An electric drilling and fracturing optimization method and system for oil and gas production

Abstract

The present invention relates to the technical field related to oil and gas production, and specifically includes an electric drilling fracturing optimization method and system for oil and gas production, the method comprising: collecting geological information of target strata, optimizing electric drilling control parameters, generating drilling crack distribution information, combining the optimized drilling fitness set with the crack distribution information, and integrating and analyzing fracturing fluid and proppant parameters; combining the optimal electric drilling parameters with the integrated parameters as the electric drilling fracturing optimization result; solving the technical problems that it is difficult to fully develop oil and gas resources in complex areas such as deep strata, and oil and gas production has insufficient adaptability in complex strata, achieving comprehensive collection of geological information of target strata and optimizing electric drilling control parameters, improving geological fitness and oil and gas fitness, widely adapting to the production of oil and gas resources in various complex areas, generating drilling crack distribution, accurately analyzing crack formation and distribution, and improving the technical effect of oil and gas production efficiency.

Description

Technical Field

[0001] The present invention relates to the technical field related to oil and gas exploitation, and in particular to an electric perforation fracturing optimization method and system for oil and gas exploitation. Background Art

[0002] In today's situation of continued growth in global energy demand, oil and gas resources are important sources of energy, and their efficient exploitation is of vital importance. Conventional oil and gas exploitation is mostly a single mapping model, but in actual applications, facing complex stratigraphic conditions, some limitations are gradually exposed. With the continuous deepening of oil and gas exploration and development, more and more oil and gas reservoirs are located in complex geological structure areas, such as deep formations, low permeability reservoirs, etc. The geological characteristics are complex and diverse, and the distribution of oil and gas is uneven, making it difficult to fully and effectively develop these resources. For example, conventional hydraulic fracturing technology may not work well in some hard rock formations and cannot form an ideal fracture network, thus affecting the flow and exploitation efficiency of oil and gas.

[0003] In summary, the existing technologies have the technical problems of being difficult to fully develop oil and gas resources in complex areas such as deep formations, and the insufficient adaptability of oil and gas extraction in complex formations. Summary of the invention

[0004] The present application provides an electric perforation and fracturing optimization system for oil and gas production, aiming to solve the technical problems in the prior art of difficulty in fully developing oil and gas resources in complex areas such as deep formations, and insufficient adaptability of oil and gas production in complex formations.

[0005] In view of the above problems, the technical solution to implement this application is:

[0006] In one aspect, the present application provides an electric perforation fracturing optimization method for oil and gas production, wherein the method comprises: collecting stratigraphic geological information of a target stratum to be subjected to oil and gas production, wherein the stratigraphic geological information comprises rock formation characteristic information and oil and gas characteristic information;

[0007] According to the formation geological information, the electric drilling control parameters are optimized to obtain an optimized electric drilling control parameter set and a corresponding optimized drilling fitness set, wherein the optimization of the electric drilling control parameters includes maximizing the geological fitness and the oil and gas fitness;

[0008] According to the optimized electro-perforation control parameter set combined with the rock formation characteristic information, the perforation fracture distribution of the target formation is generated to obtain a plurality of fracture distribution information, each of which includes fracture depth information and fracture width information;

[0009] According to the optimized perforation fitness set, combined with the plurality of fracture distribution information, an integrated analysis of the fracturing fluid injection pressure and the proppant injection parameters is performed to obtain an integrated fracturing fluid injection pressure and an integrated proppant injection parameter;

[0010] The optimal electro-perforation control parameters in the optimized electro-perforation control parameter set are combined with the integrated fracturing fluid injection pressure and the integrated proppant injection parameters to be used as the electro-perforation fracturing optimization result.

[0011] On the other hand, the present application provides an electric perforation fracturing optimization system for oil and gas production, wherein the system comprises: an information acquisition module, for acquiring stratigraphic geological information of a target stratum to be subjected to oil and gas production, wherein the stratigraphic geological information comprises rock formation characteristic information and oil and gas characteristic information;

[0012] A parameter optimization module, used to optimize the electric drilling control parameters according to the formation geological information, and obtain an optimized electric drilling control parameter set and a corresponding optimized drilling fitness set, wherein the optimization of the electric drilling control parameters includes maximizing the geological fitness and the oil and gas fitness;

[0013] A fracture distribution module, used to generate the perforation fracture distribution of the target formation according to the optimized electro-perforation control parameter set combined with the rock formation characteristic information, and obtain a plurality of fracture distribution information, each of which includes fracture depth information and fracture width information;

[0014] An integrated analysis module, configured to perform integrated analysis of the fracturing fluid injection pressure and the proppant injection parameters according to the optimized perforation fitness set and in combination with the plurality of fracture distribution information, to obtain an integrated fracturing fluid injection pressure and an integrated proppant injection parameter;

[0015] The result determination module is used to combine the optimal electro-perforation control parameter in the optimized electro-perforation control parameter set with the integrated fracturing fluid injection pressure and the integrated proppant injection parameter as the electro-perforation fracturing optimization result.

[0016] In summary, one or more technical solutions provided in this application solve the technical problems of difficulty in fully developing oil and gas resources in complex areas such as deep formations, and insufficient adaptability of oil and gas extraction in complex formations. It realizes the comprehensive collection of geological information of the target formation and optimization of electric drilling control parameters, improves geological adaptability and oil and gas adaptability, and is widely adapted to the exploitation of oil and gas resources in various complex areas. It generates drilling fracture distribution, accurately analyzes fracture formation and distribution, and improves the efficiency of oil and gas extraction. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 A schematic flow chart of an electro-perforation fracturing optimization method for oil and gas production is provided for this application;

[0018] Figure 2 A structural schematic diagram of an electric perforation and fracturing optimization system for oil and gas production is provided for this application.

[0019] Explanation of reference numerals: information collection module M100, parameter optimization module M200, crack distribution module M300, integrated analysis module M400, result determination module M500. DETAILED DESCRIPTION

[0020] Embodiment 1

[0021] The present application is described in detail below with reference to the accompanying drawings. Figure 1 As shown, the present application provides an electro-perforation fracturing optimization method for oil and gas production, wherein the method comprises:

[0022] S1: Collecting stratigraphic geological information of a target stratum to be exploited for oil and gas, wherein the stratigraphic geological information includes rock stratum characteristic information and oil and gas characteristic information.

[0023] Furthermore, to collect geological information of the target stratum for oil and gas production, the method of the present application includes:

[0024] S1-1: Collect rock formation characteristic information of the target stratum for oil and gas extraction.

[0025] S1-2: Collecting oil and gas characteristic information of the target formation.

[0026] S1-3: Integrate the rock formation characteristic information and the oil and gas characteristic information to obtain the formation geological information.

[0027] In the process of oil and gas extraction, the use of electroperforation technology helps to improve the production capacity and development efficiency of oil and gas wells. Inevitably, there is a certain probability that the electroperforation process will cause damage to the well wall, and even cause the risk of well wall collapse, affecting the stability of the oil and gas well. Based on this, the present application provides an electroperforation fracturing optimization method for oil and gas extraction, which maximizes the advantages of electroperforation technology while reducing its potential risks and negative impacts.

