An oil well comprehensive evaluation method, device, equipment and storage medium

Abstract

The application discloses an oil well comprehensive evaluation method, device, equipment and storage medium. An oil well comprehensive evaluation method, characterized in that, comprising: obtaining oil well evaluation influence factors corresponding to a target oil well, the oil well evaluation influence factors including at least two of the number of evaluation indexes, the oil well exploitation stage, geological condition information and production management demand information; determining applicable data of various pre-configured oil well evaluation modes based on each oil well evaluation influence factor, the applicable data representing the matching degree of the oil well evaluation mode and the oil well evaluation influence factor; determining an oil well evaluation strategy based on the applicable data of each oil well evaluation influence factor for each oil well evaluation mode, the oil well evaluation strategy including at least one oil well evaluation mode; and performing evaluation processing on the target oil well based on the oil well evaluation strategy to obtain an evaluation result of the target oil well, thereby improving the accuracy of the evaluation result of the target oil well and the utilization rate of the evaluation indexes.

Description

Technical Field

[0001] This invention relates to the field of oilfield mechanical oil production technology, and in particular to a comprehensive evaluation method, apparatus, equipment and storage medium for oil wells. Background Technology

[0002] In the process of oilfield development, comprehensive evaluation of oil wells to determine their health is crucial. Currently, the comprehensive evaluation of oil wells faces challenges such as low utilization of production data and low accuracy of evaluation results. Summary of the Invention

[0003] This invention provides a method, apparatus, equipment, and storage medium for comprehensive evaluation of oil wells, in order to solve the problems of low utilization rate of oil well production data and low accuracy of oil well evaluation results in the prior art.

[0004] According to one aspect of the present invention, a comprehensive evaluation method for oil wells is provided, the method comprising:

[0005] Obtain the influencing factors for the target oil well evaluation. The influencing factors for oil well evaluation include at least two of the following: the number of evaluation indicators, the oil well development stage, geological condition information, and production management requirements information.

[0006] Based on each oil well evaluation influencing factor, pre-configured applicable data for various oil well evaluation methods are determined. The applicable data characterizes the matching degree between the oil well evaluation method and the oil well evaluation influencing factor.

[0007] Based on the applicable data of each oil well evaluation method for each oil well evaluation influencing factors, an oil well evaluation strategy is determined, and the oil well evaluation strategy includes at least one oil well evaluation method.

[0008] The target oil well is evaluated based on the oil well evaluation strategy to obtain the evaluation results of the target oil well.

[0009] According to another aspect of the present invention, an oil well comprehensive evaluation device is provided, the device comprising:

[0010] The oil well evaluation influencing factor acquisition module is used to acquire the oil well evaluation influencing factors corresponding to the target oil well. The oil well evaluation influencing factors include at least two of the following: the number of evaluation indicators, the oil well development stage, geological condition information, and production management demand information.

[0011] The applicable data determination module is used to determine the applicable data for various pre-configured oil well evaluation methods based on each oil well evaluation influencing factor. The applicable data characterizes the matching degree between the oil well evaluation method and the oil well evaluation influencing factor.

[0012] The oil well evaluation strategy determination module is used to determine the oil well evaluation strategy based on the applicable data of each oil well evaluation method for each oil well evaluation influencing factor. The oil well evaluation strategy includes at least one oil well evaluation method.

[0013] The evaluation result acquisition module is used to evaluate the target oil well based on the oil well evaluation strategy and obtain the evaluation result of the target oil well.

[0014] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising:

[0015] At least one processor; and

[0016] A memory that is communicatively connected to at least one processor; wherein,

[0017] The memory stores a computer program that can be executed by at least one processor, such that the at least one processor is able to execute the oil well comprehensive evaluation method of any embodiment of the present invention.

[0018] According to another aspect of the present invention, a computer-readable storage medium is provided, which stores computer instructions for causing a processor to execute and implement the oil well comprehensive evaluation method of any embodiment of the present invention.

[0019] The technical solution of this invention obtains the oil well evaluation influencing factors corresponding to the target oil well. These factors include at least two of the following: the number of evaluation indicators, the oil well development stage, geological conditions, and production management requirements. This allows for the acquisition of oil well evaluation influencing factors from multiple dimensions, providing comprehensive data support for subsequent task analysis and processing. Based on each oil well evaluation influencing factor, pre-configured applicable data for various oil well evaluation methods is determined. This applicable data characterizes the matching degree between the oil well evaluation method and the oil well evaluation influencing factors, improving the accuracy of the applicable data and providing a basis for subsequent task analysis and processing. Based on the applicable data for each oil well evaluation influencing factor, an oil well evaluation strategy is determined. This strategy includes at least one oil well evaluation method, improving the accuracy of the strategy determination and thus improving the accuracy of the target oil well evaluation results. The target oil well is then evaluated based on the evaluation strategy to obtain the evaluation results, achieving a comprehensive evaluation of the target oil well. This solves the problems of low utilization rate of oil well production data and low accuracy of oil well evaluation results in the prior art, improving both the utilization rate of oil well production data and the accuracy of oil well evaluation results.

