determination of information entropy weights in an embodiment of the present invention;

[0028] Figure 4This is a schematic diagram of the layered logic in an embodiment of the present invention;

[0029] Figure 5 This is a structural example diagram of the reservoir water-gas alternating development effect evaluation device in an embodiment of the present invention;

[0030] Figure 6 This is a specific example diagram of the structure of the reservoir water-gas alternating development effect evaluation device in an embodiment of the present invention.

[0031] Figure 7 This is a schematic diagram of the computer device structure according to an embodiment of the present invention. Detailed Implementation

[0032] 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 embodiments of the present invention, and not all embodiments. 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.

[0033] The inventors' research revealed that there are few existing evaluation methods specifically for the development effects of water-gas alternation. Traditional development effect evaluation methods mainly rely on single or a few indicators and depend heavily on the experience and judgment of field personnel. This singularity and subjectivity often leads to one-sided evaluation results that fail to reflect complex underground conditions and dynamic changes. In addition, traditional evaluation methods rarely consider the heterogeneity of reservoir conditions and the synergistic effects of multiple influencing factors, making it difficult to fully capture the comprehensive effects of various dynamic parameters during water-gas alternation. This not only limits the accuracy and reliability of the evaluation results but also easily leads to unreasonable development decisions, ultimately affecting the production efficiency and economic benefits of the oilfield.

[0034] To address the problems existing in the current technology, the inventors have comprehensively considered the coupling effect of multiple factors and proposed a method for evaluating the development effect of alternating water and gas. The aim is to establish an accurate and reliable evaluation method for the development effect and health status of production wells in well groups, filling the gap in this technical field.

[0035] Figure 1 This is an example diagram illustrating the method for evaluating the effectiveness of alternating oil reservoir water-gas development in an embodiment of the present invention. Figure 1 As shown, the evaluation method for the effectiveness of water-gas alternation development in this reservoir includes:

[0036] Step 101: Obtain well group data for each production well and injection well within the reservoir water-gas alternating development well group;

[0037] Step 102: Based on the well group data of each production well and injection well in the alternating development well group of the reservoir water and gas, calculate the coefficient of variation of the well group data based on the entropy weight method, and calculate the information entropy of the well group data based on the coefficient of variation of the well group data.

[0038] Step 103: Determine the information entropy weights of each production well and injection well in the well group for alternating development of oil, water and gas reservoirs based on the information entropy of the well group data.

[0039] Step 104: Based on the analytic hierarchy process (AHP), determine the AHP weights of each production well and injection well in the well group for alternating development of oil, water and gas in the reservoir.

[0040] Step 105: The information entropy weights and analytic hierarchy process weights of each production well and injection well in the alternating development well group of the reservoir are linearly combined using the game theory combination weighting method to obtain the comprehensive weights of each production well and injection well in the alternating development well group of the reservoir.

[0041] Step 106: Determine the development effect score of each group of production wells and injection wells in the reservoir water-gas alternating development well group based on the comprehensive weight of each group of production wells and injection wells.

[0042] In step 101, the well group data of each production well and injection well in the reservoir water-gas alternating development well group are obtained.

[0043] In the embodiments, the well group data of each production well and injection well in the alternating development well group of the reservoir water and gas may include static data and dynamic data;

[0044] Static data may include well number, length of horizontal section of production well, porosity, and permeability;

[0045] Dynamic data may include cumulative oil production, injection volume, gas-oil ratio, water cut, injected gas-water ratio, gas injection rate, and water injection rate.

[0046] In a specific embodiment, the data acquisition range and cycle of the well group are first determined: taking the well group with alternating oil, water, and gas development in the reservoir as the unit, for example... Figure 2 This is a schematic diagram showing the location distribution of each well in the well group developed in this embodiment of the invention, such as... Figure 2 As shown, I1, I2, I3, and I4 represent injection wells in the development well group, and P1, P2, P3, and P4 represent production wells in the development well group. For the well group of the K reservoir water-gas alternation test area 1, the well group data of all production wells and injection wells (8 horizontal wells, including 4 injection wells and 4 production wells) in the well group were obtained within one water-gas alternation development cycle. One water-gas alternation development cycle is usually 12 months of water injection + 6 months of gas injection.

[0047] Then, the type and specific indicators of the well group data are clarified, including:

[0048] Static data includes: well number (N), length of horizontal section of production well (L), porosity ( ), penetration rate (K);

[0049] Dynamic data includes: cumulative oil production ( ), injection volume ( Gas-oil ratio (GOR), water cut (WCT), and injected gas-water ratio ( ), Injection rate ( ), water injection speed ( ).

