Method, device, electronic device and storage medium for evaluating suitability of water injection oil well

Abstract

The present disclosure provides a method, device, electronic device and storage medium for evaluating the suitability of a water injection oil replacement well. The method includes determining the evaluation factors and their corresponding specific values ​​that affect the water injection oil replacement effect of the target water injection oil replacement well based on the dynamic and static data; constructing a hierarchical analysis model of the evaluation factors; constructing a judgment matrix corresponding to each level based on the hierarchical analysis model through the three-scale method; calculating the combined weights of each evaluation factor in the lowest level according to the judgment matrix corresponding to each level; calculating the evaluation result factor of the target water injection oil replacement well according to the specific values ​​and combined weights of each evaluation factor in the lowest level, as well as the preset suitability evaluation level and its corresponding index interval, so as to obtain the suitability evaluation result of the target water injection oil replacement well. This method has a simple evaluation process, is easy to promote and apply, has a fast judgment matrix establishment, satisfies consistency test, and has great theoretical and guiding significance.

Description

Technical Field

[0001] The present invention relates to the technical field of water injection for oil replacement development in oil reservoirs, and in particular to a method, device, electronic equipment and storage medium for evaluating the suitability of a water injection for oil replacement well. Background Art

[0002] Fracture-cavity reservoirs are a special type of reservoirs, whose storage space is mainly fractures and caves. The matrix part has basically no fluid seepage capacity, and the flow of fluid in the reservoir mainly depends on the communication between fractures and caves, caves and caves, and fractures and fractures. Due to the random distribution of fractures and caves, generally a good fracture-cavity system will not be formed, so the heterogeneity of fracture-cavity reservoirs is particularly strong.

[0003] The most basic development unit of fracture-cave reservoirs is the single-well fracture-cave unit. According to incomplete statistics, fracture-cave reservoirs are relatively strong in natural energy. In the early stage of development, they mainly rely on natural energy for depletion development. Due to the rapid energy decay and low pressure retention, the oil well production capacity drops rapidly, so a large amount of residual oil remains in the single-well fracture-cave unit. When the natural energy drops to a certain level, it will be pumped. Due to the coning of bottom water, the oil-water interface rises, the water content of the oil well increases, and some of the remaining oil cannot be produced. If the controlled reserves of the single-well fracture-cave unit are large enough, it is possible to consider drilling new wells and establishing an injection-production well network to continue to use the remaining oil; if the controlled reserves of the single-well fracture-cave unit are not enough to support the drilling of new wells and the economic benefits are poor, water injection can be selected to replace oil. Since the conductivity of fracture-cave reservoirs is relatively strong and the interfacial tension is relatively weak, it is easier to replace oil and water. Water injection to replace oil is an economical and effective development method to improve the recovery rate of single-well fracture-cave units. However, how to accurately evaluate the suitability of water injection wells to replace oil, select suitable water injection wells to replace oil, and improve the success rate of well selection is still a technical problem that needs to be solved urgently. Summary of the invention

[0004] In view of the above problems, the present disclosure provides a method, device, electronic device and storage medium for evaluating the suitability of a water injection well for oil replacement, which solves the technical problem in the prior art that it is difficult to accurately evaluate the suitability of a water injection well for oil replacement.

[0005] In a first aspect, the present disclosure provides a method for evaluating the suitability of a water injection well for oil replacement, the method comprising:

[0006] Acquire dynamic and static data of the target water injection oil replacement well, and determine the evaluation factors affecting the water injection oil replacement effect of the target water injection oil replacement well and their corresponding specific values ​​according to the dynamic and static data;

[0007] Classify each evaluation factor to determine the category to which each evaluation factor belongs, and determine the level of each evaluation factor based on the specific value of each evaluation factor;

[0008] According to the categories and levels of each evaluation factor, a hierarchical analysis model of evaluation factors is constructed;

[0009] Based on the analytic hierarchy model, a judgment matrix corresponding to each level is constructed through the three-scale method;

[0010] According to the judgment matrix corresponding to each level, the weight vector of each level is obtained, and according to the weight vector of each level, the combined weight of each evaluation factor in the lowest level is calculated;

[0011] Calculate the evaluation result factor of the target water injection well according to the specific values ​​and combined weights of each evaluation factor in the lowest level, as well as the preset suitability evaluation level and its corresponding index range;

[0012] According to the index interval in which the evaluation result factor is located, the suitability evaluation level corresponding to the evaluation result factor is determined to obtain the suitability evaluation result of the target water injection oil replacement well.

[0013] According to an embodiment of the present disclosure, optionally, in the above-mentioned water injection oil well suitability evaluation method, the level of each evaluation factor is determined according to the specific value of each evaluation factor, including the following steps:

[0014] According to the specific value and value range of each evaluation factor, the specific value of each evaluation factor is normalized to obtain the normalized specific value of each evaluation factor;

[0015] According to the normalized specific values ​​of each evaluation factor, calculate the contribution rate of each evaluation factor;

[0016] According to the contribution rate of each evaluation factor, the level of each evaluation factor is determined.

[0017] According to an embodiment of the present disclosure, optionally, in the above-mentioned water injection oil well suitability evaluation method, according to the specific value and value range of each evaluation factor, the specific value of each evaluation factor is normalized to obtain the normalized specific value of each evaluation factor, including the following steps:

[0018] Determine a corresponding normalized calculation formula according to the influence of the specific numerical values ​​of each evaluation factor on the water injection oil replacement effect of the target water injection oil replacement well;

[0019] When the specific value of the current evaluation factor is larger, the effect on the water injection oil replacement effect of the target water injection oil replacement well is better, and the corresponding normalized calculation formula is:

[0020]

[0021] Among them, a iis the normalized specific value of the ith evaluation factor, v i is the specific value of the i-th evaluation factor, u i is the lower limit of the value range of the i-th evaluation factor, w i is the upper limit of the value range of the i-th evaluation factor;

[0022] When the specific value of the current evaluation factor is smaller, the effect on the water injection oil replacement effect of the target water injection oil replacement well is better, the corresponding normalized calculation formula is:

[0023]

[0024] According to the specific value of each evaluation factor and the value range of each evaluation factor, the specific value of each evaluation factor is normalized through the corresponding normalization calculation formula to obtain the normalized specific value of each evaluation factor.