[0028] Specifically, stratigraphic geological information is comprehensive data used to characterize the geological structure and characteristics of the strata, including rock formation characteristic information and oil and gas characteristic information. The rock formation characteristic information refers to the physical and chemical properties of the rocks that constitute the strata, such as the type, structure, thickness, hardness, etc. For example, some rock formations are rich in quartz, while others are mainly composed of limestone. These differences will affect the effects of drilling and fracturing; oil and gas characteristic information refers to the distribution, enrichment level, type (such as light oil, heavy oil, natural gas, etc.) of oil and gas reservoirs in the strata, and their relationship with the surrounding rock formations.

[0029] Execution steps: Conduct geological exploration to collect information such as rock thickness and oil and gas distribution depth. Specifically, analyze the rocks, minerals, and stratigraphic contact relationships exposed on the surface to infer the conditions of underground rock formations. For example, a certain type of rock outcrop found on the surface may indicate the existence of large areas of the same rock formation underground. Use professional tools such as geological hammers, compasses, and GPS locators to infer the underground rock formation structure through the propagation speed and reflection of waves in the formation, determine the underground rock formation structure and oil and gas distribution, and provide data support for subsequent analysis.

[0030] Preferably, the formation geological information of the target formation to be exploited for oil and gas is collected. Specifically, the rock formation characteristic information of the target formation to be exploited for oil and gas is collected, including rock sampling, formation profile analysis, and geophysical measurement. For example, seismic exploration can reveal the thickness and properties of the rock formation by measuring the propagation of seismic waves in the formation; collecting oil and gas characteristic information involves direct observation and analysis of oil and gas displays in the formation, such as coring through drilling (coring through a rock sampler, and then using a gas detector to detect hydrocarbon gases released during the drilling process to determine the existence of oil and gas layers) or logging technology (resistivity logging and natural gamma logging can provide detailed information on the properties of the oil and gas layers and surrounding rock formations) to determine the existence and properties of oil and gas; the distribution and characteristics of different rock formations corresponding to the rock formation characteristic information and the specific location and range of the oil and gas reservoirs corresponding to the oil and gas characteristic information are combined to obtain the formation geological information to provide data support for subsequent analysis.

[0031] S2: Optimizing the electric drilling control parameters according to the formation geological information to obtain an optimized electric drilling control parameter set and a corresponding optimized drilling fitness set, wherein the optimization of the electric drilling control parameters includes maximizing the geological fitness and the oil and gas fitness.

[0032] Furthermore, according to the formation geological information, the electric drilling control parameters are optimized to obtain an optimized electric drilling control parameter set and a corresponding optimized drilling fitness set. The method of the present application includes:

[0033] S2-1: Obtaining the electric perforation control parameter space for electric perforation fracturing.

[0034] S2-2: randomly generating a plurality of first electroporation control parameters in the electroporation control parameter space.

[0035] S2-3: Performing an electric drilling analysis based on the multiple first electric drilling control parameters and in combination with the formation geological information to obtain multiple first geological suitabilities and multiple first oil and gas suitabilities, and performing weighted calculation to obtain multiple first drilling suitabilities.

[0036] Furthermore, according to the plurality of first electro-perforation control parameters and in combination with the formation geological information, electro-perforation analysis is performed, and the method of the present application includes:

[0037] S2-31: Based on the historical data of electro-perforation fracturing, collect the sample electro-perforation control parameter set and the sample bottom geological information set, and mark the sample geological fitness set and sample oil and gas fitness set according to the stability of the rock formation after electro-perforation and the depth of the oil and gas rich layer.

[0038] S2-32: Using the sample electro-perforation control parameter set, the sample bottom geological information set, the sample geological fitness set and the sample oil and gas fitness set, train an electro-perforation analyzer.

[0039] S2-33: Using the electro-perforation analyzer, the electro-perforation analysis is performed on the formation geological information in combination with the plurality of first electro-perforation control parameters to obtain a plurality of first geological suitabilities and a plurality of first oil and gas suitabilities.

[0040] S2-4: clustering the plurality of first electro-perforation control parameters according to the plurality of first perforation fitnesses, and performing iterative optimization to obtain an electro-perforation control parameter cluster with the maximum sum of perforation fitnesses as an optimized electro-perforation control parameter set.

[0041] Furthermore, according to the plurality of first perforation fitnesses, the plurality of first electroporation control parameters are clustered and iteratively optimized. The method of the present application includes:

[0042] S2-41: Divide and obtain a plurality of first cluster head electro-perforation control parameters according to the plurality of first perforation fitnesses, and cluster the other first electro-perforation control parameters to obtain a plurality of electro-perforation control parameter clusters.

[0043] S2-42: Taking the cluster head electroporation control parameter in each electroporation control parameter cluster as the adjustment direction, in the electroporation control parameter space, adjust and update other electroporation control parameters in the electroporation control parameter cluster.

[0044] S2-43: Conducting electric drilling analysis on the adjusted and updated electric drilling control parameters in combination with the formation geological information, calculating and obtaining updated drilling fitness, updating the electric drilling control parameter with the maximum drilling fitness as the cluster head electric drilling control parameter, and obtaining multiple updated electric drilling control parameter clusters.

[0045] S2-44: Continue iterative optimization until convergence, and output the electroporation control parameter cluster with the largest sum of pore fitness as the optimized electroporation control parameter set.

[0046] Specifically, the electro-perforating control parameters refer to the parameters that can be adjusted during the electro-perforating operation, such as voltage, current, perforating time, etc.; the geological fitness is used to measure the degree of matching between the electro-perforating control parameters and the rock formation characteristics in the formation geological information, such as whether the stability of the rock formation after electro-perforation and the distribution of cracks are conducive to oil and gas extraction; the oil and gas fitness is used to measure the degree of matching between the electro-perforating control parameters and the oil and gas characteristics in the formation geological information, such as whether the oil and gas rich layers can be better exposed and the fluidity of oil and gas can be improved; the elements in the optimized electro-perforating control parameter set include voltage, current, etc., to improve the stability of the rock formation after perforation and the depth of the oil and gas rich layer; the elements in the optimized drilling fitness set correspond one-to-one to the elements in the optimized electro-perforating control parameter set, and are a collection of fitness values ​​of each electro-perforating control parameter after considering the geological fitness and oil and gas fitness.

[0047] Execution steps: Different rock formations and oil and gas distributions require different electric drilling parameters to achieve the best mining effect. Therefore, the optimization of electric drilling control parameters is to find a set of electric drilling parameters that best suits the current geological conditions, that is, to optimize the electric drilling control parameter set. The parameters in the optimized electric drilling control parameter set can achieve the best drilling effect under the current geological conditions, and at the same time, obtain the corresponding optimized drilling fitness set; the optimization of electric drilling control parameters includes balanced geological fitness and oil and gas fitness; geological fitness refers to the degree of matching between electric drilling parameters and rock formation characteristics of the formation. For example, if the rock formation is hard, higher voltage and current are required for drilling to ensure the depth and effect of drilling; oil and gas fitness refers to the degree of matching between electric drilling parameters and oil and gas characteristics in the formation. For example, the cracks after drilling should be able to better guide the flow of oil and gas and improve the mining efficiency of oil and gas. Through balanced geological fitness and oil and gas fitness, it can be ensured that the optimized electric drilling control parameters can not only adapt to the rock formation characteristics of the formation, but also be conducive to the mining of oil and gas.

