A method, device and medium for evaluating the effect of water flooding development in oil reservoirs

Abstract

The present application discloses an evaluation method, device and medium for the water drive development effect of oil reservoirs, and relates to the technical field of data processing for management purposes. The method includes: determining a number of production wells set in the oil reservoir, obtaining a number of influencing factors affecting the water drive development effect of the production wells, classifying the production wells according to the influencing factors, and obtaining a number of production well groups consisting of at least one production well; assigning different parameter weight values ​​to the evaluation parameters; for the production well group, performing a preliminary evaluation of the water drive development effect of the production well group according to the parameter weight value, and obtaining a group evaluation result consisting of a single evaluation result corresponding to a plurality of production wells; according to the group evaluation result, selecting a target evaluation parameter for evaluating the water drive development effect corresponding to the production well group from the evaluation parameters; calculating the membership of the target evaluation parameter value within the preset evaluation level; and determining the water drive development effect corresponding to the production well according to the parameter weight value and the membership.

Description

Technical Field

[0001] The present application relates to the technical field of data processing for management purposes, and in particular to an evaluation method, equipment and medium for the effect of water flooding development of oil reservoirs. Background Art

[0002] As global energy demand continues to grow, the development and utilization of oil resources has become increasingly important. In oil development, water drive oil recovery technology, as an effective method of exploitation, is widely used in various types of oil reservoirs. However, factors such as different reservoir types, geological conditions, and development strategies lead to significant differences in the effects of water drive development. Therefore, accurate evaluation of the effects of water drive development in oil reservoirs is of great significance for optimizing development strategies and improving recovery.

[0003] Traditional methods mostly analyze reservoir development effects based on industry standards for certain evaluation parameters that affect water drive development effects. However, the selection of parameters is often affected by human subjective factors, making it difficult to ensure the objectivity and accuracy of the evaluation results. In addition, there are certain differences between different reservoirs. The above methods can only provide relatively rough evaluation results and are difficult to accurately reflect the actual development effects of the reservoirs. Summary of the invention

[0004] In order to solve the above problems, this application proposes a method for evaluating the effect of water flooding development in oil reservoirs, including:

[0005] Determine a number of production wells set in the oil reservoir, obtain a number of influencing factors that affect the water flooding development effect of the production wells, and classify the number of production wells according to the influencing factors to obtain a plurality of production well groups consisting of at least one production well; wherein the influencing factors include geological characteristic parameters, reservoir characteristic parameters and crude oil property parameters, the geological characteristic parameters at least include formation thickness, formation dip, and fault distribution, the reservoir characteristic parameters at least include permeability, porosity, and water saturation, and the crude oil property parameters at least include crude oil density, viscosity, and sulfur content;

[0006] Determining preset evaluation parameters for evaluating water flooding development effects, and assigning different parameter weight values ​​to the evaluation parameters according to the analytic hierarchy process;

[0007] For the production well group, a preliminary evaluation of the water flooding development effect of the production well group is performed according to the parameter weight value to obtain a group evaluation result consisting of single evaluation results corresponding to multiple production wells;

[0008] According to the group evaluation result, a target evaluation parameter for evaluating the water flooding development effect of the production well group is selected from the evaluation parameters;

[0009] For each production well, a membership function corresponding to the target evaluation parameter is constructed, and the target evaluation parameter value corresponding to the production well is collected, and the membership of the target evaluation parameter value within a preset evaluation level is calculated according to the membership function and the target evaluation parameter value;

[0010] The water drive development effect corresponding to the production well is determined according to the parameter weight value and the membership degree.

[0011] In an implementation of the present application, the plurality of production wells are classified according to the influencing factors to obtain a plurality of production well groups consisting of at least one production well, specifically including:

[0012] According to the influencing factors, determining the influencing factor values ​​corresponding to the plurality of production wells respectively; wherein the influencing factors include at least one or more of the following: geological characteristic parameters, reservoir characteristic parameters and crude oil property parameters;

[0013] From the plurality of production wells, designated production wells whose differences between the corresponding influencing factor values ​​of the influencing factors are within a preset range are selected as a production well group, so as to classify the plurality of production wells.