[0050] In this embodiment, after acquiring the well group data of each production well and injection well within the alternating development well group of the reservoir water and gas, the following can be included:

[0051] The positive, negative, and extreme index data of each production well and injection well in the well group of alternating water and gas development in the reservoir were standardized. The positive index data included porosity, permeability, cumulative oil production, injection volume, gas injection rate, and water injection rate. The negative index data included gas-oil ratio and water cut. The extreme index data included the horizontal section length of the production well and the injected gas-water ratio.

[0052] In a specific implementation, the classification of indicator types is first clarified, wherein:

[0053] Positive indicator data: The larger the indicator value, the better the effect of water-gas alternation development. Examples include cumulative oil production, permeability, porosity, injection volume, gas injection rate, and water injection rate.

[0054] Inverse indicator data: The larger the indicator value, the worse the effect of water-gas alternation development, such as gas-oil ratio and water content;

[0055] Extreme value index data: The index value should be close to a certain optimal value. If it deviates from the value, the development effect will be worse. Examples include the length of the horizontal section of the production well and the injected gas-water ratio.

[0056] Then, data standardization calculations were performed on the well group data of each production well and injection well within the alternating development of oil, water, and gas in the reservoir. In the example, the positive index data was standardized according to the following formula:

[0057]

[0058] in, The data represents standardized positive indicators. This is a positive indicator data. The minimum value of the positive indicator data. This represents the maximum value of the positive indicator data.

[0059] Standardize the reverse indicator data using the following formula:

[0060]

[0061] in, This is the standardized reverse indicator data. This is reverse indicator data. The minimum value of the reverse indicator data. This represents the maximum value of the reverse indicator data.

[0062] The extreme value index data is standardized using the following formula:

[0063]

[0064] in, The data represents the standardized extreme value index. This is extreme value index data. The minimum value of the extreme value index data. The maximum value of the extreme value index data. This represents the optimal value of the extreme value index data.

[0065] Table 1 Standard Data Table for Evaluating the Effects of Alternating Water and Gas Development in Oil Reservoirs

[0066]

[0067] Table 1 is a standard data table for evaluating the effect of alternating development of oil reservoir water and gas in the embodiments of the present invention. As shown in Table 1, through the above standardization process, all well group data are transformed into data with a value range of 0-1, eliminating the influence of differences in dimensions and orders of magnitude on the evaluation results, and obtaining standard data for evaluating the effect of alternating development of oil reservoir water and gas.

[0068] In step 102, based on the well group data of each production well and injection well in the alternating development well group of the reservoir water and gas, the coefficient of variation of the well group data is calculated based on the entropy weight method, and the information entropy of the well group data is calculated based on the coefficient of variation of the well group data.

[0069] In a specific embodiment, firstly, the basic data for the calculation is determined. For example, the standardized data of eight horizontal wells in the water-gas alternation development well group of the K-type carbonate reservoir in test area 1 is used as the calculation input. Based on the entropy weight method principle, the calculation is performed using the formula:

[0070]

[0071] Calculate the coefficient of variation of data for each production well group, where Represents the coefficient of variation of the data of the j-th well group from the i-th well. This represents the standardized well group data for the j-th item of the i-th well. This represents the sum of the standardized well group data for the j-th term of all wells;

[0072] Then, based on the coefficient of variation obtained above, the formula is used:

[0073]

[0074] Calculate the information entropy corresponding to the data of each well group, where, Let n represent the information entropy of the j-th well group data, and n represent the number of producing wells in the well group. =0, then define =0.

[0075] After calculating the coefficient of variation and information entropy of all well group data, the information entropy of each production well group within the well group is obtained, providing a basis for subsequent calculation of information entropy weights.

[0076] Figure 3 This is a specific example diagram illustrating the determination of information entropy weights in an embodiment of the present invention, such as... Figure 3 As shown, based on the information entropy of well group data, determining the information entropy weights of each production well and injection well within a well group for alternating oil, water, and gas development in a reservoir can include:

[0077] Step 301: Calculate the information validity of the well group data based on the information entropy of the well group data;

[0078] Step 302: Calculate the total information validity of all production well data within the alternating development well group of the reservoir;

[0079] Step 303: The ratio of the information validity of all production well group data to the sum of information validity is used as the weighting coefficient corresponding to each group of production well and injection well group data.

[0080] Step 304: Determine the information entropy weight of each group of production wells and injection wells in the reservoir water-gas alternating development well group based on the weight coefficients corresponding to the data of each group of production wells and injection wells.

[0081] Table 2 Information Entropy Weight Table

[0082]

[0083] Table 2 is the information entropy weight table in the embodiments of the present invention. As shown in Table 2, in a specific embodiment, the information validity of the well group data is first calculated: based on the information entropy of the well group data of the four producing wells (Well-1 to Well-4) in the well group of the water-gas alternating development of the reservoir, such as the well group of the K reservoir water-gas alternating test area 1 of the carbonate rock, the formula is:

[0084]

[0085] The validity of information from all production well data within a well group undergoing alternating water and gas development in an oil reservoir is calculated. This indicates the information validity of the data from the j-th well group. This represents the information entropy of the data from the j-th well group; for example, the information validity of the Well-1 well group data is d1=1-0.75=0.25, and the information validity of the Well-2 well group data is d2=1-0.92=0.08. The calculation results correspond to the information validity d column data in Table 2.