[0048] Preferably, the electro-perforating control parameters are optimized according to the formation geological information to obtain an optimized electro-perforating control parameter set and a corresponding optimized perforating fitness set. Furthermore, the electro-perforating control parameter space refers to all possible combinations of value ranges of the electro-perforating control parameters. For example, the electro-perforating control parameters include voltage, current, perforating time, etc. Then the electro-perforating control parameter space is a multidimensional space composed of different voltage values, different current values, and different perforating time values. The first electro-perforating control parameter is a set of electro-perforating control parameters randomly generated in the electro-perforating control parameter space, which serve as the initial parameters to be analyzed. The first geological fitness reflects the adaptation of the stability of the rock formation after electro-perforation, the influence of cracks on the rock formation structure, and other aspects to the rock formation characteristics.

[0049] Execution step: randomly generate a plurality of first electroporation control parameters in the electroporation control parameter space, for example, randomly generate a set of voltages of Volts, current Ampere, punching time is The electroporation control parameter of 1 second is used as a first electroporation control parameter; a set of voltages is randomly generated as Volts, current Ampere, punching time is The electroporation control parameter of 10 seconds is used as the second first electroporation control parameter; the process is repeated continuously to randomly generate a plurality of other first electroporation control parameters with different values.

[0050] Preferably, according to the multiple first electro-perforating control parameters, in combination with the formation geological information, electro-perforating analysis is performed. Furthermore, the sample electro-perforating control parameter set refers to various different combinations of electro-perforating control parameters collected from historical data of electro-perforating fracturing, for example, a combination of different voltages, currents and perforating times; the sample bottom geological information set is used to characterize the geological information of different strata obtained from historical data, covering the hardness, thickness, porosity of the strata, and the reserves and distribution of oil and gas and other characteristics; the sample geological fitness set refers to the fitness set obtained by annotating the sample electro-perforating control parameters and the sample bottom geological information according to the stability of the strata after electro-perforation, reflecting the influence of different electro-perforating parameters on the stability of the strata in different strata; the sample oil and gas fitness set refers to the fitness set obtained by annotating the depth of the oil and gas rich strata after electro-perforation, reflecting the suitability of the electro-perforating parameters for the exposure and exploitation of the oil and gas rich strata; the electro-perforating analyzer is a trained digital model that can perform analysis based on the formation geological information and the electro-perforating control parameters to obtain geological fitness and oil and gas fitness.

[0051] Execution steps: Collect a sample electric perforation control parameter set and a sample bottom geological information set from the historical data of electric perforation and fracturing. For example, collect different voltage, current, and perforation time combinations from multiple electric perforation and fracturing projects in the historical data as a sample electric perforation control parameter set, and collect the rock hardness, thickness, oil and gas reserves and other information of the strata corresponding to these projects as a sample bottom geological information set; label these samples according to the rock stability after electric perforation and the depth of the oil and gas rich layer. For example, if the rock formation is very stable after the electric perforation operation of a certain sample, without collapse, etc., and the oil and gas rich layer is well exposed and deeply mined, then a higher rock stability and oil and gas rich layer depth labeling value is given. Through these labels, A sample geological fitness set and a sample oil and gas fitness set are obtained; a sample electro-perforating control parameter set, a sample bottom geological information set, a sample geological fitness set and a sample oil and gas fitness set are used to train an electro-perforating analyzer. Specifically, a machine learning algorithm, such as a neural network, can be used, with the sample electro-perforating control parameters and the sample bottom geological information as input, and the sample geological fitness and the sample oil and gas fitness as output targets for training. After the training is completed, the electro-perforating analyzer is used to perform electro-perforating analysis on the current formation geological information in combination with a plurality of first electro-perforating control parameters, and the rock formation stability and the depth of the oil and gas enrichment layer under the plurality of first electro-perforating control parameter combinations are analyzed respectively, so as to obtain the corresponding plurality of first geological fitness and plurality of first oil and gas fitness.

[0052] Preferably, according to the multiple first perforating fitnesses, the multiple first electric perforating control parameters are clustered and iteratively optimized. Furthermore, the first perforating fitness is used to comprehensively measure the overall adaptability of the first electric perforating control parameters in geology and oil and gas; the first cluster head electric perforating control parameter is an electric perforating control parameter with higher fitness divided according to the multiple first perforating fitnesses, which serves as the initial center of subsequent clustering; the electric perforating control parameter cluster is a parameter set formed around the first cluster head electric perforating control parameter by clustering other first electric perforating control parameters; the optimized electric perforating control parameter set is the electric perforating control parameter cluster with the largest sum of perforating fitness after iterative optimization, which represents the optimal combination of electric perforating control parameters under the current formation geological information.

[0053] Execution steps: clustering according to multiple first punching fitnesses, assuming that there are multiple first punching fitnesses, for example, fitness values ​​are 7, 7.5, 8.5, etc.; arranging the fitness values ​​in order from large to small, selecting multiple parameters with fitness values ​​in the top few positions as multiple first cluster head electroporation control parameters, clustering the other first electroporation control parameters, and using clustering algorithms, such as K-Means algorithm, etc., to assign them to different clusters according to the similarities between the parameters, thereby obtaining multiple electroporation control parameter clusters; taking the cluster head electroporation control parameters in each electroporation control parameter cluster as the adjustment direction, adjusting and updating the other electroporation control parameters in the cluster in the electroporation control parameter space, for example, if the voltage of a cluster head parameter is 100 volts, the current is 5 amperes, and the punching time is 10 seconds, then the other parameters in the cluster can be fine-tuned in this direction, such as increasing or decreasing the voltage within a certain range, and the current and The drilling time is also adjusted accordingly; the adjusted and updated electric drilling control parameters are combined with the formation geological information to perform electric drilling analysis again. Similar to the electric drilling analysis process described previously, the electric drilling analyzer is used to calculate the updated drilling fitness based on the stability of the rock formation after electric drilling and the depth of the oil and gas rich layer. Then, in each electric drilling control parameter cluster, the electric drilling control parameter with the largest drilling fitness is updated as the cluster head electric drilling control parameter, thereby obtaining multiple updated electric drilling control parameter clusters; iterative optimization is continued, and the above process is repeated until the convergence condition is met. The convergence condition can be that the change in drilling fitness in several consecutive iterations is less than a certain threshold, or the preset maximum number of iterations is reached; finally, the electric drilling control parameter cluster with the largest sum of drilling fitness is output as the optimized electric drilling control parameter set. The optimized electric drilling control parameter set represents the parameter combination that is most suitable for electric drilling fracturing under the current geological information. In the above steps, the physical process of electro-drilling is taken into consideration, and combined with geological information and the characteristics of oil and gas-rich layers, through continuous optimization and iteration, the changes in geological conditions and oil and gas conditions are adapted to provide support for efficient and stable oil and gas exploitation.