[0014] In one implementation of the present application, before selecting, from the plurality of production wells, designated production wells whose differences between the corresponding impact factor values ​​of the impact factors are within a preset range, the method further includes:

[0015] Generate a corresponding historical production change curve based on the historical production data of the several production wells, and estimate the production stage corresponding to the current several production wells based on the historical production change curve;

[0016] According to the production stage, the difference between the impact factor values ​​is determined; wherein the difference is negatively correlated with the sequence of the production stages.

[0017] In one implementation of the present application, according to the group evaluation result, target evaluation parameters for evaluating the water flooding development effect of the production well group are screened out from the evaluation parameters, specifically including:

[0018] Determine the fluctuation value between the single evaluation results corresponding to any two production wells in the group evaluation results, and select the maximum fluctuation value from the fluctuation values;

[0019] When the maximum fluctuation value is within a preset range, the evaluation parameter is used as a target evaluation parameter for evaluating the water flooding development effect of the production group;

[0020] Otherwise, the evaluation parameters are combined to obtain an evaluation parameter set composed of arbitrary evaluation parameters, and the water drive development effect corresponding to the production well group is iteratively evaluated according to the evaluation parameter set, until the fluctuation values ​​corresponding to the evaluation parameter set all meet the preset range, and the evaluation parameter set is used as the target evaluation parameter for evaluating the water drive development effect corresponding to the production well group.

[0021] In one implementation of the present application, after iteratively evaluating the water flooding development effect corresponding to the production well group according to the evaluation parameter set, the method further includes:

[0022] When there are fluctuation values ​​corresponding to multiple evaluation parameter sets that satisfy the preset range, calculating the average value between the fluctuation values;

[0023] According to the mean, an evaluation parameter set with the smallest corresponding mean is selected from the multiple evaluation parameter sets as a target evaluation parameter for evaluating the water drive development effect of the production well group.

[0024] In one implementation of the present application, constructing a membership function corresponding to the target evaluation parameter specifically includes:

[0025] Dividing the evaluation levels corresponding to the target evaluation parameters; wherein each evaluation level corresponds to a parameter interval;

[0026] For each target evaluation parameter, the level membership corresponding to the target evaluation parameter in each parameter interval is determined, and the level membership is standardized to obtain the membership function of the target evaluation parameter for each evaluation level.

[0027] In one implementation of the present application, the water drive development effect corresponding to the production well is determined according to the parameter weight value and the membership degree, specifically including:

[0028] Generating an evaluation vector corresponding to the target evaluation parameter value according to the degree of membership of the target evaluation parameter value in each evaluation level;

[0029] The evaluation vectors corresponding to each target evaluation parameter value are concatenated to obtain an evaluation matrix corresponding to the production well;

[0030] A fuzzy transformation is performed based on the parameter weight value and the evaluation matrix to obtain a target evaluation vector for characterizing the water drive development effect corresponding to the production well, and the water drive development effect corresponding to the production well is determined through the target evaluation vector; wherein the target evaluation vector is composed of the fuzzy membership corresponding to the evaluation level.

[0031] In one implementation of the present application, the water flooding development effect corresponding to the production well is determined by the target evaluation vector, specifically including:

[0032] From the target evaluation vector, select the evaluation level to which the fuzzy membership degree with the largest corresponding value belongs;

[0033] The evaluation grade is used as the water drive development effect corresponding to the production well.

[0034] The present application embodiment provides a device for evaluating the effect of water flooding development of oil reservoirs, the device comprising:

[0035] at least one processor;

[0036] and, a memory communicatively coupled to the at least one processor;

[0037] The memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute a method for evaluating the effect of water flooding development of an oil reservoir as described in any one of the above items.

[0038] The embodiment of the present application provides a non-volatile computer storage medium storing computer executable instructions, wherein the computer executable instructions are configured as follows:

[0039] A method for evaluating the effect of water flooding development of an oil reservoir as described in any of the above items.