[0020] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0021] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0022] Figure 1 This is a flowchart of a comprehensive evaluation method for oil wells provided in Embodiment 1 of the present invention;

[0023] Figure 2 This is a flowchart of a comprehensive evaluation method for oil wells provided in Embodiment 2 of the present invention;

[0024] Figure 3 This is a schematic diagram of an oil well evaluation method selection method provided in an embodiment of the present invention;

[0025] Figure 4 This is a schematic diagram of the structure of an oil well comprehensive evaluation device provided in Embodiment 3 of the present invention;

[0026] Figure 5 This is a schematic diagram of the structure of an electronic device provided in Embodiment 4 of the present invention. Detailed Implementation

[0027] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0028] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0029] Oil well evaluation methods include, but are not limited to, neural network evaluation, grey relational analysis, and weighted hierarchical analysis. Neural network evaluation uses neural network models to evaluate oil wells. When an oilfield accumulates a large amount of high-quality evaluation index data covering various operating conditions and different time spans, neural network evaluation has significant advantages. Specifically, the neural network model can extract potential patterns from massive and complex evaluation index data, accurately capture the complex relationship between each evaluation index data and the health of the oil well, has strong nonlinear fitting capabilities, and provides high accuracy in oil well evaluation results. Furthermore, it can predict the future health of oil wells based on a trained neural network model, providing data support for oil well maintenance. However, neural network evaluation has certain limitations, including: reliance on a large amount of high-quality evaluation index data; complex neural network model structure selection and training; and poor interpretability of evaluation results.

[0030] Grey relational analysis calculates the correlation degree between oil wells to obtain evaluation results. The calculation process is simple, with low requirements on the distribution and quantity of evaluation index data. It can effectively handle small sample sizes and information-poor problems. Grey relational analysis has significant advantages when the number of evaluation indicators is small, information is incomplete, and uncertain, such as when evaluation index data for oil wells in remote areas is limited. However, the limitation of grey relational analysis lies in its inability to deeply explore the complex nonlinear relationships between evaluation index data, leading to low accuracy in the obtained oil well evaluation results.

[0031] The Weighted Analytic Hierarchy Process (WAHP) is a method for evaluating oil wells that combines the Analytic Hierarchy Process (AHP) with a weighted comprehensive evaluation method. This method can comprehensively consider multiple influencing factors in oil well evaluation. It offers several advantages when the number of evaluation indicators is limited and subjective experience needs to be considered. Specifically, it decomposes the comprehensive evaluation of oil wells into target, criterion, and indicator layers, comprehensively considering various influencing factors to ensure rigorous and scientific evaluation results; the weights are reasonably determined, using expert experience to construct a judgment matrix to calculate weights, aligning with actual production needs; the calculation is simple and the results are intuitive, obtaining a comprehensive score through weighted summation, which, combined with preset standards, allows for a direct assessment of the oil well's health, facilitating decision-making; and it has wide applicability, not relying on large amounts of complex data, and is applicable to both new and old oilfields. The limitations of the WAHP lie in the significant influence of subjective factors. During the evaluation process, differences in expert experience and preferences may lead to inaccurate determination of the weights in the judgment matrix and evaluation indicator data, thus affecting the evaluation results. Furthermore, the selection of evaluation indicators is difficult and requires adjustment and updating based on changes in extraction technology and the environment.

[0032] Different oil well evaluation methods have different advantages and disadvantages, and are suitable for different oil well evaluation needs. The accuracy of the selection of the oil well evaluation method affects the accuracy of the oil well evaluation. To address the above issues, this disclosure provides a comprehensive oil well evaluation method.

[0033] Example 1

[0034] Figure 1 This is a flowchart of an oil well comprehensive evaluation method provided in Embodiment 1 of the present invention. This embodiment is applicable to situations requiring improved accuracy of oil well evaluation results. The method can be executed by an oil well comprehensive evaluation device, which can be implemented in hardware and / or software. This device can be configured in the electronic equipment provided in this embodiment of the invention. The electronic equipment can be a server, computer, or mobile terminal, such as a mobile phone or tablet computer. Figure 1 As shown, the method includes:

[0035] S110. Obtain the oil well evaluation influencing factors corresponding to the target oil well. The oil well evaluation influencing factors include at least two of the following: the number of evaluation indicators, the oil well development stage, geological condition information, and production management requirements information.