[0054] S3: generating the perforation fracture distribution of the target formation according to the optimized electro-perforation control parameter set in combination with the rock formation characteristic information, and obtaining a plurality of fracture distribution information, each of which includes fracture depth information and fracture width information.

[0055] Furthermore, according to the optimized electro-perforation control parameter set combined with the rock formation characteristic information, the perforation fracture distribution of the target formation is generated. The method of the present application includes:

[0056] S3-1: Based on the historical data of electric drilling and fracturing, collect a set of sample electric drilling control parameters and a set of sample rock formation characteristic information, and mark the sample fracture depth information and sample fracture width information according to the depth and width of the rock formation fractures obtained by drilling and fracturing as a set of sample fracture distribution information.

[0057] S3-2: Using the sample electric drilling control parameter set, the sample rock formation characteristic information set, and the sample fracture distribution information set, a drilling fracture generator is trained.

[0058] S3-3: Utilizing the perforation fracture generator, the multiple optimized electric perforation control parameters in the optimized electric perforation control parameter set are respectively combined with the rock formation characteristic information to generate perforation fracture distribution of the target formation, and obtain multiple fracture distribution information.

[0059] Specifically, the rock formation characteristic information is used to describe various characteristics of the rock formation in the target formation, such as the hardness, thickness, porosity, etc. of the rock formation; the fracture distribution information is used to characterize the detailed description of the fractures formed in the target formation after the electro-perforation operation, including fracture depth information (such as the longitudinal extension length of the fracture in the rock formation) and fracture width information (the lateral opening degree of the fracture).

[0060] Execution steps: According to multiple optimized electric drilling control parameters and in combination with rock formation characteristics, the depth and width of rock formation cracks after drilling are analyzed to generate crack distribution information. Specifically, numerical simulation software or machine learning-based models and other tools can be used. For example, finite element analysis software is used to take the optimized electric drilling control parameter set and rock formation characteristic information as input. Assume a specific example, the optimized electric drilling control parameter set includes a set of parameters such as voltage of 1000 volts, current of 50 amperes, and drilling time of 8 minutes. The rock formation characteristic information is that the rock formation hardness is medium hardness (can also be represented by a fixed hardness numerical table), thickness is 50 meters, and porosity is a certain proportion; based on these input information, the effect of the electric drilling process on the rock formation is simulated. During the simulation process, the formation and development of the cracks are determined by calculating the physical processes such as stress distribution and energy transfer in the rock formation, and multiple crack distribution information are output, each of which contains crack depth information and crack width information. For example, after simulation, a crack distribution information is obtained, and the crack depth is 20 meters and the crack width is 5 centimeters. Each parameter combination in the optimized electric drilling control parameter set is simulated to obtain multiple crack distribution information.

[0061] Preferably, the perforation fracture distribution of the target formation is generated according to the optimized electro-perforation control parameter set in combination with the rock formation characteristic information. Furthermore, the sample fracture depth information is information obtained by marking the fracture depth of the rock formation after electro-perforation fracturing in the historical data; the sample fracture width information is information associated with the sample fracture depth information, and is information obtained by marking the fracture width of the rock formation after electro-perforation fracturing in the historical data; the sample fracture distribution information set consists of the sample fracture depth information and the sample fracture width information, which is used to describe the fracture distribution in the historical data; the perforation fracture generator is a tool obtained by training that can generate the perforation fracture distribution of the target formation according to the electro-perforation control parameters and the rock formation characteristic information; the fracture distribution information includes the fracture depth information and the fracture width information, which describes the fracture distribution of the target formation under specific electro-perforation control parameters and rock formation characteristics.

[0062] Execution steps: based on the historical data of electric perforation and fracturing, collect a sample electric perforation control parameter set and a sample rock formation characteristic information set. For example, different combinations of electric perforation control parameters such as voltage, current, and perforation time are collected from multiple historical electric perforation and fracturing projects as a sample electric perforation control parameter set, and at the same time, the hardness, thickness, porosity and other information of the formations and rock layers corresponding to these projects are collected as a sample rock formation characteristic information set; according to the depth and width of the rock formation cracks after perforation and fracturing, mark each sample in the sample rock formation characteristic information set to obtain sample crack depth information and sample crack width information. For example, in a certain historical project, after electric perforation and fracturing, the rock formation crack depth is u meters and the crack width is v centimeters, and the values ​​u and v are marked; then these crack depth and width information are combined as a sample crack distribution information set. The perforation fracture generator is trained by using a set of sample electric perforation control parameters, a set of sample rock formation characteristic information, and a set of sample fracture distribution information. A machine learning algorithm, such as a neural network, can be used to train the sample electric perforation control parameters and the sample rock formation characteristic information as inputs and the sample fracture distribution information as output targets. After the training is completed, an optimized electric perforation control parameter combination in the optimized electric perforation control parameter set is randomly extracted and input into the trained perforation fracture generator together with the rock formation characteristic information of the target formation, and the corresponding fracture distribution (including the depth and width of the fracture) is predicted to obtain the first fracture distribution information, which includes the rock formation characteristic information of the target formation and the association of a randomly extracted optimized electric perforation control parameter combination. Then, each optimized electric perforation control parameter combination in the optimized electric perforation control parameter set is traversed, and the multiple optimized electric perforation control parameters in the optimized electric perforation control parameter set are respectively combined with the rock formation characteristic information to generate the perforation fracture distribution of the target formation to obtain multiple fracture distribution information. The perforation fracture generator is trained to provide model support for the analysis of the depth and width of the rock formation fractures after perforation.

[0063] S4: performing integrated analysis of fracturing fluid injection pressure and proppant injection parameters according to the optimized perforation fitness set and in combination with the plurality of fracture distribution information to obtain integrated fracturing fluid injection pressure and integrated proppant injection parameters.

[0064] Furthermore, according to the optimized perforation fitness set and in combination with the plurality of fracture distribution information, an integrated analysis of the fracturing fluid injection pressure and the proppant injection parameters is performed, and the method of the present application includes:

[0065] S4-1: According to the plurality of fracture distribution information, a plurality of fracturing fluid injection pressures and a plurality of proppant injection parameters are obtained by classification, wherein the plurality of proppant injection parameters include a plurality of proppant particle size information and a plurality of proppant injection amounts.

[0066] Further, according to the plurality of fracture distribution information, a plurality of fracturing fluid injection pressures and a plurality of proppant injection parameters are obtained by classification, and the method of the present application includes:

[0067] S4-11: Acquire a sample crack distribution information set, wherein the sample crack distribution information set includes a sample crack depth information set and a sample crack width information set.

[0068] S4-12: According to the sample fracture depth information set and the sample fracture width information set, and according to the fracturing history data, the corresponding sample fracturing fluid injection pressure set, the sample proppant particle size information set and the sample proppant injection amount set are annotated.