[0086] Then, the total information validity is calculated: the information validity of all producing wells (Well-1 to Well-4) within the well group is added together to obtain the total information validity; using the formula:

[0087]

[0088] Calculate the weighting coefficients corresponding to the data of all producing wells in the well group within the reservoir water-gas alternating development well group, where, This represents the weighting coefficient of the data from the j-th well group. Let represent the information entropy of the data of the j-th well group, and k represent the number of data of all production well groups in the reservoir water-gas alternating development well group.

[0089] For example, the weighting coefficients for Well-1 are W1≈0.3659, Well-2 are W2≈0.1121, Well-3 are W3≈0.2834, and Well-4 are W4≈0.2386.

[0090] Finally, the information entropy weights are determined. The weight coefficients corresponding to the data of all production wells and injection wells in the reservoir water-gas alternating development well group are calculated and used as the information entropy weights of the corresponding production wells in the reservoir water-gas alternating development well group. That is, the information entropy weight of Well-1 is 36.59%, the information entropy weight of Well-2 is 11.21%, the information entropy weight of Well-3 is 28.34%, and the information entropy weight of Well-4 is 23.86%. The final information entropy weight results of each production well and injection well in the well group are formed.

[0091] In step 104, the weights of each production well and injection well in the well group for alternating development of oil, water and gas in the reservoir are determined based on the analytic hierarchy process (AHP).

[0092] In a specific embodiment, a hierarchical structure model is first constructed: Figure 4 This is a schematic diagram of the layered logic in an embodiment of the present invention, such as... Figure 4 As shown, taking the well group in the water-gas alternation test area 1 of the carbonate rock K reservoir as the evaluation object, a three-layer hierarchical structure was constructed:

[0093] Target layer: {Evaluation of the effectiveness of alternating water and air development};

[0094] Criterion layer: {porosity, permeability, length of horizontal section of production well, cumulative oil production, injection volume, gas-oil ratio, water cut, injected gas-water ratio, gas injection rate, water injection rate};

[0095] Solution layer: {Well-1, Well-2, Well-3, Well-4}.

[0096] Clarify the hierarchical relationships between each level, which follow the progressive logic of target level, criterion level, and scheme level. That is, by analyzing the performance of each well in the scheme level through the indicators of the criterion level, the purpose of evaluating the effect of water and gas alternation development in the target level can be achieved.

[0097] Then, a judgment matrix is ​​constructed: based on the proportional scale of the development effect of each well, where scale 1 indicates that the development effect of two wells is the same, scale 3 indicates that one well is slightly stronger than the other, scale 5 indicates that one well is stronger than the other, scale 7 indicates that one well is very stronger than the other, and scale 9 indicates that one well is absolutely stronger than the other, pairwise comparisons are made for the four production wells in the scheme layer to construct the judgment matrix:

[0098]

[0099] in, To determine the matrix, , , , , , , , The element symbols of the judgment matrix are defined, where the first subscript represents the well being compared, and the second subscript represents the well used for comparison; the judgment matrix satisfies and satisfies , =1; Ensure the logical consistency of pairwise comparisons and avoid logical contradictions such as well 1 being stronger than well 2, or well 2 being stronger than well 1.

[0100] Table 3 Judgment Matrix Data Table

[0101]

[0102] Table 3 is a judgment matrix data table in an embodiment of the present invention. The specific values ​​of the judgment matrix can be as shown in Table 3.

[0103] After constructing the judgment matrix, calculate the eigenvectors and normalized weights; then, find the largest eigenvalue λ of the constructed judgment matrix A. max The corresponding eigenvectors are then normalized to obtain the hierarchical analysis weights for each production well.

[0104] Table 4. Hierarchical Analysis Weight Data Table

[0105]

[0106] Table 4 shows the weight data table for hierarchical analysis in this embodiment of the invention. As shown in Table 4, the calculated eigenvectors for Well-1, Well-2, Well-3, and Well-4 are 0.5, 0.5, 1.5, and 1.5, respectively. The normalized weight calculation formula is as follows:

[0107] Single-well weight (%) = (Single-well eigenvector / Sum of all well eigenvectors) × 100%

[0108] That is, the sum of all well eigenvectors = 0.5 + 0.5 + 1.5 + 1.5 = 4.0. Therefore, the weight of Well-1 = (0.5 / 4.0) × 100% = 12.5%, the weight of Well-2 = 12.5%, the weight of Well-3 = 37.5%, and the weight of Well-4 = 37.5%.