[0025] According to an embodiment of the present disclosure, optionally, in the above-mentioned water injection oil well suitability evaluation method, the contribution rate of each evaluation factor is calculated according to the normalized specific value of each evaluation factor, including the following steps:

[0026] According to the normalized specific values ​​of each evaluation factor, the first matrix is ​​obtained as follows:

[0027] A=(a 1 , a 2 , …, a n );

[0028] Among them, A is the first matrix, a n is the normalized specific value of the nth evaluation factor and is the nth element in the first matrix, where n is the total number of evaluation factors;

[0029] The average value of the first matrix is ​​calculated, and the average value is subtracted from each element in the first matrix to perform standardization processing on the first matrix, so as to obtain a second matrix as follows:

[0030] B=(b 1 , b 2 , …, b n );

[0031] Among them, B is the second matrix, b n is the nth element in the second matrix;

[0032] Calculate the covariance of the second matrix and obtain the corresponding covariance matrix;

[0033] Obtaining the eigenvectors of the covariance matrix, and arranging the corresponding eigenvalues ​​in order from small to large to obtain a corresponding eigenvalue matrix;

[0034] Multiply the second matrix by the eigenvalue matrix to obtain a third matrix:

[0035] X=BD=(x 1 , x 2 , …, x n );

[0036] Where X is the third matrix, D is the eigenvalue matrix, x n is the nth element in the third matrix;

[0037] According to the third matrix, the contribution rate of each evaluation factor is calculated according to the following formula:

[0038]

[0039] Among them, M i is the contribution value of the ith evaluation factor, x i is the i-th element in the third matrix.

[0040] According to an embodiment of the present disclosure, optionally, in the above-mentioned water injection oil replacement well suitability evaluation method, the hierarchical analysis model includes a first level and a second level;

[0041] According to the contribution rate of each evaluation factor, the level of each evaluation factor is determined, including the following steps:

[0042] Determine the level of each evaluation factor based on the comparison result of the contribution rate of each evaluation factor and the preset threshold value;

[0043] When the contribution rate of the current evaluation factor is greater than or equal to the preset threshold, the level of the current evaluation factor is the first level;

[0044] When the contribution rate of the current evaluation factor is less than the preset threshold, the level of the current evaluation factor is the second level.

[0045] According to an embodiment of the present disclosure, optionally, in the above-mentioned water injection oil well suitability evaluation method, based on the hierarchical analysis model, a judgment matrix corresponding to each level is constructed by a three-scaling method, including the following steps:

[0046] Based on the evaluation factors at each level in the hierarchical analysis model, the three-scale method is used to obtain the comparison matrix corresponding to each level:

[0047]

[0048] Among them, E is the comparison matrix of the current level;

[0049] m is the number of evaluation factors at the current level in the hierarchical analysis model;

[0050] e ij is the element in the i-th row and j-th column of the comparison matrix of the current level;

[0051]

[0052] According to the comparison matrix, the important ranking parameters of each row in the comparison matrix are calculated by the following formula:

[0053]

[0054] Among them, p i is the important ranking parameter of the i-th row in the comparison matrix;

[0055] According to the important ranking parameters of each row in the comparison matrix, the judgment matrix of each level is constructed by the following formula:

[0056] P=(p ij ) m×m ;

[0057] Among them, P is the judgment matrix of the current level;

[0058] p ij is the element in the i-th row and j-th column of the judgment matrix of the current level;

[0059]

[0060] p j is the important ranking parameter of the jth row in the comparison matrix of the current level;

[0061] p max is the maximum value of the important sorting parameters of each row in the comparison matrix of the current level;

[0062] p max =max(p i );

[0063] p min is the minimum value of the important sorting parameters of each row in the comparison matrix of the current level;

[0064] p min =min(p i ).

[0065] According to an embodiment of the present disclosure, optionally, in the above-mentioned water injection oil well suitability evaluation method, according to the judgment matrix corresponding to each level, the weight vector of each level is obtained, including the following steps:

[0066] According to the judgment matrix corresponding to each level, the characteristic vector of the judgment matrix of each level is obtained to obtain the weight vector of each level;

[0067] Among them, the weight vector of each level is equal to the eigenvector of the judgment matrix of the corresponding level.

[0068] According to an embodiment of the present disclosure, optionally, in the above-mentioned water injection oil well suitability evaluation method, the combined weights of the evaluation factors in the lowest level are calculated according to the weight vectors of each level, including the following steps:

[0069] According to the weight vector of each level, determine the weight of each evaluation factor in the corresponding level;

[0070] The weight of each evaluation factor in the lowest level is multiplied by the weight of the evaluation factors in all the upper levels in its corresponding category to calculate the initial combined weight of each evaluation factor in the lowest level;

[0071] The initial combined weights of the evaluation factors in the lowest level are normalized to obtain the final combined weights of the evaluation factors in the lowest level.

[0072] According to an embodiment of the present disclosure, optionally, in the above-mentioned water injection oil replacement well suitability evaluation method, according to the specific values ​​and combined weights of each evaluation factor in the lowest level, and the preset suitability evaluation level and its corresponding index interval, the evaluation result factor of the target water injection oil replacement well is calculated, including the following steps:

[0073] According to the specific values ​​and value ranges of each evaluation factor in the lowest level, the specific values ​​of each evaluation factor in the lowest level are normalized to obtain the normalized specific values ​​of each evaluation factor in the lowest level;

[0074] According to the normalized specific values ​​of each evaluation factor in the lowest level, as well as the preset suitability evaluation level and its corresponding index range, the evaluation matrix is ​​obtained as follows:

[0075] R=(r ij ) m×n ;

[0076] Among them, R is the evaluation matrix, r ij is the element in the i-th row and j-th column of the evaluation matrix, r ij =1-|a i -(y j +(z j -y j ) / 2)|, m is the number of evaluation factors in the lowest level, n is the number of preset suitability evaluation levels, a iis the i-th evaluation factor in the lowest level, y j is the lower limit of the preset index interval of the jth level, z j is the lower limit of the preset index range of the jth level;

[0077] The combined weight vector formed by the combined weights of the evaluation factors in the lowest level is multiplied by the evaluation matrix to obtain the evaluation vector:

[0078] S=W×R=[s 1 ,s 2 ,…,s j ,…,s n ];

[0079] Where S is the evaluation vector, W is the combined weight vector, s j is the jth element of the evaluation vector, j=1,2,…,n,W i is the i-th element of the combined weight vector;

[0080] According to the evaluation vector, the evaluation result factor of the target water injection oil replacement well is calculated by the following formula:

[0081]

[0082] Wherein, F is the evaluation result factor of the target water injection oil well.