[0069] S4-13: Based on the decision tree, the sample fracture depth information set and the sample fracture width information set are used as decision classification inputs, and the sample fracturing fluid injection pressure set, the sample proppant particle size information set and the sample proppant injection amount set are used as decision classification outputs to construct a fracturing classifier.

[0070] S4-14: Using the fracturing classifier, classify the fracture depth information and fracture width information inputs in the plurality of fracture distribution information to obtain a plurality of fracturing fluid injection pressures and a plurality of proppant injection parameters.

[0071] S4-2: According to the multiple optimized puncturing fitnesses in the optimized puncturing fitness set, multiple integrated weights are allocated.

[0072] S4-3: Perform weighted integrated calculation on the multiple fracturing fluid injection pressures and the multiple proppant injection parameters according to the multiple integrated weights to obtain the integrated fracturing fluid injection pressure, integrated proppant particle size information and integrated proppant injection amount as integrated proppant injection parameters.

[0073] Specifically, the fracturing fluid injection pressure refers to the pressure used when injecting fracturing fluid during the oil and gas production process. Appropriate pressure can make the fracturing fluid effectively expand the cracks and improve the efficiency of oil and gas production. The proppant injection parameters include proppant particle size information and proppant injection amount. The proppant is used to keep the cracks open so that the oil and gas can flow smoothly. The integrated fracturing fluid injection pressure takes into account the adaptability of different crack conditions and electro-perforation parameters to achieve the best oil and gas production effect. The integrated proppant injection parameters are used to ensure the stable support of the cracks and the efficient flow of oil and gas.

[0074] Execution steps: The optimized drilling fitness set reflects the pros and cons of different electric drilling control parameters, while the fracture distribution information describes the state of the fractures in the formation in detail. According to the fracture depth and width in the fracture distribution information, the fracturing fluid injection pressure range under different fracture conditions is preliminarily determined. Generally speaking, for deeper and wider fractures, higher fracturing fluid injection pressure is required. According to the depth and width of the fractures, the injection pressure of the fracturing fluid (the main function of the fracturing fluid is to transfer the high pressure formed by the ground equipment to the formation, so that the formation breaks to form cracks and transports proppant along the cracks) and the particle size and injection amount of the proppant (proppant is a solid particle filled in the crack to prevent the crack from closing) are classified to obtain the integrated fracturing fluid injection pressure and integrated proppant injection parameters.

[0075] Preferably, according to the optimized drilling fitness set and in combination with the multiple fracture distribution information, an integrated analysis of fracturing fluid injection pressure and proppant injection parameters is performed. Furthermore, the fracturing fluid injection pressure refers to the pressure used when injecting fracturing fluid into the formation during oil and gas production. Suitable pressure can make the fracturing fluid effectively expand the fractures and improve the oil and gas production efficiency; the proppant injection parameters include proppant particle size information and proppant injection amount. The proppant particle size determines the effect of supporting the fracture and the size of the channel for oil and gas flow, and the proppant injection amount affects the support stability of the fracture and the oil and gas flow capacity; the integrated proppant injection parameters include integrated proppant particle size information and integrated proppant injection amount, which is a comprehensive optimal parameter combination obtained by weighted integrated calculation of multiple proppant injection parameters; the integrated fracturing fluid injection pressure refers to the comprehensive optimal fracturing fluid injection pressure obtained by weighted integrated calculation of the fracturing fluid injection pressures corresponding to multiple fracture distribution information.

[0076] Execution steps: It should be noted that fracturing fluid is used as working fluid during fracturing transformation of oil and gas layers. Its main function is to transfer the high pressure formed by ground equipment to the formation, so that the formation breaks to form cracks and transport proppant along the cracks. It can be seen that the integrated proppant injection parameters and the integrated fracturing fluid injection pressure are controlled in a joint manner in terms of timing control. According to the classification of multiple fracture distribution information, multiple fracturing fluid injection pressures and multiple proppant injection parameters are obtained. Specifically, by establishing a relationship fitting between fracture characteristics and fracturing fluid injection pressure and proppant injection parameters, different fracture depth and width combinations are set according to historical data and the fitting relationship to determine the corresponding fracturing fluid injection pressure range and proppant injection parameter range. For verification, the fracture depth of fracture distribution one is 10 The fracture distribution of the first crack is 15 meters deep and 4 centimeters wide. The corresponding fracturing fluid injection pressure is between 15MPa and 18MPa, the proppant particle size is between 1mm and 1.2mm, and the proppant injection amount is 70kg per cubic meter of fracture volume. The fracture distribution of the second crack is 15 meters deep and 4 centimeters wide. The corresponding fracturing fluid injection pressure is between 15MPa and 18MPa, the proppant particle size is between 1mm and 1.5mm, and the proppant injection amount is 70kg per cubic meter of fracture volume. The fracture distribution of the third crack is 8 meters deep and 2 centimeters wide. The corresponding fracturing fluid injection pressure is between 10MPa and 12MPa, the proppant particle size is between 0.5mm and 1mm, and the proppant injection amount is 50kg per cubic meter of fracture volume. 0 kg; multiple integrated weights are obtained according to the multiple optimized drilling fitness distributions in the optimized drilling fitness set. Specifically, the weight is determined according to the fitness. The higher the fitness, the larger the corresponding weight. For example, assuming that the optimized drilling fitnesses corresponding to the three fracture distribution information are 0.8, 0.7 and 0.6 respectively, after normalizing the sum of the fitnesses, the integrated weights corresponding to the three fracture distribution information are 0.4, 0.35 and 0.25 respectively; according to the multiple integrated weights, multiple fracturing fluid injection pressures and multiple proppant injection parameters are weighted integrated and calculated. Specifically, for the fracturing fluid injection pressure, the fracturing fluid injection pressure range corresponding to each fracture distribution information is multiplied by its corresponding integrated weight, and then the sum is calculated to obtain the integrated pressure. The range of fracturing fluid injection pressure, for example, for the above three fracture distribution information, the integrated fracturing fluid injection pressure is between (12MPa×0.4+15MPa×0.35+10MPa×0.25) and (15MPa×0.4+18MPa×0.35+12MPa×0.25); for proppant injection parameters, weighted calculation is also performed to obtain integrated proppant particle size information and integrated proppant injection amount; for example, the integrated proppant particle size is between (0.8mm×0.4+1mm×0.35+0.5mm×0.25) and (1.2mm×0.4+1.5mm×0.35+1mm×0.25), and the integrated proppant injection amount is between (60kg×0.4+70kg×0.35+50 kg×0.25) per cubic meter of fracture volume. Through the above steps, the fracture distribution information and the optimized drilling adaptability are comprehensively considered to achieve the integrated analysis of the fracturing fluid injection pressure and proppant injection parameters, and obtain the integrated fracturing fluid injection pressure and integrated proppant injection parameters that are more suitable for the target formation.

[0077] Preferably, based on the multiple fracture distribution information, multiple fracturing fluid injection pressures and multiple proppant injection parameters are classified and obtained. Furthermore, the sample fracture distribution information set refers to a set of various fracture distribution conditions collected from historical data, including a sample fracture depth information set and a sample fracture width information set; the sample fracturing fluid injection pressure set is used to characterize the set of fracturing fluid injection pressures corresponding to different sample fracture distributions; the sample proppant particle size information set is used to characterize the set of proppant particle sizes corresponding to different sample fracture distributions; the sample proppant injection amount set is used to characterize the set of proppant injection amounts corresponding to different sample fracture distributions.