[0040] The evaluation method of reservoir water flooding development effect proposed in this application can bring the following beneficial effects:

[0041] By constructing production well groups and performing differential analysis on the group evaluation results of production well groups, we can select target evaluation parameters that can provide more stable evaluation results. Compared with the manual selection of evaluation parameters, the selection of parameters is more scientific by combining the actual situation of the production well group. Combining the parameter weight value and the degree of membership, the evaluation parameter value can be converted into the degree of membership of the evaluation level, comprehensively considering multiple evaluation parameters and their relative importance, and considering the performance of different production wells in the specific evaluation parameters, so that the evaluation results are more comprehensive and accurate. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0043] Figure 1 A schematic flow chart of a method for evaluating the effect of water flooding development of an oil reservoir provided in an embodiment of the present application;

[0044] Figure 2 A schematic diagram of the structure of an evaluation device for the effect of water flooding development of oil reservoirs provided in an embodiment of the present application. DETAILED DESCRIPTION

[0045] In order to make the purpose, technical solution and advantages of the present application clearer, the technical solution of the present application will be clearly and completely described below in combination with the specific embodiments of the present application and the corresponding drawings. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present application.

[0046] The technical solutions provided by various embodiments of the present application are described in detail below in conjunction with the accompanying drawings.

[0047] like Figure 1 As shown, an evaluation method for the effect of water flooding development of an oil reservoir provided in an embodiment of the present application includes:

[0048] S101: Determine a number of production wells set in the oil reservoir, obtain a number of influencing factors that affect the water flooding development effect of the production wells, and classify the number of production wells according to the influencing factors to obtain a number of production well groups consisting of at least one production well.

[0049] Oil reservoir development usually sets up several production wells, which are wells specially used for extracting oil and natural gas. Their basic function is to extract resources from underground oil and gas layers. In the process of water drive development, the effect of water drive development directly affects the effect of oil reservoir development, the recovery rate of water drive, and the stability of crude oil production. Therefore, joint management and optimization of the development effect of each production well is very important.

[0050] The water drive development effect of production wells is affected by many factors, which may include geological conditions, well layout, water injection strategy, etc. In order to more accurately evaluate the water drive development effect of different production wells, it is necessary to first determine the influencing factors and classify the production wells according to the influencing factors to form different production well groups. First, collect detailed information about several production wells set in the reservoir, including well location, production capacity, water injection conditions, etc. Then, through geological exploration, production data analysis and other means, obtain multiple influencing factors that affect the water drive development effect of these production wells. The influencing factors include at least one or more of the following: geological characteristic parameters, reservoir characteristic parameters and crude oil property parameters, such as formation permeability, porosity, water saturation, etc.

[0051] After obtaining the influencing factors, the production wells are classified according to the numerical characteristics of the above influencing factors. The purpose of classification is to classify the production wells with similar water flooding development effect influencing factors into one category to form different production well groups. The production wells in each group should have certain similarities in water flooding development effect.

[0052] Specifically, according to the influencing factors, the influencing factor values ​​corresponding to the several production wells are determined by means of geological exploration, laboratory testing, production data analysis, etc. The influencing factors include geological characteristic parameters (such as formation thickness, formation dip, fault distribution, etc.), reservoir characteristic parameters (permeability, porosity, water saturation, etc.) and crude oil property parameters (crude oil density, viscosity, sulfur content, etc.). According to the above-mentioned influencing factor values, from several production wells, the designated production wells whose difference between the corresponding influencing factor values ​​of each influencing factor is within the preset range are screened out as a production well group to realize the classification of several production wells. The preset range can be set according to actual needs and experience to ensure that the screened production wells are similar in influencing factors. By traversing all production wells, calculating the difference between each influencing factor between each pair of production wells, and checking whether these differences are within the preset range, the production wells whose influencing factor differences are within the preset range are classified into a production well group. In this way, several production wells can be classified according to the similarity of influencing factors to form multiple production well groups. The production wells in each group have high similarity in geological characteristics, reservoir characteristics and crude oil properties, which facilitates more accurate evaluation and analysis of the characteristics of different groups in the future.