[0083] In a second aspect, the present disclosure provides a water injection oil well suitability evaluation device, the device comprising:

[0084] An evaluation factor determination module is used to obtain dynamic and static data of a target water injection oil replacement well, and determine evaluation factors affecting the water injection oil replacement effect of the target water injection oil replacement well and their corresponding specific values ​​based on the dynamic and static data;

[0085] The category and level determination module is used to classify each evaluation factor to determine the category to which each evaluation factor belongs, and determine the level of each evaluation factor according to the specific value of each evaluation factor;

[0086] A hierarchical analysis model building module is used to build a hierarchical analysis model of evaluation factors according to the categories and levels of each evaluation factor;

[0087] A judgment matrix construction module is used to construct a judgment matrix corresponding to each level based on the hierarchical analysis model through a three-scaling method;

[0088] The combined weight calculation module is used to obtain the weight vector of each level according to the judgment matrix corresponding to each level, and calculate the combined weight of each evaluation factor in the lowest level according to the weight vector of each level;

[0089] An evaluation result factor calculation module, used to calculate the evaluation result factor of the target water injection replacement well according to the specific values ​​and combined weights of each evaluation factor in the lowest level, as well as the preset suitability evaluation level and its corresponding index interval;

[0090] The evaluation grade determination module is used to determine the suitability evaluation grade corresponding to the evaluation result factor according to the index interval in which the evaluation result factor is located, so as to obtain the suitability evaluation result of the target water injection oil replacement well.

[0091] In a third aspect, the present disclosure provides an electronic device, comprising a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the method for evaluating the suitability of a water injection well for oil replacement as described in any one of the first aspects is executed.

[0092] In a fourth aspect, the present disclosure provides a storage medium, wherein a computer program stored in the storage medium can be executed by one or more processors and can be used to implement the method for evaluating the suitability of a water injection well for oil replacement as described in any one of the first aspects.

[0093] Compared with the prior art, one or more embodiments of the above scheme may have the following advantages or beneficial effects:

[0094] (1) Comprehensively utilize dynamic and static data to quantify the suitability of water injection for oil wells, transforming the water injection for oil problem from qualitative evaluation to quantitative comprehensive evaluation. It has the characteristics of solid theoretical basis, strong systematicity, simplicity and ease of use, and clear results;

[0095] (2) It not only overcomes the limitations of ambiguity and subjective judgment in comparing various evaluation factors, but also simplifies the evaluation process and effectively solves the technical problem of selecting water injection wells for oil replacement in the mine;

[0096] (3) Based on the quantitative comprehensive evaluation index of water injection suitability for oil replacement, the water injection parameters can be optimized according to the different stages of the water injection wells, the potential of remaining oil can be tapped, the utilization of single well reserves can be improved, and the actual production of the mine can be better guided;

[0097] (4) It has certain guiding and practical value. It can not only serve as a reference method for selecting wells for water injection replacement, but also solve the technical problems of blindness and subjectivity, uncertainty and multi-factor influence in the current development of fracture-cavity reservoirs. BRIEF DESCRIPTION OF THE DRAWINGS

[0098] The present disclosure will be described in more detail below based on embodiments and with reference to the accompanying drawings:

[0099] Figure 1 A schematic flow chart of a method for evaluating the suitability of a water injection well for oil replacement provided in an embodiment of the present disclosure;

[0100] Figure 2 A schematic diagram of the structure of a water injection oil well suitability evaluation device provided in an embodiment of the present disclosure;

[0101] In the drawings, the same reference numerals are used for the same components and the drawings are not drawn to scale. DETAILED DESCRIPTION

[0102] The following will describe the implementation methods of the present disclosure in detail with reference to the accompanying drawings and embodiments, so that the implementation process of how the present disclosure applies technical means to solve technical problems and achieve corresponding technical effects can be fully understood and implemented accordingly. The embodiments of the present disclosure and the various features in the embodiments can be combined with each other without conflict, and the technical solutions formed are all within the protection scope of the present disclosure.

[0103] Meanwhile, in the following description, many specific details are set forth for the purpose of explanation to provide a thorough understanding of the embodiments of the present invention. However, it is obvious to those skilled in the art that the present invention can be implemented without the specific details or the specific manner described herein.

[0104] Embodiment 1

[0105] Figure 1 A schematic diagram of a water injection well suitability evaluation method provided in the embodiment of the present disclosure is provided in FIG. Figure 1 This embodiment provides a method for evaluating the suitability of a water injection oil well, comprising:

[0106] Step S101: acquiring dynamic and static data of a target water injection well for oil replacement, and determining evaluation factors affecting the water injection effect of the target water injection well for oil replacement and their corresponding specific values ​​based on the dynamic and static data.

[0107] Specifically, the dynamic and static data include the well history of a single well, production dynamic data, drilling and logging data, etc. The evaluation factors affecting the water injection and oil replacement effect of the target water injection and oil replacement well include: emptying and leakage, drilling location, reservoir type, reservoir shape, reservoir closure, dynamic reserves, driving type, water body energy, water breakthrough characteristics, production range before water injection, water content before water injection, drilling characteristics, geological characteristics, reservoir characteristics and development characteristics.

[0108] This method comprehensively utilizes dynamic and static data to quantify the suitability of water injection for oil wells, and transforms the water injection for oil problem from a qualitative evaluation to a quantitative comprehensive evaluation. It has the characteristics of solid theoretical basis, strong systematicity, simplicity and ease of use, and clear results.

[0109] In step S101, in addition to determining the specific values ​​of each evaluation factor, the value range of each evaluation factor and the impact of the specific value of each evaluation factor on the target water injection oil replacement well are also determined. For some evaluation factors, the larger the value, the better the impact on the water injection oil replacement effect of the target water injection oil replacement well, while for some evaluation factors, the smaller the value, the better the impact on the water injection oil replacement effect of the target water injection oil replacement well.

[0110] Step S102: Classify each evaluation factor to determine the category to which each evaluation factor belongs, and determine the level of each evaluation factor according to the specific value of each evaluation factor.

[0111] Specifically, step S102 includes the following steps:

[0112] S102a: Classify each evaluation factor to determine the category to which each evaluation factor belongs;

[0113] S102b: normalizing the specific values ​​of each evaluation factor according to the specific values ​​and value ranges of each evaluation factor to obtain the normalized specific values ​​of each evaluation factor;

[0114] S102c: Calculate the contribution rate of each evaluation factor according to the normalized specific value of each evaluation factor;

[0115] S102d: Determine the level of each evaluation factor according to its contribution rate.

[0116] Exemplarily, among the evaluation factors given above, drilling characteristics, drain leakage and drilling location are one category, geological characteristics, reservoir type, reservoir shape and reservoir closure are one category, reservoir characteristics, dynamic reserves, driving type and water body energy are one category, and development characteristics, water breakthrough characteristics, production range before water injection and water content before water injection are one category.