[0078] Execution steps: obtain a sample fracture distribution information set, which includes various combinations of fracture depths and widths in historical data. For example, the sample fracture depth information set includes different fracture depth values ​​such as 5 meters, 8 meters, and 10 meters, and the sample fracture width information set includes different fracture width values ​​such as 2 centimeters, 3 centimeters, and 4 centimeters; then, based on the sample fracture depth information set and the sample fracture width information set, mark the historical fracturing data and determine the corresponding fracturing fluid injection pressure, proppant particle size, and injection amount from past fracturing projects according to different fracture depths and widths. Mark them to form a sample fracturing fluid injection pressure set, a sample proppant particle size information set, and a sample proppant injection amount set. For example, when the fracture depth is 8 meters and the width is 3 centimeters, the corresponding fracturing fluid injection pressure in the historical data is 15 MPa, the proppant particle size is 0.8 mm, and the proppant injection amount is 200 g. The input is 60 kg per cubic meter of fracture volume, and the above values ​​are added to the corresponding sets respectively; then, based on the decision tree, the sample fracture depth information set and the sample fracture width information set are used as the decision classification input, and the sample fracturing fluid injection pressure set, the sample proppant particle size information set and the sample proppant injection amount set are used as the decision classification output to construct a fracturing classifier. The decision tree algorithm can automatically learn and determine the classification rules of the best fracturing fluid injection pressure and proppant injection parameters according to different fracture depth and width characteristics; then, using the constructed fracturing classifier, the fracture depth information and fracture width information in the current multiple fracture distribution information are input and classified, and finally, this information is input into the fracturing classifier. The classifier outputs the corresponding fracturing fluid injection pressure and proppant injection parameters according to the previously learned rules, thereby obtaining multiple fracturing fluid injection pressures and multiple proppant injection parameters. Through the decision tree algorithm, the process of automatically determining the fracturing operation parameters according to the fracture characteristics is realized. The classifier can output more accurate and reasonable fracturing fluid injection pressure and proppant injection parameters, speed up the decision-making speed, and improve the efficiency and success rate of the fracturing operation.

[0079] S5: taking the optimal electro-perforation control parameter in the optimized electro-perforation control parameter set, combined with the integrated fracturing fluid injection pressure and the integrated proppant injection parameter, as the electro-perforation fracturing optimization result.

[0080] Specifically, the optimal electro-perforating control parameter is the one with the best comprehensive performance in the set of optimized electro-perforating control parameters; the electro-perforating fracturing optimization result is an optimization scheme for electro-perforating fracturing in oil and gas production.

[0081] Execution steps: Determine the optimal electro-perforation control parameter from the set of optimized electro-perforation control parameters. Specifically, the optimal electro-perforation control parameter is determined by comparing the performance of each parameter in terms of geological fitness and oil and gas fitness. For example, if the geological fitness and oil and gas fitness of a parameter obtained in the electro-perforation analysis are both very high, and it always performs well in the iterative optimization process, then it can be determined as the optimal electro-perforation control parameter, and the optimal electro-perforation control parameter is combined with the integrated fracturing fluid injection pressure and the integrated proppant injection parameter, and then weighted according to multiple optimized fitness as the electro-perforation fracturing optimization result of post-perforation fracturing. Through the above steps, in order to adapt to different geological and oil and gas conditions, by adjusting the weights of parameters and optimized fitness, the scientific nature of the selection of electro-perforation control parameters is ensured.

[0082] In summary, the beneficial effects of the embodiments of the present application are:

[0083] 1. By collecting geological information of the target formation and optimizing the control parameters of the electro-perforation, the most suitable combination of perforation parameters for the formation can be found, making the electro-perforation process more efficient and forming a fracture network in the target formation that is more conducive to the flow of oil and gas.

[0084] 2. Through the comprehensive collection and analysis of geological information and the optimization of electric drilling control parameters, personalized mining plans can be formulated for different formation conditions, so that oil and gas mining is no longer restricted.

[0085] 3. The fracturing fluid injection pressure and proppant injection parameters obtained through integrated analysis can better adapt to the characteristics of the fracture, ensure that the proppant can effectively support the fracture and improve the stability of the oil and gas flow channel.

[0086] 4. Based on the adoption of multiple first perforation fitness, multiple first cluster head electric perforation control parameters are obtained, and other first electric perforation control parameters are clustered to obtain multiple electric perforation control parameter clusters; the cluster head electric perforation control parameters in each electric perforation control parameter cluster are used as the adjustment direction, and other electric perforation control parameters in the electric perforation control parameter cluster are adjusted and updated in the electric perforation control parameter space; the adjusted and updated electric perforation control parameters are combined with the formation geological information to perform electric perforation analysis, and the updated perforation fitness is calculated and obtained, and the electric perforation control parameter with the largest perforation fitness is updated as the cluster head electric perforation control parameter to obtain multiple updated electric perforation control parameter clusters; iterative optimization is continued until convergence, and the electric perforation control parameter cluster with the largest sum of perforation fitness is output as the optimized electric perforation control parameter set. In the above steps, the physical process of electric perforation is considered, and combined with the geological information and the characteristics of the oil and gas rich layer, through continuous optimization and iteration, the changes in geological conditions and oil and gas conditions are adapted to provide support for efficient and stable oil and gas production.

[0087] Embodiment 2

[0088] Based on the same inventive concept as the electric perforation fracturing optimization method for oil and gas production in the above-mentioned embodiment, Figure 2 As shown, an embodiment of the present application provides an electric perforation fracturing optimization system for oil and gas production, wherein the system comprises:

[0089] The information acquisition module M100 is used to acquire the stratigraphic geological information of the target stratum to be exploited for oil and gas, wherein the stratigraphic geological information includes rock formation characteristic information and oil and gas characteristic information;

[0090] The parameter optimization module M200 is used to optimize the electric drilling control parameters according to the formation geological information, and obtain an optimized electric drilling control parameter set and a corresponding optimized drilling fitness set, wherein the optimization of the electric drilling control parameters includes maximizing the geological fitness and the oil and gas fitness;

[0091] A fracture distribution module M300 is used to generate a perforation fracture distribution of the target formation according to the optimized electro-perforation control parameter set combined with the rock formation characteristic information, and obtain a plurality of fracture distribution information, each of which includes fracture depth information and fracture width information;

[0092] An integrated analysis module M400 is used to perform integrated analysis of fracturing fluid injection pressure and proppant injection parameters according to the optimized perforation fitness set and in combination with the plurality of fracture distribution information, so as to obtain integrated fracturing fluid injection pressure and integrated proppant injection parameters;

[0093] The result determination module M500 is used to combine the optimal electro-perforation control parameters in the optimized electro-perforation control parameter set with the integrated fracturing fluid injection pressure and the integrated proppant injection parameters as the electro-perforation fracturing optimization result.