[0053] It should be noted that the selection of influencing factors should be based on specific reservoir characteristics and development needs. At the same time, as reservoir development progresses and data accumulates, the selection of influencing factors needs to be continuously updated and adjusted to adapt to changes in the reservoir development process.

[0054] Assume that there are four production wells, A, B, C, and D. The address characteristic parameters, reservoir characteristic parameters, and crude oil property parameters of each production well are determined through geological exploration, laboratory testing, production data analysis, and other means. The specific influencing factor values ​​are as follows:

[0055]

[0056] Set the preset range for each impact factor value (Here we take the smaller impact factor value ), for fault distribution, an absolute difference of 0.1 is used as the preset range. Taking production wells A and B as examples, the difference in formation thickness is 2, which does not exceed 10% of the formation thickness of production well A. By repeating the above process, it can be calculated that the difference between the values ​​of each influencing factor is within the preset range. Therefore, it can be considered that the difference between production wells A and B is small. For production wells whose values ​​of all influencing factors are within the preset range, they are classified as a production well group, and for production wells with large differences, they can be listed as a separate group. The final classification results are production well group 1: production wells A and B, production well group 2: production well C, production well group 3: production well 4.

[0057] In one embodiment, as the progress of reservoir development continues to advance, factors such as geological conditions, reservoir characteristics, and crude oil properties at different production stages may change, so the influencing factor values ​​will also be adjusted accordingly. Based on the historical production data of several production wells, a corresponding historical production change curve is generated, and based on the historical production change curve, the production stages corresponding to several current production wells are estimated. The production stage can usually be divided into the initial stage, the stable production stage, the decreasing stage, etc. The initial stage is usually characterized by a rapid increase in production, the stable production stage is relatively stable, and the decreasing stage is a gradual decrease in production. By comparing the characteristics of the historical production change curve with the typical production stage curve, it is possible to preliminarily determine the production stage of the current production well.

[0058] After determining the production stage of the current production well, the difference between the influencing factor values ​​is determined according to the production stage. The difference is negatively correlated with the order of the production stages, that is, as the production stage advances, the difference between the influencing factor values ​​should gradually decrease. This is because as the development progresses, the production capacity of the production well decreases, the impact of the influencing factors on the output gradually converges, and the difference between the influencing factors tends to gradually decrease.

[0059] S102: Determine preset evaluation parameters for evaluating water flooding development effects, and assign different parameter weight values ​​to the evaluation parameters according to the analytic hierarchy process.

[0060] There are multiple evaluation parameters for evaluating the effect of water flooding development, including recovery factor, water flooding reserve control degree, water cut rise rate, water cut recovery ratio, etc. Since the actual conditions of each production well are different, the importance of each evaluation parameter is also different when evaluating the effect of water flooding development on production wells. Therefore, when evaluating the effect of water flooding development on production wells, it is first necessary to assign different parameter weight values ​​to the evaluation parameters based on the hierarchical analysis method. The parameter weight value is used to reflect the importance of different evaluation parameters to the effect of water flooding development in the subsequent evaluation of water flooding development.

[0061] S103: For the production well group, a preliminary evaluation of the water drive development effect of the production well group is performed according to the parameter weight value, and a group evaluation result consisting of single evaluation results corresponding to multiple production wells is obtained.

[0062] In the actual process of waterflooding development effect evaluation, the importance of each evaluation parameter is different, and the evaluation effects they can produce are also different. Therefore, for a large number of evaluation parameters, it is necessary to select the evaluation parameters that can best guarantee the accuracy of the evaluation based on the actual production well conditions to ensure the accuracy and reliability of the waterflooding development effect evaluation results.

[0063] After obtaining at least one production well group through the above process, since each production well group has a high similarity, when the water drive development effect of each production well in the production well group is evaluated by the same evaluation parameters, the evaluation results obtained should also have a certain degree of similarity. In this way, by screening the evaluation parameters based on the similarity between the evaluation effects, the target evaluation parameters that can best ensure the stability of the evaluation results can be selected, thereby improving the accuracy of the evaluation results.