[0109] Then, a consistency check is performed; first, the consistency index C is calculated using the formula:

[0110]

[0111] Where n is the number of production wells in the scheme layer, and C is the consistency index. In this embodiment, λ max =4.0, substituting into the formula, we get C=0.0;

[0112] Finally, calculate the random consistency ratio C. R The calculation formula is:

[0113]

[0114] in, The random consistency ratio, It is a random consistency indicator.

[0115] After determining the random consistency ratio, a consistency judgment is performed: when When the value is less than 0.1, the consistency of the judgment matrix is ​​acceptable. In this embodiment... =0.0 < 0.1, which means the consistency test passed.

[0116] After the above steps, the hierarchical analysis weights of the four production wells in the reservoir water-gas alternating development well group were finally determined as follows: Well-1 12.5%, Well-2 12.5%, Well-3 37.5%, and Well-4 37.5%.

[0117] In this embodiment, the information entropy weights and analytic hierarchy process (AHP) weights of each production well and injection well within the alternating water-gas development well group are linearly combined using a game-theoretic combination weighting method to obtain the comprehensive weights of each production well and injection well within the alternating water-gas development well group. This may include:

[0118] Construct a linear combination model of information entropy weight and hierarchical analysis weight, and set the weighting coefficients of information entropy weight and hierarchical analysis weight, with the sum of the two coefficients being 1.

[0119] Based on the principles of game theory, with the goal of minimizing the deviation between information entropy weights and hierarchical analysis weights, the optimal values ​​of the weighting coefficients of information entropy weights and hierarchical analysis weights are obtained.

[0120] The comprehensive weights of each production well and injection well in the reservoir water-gas alternating development well group are obtained by multiplying the information entropy weight and the hierarchical analysis weight by the optimal values ​​of the corresponding weighting coefficients and summing them.

[0121] In a specific embodiment, a linear combination model is first constructed and weighting coefficients are set; taking the well group in the water-gas alternation test area 1 of the carbonate rock K reservoir as the evaluation object, the basic weight data are clarified:

[0122]

[0123] in, Represents the information entropy weight vector. This represents the transpose of the information entropy weight vector. This represents the weight vector in hierarchical analysis. This represents the transpose of the weight vector in the hierarchical analysis. This indicates the overall weight of horizontal production wells. The weighting coefficients representing the information entropy weights. This represents the optimal weighting coefficient for information entropy weights. The weighting coefficients represent the weights assigned in the analytic hierarchy process. This represents the optimal weighting coefficient for the weights in the hierarchical analysis.

[0124] Based on game theory principles, the goal is to minimize information entropy weights. With Hierarchical Analysis Weights Taking the deviation as the objective, the solution is obtained through an optimization algorithm. and The optimal value is determined to ensure that the combined weights can balance the authenticity of the information entropy data with the rationality of the hierarchical analysis.

[0125] Table 5 Comprehensive Weighting Data Table

[0126]

[0127] Table 5 is a comprehensive weight data table in the embodiments of the present invention. As shown in Table 5, the optimal value of the weighting coefficient is calculated as follows: =0.6, =0.4, verification shows that it satisfies the condition. + =0.6+0.4=1, which meets the constraint conditions.

[0128] Finally, calculate the overall weight of each production well:

[0129] The information entropy weight and analytic hierarchy process weight of each production well are multiplied by their corresponding optimal weighting coefficients and then summed. The specific calculation is as follows:

[0130] Well-1 overall weight: W1 = 0.6 × 36.59% + 0.4 × 12.5% ​​= 21.954% + 5% = 26.95%;

[0131] Well-2 overall weight: W2 = 0.6 × 11.21% + 0.4 × 12.5% ​​= 6.726% + 5% = 11.73%;

[0132] Well-3 Overall Weighting: W3 = 0.6 × 28.34% + 0.4 × 37.5% = 17.004% + 15% = 32.00%;

[0133] Well-4 overall weight: W4 = 0.6 × 23.86% + 0.4 × 37.5% = 14.316% + 15% = 29.32%.

[0134] In this embodiment, the development effect score of each group of production wells and injection wells in the alternating oil-water-gas development well group is determined based on the comprehensive weight of each group of production wells and injection wells. This may include:

[0135] Based on historical well group data of well groups with alternating oil, water and gas development in reservoirs, a mapping relationship between comprehensive weight and development effect score is established;

[0136] Based on the comprehensive weight of each production well and injection well in the reservoir water-gas alternating development well group, and based on the mapping relationship between the comprehensive weight and the development effect score, the development effect score of each production well and injection well in the reservoir water-gas alternating development well group is obtained.