[0117] Step S102b includes the following steps:

[0118] (a) determining a corresponding normalized calculation formula according to the influence of the specific numerical values ​​of each evaluation factor on the water injection effect of the target water injection oil replacement well;

[0119] (b) When the specific value of the current evaluation factor is larger, the effect on the water injection oil replacement effect of the target water injection oil replacement well is better, and the corresponding normalized calculation formula is:

[0120]

[0121] Among them, a i is the normalized specific value of the ith evaluation factor, v i is the specific value of the i-th evaluation factor, u i is the lower limit of the value range of the i-th evaluation factor, w i is the upper limit of the value range of the i-th evaluation factor;

[0122] (c) When the specific value of the current evaluation factor is smaller, the effect on the water injection oil replacement effect of the target water injection oil replacement well is better, the corresponding normalized calculation formula is:

[0123]

[0124] (d) According to the specific value of each evaluation factor and the value range of each evaluation factor, the specific value of each evaluation factor is normalized by a corresponding normalization calculation formula to obtain the normalized specific value of each evaluation factor.

[0125] Step S102c includes the following steps:

[0126] (a) According to the normalized specific values ​​of each evaluation factor, the first matrix is ​​obtained as follows:

[0127] A=(a 1 , a 2 , …, a n );

[0128] Where A is the first matrix;

[0129] a n is the normalized specific value of the nth evaluation factor and is the nth element in the first matrix;

[0130] n is the total number of evaluation factors;

[0131] (b) Calculate the average value of the first matrix, and subtract the average value from each element in the first matrix to standardize the first matrix, so as to obtain a second matrix:

[0132] B=(b 1 , b 2 , …, b n );

[0133] Wherein, B is the second matrix;

[0134] b n is the nth element in the second matrix;

[0135] (c) obtaining the covariance of the second matrix and obtaining a corresponding covariance matrix;

[0136] (d) obtaining the eigenvectors of the covariance matrix and arranging the corresponding eigenvalues ​​in order from small to large to obtain a corresponding eigenvalue matrix;

[0137] (e) multiplying the second matrix by the eigenvalue matrix to obtain a third matrix:

[0138] X=BD=(x 1 , x 2 , …, x n );

[0139] Where, X is the third matrix;

[0140] D is the eigenvalue matrix;

[0141] x n is the nth element in the third matrix;

[0142] (f) Based on the third matrix, the contribution rate of each evaluation factor is calculated according to the following formula:

[0143]

[0144] Among them, M i is the contribution value of the i-th evaluation factor;

[0145] x i is the i-th element in the third matrix.

[0146] Exemplarily, when the hierarchical analysis model includes a first level and a second level, step S102d includes the following steps:

[0147] (a) Determine the level of each evaluation factor based on the comparison result between the contribution rate of each evaluation factor and the preset threshold value;

[0148] (b) When the contribution rate of the current evaluation factor is greater than or equal to the preset threshold, the level of the current evaluation factor is the first level;

[0149] (c) When the contribution rate of the current evaluation factor is less than the preset threshold, the level of the current evaluation factor is the second level.

[0150] Exemplarily, when the hierarchical analysis model includes a first level, a second level, and a third level, step S102d includes the following steps:

[0151] (a) Determine the level of each evaluation factor based on the comparison result between the contribution rate of each evaluation factor and the preset threshold value;

[0152] (b) when the contribution rate of the current evaluation factor is greater than or equal to the first preset threshold, the level of the current evaluation factor is the first level;

[0153] (c) when the contribution rate of the current evaluation factor is less than the first preset threshold but greater than or equal to the second preset threshold, the level of the current evaluation factor is the second level;

[0154] (d) When the contribution rate of the current evaluation factor is less than the second preset threshold, the level of the current evaluation factor is the third level.

[0155] Among them, the first preset threshold>the second preset threshold.

[0156] By analogy, this embodiment is applicable to situations at multiple levels.

[0157] Step S103: constructing a hierarchical analysis model of the evaluation factors according to the categories and levels of the evaluation factors.

[0158] The constructed hierarchical model (taking a two-layer structure as an example) is shown in Table 1.

[0159] Table 1

[0160]

[0161] Step S104: Based on the hierarchical analysis model, a judgment matrix corresponding to each level is constructed by three-scaling method.

[0162] Specifically, step S104 includes the following steps:

[0163] S104a: Based on the evaluation factors at each level in the hierarchical analysis model, a three-scaling method is used to obtain a comparison matrix corresponding to each level:

[0164]

[0165] Among them, E is the comparison matrix of the current level;

[0166] m is the number of evaluation factors at the current level in the hierarchical analysis model;

[0167] e ij is the element in the i-th row and j-th column of the comparison matrix of the current level;

[0168]

[0169] S104b: According to the comparison matrix, the important ranking parameter of each row in the comparison matrix is ​​calculated by the following formula:

[0170]

[0171] Among them, p i is the important ranking parameter of the i-th row in the comparison matrix;

[0172] S104c: According to the important ranking parameters of each row in the comparison matrix, the judgment matrix of each level is constructed by the following formula:

[0173] P=(p ij ) m×m ;

[0174] Among them, P is the judgment matrix of the current level;

[0175] p ij is the element in the i-th row and j-th column of the judgment matrix of the current level;

[0176]

[0177] p j is the important ranking parameter of the jth row in the comparison matrix of the current level;

[0178] p max is the maximum value of the important sorting parameters of each row in the comparison matrix of the current level;

[0179] p max =max(p i );

[0180] p min is the minimum value of the important sorting parameters of each row in the comparison matrix of the current level;

[0181] p min =min(p i ).

[0182] The three-scale method is adopted to overcome the problems of large blindness, large ambiguity and poor consistency in the construction results of the judgment matrix in the prior art. When two evaluation factors are compared with each other, the relative importance of the two evaluation factors can be identified, so that the construction results of the judgment matrix meet the consistency test.

[0183] This embodiment establishes a new judgment matrix generation method based on the judgment matrix construction principle of the hierarchical analysis method, which not only simplifies the judgment matrix generation process, but also is simple to operate and easy to master, ensuring that the generated judgment matrix can meet the consistency test. It not only overcomes the limitations of the ambiguity and subjective judgment of the mutual comparison between the evaluation factors, but also simplifies the evaluation process and effectively solves the technical problem of optimizing water injection to replace oil wells in the mine.

[0184] Step S105: Obtain the weight vector of each level according to the judgment matrix corresponding to each level, and calculate the combined weight of each evaluation factor in the lowest level according to the weight vector of each level.