[0064] Therefore, it is necessary to conduct a preliminary evaluation of the water drive development effect of the production well group according to the parameter weight value, and obtain a group evaluation result composed of single evaluation results corresponding to multiple production wells. It should be noted that only a preliminary evaluation is carried out at this time, and the purpose is to select more appropriate target evaluation parameters. Therefore, when conducting a preliminary evaluation of the water drive development effect of the production well group, a simple quantification of the water drive development effect is sufficient, aiming to discover the difference in effect between different production wells. Therefore, by collecting parameter values ​​corresponding to different evaluation parameters and performing weighted summation of the parameter values ​​according to the parameter weight value, a single evaluation result corresponding to each production well can be obtained, and then a group evaluation result corresponding to each production well group can be obtained.

[0065] S104: According to the group evaluation result, target evaluation parameters for evaluating the water drive development effect of the production well group are selected from the evaluation parameters.

[0066] After obtaining the group evaluation results, it is necessary to iteratively optimize the selected evaluation parameters based on the group evaluation results, so as to screen out the target evaluation parameters that are most suitable for evaluating the water flooding development effect.

[0067] In one embodiment, the fluctuation value between the single evaluation results corresponding to any two production wells in the group evaluation results is determined, and the fluctuation value is the difference between the single evaluation results. The maximum fluctuation value is selected from the fluctuation value, and the maximum fluctuation value is compared with the preset range. The preset range can limit the difference limit value between different single evaluation results. When the maximum fluctuation value is within the preset range, it means that the group evaluation results obtained according to the above evaluation parameters are relatively similar. At this time, the selected evaluation parameters can provide a relatively stable and accurate evaluation result. Therefore, at this time, the evaluation parameters can be used as the target evaluation parameters for evaluating the water drive development effect corresponding to the production group group. On the contrary, when the maximum fluctuation value is not within the preset range, it means that there are large differences in the single evaluation results corresponding to each production well in the production well group, and the selected evaluation parameters need to be optimized at this time. In other words, it is necessary to combine the evaluation parameters to obtain an evaluation parameter set composed of any evaluation parameters, and iteratively evaluate the water drive development effect corresponding to the production well group according to the evaluation parameter set, until the fluctuation values ​​corresponding to the evaluation parameter set meet the preset range, the optimization of the evaluation parameters is completed, and the evaluation parameter set at this time is the final target evaluation parameter for evaluating the water drive development effect corresponding to the production well group. When the initial evaluation is performed for the first time, all evaluation parameters are selected by default for evaluation. If the evaluation parameters need to be optimized later, they can be combined in the order of gradually decreasing evaluation parameters to obtain several evaluation parameter sets.

[0068] Assume that the production well group includes production well A, production well B and production well C, and the selected evaluation parameters are recovery factor, water drive reserve control degree, water cut rise rate and water cut recovery ratio. After a preliminary evaluation of each production well in the production well group according to the above-mentioned evaluation method, the corresponding single evaluation results are obtained: production well A: 60.32, production well B: 65.43, production well C: 56.24. By calculating the difference between the above single evaluation results, the fluctuation values ​​between different production wells are obtained, and the maximum fluctuation value is selected from the fluctuation values, that is, the fluctuation value between production well B and production well C is 9.19. The preset range is set to [0,3]. The maximum fluctuation value has exceeded this preset range, indicating that under such evaluation parameters, the single evaluation results obtained by the production well group are quite different, and it is difficult to ensure the stability of the evaluation results. At this time, it is necessary to combine the evaluation parameters. Since all the evaluation parameters are selected in the initial evaluation, only some evaluation parameters need to be selected to form the evaluation parameter set in the subsequent re-combination. For example, the evaluation parameter set may be the recovery factor, water drive reserve control degree, water cut increase rate, or water drive reserve control degree, water cut increase rate, water cut recovery ratio, etc. Based on the evaluation parameter set obtained by the above recombination, the water drive development effect of the production well group is re-evaluated until the fluctuation value corresponding to the evaluation parameter set meets the range of [0,3], and then an evaluation parameter set that can ensure the stability of the evaluation result is obtained.