[0137] Table 6 Score Conversion Evaluation Reference Table

[0138]

[0139] In a specific embodiment, Table 6 is a score conversion evaluation reference table in this invention. As shown in Table 6, a mapping relationship between comprehensive weight and development effect score is established. Based on the historical well group data of the water-gas alternation test area 1 of the carbonate rock K reservoir, a mapping relationship between comprehensive weight and development effect score is constructed through a linear proportional conversion relationship to form a score conversion evaluation reference. The mapping rule is as follows:

[0140] When the overall weight ∈ [0, 5)%, the development effect score ∈ [0, 50).

[0141] When the overall weight ∈ [5, 10)%, the development effect score ∈ [50, 52);

[0142] When the overall weight ∈ [10, 25)%, the development effect score ∈ [52, 60);

[0143] When the overall weight ∈ [25, 64)%, the development effect score ∈ [60, 80);

[0144] When the overall weight ∈ [64, 100]%, the development effect score ∈ [80, 100].

[0145] Then, the development effectiveness score of each production well was determined: the comprehensive weights of the four production wells in the well group of the water-gas alternation test area 1 of the carbonate rock K reservoir were extracted: Well-1 was 26.95%, Well-2 was 11.73%, Well-3 was 32.00%, and Well-4 was 29.32%. Based on the above mapping relationship, the corresponding development effectiveness scores were matched:

[0146] Well-1 has a comprehensive weight of 26.95% ∈ [25, 64)%, corresponding to a development effectiveness score of 61;

[0147] Well-2 has a comprehensive weight of 11.73% ∈ [10, 25)%, corresponding to a development effectiveness score of 52;

[0148] Well-3 overall weight 32.00%∈[25,64)%, corresponding to a development effectiveness score of 64;

[0149] Well-4 has a comprehensive weight of 29.32% ∈ [25, 64)%, corresponding to a development effectiveness score of 62.

[0150] In this embodiment, after obtaining the development effect scores of each group of production wells and injection wells within the alternating development well group of the reservoir water and gas, the following may also be included:

[0151] Based on the development performance scores of each production well and injection well in the alternating development well group of the reservoir, analyze the contradictory indicators that restrict the development performance of the production well or injection well, and give corresponding adjustment measures.

[0152] Table 7 Evaluation Results of Development Effectiveness and Rational Adjustment Measures

[0153]

[0154] In a specific embodiment, Table 7 shows the evaluation results of the development effect and the rational adjustment measures in the embodiment of the present invention. As shown in Table 7, for the most prominent contradictory indicators restricting the development of horizontal production wells, and in combination with economic costs and the principle of efficient development throughout the entire life cycle of oil wells, reasonable adjustment measures for the next step are given:

[0155] Well-1 (Development Effectiveness Score: 61):

[0156] Adjustment measures: Optimize drilling trajectory, attempt to side-drill on the basis of existing wellbore, extend the horizontal section, and expand the reservoir contact range; increase injection volume to enhance the energy replenishment effect of water-gas alternation.

[0157] Well-2 (Development Effectiveness Score: 52):

[0158] Adjustment measures: Adjust injection and production parameters, reduce water injection volume and increase gas injection rate to improve gas-oil ratio and enhance gas injection-driven oil recovery.

[0159] Well-3 (Development Effectiveness Score: 64):

[0160] Adjustment measures: Optimize the control program of the gas injection equipment, stabilize the gas injection rate, and enhance the utilization effect of gas-water synergistic displacement on oil and gas.

[0161] Well-4 (Development Effectiveness Score: 62):

[0162] Adjustment measures: Implement reservoir stimulation measures, such as acid fracturing, to improve reservoir permeability; increase water injection rate to ensure timely replenishment of water drive energy.

[0163] The reservoir water-gas alternation development effect evaluation method of the present invention has been verified to have the following beneficial effects:

[0164] 1. By collecting and organizing static and dynamic data of production wells and injection wells in well groups that are easily obtainable on-site in reservoir horizontal wells, a comprehensive evaluation of the effectiveness of water-gas alternation development was achieved, which is both subjective and objective, accurate and reliable.

[0165] 2. Combining geological and engineering factors, and fully considering the development evaluation indicators that characterize water-gas alternation, a dynamic and static indicator evaluation system for evaluating the development effect of water-gas alternation is formed.

[0166] 3. An objective analysis and evaluation process was established based on the principle of entropy weight method, which ensured the accuracy of the results.

[0167] 4. A subjective analysis and evaluation process was proposed based on the principles of the Analytic Hierarchy Process (AHP), which ensured the reliability of the results.

[0168] 5. Based on the established comprehensive weight calculation system, a comprehensive evaluation method for the effects of water-air alternation development has been formed.

[0169] 6. A unique "weight-score-evaluation" score conversion evaluation table was established, and reasonable adjustment measures were given for different score evaluation results.

[0170] 7. It fills the technical gap in the current research methods in this field; it solves the technical problem that the traditional methods have poor accuracy and reliability of water-air alternation development effects due to the single evaluation index, strong subjective dependence, and failure to consider the synergistic effect of many factors.