[0094] Furthermore, the information collection module M100 is used to perform the following method:

[0095] Collect rock formation characteristic information of target strata for oil and gas extraction;

[0096] Collecting oil and gas characteristic information of the target formation;

[0097] The rock formation characteristic information and the oil and gas characteristic information are integrated to obtain the formation geological information.

[0098] Furthermore, the parameter optimization module M200 is used to perform the following method:

[0099] Acquire an electric perforation control parameter space for electric perforation fracturing;

[0100] Randomly generating a plurality of first electroporation control parameters in the electroporation control parameter space;

[0101] According to the plurality of first electric perforation control parameters, combined with the formation geological information, electric perforation analysis is performed to obtain a plurality of first geological suitability and a plurality of first oil and gas suitability, and a plurality of first perforation suitability is obtained by weighted calculation;

[0102] The multiple first electro-perforation control parameters are clustered according to the multiple first perforation fitnesses, and iterative optimization is performed to obtain an electro-perforation control parameter cluster with the maximum sum of perforation fitnesses as an optimized electro-perforation control parameter set.

[0103] Furthermore, the parameter optimization module M200 is also used to execute the following method:

[0104] According to the historical data of electric drilling and fracturing, the sample electric drilling control parameter set and the sample bottom geological information set are collected, and according to the stability of the rock formation after electric drilling and the depth of the oil and gas rich layer, the sample geological fitness set and the sample oil and gas fitness set are marked;

[0105] Using the sample electro-perforation control parameter set, the sample bottom geological information set, the sample geological fitness set and the sample oil and gas fitness set to train an electro-perforation analyzer;

[0106] The electro-perforation analyzer is used to perform electro-perforation analysis on the formation geological information in combination with the plurality of first electro-perforation control parameters to obtain a plurality of first geological suitabilities and a plurality of first oil and gas suitabilities.

[0107] Furthermore, the parameter optimization module M200 is also used to execute the following method:

[0108] According to the plurality of first perforation fitnesses, a plurality of first cluster head electro-perforation control parameters are obtained by dividing, and the other first electro-perforation control parameters are clustered to obtain a plurality of electro-perforation control parameter clusters;

[0109] Taking the cluster head electroporation control parameter in each electroporation control parameter cluster as the adjustment direction, in the electroporation control parameter space, adjusting and updating other electroporation control parameters in the electroporation control parameter cluster;

[0110] Conducting electric drilling analysis on the adjusted and updated electric drilling control parameters in combination with the formation geological information, calculating and obtaining updated drilling fitness, updating the electric drilling control parameter with the largest drilling fitness as the cluster head electric drilling control parameter, and obtaining multiple updated electric drilling control parameter clusters;

[0111] Continue iterative optimization until convergence, and output the electroporation control parameter cluster with the largest sum of pore fitness as the optimized electroporation control parameter set.

[0112] Furthermore, the crack distribution module M300 is used to perform the following method:

[0113] According to the historical data of electric drilling and fracturing, a set of sample electric drilling control parameters and a set of sample rock formation characteristic information are collected, and according to the depth and width of rock formation cracks in the drilling and fracturing, the sample crack depth information and the sample crack width information are marked as a set of sample crack distribution information;

[0114] Using the sample electric drilling control parameter set, the sample rock formation characteristic information set, and the sample fracture distribution information set to train a drilling fracture generator;

[0115] The perforation fracture generator is used to respectively combine the multiple optimized electric perforation control parameters in the optimized electric perforation control parameter set with the rock formation characteristic information to generate perforation fracture distribution of the target formation and obtain multiple fracture distribution information.

[0116] Furthermore, the integrated analysis module M400 is used to perform the following method:

[0117] According to the plurality of fracture distribution information, a plurality of fracturing fluid injection pressures and a plurality of proppant injection parameters are obtained by classification, wherein the plurality of proppant injection parameters include a plurality of proppant particle size information and a plurality of proppant injection amounts;

[0118] According to a plurality of optimized puncturing fitnesses in the optimized puncturing fitness set, a plurality of integrated weights are allocated;

[0119] According to the multiple integrated weights, the multiple fracturing fluid injection pressures and the multiple proppant injection parameters are weighted integrated and calculated to obtain the integrated fracturing fluid injection pressure, the integrated proppant particle size information and the integrated proppant injection amount as the integrated proppant injection parameters.

[0120] Furthermore, the integrated analysis module M400 is also used to perform the following method:

[0121] Acquire a sample crack distribution information set, wherein the sample crack distribution information set includes a sample crack depth information set and a sample crack width information set;

[0122] According to the sample fracture depth information set and the sample fracture width information set, and according to the fracturing history data, the corresponding sample fracturing fluid injection pressure set, the sample proppant particle size information set and the sample proppant injection amount set are annotated;

[0123] Based on the decision tree, the sample fracture depth information set and the sample fracture width information set are used as decision classification inputs, and the sample fracturing fluid injection pressure set, the sample proppant particle size information set and the sample proppant injection amount set are used as decision classification outputs to construct a fracturing classifier;

[0124] The fracturing classifier is used to classify the fracture depth information and fracture width information in the plurality of fracture distribution information, and obtain a plurality of fracturing fluid injection pressures and a plurality of proppant injection parameters.

[0125] In summary, any step can be stored as a computer instruction or program in an unlimited computer memory, and can be called and recognized by an unlimited computer processor, and no unnecessary restrictions are made here.

[0126] Furthermore, the above-mentioned technical scheme only reflects the preferred technical scheme of the technical scheme of the embodiment of the present application. Some changes that may be made to some parts thereof by technicians in this technical field all reflect the novel principles of the embodiment of the present application. Obviously, technicians in this field can make various changes and modifications to the present application without departing from the scope of the present application.

Claims

1. An electro-perforation fracturing optimization method for oil and gas production, characterized in that: The method comprises: Collecting stratigraphic geological information of a target stratum to be exploited for oil and gas, wherein the stratigraphic geological information includes rock stratum characteristic information and oil and gas characteristic information; According to the formation geological information, the electric drilling control parameters are optimized to obtain an optimized electric drilling control parameter set and a corresponding optimized drilling fitness set, wherein the optimization of the electric drilling control parameters includes maximizing the geological fitness and the oil and gas fitness; According to the optimized electro-perforation control parameter set combined with the rock formation characteristic information, the perforation fracture distribution of the target formation is generated to obtain a plurality of fracture distribution information, each of which includes fracture depth information and fracture width information; According to the optimized perforation fitness set, combined with the plurality of fracture distribution information, an integrated analysis of the fracturing fluid injection pressure and the proppant injection parameters is performed to obtain an integrated fracturing fluid injection pressure and an integrated proppant injection parameter; The optimal electro-perforation control parameters in the optimized electro-perforation control parameter set are combined with the integrated fracturing fluid injection pressure and the integrated proppant injection parameters to be used as the electro-perforation fracturing optimization result.