[0185] Specifically, step S105 includes the following steps:

[0186] S105a: According to the judgment matrix corresponding to each level, the eigenvector of the judgment matrix of each level is obtained to obtain the weight vector of each level; wherein the weight vector of each level is equal to the eigenvector of the judgment matrix of the corresponding level.

[0187] S105b: Determine the weight of each evaluation factor in the corresponding level according to the weight vector of each level;

[0188] S105c: multiplying the weight of each evaluation factor in the lowest level by the weight of each evaluation factor in all upper levels in its corresponding category to calculate the initial combined weight of each evaluation factor in the lowest level;

[0189] S105d: normalizing the initial combined weights of the evaluation factors in the lowest level to obtain the final combined weights of the evaluation factors in the lowest level.

[0190] Step S106: Calculate the evaluation result factor of the target water injection well based on the specific values ​​and combined weights of the evaluation factors in the lowest level, as well as the preset suitability evaluation levels and their corresponding index ranges.

[0191] Specifically, step S106 includes the following steps:

[0192] S106a: normalizing the specific values ​​of the evaluation factors in the lowest level according to the specific values ​​and value ranges of the evaluation factors in the lowest level to obtain the normalized specific values ​​of the evaluation factors in the lowest level;

[0193] S106b: Based on the normalized specific values ​​of each evaluation factor in the lowest level, as well as the preset suitability evaluation level and its corresponding index range, the evaluation matrix is ​​obtained as follows:

[0194] R=(r ij ) m×n ;

[0195] Wherein, R is the evaluation matrix;

[0196] r ij is the element in the i-th row and j-th column of the evaluation matrix;

[0197] r ij =1-|ai -(y j +(z j -y j ) / 2)|;

[0198] m is the number of evaluation factors in the lowest level;

[0199] n is the number of preset suitability evaluation levels;

[0200] a i is the i-th evaluation factor in the lowest level;

[0201] y j is the lower limit of the preset index range of the jth level;

[0202] z j is the lower limit of the preset index range of the jth level;

[0203] S106c: Multiply the combined weight vector formed by the combined weights of the evaluation factors in the lowest level by the evaluation matrix to obtain an evaluation vector:

[0204] S=W×R=[s 1 ,s 2 ,…,s j ,…,s n ];

[0205] Wherein, S is the evaluation vector;

[0206] W is the combined weight vector;

[0207] s j is the j-th element of the evaluation vector;

[0208] j = 1, 2, ..., n;

[0209] W i is the i-th element of the combined weight vector;

[0210] S106d: According to the evaluation vector, the evaluation result factor of the target water injection oil replacement well is calculated by the following formula:

[0211]

[0212] Wherein, F is the evaluation result factor of the target water injection oil well.

[0213] Exemplarily, the preset suitability evaluation levels and their corresponding index ranges are shown in Table 2.

[0214] Table 2

[0215]

[0216] Step S107: determining the suitability evaluation level corresponding to the evaluation result factor according to the index interval in which the evaluation result factor is located, so as to obtain the suitability evaluation result of the target water injection oil replacement well.

[0217] For example, if the evaluation result factor calculated in step S106 is 0.7, and 0.7 falls within the interval [0.5-0.75], then the suitability evaluation level corresponding to the evaluation result factor is "good", which is the suitability evaluation result of the target water injection well.

[0218] This method quantifies the comprehensive evaluation index of water injection suitability for oil replacement. It can optimize water injection parameters according to the different stages of water injection wells, tap the potential of remaining oil, improve the utilization of single well reserves, and better guide the actual production of mines. It has certain guiding and practical value. It can not only serve as a reference method for well selection for water injection wells, but also solve the technical problems of blindness and subjectivity, uncertainty, and multi-factor influence in the current development of fracture-cavity reservoirs.

[0219] The embodiment of the present disclosure provides a method for evaluating the suitability of a water-injection oil replacement well, the method comprising determining the evaluation factors and their corresponding specific values ​​that affect the water-injection oil replacement effect of the target water-injection oil replacement well according to the dynamic and static data; determining the category and level of each evaluation factor to construct a hierarchical analysis model of the evaluation factor; constructing a judgment matrix corresponding to each level through the three-scaling method based on the hierarchical analysis model; obtaining the weight vector of each level according to the judgment matrix corresponding to each level, and calculating the combined weight of each evaluation factor in the lowest level according to the weight vector of each level; calculating the evaluation result factor of the target water-injection oil replacement well according to the specific value and combined weight of each evaluation factor in the lowest level, as well as the preset suitability evaluation level and its corresponding index interval; determining the suitability evaluation level corresponding to the evaluation result factor according to the index interval where the evaluation result factor is located, so as to obtain the suitability evaluation result of the target water-injection oil replacement well. This method has a simple evaluation process, is easy to promote and apply; the judgment matrix is ​​quickly established and meets the consistency test; and has great theoretical and guiding significance for the blind and subjective non-deterministic and multi-factor influencing technical problems existing in the current fracture-cavity oil reservoir development.

[0220] Embodiment 2

[0221] Based on the first embodiment, this embodiment illustrates the method described in the first embodiment through a specific implementation case.

[0222] (1) First, basic information data of the target water injection oil replacement well M1 is collected, and based on the dynamic and static data, the evaluation factors affecting the water injection oil replacement effect of the target water injection oil replacement well and their corresponding specific values ​​are determined. The results are shown in Table 3.

[0223] Table 3

[0224]

[0225] (2) The various evaluation factors are classified into: drilling characteristics, emptying and leakage, and drilling location are one category; geological characteristics, reservoir type, reservoir shape, and reservoir closure are one category; reservoir characteristics, dynamic reserves, driving type, and water energy are one category; development characteristics, water breakthrough characteristics, production range before water injection, and water content before water injection are another category.

[0226] The specific values ​​of each evaluation factor are normalized, and the normalized specific values ​​of each evaluation factor are shown in Table 3.

[0227] (3) According to step S102 in Example 1, based on the specific normalized values ​​of each evaluation factor, the first matrix A=(0.7, 0.95, 0.85, 0.8, 0.95, 0.4, 0.4, 0.6, 0.9, 0.6, 0.6, 0.8, 0.85, 0.9, 0.8), and the second matrix after data standardization is B=(-0.04, 0.21, 0.11, 0.06, 0.25, -0.34, -0.34, -0.14, 0.16, -0.14, -0.14, 0.06, 0.11, 0.16, 0.06). After obtaining the covariance matrix C of the matrix B, the eigenvector of the covariance matrix C is obtained, and the eigenvalues ​​are arranged in order from small to large, recorded as matrix D. The second matrix is ​​multiplied by the eigenvalue matrix to obtain the third matrix (contribution rate matrix) X=(0.063, 0.061, 0.057, 0.055, 0.051, 0.046, 0.047, 0.071, 0.044, 0.056, 0.055, 0.094, 0.101, 0.105, 0.094). In this embodiment, the hierarchical analysis model includes the first level and the second level (two-layer structure), and the preset threshold used when determining each level is 0.09, and the obtained hierarchical analysis model of the M1 well is shown in Table 4.