[0069] It should be noted that when there are multiple evaluation parameter sets whose corresponding fluctuation values ​​meet the preset range, it is necessary to further select an optimal one from these evaluation parameter sets as the target evaluation parameter. First, the mean between the fluctuation values ​​is calculated, and then, based on the mean, the evaluation parameter set with the smallest corresponding mean is selected from multiple evaluation parameter sets as the target evaluation parameter for evaluating the corresponding water drive development effect of the production well group. Selecting the evaluation parameter set with the smallest mean indicates that the evaluation result corresponding to the evaluation parameter set is relatively stable, and accordingly, the evaluation parameter has the best overall stability when reflecting the differences in water drive development effects of the production well group.

[0070] S105: For each production well, construct a membership function corresponding to the target evaluation parameter, collect the target evaluation parameter value corresponding to the production well, and calculate the membership of the target evaluation parameter value within the preset evaluation level based on the membership function and the target evaluation parameter value.

[0071] After selecting the target evaluation parameters, it is necessary to conduct a more accurate evaluation of the water drive development effect of the production wells based on the above parameters. The embodiment of the present application uses the fuzzy comprehensive evaluation method to evaluate the water drive development effect of the production wells. Compared with the traditional method of obtaining the evaluation result by simple calculation of the index value, the qualitative description affecting the water drive development effect is quantified using mathematical methods, taking into account the differences between different production wells, which can make the evaluation effect more accurate and reliable. Therefore, it is necessary to construct a membership function corresponding to the target evaluation parameters, and collect the target evaluation parameter values ​​corresponding to the production wells. According to the membership function and the target evaluation parameter values, the membership of the target evaluation parameter values ​​within the preset evaluation level is calculated.

[0072] In one embodiment, the evaluation parameters must first be classified into types to determine their corresponding monotonicity. If the larger the parameter value of a certain evaluation parameter, the better the development effect, the evaluation parameter has a monotonically increasing property, otherwise it has a monotonically decreasing property. Membership functions are constructed for evaluation parameters with different monotonies respectively. The embodiment of the present application evaluates the water drive development effect through different evaluation levels. Therefore, it is necessary to divide the evaluation levels corresponding to the target evaluation parameters. The evaluation levels are divided into excellent, general, and poor, and each evaluation level corresponds to a parameter interval. For example, for the target evaluation parameter of recovery rate, when the recovery rate is greater than or equal to 30%, it belongs to the evaluation level of "excellent", when the recovery rate is less than 20%, it belongs to the evaluation level of "poor", and when the recovery rate is between 20% and 30%, it belongs to the evaluation level of "general".

[0073] The membership degree is used to describe the degree of membership of the target evaluation parameter value to different parameter intervals. Therefore, for each target evaluation parameter, it is necessary to determine the level membership corresponding to the target evaluation parameter in each parameter interval, standardize the level membership, and obtain the membership function of the target evaluation parameter for each evaluation level. According to the membership function, when the target evaluation parameter value corresponding to the target evaluation parameter is known, the membership degree of each parameter value for different evaluation levels can be calculated.

[0074] S106: Determine the water drive development effect corresponding to the production well according to the parameter weight value and the degree of membership.

[0075] After obtaining the membership degree corresponding to each evaluation parameter at different evaluation levels, the evaluation vector corresponding to the target evaluation parameter value can be generated accordingly. At this time, the evaluation vector is a single-factor evaluation vector, and when evaluating the water drive development effect of the production well, it is necessary to refer to multiple target evaluation parameters. Therefore, the evaluation vectors corresponding to each target evaluation parameter value need to be spliced ​​to obtain the evaluation matrix corresponding to the production well. Row splicing is used for splicing. After obtaining the evaluation matrix, fuzzy transformation is performed according to the parameter weight value and the evaluation matrix to obtain the target evaluation vector used to characterize the water drive development effect corresponding to the production well. The specific formula is as follows: , where M represents a single row vector set consisting of parameter weight values, V represents the evaluation matrix, and L is the target evaluation vector. After the target evaluation vector is calculated, the water drive development effect corresponding to the production well can be determined through the target evaluation vector; where the target evaluation vector is composed of the fuzzy membership corresponding to the evaluation level, which is represented by the modulus membership of the water drive development effect belonging to "excellent", "average" and "poor" in turn.