[0171] This invention also provides a device for evaluating the effectiveness of alternating water-gas development in oil reservoirs, as described in the following embodiments. Since the principle by which this device solves the problem is similar to the method for evaluating the effectiveness of alternating water-gas development in oil reservoirs, the implementation of this device can refer to the implementation of the method for evaluating the effectiveness of alternating water-gas development in oil reservoirs, and will not be repeated here.

[0172] Figure 5 This is a structural example diagram of the reservoir water-gas alternating development effect evaluation device in an embodiment of the present invention, as shown below. Figure 5 As shown, the device includes:

[0173] The data acquisition module 501 is used to acquire well group data of each production well and injection well in the well group of alternating water and gas development in the reservoir;

[0174] The information entropy calculation module 502 is used to calculate the coefficient of variation of the well group data based on the entropy weight method, and to calculate the information entropy of the well group data based on the coefficient of variation of the well group data.

[0175] The information entropy weight determination module 503 is used to determine the information entropy weight of each production well and injection well in the reservoir water-gas alternating development well group based on the information entropy of the well group data.

[0176] The analytic hierarchy process (AHP) weight determination module 504 is used to determine the AHP weights of each production well and injection well in a well group for alternating development of oil, water and gas in a reservoir based on the analytic hierarchy process (AHP).

[0177] The comprehensive weight determination module 505 is used to linearly combine the information entropy weights and hierarchical analysis weights of each group of production wells and injection wells in the alternating development well group of the reservoir based on the game theory combination weighting method to obtain the comprehensive weights of each group of production wells and injection wells in the alternating development well group of the reservoir.

[0178] The development effect score determination module 506 is used to determine the development effect score of each group of production wells and injection wells in the reservoir water-gas alternating development well group based on the comprehensive weight of each group of production wells and injection wells.

[0179] In one embodiment, the well group data for each production well and injection well within the alternating development well group of the reservoir includes static data and dynamic data;

[0180] Static data includes well number, length of horizontal section of production well, porosity, and permeability;

[0181] Dynamic data includes cumulative oil production, injection volume, gas-oil ratio, water cut, injected gas-water ratio, gas injection rate, and water injection rate.

[0182] In one embodiment, the data acquisition module is further configured to:

[0183] After obtaining the well group data for each production well and injection well in the alternating water-gas development well group of the reservoir, the positive index data, negative index data, and extreme value index data in the well group data of each production well and injection well in the alternating water-gas development well group of the reservoir were standardized. The positive index data includes: porosity, permeability, cumulative oil production, injection volume, gas injection rate, and water injection rate; the negative index data includes: gas-oil ratio and water cut; the extreme value index data includes: horizontal section length of production well and injected gas-water ratio.

[0184] In one embodiment, the data acquisition module is specifically used for:

[0185] Standardize the positive indicator data using the following formula:

[0186]

[0187] in, The data represents standardized positive indicators. This is a positive indicator data. The minimum value of the positive indicator data. This represents the maximum value of the positive indicator data.

[0188] Standardize the reverse indicator data using the following formula:

[0189]

[0190] in, This is the standardized reverse indicator data. This is reverse indicator data. The minimum value of the reverse indicator data. This represents the maximum value of the reverse indicator data.

[0191] The extreme value index data is standardized using the following formula:

[0192]

[0193] in, The data represents the standardized extreme value index. This is extreme value index data. The minimum value of the extreme value index data. The maximum value of the extreme value index data. This represents the optimal value of the extreme value index data.

[0194] In one embodiment, the information entropy weight determination module is specifically used for:

[0195] Calculate the information validity of the well group data based on the information entropy of the well group data;

[0196] The sum of the information validity of all production well group data within the oil reservoir water-gas alternating development well group;

[0197] The ratio of the information validity of all production well group data to the sum of information validity is used as the weighting coefficient for each production well and injection well group data.

[0198] Based on the weighting coefficients corresponding to the data of each group of production wells and injection wells in the alternating development well group of the reservoir, the information entropy weights of each group of production wells and injection wells in the alternating development well group of the reservoir are determined.

[0199] In one embodiment, the comprehensive weight determination module is specifically used for:

[0200] Construct a linear combination model of information entropy weight and hierarchical analysis weight, and set the weighting coefficients of information entropy weight and hierarchical analysis weight, with the sum of the two coefficients being 1.

[0201] Based on the principles of game theory, with the goal of minimizing the deviation between information entropy weights and hierarchical analysis weights, the optimal values ​​of the weighting coefficients of information entropy weights and hierarchical analysis weights are obtained.

[0202] The comprehensive weights of each production well and injection well in the reservoir water-gas alternating development well group are obtained by multiplying the information entropy weight and the hierarchical analysis weight by the optimal values ​​of the corresponding weighting coefficients and summing them.