[0228] Table 4

[0229]

[0230] (4) According to step S104 in the first embodiment, the construction results of the judgment matrix at each level are obtained, as shown below:

[0231]

[0232]

[0233]

[0234]

[0235]

[0236] (5) According to step S105a in the first embodiment, the weight vector results of each layer are obtained, as shown in Table 5.

[0237] Table 5

[0238]

[0239] Among them, λ max is the maximum value of the characteristic root.

[0240] (6) According to steps S105b and S105d in the first embodiment, the combined weights of the evaluation factors in the lowest level are calculated according to the weight vectors of each level, as shown in Table 6.

[0241] Table 6

[0242]

[0243]

[0244] For example, B 1 The weight (0.0374) is multiplied by C 1 The weight of (0.833) is obtained. 1 The initial combination weights of C 1 The initial combination weights are normalized (C 1 The initial portfolio weight is divided by C 1 ~C 11 The sum of the initial combination weights to ensure that C 1 ~C 11 The sum of the combined weights of is 1), and we get C 1 The combined weight of (0.057).

[0245] From Table 6, we can get the combined weight vector W composed of the combined weights of each evaluation factor in the lowest level of Well M1 is (0.057, 0.011, 0.073, 0.017, 0.062, 0.026, 0.182, 0.182, 0.177, 0.035, 0.177).

[0246] (6) According to step S106 in the first embodiment, the evaluation matrix R is obtained:

[0247]

[0248] Multiplying the combined weight vector by the evaluation matrix, we can get the evaluation vector S, that is, S = (0.449, 0.685, 0.820, 0.767). Then we can calculate that the evaluation result factor F of M1 well is 0.7901, and the corresponding suitability result of M1 well is as shown in Table 7. Combined with the calculation results of Table 7, we can see that M1 well has good suitability for water injection to replace oil.

[0249] Table 7

[0250]

[0251]

[0252] Similarly, the suitability evaluation results of water injection for oil displacement of M2 and M3 wells can be obtained, as shown in Table 8. The field evaluation results of water injection for oil displacement of M1, M2 and M3 are shown in Table 9.

[0253] Table 8

[0254]

[0255] Table 9

[0256]

[0257]

[0258] It can be seen that the evaluation results of this embodiment are in good agreement with the on-site production, which indicates that the water injection well suitability evaluation method provided by the present disclosure is reasonable and scientific, and can realize rapid and accurate evaluation of the suitability of water injection wells.

[0259] Embodiment 3

[0260] Figure 2 For a schematic diagram of a water injection oil well suitability evaluation device provided in an embodiment of the present disclosure, please refer to Figure 2 The present embodiment provides a water injection oil well suitability evaluation device 100, including an evaluation factor determination module 101, a category and hierarchy determination module 102, a hierarchical analysis model construction module 103, a judgment matrix construction module 104, a combination weight calculation module 105, an evaluation result factor calculation module 106 and an evaluation level determination module 107.

[0261] The evaluation factor determination module 101 is used to obtain dynamic and static data of a target water injection oil replacement well, and determine the evaluation factors affecting the water injection oil replacement effect of the target water injection oil replacement well and their corresponding specific values ​​according to the dynamic and static data.

[0262] The category and level determination module 102 is used to classify each evaluation factor to determine the category to which each evaluation factor belongs, and to determine the level of each evaluation factor according to the specific value of each evaluation factor.

[0263] The hierarchical analysis model building module 103 is used to build a hierarchical analysis model of the evaluation factors according to the categories and levels of each evaluation factor.

[0264] The judgment matrix construction module 104 is used to construct a judgment matrix corresponding to each level based on the hierarchical analysis model by using the three-scaling method.

[0265] The combined weight calculation module 105 is used to obtain the weight vector of each level according to the judgment matrix corresponding to each level, and calculate the combined weight of each evaluation factor in the lowest level according to the weight vector of each level.

[0266] The evaluation result factor calculation module 106 is used to calculate the evaluation result factor of the target water injection replacement well according to the specific values ​​and combined weights of each evaluation factor in the lowest level, as well as the preset suitability evaluation level and its corresponding index range.

[0267] The evaluation level determination module 107 is used to determine the suitability evaluation level corresponding to the evaluation result factor according to the index interval in which the evaluation result factor is located, so as to obtain the suitability evaluation result of the target water injection oil replacement well.

[0268] The specific implementation example of the method for evaluating the suitability of a water injection well for oil replacement based on the above modules has been described in detail in the first embodiment and will not be repeated here.

[0269] Embodiment 4

[0270] This embodiment provides an electronic device, which may be a mobile phone, a computer or a tablet computer, etc., including a memory and a processor, wherein a computer program is stored in the memory, and when the computer program is executed by the processor, the water injection oil well suitability evaluation method described in Embodiment 1 is implemented. It is understood that the electronic device may also include an input / output (I / O) interface and a communication component.

[0271] The processor is used to execute all or part of the steps in the water injection oil well suitability evaluation method in Example 1. The memory is used to store various types of data, which may include instructions of any application or method in the electronic device, and data related to the application.

[0272] The processor can be an application specific integrated circuit (ASIC), a digital signal processor (DSP), a digital signal processing device (DSPD), a programmable logic device (PLD), a field programmable gate array (FPGA), a controller, a microcontroller, a microprocessor or other electronic components, and is used to execute the water injection well suitability evaluation method in the above-mentioned embodiment 1.

[0273] The memory can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk or optical disk.