[0076] In order to obtain accurate evaluation results, it is necessary to follow the maximum membership principle, select the evaluation level of the fuzzy membership with the largest corresponding value from the target evaluation vector, and use the evaluation level as the water drive development effect corresponding to the production well. If the evaluation results show that the water drive development effect is not ideal, it may be necessary to adjust the water injection plan, change the water injection speed or direction, or even consider other development methods, such as gas drive, chemical drive, etc. At the same time, with the help of the evaluation results, the development potential of the block or layer can also be judged, so as to optimize the development sequence and maximize the overall development benefits of the oil field.

[0077] The above are embodiments of the method proposed in this application. Based on the same idea, some embodiments of this application also provide devices and non-volatile computer storage media corresponding to the above methods.

[0078] Figure 2 This is a schematic diagram of a device for evaluating the effect of water flooding development of oil reservoirs provided in an embodiment of the present application. Figure 2 As shown, including:

[0079] at least one processor; and,

[0080] at least one processor is communicatively connected to a memory; wherein,

[0081] The memory stores instructions that can be executed by at least one processor, and the instructions are executed by at least one processor so that the at least one processor can execute a method for evaluating the effect of water flooding development of an oil reservoir as described in any one of the above items.

[0082] The embodiment of the present application provides a non-volatile computer storage medium storing computer executable instructions, wherein the computer executable instructions are configured as follows:

[0083] A method for evaluating the effect of water flooding development of an oil reservoir as described in any of the above items.

[0084] Each embodiment in this application is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the device and medium embodiments, since they are basically similar to the method embodiments, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiments.

[0085] The devices and media provided in the embodiments of the present application correspond one-to-one to the methods. Therefore, the devices and media also have similar beneficial technical effects as the corresponding methods. Since the beneficial technical effects of the methods have been described in detail above, the beneficial technical effects of the devices and media will not be repeated here.

[0086] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present application may adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0087] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0088] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0089] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0090] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0091] Memory may include non-permanent storage in a computer-readable medium, in the form of random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory is an example of a computer-readable medium.

[0092] Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

[0093] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity 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, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0094] The above is only an embodiment of the present application and is not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.

Claims

1. A method for evaluating the effect of water flooding development in oil reservoirs, characterized in that: The method comprises: Determine a number of production wells set in the oil reservoir, obtain a number of influencing factors that affect the water flooding development effect of the production wells, and classify the number of production wells according to the influencing factors to obtain a plurality of production well groups consisting of at least one production well; wherein the influencing factors include geological characteristic parameters, reservoir characteristic parameters and crude oil property parameters, the geological characteristic parameters at least include formation thickness, formation dip, and fault distribution, the reservoir characteristic parameters at least include permeability, porosity, and water saturation, and the crude oil property parameters at least include crude oil density, viscosity, and sulfur content; Determining preset evaluation parameters for evaluating water flooding development effects, and assigning different parameter weight values ​​to the evaluation parameters according to the analytic hierarchy process; For the production well group, a preliminary evaluation of the water flooding development effect of the production well group is performed according to the parameter weight value to obtain a group evaluation result consisting of single evaluation results corresponding to multiple production wells; According to the group evaluation result, a target evaluation parameter for evaluating the water flooding development effect corresponding to the production well group is selected from the evaluation parameters; For each production well, a membership function corresponding to the target evaluation parameter is constructed, and the target evaluation parameter value corresponding to the production well is collected, and the membership of the target evaluation parameter value within a preset evaluation level is calculated according to the membership function and the target evaluation parameter value; Determining the water drive development effect corresponding to the production well according to the parameter weight value and the membership degree; According to the group evaluation result, target evaluation parameters for evaluating the water flooding development effect of the production well group are screened out from the evaluation parameters, specifically including: Determine the fluctuation value between the single evaluation results corresponding to any two production wells in the group evaluation results, and select the maximum fluctuation value from the fluctuation values; When the maximum fluctuation value is within a preset range, the evaluation parameter is used as a target evaluation parameter for evaluating the water flooding development effect of the production well group; Otherwise, the evaluation parameters are combined to obtain an evaluation parameter set composed of arbitrary evaluation parameters, and the water drive development effect corresponding to the production well group is iteratively evaluated according to the evaluation parameter set, until the fluctuation values ​​corresponding to the evaluation parameter set all meet the preset range, and the evaluation parameter set is used as the target evaluation parameter for evaluating the water drive development effect corresponding to the production well group.