2. The electric drilling and fracturing optimization method for oil and gas production according to claim 1, characterized in that: Collect geological information of the target strata for oil and gas production, including: Collect rock formation characteristic information of target strata for oil and gas extraction; Collecting oil and gas characteristic information of the target formation; The rock formation characteristic information and the oil and gas characteristic information are integrated to obtain the formation geological information.

3. The electric drilling and fracturing optimization method for oil and gas production according to claim 1, characterized in that: According to the formation geological information, the electric drilling control parameters are optimized to obtain an optimized electric drilling control parameter set and a corresponding optimized drilling fitness set, including: Acquire an electric perforation control parameter space for electric perforation fracturing; Randomly generating a plurality of first electroporation control parameters in the electroporation control parameter space; According to the plurality of first electric perforation control parameters, combined with the formation geological information, electric perforation analysis is performed to obtain a plurality of first geological suitability and a plurality of first oil and gas suitability, and a plurality of first perforation suitabilities are obtained by weighted calculation; The multiple first electro-perforation control parameters are clustered according to the multiple first perforation fitnesses, and iterative optimization is performed to obtain an electro-perforation control parameter cluster with the maximum sum of perforation fitnesses as an optimized electro-perforation control parameter set.

4. The electric drilling and fracturing optimization method for oil and gas production according to claim 3, characterized in that: According to the plurality of first electro-perforation control parameters, combined with the formation geological information, electro-perforation analysis is performed, including: According to the historical data of electric drilling and fracturing, the sample electric drilling control parameter set and the sample bottom geological information set are collected, and according to the stability of the rock formation after electric drilling and the depth of the oil and gas rich layer, the sample geological fitness set and the sample oil and gas fitness set are marked; Using the sample electro-perforation control parameter set, the sample bottom geological information set, the sample geological fitness set and the sample oil and gas fitness set to train an electro-perforation analyzer; The electro-perforation analyzer is used to perform electro-perforation analysis on the formation geological information in combination with the plurality of first electro-perforation control parameters to obtain a plurality of first geological suitabilities and a plurality of first oil and gas suitabilities.

5. The electric drilling and fracturing optimization method for oil and gas production according to claim 3, characterized in that: According to the plurality of first perforation fitnesses, the plurality of first electroperforation control parameters are clustered and iteratively optimized, including: According to the plurality of first puncturing fitnesses, a plurality of first cluster head electro-puncturing control parameters are obtained by dividing, and the other first electro-puncturing control parameters are clustered to obtain a plurality of electro-puncturing control parameter clusters; Taking the cluster head electroporation control parameter in each electroporation control parameter cluster as the adjustment direction, in the electroporation control parameter space, adjusting and updating other electroporation control parameters in the electroporation control parameter cluster; Conducting electric drilling analysis on the adjusted and updated electric drilling control parameters in combination with the formation geological information, calculating and obtaining updated drilling fitness, updating the electric drilling control parameter with the largest drilling fitness as the cluster head electric drilling control parameter, and obtaining multiple updated electric drilling control parameter clusters; Continue iterative optimization until convergence, and output the electroporation control parameter cluster with the largest sum of pore fitness as the optimized electroporation control parameter set.

6. The electric drilling and fracturing optimization method for oil and gas production according to claim 1, characterized in that: The method of generating a perforation fracture distribution of the target formation according to the optimized electro-perforation control parameter set combined with the rock formation characteristic information includes: According to the historical data of electric drilling and fracturing, a set of sample electric drilling control parameters and a set of sample rock formation characteristic information are collected, and according to the depth and width of rock formation cracks in the drilling and fracturing, the sample crack depth information and the sample crack width information are marked as a set of sample crack distribution information; Using the sample electric drilling control parameter set, the sample rock formation characteristic information set, and the sample fracture distribution information set to train a drilling fracture generator; The perforation fracture generator is used to respectively combine the multiple optimized electric perforation control parameters in the optimized electric perforation control parameter set with the rock formation characteristic information to generate perforation fracture distribution of the target formation and obtain multiple fracture distribution information.

7. The electric drilling and fracturing optimization method for oil and gas production according to claim 1, characterized in that: According to the optimized perforation fitness set and in combination with the plurality of fracture distribution information, an integrated analysis of the fracturing fluid injection pressure and the proppant injection parameters is performed, including: According to the plurality of fracture distribution information, a plurality of fracturing fluid injection pressures and a plurality of proppant injection parameters are obtained by classification, wherein the plurality of proppant injection parameters include a plurality of proppant particle size information and a plurality of proppant injection amounts; According to a plurality of optimized puncture fitnesses in the optimized puncture fitness set, a plurality of integrated weights are allocated; According to the multiple integrated weights, the multiple fracturing fluid injection pressures and the multiple proppant injection parameters are weighted integrated and calculated to obtain the integrated fracturing fluid injection pressure, the integrated proppant particle size information and the integrated proppant injection amount as the integrated proppant injection parameters.

8. The electric drilling and fracturing optimization method for oil and gas production according to claim 7, characterized in that: According to the plurality of fracture distribution information, a plurality of fracturing fluid injection pressures and a plurality of proppant injection parameters are obtained by classification, including: Acquire a sample crack distribution information set, wherein the sample crack distribution information set includes a sample crack depth information set and a sample crack width information set; According to the sample fracture depth information set and the sample fracture width information set, and according to the fracturing history data, the corresponding sample fracturing fluid injection pressure set, the sample proppant particle size information set and the sample proppant injection amount set are annotated; Based on the decision tree, the sample fracture depth information set and the sample fracture width information set are used as decision classification inputs, and the sample fracturing fluid injection pressure set, the sample proppant particle size information set and the sample proppant injection amount set are used as decision classification outputs to construct a fracturing classifier; The fracturing classifier is used to classify the fracture depth information and fracture width information in the plurality of fracture distribution information, and obtain a plurality of fracturing fluid injection pressures and a plurality of proppant injection parameters.

9. An electric drilling and fracturing optimization system for oil and gas production, characterized in that: A method for optimizing electric perforation and fracturing for oil and gas production according to any one of claims 1 to 8, the system comprising: An information collection module, used to collect stratum geological information of a target stratum to be exploited for oil and gas, wherein the stratum geological information includes rock stratum characteristic information and oil and gas characteristic information; A parameter optimization module, used to optimize the electric drilling control parameters according to the formation geological information, and obtain an optimized electric drilling control parameter set and a corresponding optimized drilling fitness set, wherein the optimization of the electric drilling control parameters includes maximizing the geological fitness and the oil and gas fitness; A fracture distribution module, used to generate the perforation fracture distribution of the target formation according to the optimized electro-perforation control parameter set combined with the rock formation characteristic information, and obtain a plurality of fracture distribution information, each of which includes fracture depth information and fracture width information; An integrated analysis module, configured to perform integrated analysis of the fracturing fluid injection pressure and the proppant injection parameters according to the optimized perforation fitness set and in combination with the plurality of fracture distribution information, to obtain an integrated fracturing fluid injection pressure and an integrated proppant injection parameter; The result determination module is used to combine the optimal electro-perforation control parameter in the optimized electro-perforation control parameter set with the integrated fracturing fluid injection pressure and the integrated proppant injection parameter as the electro-perforation fracturing optimization result.

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