[0274] Embodiment 5

[0275] This embodiment also provides a computer-readable storage medium, such as a flash memory, a hard disk, a multimedia card, a card-type memory (for example, an SD or DX memory, etc.), a random access memory (RAM), a static random access memory (SRAM), a read-only memory (ROM), an electrically erasable programmable read-only memory (EEPROM), a programmable read-only memory (PROM), a magnetic memory, a disk, an optical disk, a server, an App application store, etc., on which a computer program is stored. When the computer program is executed by a processor, the following method steps can be implemented:

[0276] Step S101: acquiring dynamic and static data of a target water injection oil replacement well, and determining evaluation factors affecting the water injection oil replacement effect of the target water injection oil replacement well and their corresponding specific values ​​according to the dynamic and static data;

[0277] Step S102: Classify each evaluation factor to determine the category to which each evaluation factor belongs, and determine the level of each evaluation factor according to the specific value of each evaluation factor;

[0278] Step S103: constructing a hierarchical analysis model of evaluation factors according to the categories and levels of each evaluation factor;

[0279] Step S104: Based on the hierarchical analysis model, a judgment matrix corresponding to each level is constructed by a three-scaling method;

[0280] Step S105: Obtaining the weight vector of each level according to the judgment matrix corresponding to each level, and calculating the combined weight of each evaluation factor in the lowest level according to the weight vector of each level;

[0281] Step S106: Calculate the evaluation result factor of the target water injection well according to the specific values ​​and combined weights of the evaluation factors in the lowest level, as well as the preset suitability evaluation level and its corresponding index range;

[0282] Step S107: determining the suitability evaluation level corresponding to the evaluation result factor according to the index interval in which the evaluation result factor is located, so as to obtain the suitability evaluation result of the target water injection oil replacement well.

[0283] The specific implementation process of the above method steps can be found in Example 1, and this embodiment will not be repeated here.

[0284] In summary, the present disclosure provides a method, device, electronic device and storage medium for evaluating the suitability of a water injection oil replacement well. The method includes determining the evaluation factors and their corresponding specific values ​​that affect the water injection oil replacement effect of the target water injection oil replacement well based on the dynamic and static data; determining the category and level of each evaluation factor to construct a hierarchical analysis model of the evaluation factors; based on the hierarchical analysis model, constructing a judgment matrix corresponding to each level through a three-scaling method; according to the judgment matrix corresponding to each level, obtaining the weight vector of each level, and calculating the combined weight of each evaluation factor in the lowest level according to the weight vector of each level; calculating the evaluation result factor of the target water injection oil replacement well according to the specific values ​​and combined weights of each evaluation factor in the lowest level, as well as the preset suitability evaluation level and its corresponding index interval; determining the suitability evaluation level corresponding to the evaluation result factor according to the index interval in which the evaluation result factor is located, so as to obtain the suitability evaluation result of the target water injection oil replacement well. This method has a simple evaluation process and is easy to promote and apply. The judgment matrix is ​​quickly established and meets the consistency test. It has great theoretical and guiding significance for the blind and subjective non-deterministic and multi-factor technical problems existing in the current development of fracture-cavity reservoirs.

[0285] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the sentence "comprises a ..." does not exclude the existence of other identical elements in the process, method, article or device including the element.

[0286] Although the embodiments disclosed in the present disclosure are as above, the contents described are only embodiments adopted for facilitating the understanding of the present disclosure and are not intended to limit the present disclosure. Any technician in the technical field to which the present disclosure belongs can make any modifications and changes in the form and details of the implementation without departing from the spirit and scope disclosed in the present disclosure, but the scope of patent protection of the present disclosure shall still be subject to the scope defined in the attached claims.

Claims

1. A method for evaluating the suitability of a water injection well for oil replacement, characterized in that: The method comprises: Acquire dynamic and static data of the target water injection oil replacement well, and determine the evaluation factors affecting the water injection oil replacement effect of the target water injection oil replacement well and their corresponding specific values ​​according to the dynamic and static data; Classify each evaluation factor to determine the category to which each evaluation factor belongs, and determine the level of each evaluation factor based on the specific value of each evaluation factor; According to the categories and levels of each evaluation factor, a hierarchical analysis model of evaluation factors is constructed; Based on the analytic hierarchy model, a judgment matrix corresponding to each level is constructed through the three-scale method; According to the judgment matrix corresponding to each level, the weight vector of each level is obtained, and according to the weight vector of each level, the combined weight of each evaluation factor in the lowest level is calculated; Calculate the evaluation result factor of the target water injection replacement well according to the specific values ​​and combined weights of each evaluation factor in the lowest level, as well as the preset suitability evaluation level and its corresponding index range; Determining the suitability evaluation level corresponding to the evaluation result factor according to the index interval in which the evaluation result factor is located, so as to obtain the suitability evaluation result of the target water injection oil replacement well; According to the specific values ​​of each evaluation factor, the level of each evaluation factor is determined, including the following steps: According to the specific value and value range of each evaluation factor, the specific value of each evaluation factor is normalized to obtain the normalized specific value of each evaluation factor; According to the normalized specific values ​​of each evaluation factor, calculate the contribution rate of each evaluation factor; Determine the level of each evaluation factor according to its contribution rate; The hierarchical analysis model includes a first level and a second level; According to the contribution rate of each evaluation factor, the level of each evaluation factor is determined, including the following steps: Determine the level of each evaluation factor based on the comparison result of the contribution rate of each evaluation factor and the preset threshold value; When the contribution rate of the current evaluation factor is greater than or equal to the preset threshold, the level of the current evaluation factor is the first level; When the contribution rate of the current evaluation factor is less than the preset threshold, the level of the current evaluation factor is the second level; Based on the hierarchical analysis model, a judgment matrix corresponding to each level is constructed by the three-scale method, including the following steps: Based on the evaluation factors at each level in the hierarchical analysis model, the three-scale method is used to obtain the comparison matrix corresponding to each level: Among them, E is the comparison matrix of the current level; m is the number of evaluation factors at the current level in the hierarchical analysis model; e ij is the element in the i-th row and j-th column of the comparison matrix of the current level; According to the comparison matrix, the important ranking parameters of each row in the comparison matrix are calculated by the following formula: Among them, p i is the important ranking parameter of the i-th row in the comparison matrix; According to the important ranking parameters of each row in the comparison matrix, the judgment matrix of each level is constructed by the following formula: P=(p ij ) m×m ; Among them, P is the judgment matrix of the current level; p ij is the element in the i-th row and j-th column of the judgment matrix of the current level; p j is the important ranking parameter of the jth row in the comparison matrix of the current level; p max is the maximum value of the important sorting parameters of each row in the comparison matrix of the current level; p max =max(p i ); p min is the minimum value of the important sorting parameters of each row in the comparison matrix of the current level; on min =min(p i ); According to the weight vectors of each level, the combined weights of each evaluation factor in the lowest level are calculated, including the following steps: According to the weight vector of each level, determine the weight of each evaluation factor in the corresponding level; The weight of each evaluation factor in the lowest level is multiplied by the weight of the evaluation factors in all the upper levels in its corresponding category to calculate the initial combined weight of each evaluation factor in the lowest level; Normalize the initial combined weights of the evaluation factors in the lowest level to obtain the final combined weights of the evaluation factors in the lowest level; According to the specific values ​​and combined weights of the evaluation factors in the lowest level, as well as the preset suitability evaluation levels and their corresponding index intervals, the evaluation result factor of the target water injection oil replacement well is calculated, including the following steps: According to the specific values ​​and value ranges of each evaluation factor in the lowest level, the specific values ​​of each evaluation factor in the lowest level are normalized to obtain the normalized specific values ​​of each evaluation factor in the lowest level; According to the normalized specific values ​​of each evaluation factor in the lowest level, as well as the preset suitability evaluation level and its corresponding index range, the evaluation matrix is ​​obtained as follows: R＝(r ij ) m×n ； Among them, R is the evaluation matrix, r ij is the element in the i-th row and j-th column of the evaluation matrix, r ij =1-|a i -(y j +(z j -y j ) / 2)|, m is the number of evaluation factors in the lowest level, n is the number of preset suitability evaluation levels, a i is the normalized specific value of the ith evaluation factor in the lowest level, y j is the lower limit of the preset index interval of the jth level, z j is the lower limit of the preset index range of the jth level; The combined weight vector formed by the combined weights of the evaluation factors in the lowest level is multiplied by the evaluation matrix to obtain the evaluation vector: S=W×R=[s1,s2,…,s j ,…,s n ]; Where S is the evaluation vector, W is the combined weight vector, s j is the jth element of the evaluation vector, W i is the i-th element of the combined weight vector; According to the evaluation vector, the evaluation result factor of the target water injection oil replacement well is calculated by the following formula: Wherein, F is the evaluation result factor of the target water injection oil well.