2. The method for evaluating the effect of water flooding development of an oil reservoir according to claim 1, characterized in that: According to the influencing factors, the plurality of production wells are classified to obtain a plurality of production well groups consisting of at least one production well, specifically including: According to the influencing factors, determining the influencing factor values ​​corresponding to the plurality of production wells respectively; From the plurality of production wells, designated production wells whose differences between the corresponding influencing factor values ​​of the influencing factors are within a preset range are selected as a production well group, so as to classify the plurality of production wells.

3. The method for evaluating the effect of water flooding development of oil reservoirs according to claim 2, characterized in that: Before selecting the designated production wells whose differences between the impact factor values ​​corresponding to the impact factors are within a preset range from the plurality of production wells, the method further comprises: Generate a corresponding historical production change curve based on the historical production data of the several production wells, and estimate the production stage corresponding to the current several production wells based on the historical production change curve; According to the production stage, the difference between the impact factor values ​​is determined; wherein the difference is negatively correlated with the sequence of the production stages.

4. The method for evaluating the effect of water flooding development of oil reservoirs according to claim 1, characterized in that: After iteratively evaluating the water flooding development effect corresponding to the production well group according to the evaluation parameter set, the method further includes: When there are fluctuation values ​​corresponding to multiple evaluation parameter sets that satisfy the preset range, calculating the mean between the fluctuation values; According to the mean, an evaluation parameter set with the smallest corresponding mean is selected from the multiple evaluation parameter sets as a target evaluation parameter for evaluating the water drive development effect of the production well group.

5. The method for evaluating the effect of water flooding development of oil reservoirs according to claim 1, characterized in that: Constructing the membership function corresponding to the target evaluation parameter, specifically including: Dividing the evaluation levels corresponding to the target evaluation parameters; wherein each evaluation level corresponds to a parameter interval; For each target evaluation parameter, the level membership corresponding to the target evaluation parameter in each parameter interval is determined, and the level membership is standardized to obtain the membership function of the target evaluation parameter for each evaluation level.

6. The method for evaluating the effect of water flooding development of oil reservoirs according to claim 5, characterized in that: Determining the water drive development effect corresponding to the production well according to the parameter weight value and the membership degree specifically includes: Generating an evaluation vector corresponding to the target evaluation parameter value according to the membership of the target evaluation parameter value in each evaluation level; The evaluation vectors corresponding to each target evaluation parameter value are concatenated to obtain an evaluation matrix corresponding to the production well; A fuzzy transformation is performed based on the parameter weight value and the evaluation matrix to obtain a target evaluation vector for characterizing the water drive development effect corresponding to the production well, and the water drive development effect corresponding to the production well is determined through the target evaluation vector; wherein the target evaluation vector is composed of the fuzzy membership corresponding to the evaluation level.

7. The method for evaluating the effect of water flooding development of oil reservoirs according to claim 6, characterized in that: Determining the water drive development effect corresponding to the production well through the target evaluation vector specifically includes: From the target evaluation vector, select the evaluation level to which the fuzzy membership degree with the largest corresponding value belongs; The evaluation grade is used as the water drive development effect corresponding to the production well.

8. An evaluation device for the effect of water flooding development of oil reservoirs, characterized in that: The device comprises: at least one processor; and, a memory communicatively coupled to the at least one processor; Wherein, the memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the method for evaluating the effect of water flooding development of oil reservoirs as described in any one of claims 1-7.

9. A non-volatile computer storage medium storing computer executable instructions, characterized in that: The computer executable instructions are configured to: A method for evaluating the effect of water flooding development of an oil reservoir as described in any one of claims 1 to 7.

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