[0203] In one embodiment, the development effect score determination module is specifically used for:

[0204] Based on historical well group data of well groups with alternating oil, water and gas development in reservoirs, a mapping relationship between comprehensive weight and development effect score is established;

[0205] Based on the comprehensive weight of each production well and injection well in the reservoir water-gas alternating development well group, and based on the mapping relationship between the comprehensive weight and the development effect score, the development effect score of each production well and injection well in the reservoir water-gas alternating development well group is obtained.

[0206] Figure 6 This is a specific example diagram of the structure of the reservoir water-gas alternating development effect evaluation device in an embodiment of the present invention. For example... Figure 6 As shown in one embodiment, Figure 5 The reservoir water-gas alternating development effect evaluation device shown in the embodiment of the present invention may further include: an adjustment measure determination module 601, which is used to analyze the contradictory indicators that restrict the development effect of the production well or injection well based on the development effect scores of each group of production wells and injection wells in the reservoir water-gas alternating development well group after obtaining the development effect scores of each group of production wells and injection wells in the reservoir water-gas alternating development well group, and give corresponding adjustment measures.

[0207] Based on the aforementioned inventive concept, such as Figure 7 As shown, the present invention also proposes a computer device 700, including a memory 710, a processor 720, and a computer program 730 stored in the memory 710 and executable on the processor 720. When the processor 720 executes the computer program 730, it implements the aforementioned method for evaluating the effect of alternating oil reservoir water and gas development.

[0208] This invention also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method for evaluating the effects of alternating oil reservoir water-gas development.

[0209] This invention also provides a computer program product, which includes a computer program that, when executed by a processor, implements the above-mentioned method for evaluating the effects of alternating oil reservoir water-gas development.

[0210] In this embodiment of the invention, well group data for each production well and injection well within a well group for alternating water and gas development in an oil reservoir are acquired; based on the well group data, the coefficient of variation of the well group data is calculated using the entropy weight method; based on the coefficient of variation of the well group data, the information entropy of the well group data is calculated; based on the information entropy of the well group data, the information entropy weights of each production well and injection well within the well group for alternating water and gas development in an oil reservoir are determined; based on the analytic hierarchy process (AHP), the AHP weights of each production well and injection well within the well group for alternating water and gas development in an oil reservoir are determined; and the reservoir water... The information entropy weights and hierarchical analysis weights of each production well and injection well in the alternating gas and water development well group are linearly combined based on the game theory combination weighting method to obtain the comprehensive weights of each production well and injection well in the alternating gas and water development well group. Based on the comprehensive weights of each production well and injection well in the alternating gas and water development well group, the development effect score of each production well and injection well in the alternating gas and water development well group is determined. This embodiment of the invention realizes a multi-dimensional comprehensive evaluation of the development effect of the well group, which can effectively improve the evaluation accuracy and provide a theoretical basis for reservoir development adjustment.

[0211] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0212] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0213] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1The function specified in one or more boxes.

[0214] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0215] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above descriptions are merely specific embodiments of the present invention and are not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for evaluating the effectiveness of alternating water and gas development in oil reservoirs, characterized in that, include: Acquire well group data for each production well and injection well within the well group for alternating development of oil, water and gas in the reservoir; Based on the well group data of each production well and injection well in the alternating development of oil, water and gas in the reservoir, the coefficient of variation of the well group data is calculated based on the entropy weight method, and the information entropy of the well group data is calculated based on the coefficient of variation of the well group data. Based on the information entropy of the well group data, determine the information entropy weights of each production well and injection well in the well group for alternating development of oil, water and gas in the reservoir; Based on the analytic hierarchy process (AHP), the weights of production wells and injection wells in each group of wells for alternating water and gas development in the reservoir are determined. The information entropy weights and analytic hierarchy process weights of each production well and injection well in the alternating water-gas development well group of the reservoir are linearly combined using the game theory combination weighting method to obtain the comprehensive weights of each production well and injection well in the alternating water-gas development well group of the reservoir. The development effect score of each group of production wells and injection wells in the reservoir water-gas alternating development well group is determined based on the comprehensive weight of each group of production wells and injection wells.

2. The method as described in claim 1, characterized in that, The well group data for each production well and injection well within the alternating development of oil, water and gas reservoirs includes both static and dynamic data. Static data includes well number, length of horizontal section of production well, porosity, and permeability; Dynamic data includes cumulative oil production, injection volume, gas-oil ratio, water cut, injected gas-water ratio, gas injection rate, and water injection rate.

3. The method as described in claim 2, characterized in that, After obtaining the well group data for each production well and injection well within the alternating water-gas development well group of the reservoir, including: The positive, negative, and extreme index data of each production well and injection well in the well group of alternating water and gas development in the reservoir were standardized. The positive index data included porosity, permeability, cumulative oil production, injection volume, gas injection rate, and water injection rate. The negative index data included gas-oil ratio and water cut. The extreme index data included the horizontal section length of the production well and the injected gas-water ratio.