2. The method according to claim 1, characterized in that According to the specific value and value range of each evaluation factor, the specific value of each evaluation factor is normalized to obtain the normalized specific value of each evaluation factor, including the following steps: Determine a corresponding normalized calculation formula according to the influence of the specific numerical values ​​of each evaluation factor on the water injection oil replacement effect of the target water injection oil replacement well; When the specific value of the current evaluation factor is larger, the effect on the water injection oil replacement effect of the target water injection oil replacement well is better, and the corresponding normalized calculation formula is: Among them, a i is the normalized specific value of the ith evaluation factor, v i is the specific value of the i-th evaluation factor, u i is the lower limit of the value range of the i-th evaluation factor, w i is the upper limit of the value range of the i-th evaluation factor; When the specific value of the current evaluation factor is smaller, the effect on the water injection oil replacement effect of the target water injection oil replacement well is better, the corresponding normalized calculation formula is: According to the specific value of each evaluation factor and the value range of each evaluation factor, the specific value of each evaluation factor is normalized through the corresponding normalization calculation formula to obtain the normalized specific value of each evaluation factor.

3. The method according to claim 1, characterized in that According to the normalized specific values ​​of each evaluation factor, the contribution rate of each evaluation factor is calculated, including the following steps: According to the normalized specific values ​​of each evaluation factor, the first matrix is ​​obtained as follows: <h2 style=";text-align:left;direction:ltr">A=(a1, a2,…, a<h2 style=";text-align:left;direction:ltr"> n <h2 style=";text-align:left;direction:ltr"> ); Among them, A is the first matrix, a n is the normalized specific value of the nth evaluation factor and is the nth element in the first matrix, where n is the total number of evaluation factors; The average value of the first matrix is ​​calculated, and the average value is subtracted from each element in the first matrix to perform standardization processing on the first matrix, so as to obtain a second matrix as follows: B=(b1,b2,…,b n ); Among them, B is the second matrix, b n is the nth element in the second matrix; Calculate the covariance of the second matrix and obtain the corresponding covariance matrix; Obtaining the eigenvectors of the covariance matrix, and arranging the corresponding eigenvalues ​​in order from small to large to obtain a corresponding eigenvalue matrix; Multiply the second matrix by the eigenvalue matrix to obtain a third matrix: X=BD=(x1,x2,…,x n ); Where X is the third matrix, D is the eigenvalue matrix, x n is the nth element in the third matrix; According to the third matrix, the contribution rate of each evaluation factor is calculated according to the following formula: Among them, M i is the contribution value of the ith evaluation factor, x i is the i-th element in the third matrix.

4. The method according to claim 1, characterized in that: According to the judgment matrix corresponding to each level, the weight vector of each level is obtained, including the following steps: According to the judgment matrix corresponding to each level, the characteristic vector of the judgment matrix of each level is obtained to obtain the weight vector of each level; Among them, the weight vector of each level is equal to the eigenvector of the judgment matrix of the corresponding level.

5. A water injection oil well suitability evaluation device, characterized in that: The method for evaluating the suitability of a water injection oil well according to any one of claims 1 to 4 is applied, wherein the device comprises: An evaluation factor determination module is used to obtain dynamic and static data of a target water injection oil replacement well, and determine evaluation factors affecting the water injection oil replacement effect of the target water injection oil replacement well and their corresponding specific values ​​based on the dynamic and static data; The category and level determination module is used to classify each evaluation factor to determine the category to which each evaluation factor belongs, and determine the level of each evaluation factor according to the specific value of each evaluation factor; A hierarchical analysis model building module is used to build a hierarchical analysis model of evaluation factors according to the categories and levels of each evaluation factor; A judgment matrix construction module is used to construct a judgment matrix corresponding to each level based on the hierarchical analysis model through a three-scaling method; The combined weight calculation module is used to obtain the weight vector of each level according to the judgment matrix corresponding to each level, and calculate the combined weight of each evaluation factor in the lowest level according to the weight vector of each level; An evaluation result factor calculation module, used to calculate the evaluation result factor of the target water injection replacement well according to the specific values ​​and combined weights of each evaluation factor in the lowest level, as well as the preset suitability evaluation level and its corresponding index interval; The evaluation grade determination module is used to determine the suitability evaluation grade corresponding to the evaluation result factor according to the index interval in which the evaluation result factor is located, so as to obtain the suitability evaluation result of the target water injection oil replacement well.

6. An electronic device, characterized in that: The invention comprises a memory and a processor, wherein a computer program is stored in the memory, and when the computer program is executed by the processor, the method for evaluating the suitability of a water injection well for oil replacement as claimed in any one of claims 1 to 4 is executed.

7. A storage medium, characterized in that: The computer program stored in the storage medium is executed by one or more processors to implement the method for evaluating the suitability of a water injection well for oil replacement as claimed in any one of claims 1 to 4.

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