4. The method as described in claim 3, characterized in that, Standardize the positive indicator data using the following formula: ； in, The data represents standardized positive indicators. This is a positive indicator data. The minimum value of the positive indicator data. This represents the maximum value of the positive indicator data; Standardize the reverse indicator data using the following formula: ； in, This is the standardized reverse indicator data. This is reverse indicator data. The minimum value of the reverse indicator data. This represents the maximum value of the reverse indicator data; The extreme value index data is standardized using the following formula: ； in, The data represents the standardized extreme value index. This is extreme value index data. The minimum value of the extreme value index data. The maximum value of the extreme value index data. This represents the optimal value of the extreme value index data.

5. The method as described in claim 1, characterized in that, Based on the information entropy of well group data, determine the information entropy weights of each production well and injection well within the well group for alternating oil, water, and gas development in the reservoir, including: Calculate the information validity of the well group data based on the information entropy of the well group data; The sum of the information validity of all production well group data within the oil reservoir water-gas alternating development well group; The ratio of the information validity of all production well group data to the sum of information validity is used as the weighting coefficient for each production well and injection well group data. Based on the weighting coefficients corresponding to the data of each group of production wells and injection wells in the alternating development well group of the reservoir, the information entropy weights of each group of production wells and injection wells in the alternating development well group of the reservoir are determined.

6. The method as described in claim 1, characterized in that, The information entropy weights and analytic hierarchy process (AHP) weights of each production well and injection well within the alternating water-gas development well group are linearly combined using a game-theoretic combination weighting method to obtain the comprehensive weights of each production well and injection well within the alternating water-gas development well group, including: Construct a linear combination model of information entropy weight and hierarchical analysis weight, and set the weighting coefficients of information entropy weight and hierarchical analysis weight, with the sum of the two coefficients being 1. Based on the principles of game theory, with the goal of minimizing the deviation between information entropy weights and hierarchical analysis weights, the optimal values ​​of the weighting coefficients of information entropy weights and hierarchical analysis weights are obtained. The comprehensive weights of each production well and injection well in the reservoir water-gas alternating development well group are obtained by multiplying the information entropy weight and the hierarchical analysis weight by the optimal values ​​of the corresponding weighting coefficients and summing them.

7. The method as described in claim 1, characterized in that, Based on the comprehensive weighting of each production well and injection well within the reservoir water-gas alternating development well group, the development effectiveness score for each production well and injection well within the reservoir water-gas alternating development well group is determined, including: Based on historical well group data of well groups with alternating oil, water and gas development in reservoirs, a mapping relationship between comprehensive weight and development effect score is established; Based on the comprehensive weight of each production well and injection well in the reservoir water-gas alternating development well group, and based on the mapping relationship between the comprehensive weight and the development effect score, the development effect score of each production well and injection well in the reservoir water-gas alternating development well group is obtained.

8. The method as described in claim 1, characterized in that, After obtaining the development performance scores of each production well and injection well within the alternating development well group of the reservoir water and gas, the following are also included: Based on the development performance scores of each production well and injection well in the alternating development well group of the reservoir, analyze the contradictory indicators that restrict the development performance of the production well or injection well, and give corresponding adjustment measures.

9. A device for evaluating the effectiveness of alternating water and gas development in oil reservoirs, characterized in that, include: The data acquisition module is used to acquire well group data for each production well and injection well within the well group for alternating development of oil, water and gas in the reservoir; The information entropy calculation module is used to calculate the coefficient of variation of well group data based on the entropy weight method, and then calculate the information entropy of the well group data based on the coefficient of variation of well group data. The information entropy weight determination module is used to determine the information entropy weight of each production well and injection well in the reservoir water-gas alternating development well group based on the information entropy of the well group data. The analytic hierarchy process (AHP) weight determination module is used to determine the AHP weights of each production well and injection well in a well group for alternating water and gas development of an oil reservoir, based on the analytic hierarchy process (AHP). The comprehensive weight determination module is used to linearly combine the information entropy weights and analytic hierarchy process weights of each production well and injection well in the alternating development well group of the reservoir based on the game theory combination weighting method, so as to obtain the comprehensive weight of each production well and injection well in the alternating development well group of the reservoir. The development effect score determination module is used to determine the development effect score of each group of production wells and injection wells in the reservoir water-gas alternating development well group based on the comprehensive weight of each group of production wells and injection wells.

10. A computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the method according to any one of claims 1-8.

11. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the method of any one of claims 1-8.

12. A computer program product, characterized in that, The computer program product includes a computer program that, when executed by a processor, implements the method of any one of claims 1-8.

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