[0036] In this embodiment, the factors influencing oil well evaluation are those that affect the selection of the oil well evaluation method when comprehensively evaluating the target oil well. These include at least two of the following: the number of evaluation indicators, the oil well production stage, geological condition information, and production management requirements. Evaluation indicators are parameters used to measure the production status and performance of the target oil well, including but not limited to the operating parameters of the pumping equipment, the production information of the target oil well, and the dynamic fluid level depth. The operating parameters of the pumping equipment include balance, three-phase voltage data, three-phase current data, power factor, unit pump load, and displacement information. Balance is an indicator reflecting the uniformity of load distribution during the upper and lower strokes of the pumping equipment during operation. It can be measured using a dynamometer, for example, by measuring the dynamometer diagram and calculating the ratio between the area of ​​the upper stroke and the area of ​​the lower stroke in the dynamometer diagram to obtain the balance of the pumping equipment. Three-phase voltage data can be measured, for example, using a voltmeter. Three-phase current data can be measured, for example, using an ammeter, including but not limited to clamp-on ammeters. The power factor characterizes the efficiency of an oil pumping unit's use of electrical energy. It can be obtained by the ratio of the active power to the total power of the pumping unit. The active power of the pumping unit can be measured, for example, using a wattmeter. The total power of the pumping unit can be calculated using three-phase voltage and current data. The load per pumping cycle is the load corresponding to the various forces borne by the suspension point during one reciprocating motion of the pumping unit. This can be measured using sensors, for example, by installing load sensors at the suspension point of the pumping unit to measure the load per pumping cycle. Production information reflects the production of the target oil well, including but not limited to daily liquid production and daily oil production. This can be measured using a flow meter. For example, by separating oil, water, and gas using a separator, and using a flow meter to measure the oil production of the target oil well over a preset time, the daily oil production of the target oil well can be obtained. Similarly, the daily water production of the target oil well can be calculated. The sum of the daily oil production and daily water production of the target oil well can be used to obtain the daily liquid production of the target oil well. The dynamic fluid level depth is the distance between the fluid level and the wellhead of the target oil well during the extraction process. It can be measured by instruments, such as an echo sounder.

[0037] The well production stage reflects the current stage of the target oil well during production, including the initial, intermediate, and late stages. This stage can be determined based on the well's production information. For example, in the initial stage, the well's production is high and stable; in the intermediate stage, production gradually decreases at a slow rate; and in the late stage, production decreases sharply and rapidly. Geological condition information characterizes the geological complexity of the target well's location, including both complex and stable geological conditions. This information can be obtained during drilling, for example, by analyzing rock samples collected during drilling. Production management requirements information considers factors such as optimizing production and improving efficiency during the target oil well's production process. This includes, but is not limited to, daily rapid evaluation and in-depth analysis and prediction of the target oil well. This information can be determined based on production operation procedures and actual needs.

[0038] By acquiring the influencing factors for the target oil well evaluation, which include at least two of the following: the number of evaluation indicators, the oil well development stage, geological conditions, and production management requirements, the influencing factors for the target oil well evaluation can be obtained from multiple dimensions, providing comprehensive data support for the analysis and processing of subsequent tasks.

[0039] S120. Based on each oil well evaluation influencing factor, determine the applicable data for various pre-configured oil well evaluation methods. The applicable data characterizes the matching degree between the oil well evaluation method and the oil well evaluation influencing factors.

[0040] In this embodiment, various pre-configured oil well evaluation methods are preset methods for comprehensive evaluation of target oil wells, including but not limited to machine learning methods. These methods can be set according to needs and are not limited here. Applicable data reflects the degree of matching between the oil well evaluation methods and various oil well evaluation influencing factors, and can be determined through a pre-set comparison table of oil well evaluation methods and various oil well evaluation influencing factors. Determining the applicable data for each pre-configured oil well evaluation method by identifying each oil well evaluation influencing factor improves the accuracy of the applicable data and provides a basis for subsequent task analysis and processing.

[0041] Optionally, various oil well evaluation methods are pre-configured, including neural network evaluation method, grey relational evaluation method and weighted hierarchical analysis method.

[0042] Optionally, the method further includes: obtaining a pre-established matching relationship between influencing factors and oil well evaluation methods; and determining the applicable data for each oil well evaluation influencing factor based on the matching relationship and the oil well evaluation influencing factors corresponding to the target oil well.

[0043] Specifically, the matching relationship between influencing factors and oil well evaluation methods represents the correspondence between influencing factors and evaluation methods for oil wells. Different influencing factors correspond to different evaluation methods, which can be obtained by referring to a pre-set influencing factor-oil well evaluation method comparison table. Taking the number of evaluation indicators as an example, a first preset threshold and a second preset threshold are set. When the number of evaluation indicators is greater than or equal to the first preset threshold, it indicates that the number of evaluation indicators is abundant; when the number of evaluation indicators is greater than the second preset threshold but less than the first preset threshold, it indicates that the number of evaluation indicators is limited; when the number of evaluation indicators is less than or equal to the second preset threshold, it indicates that the number of evaluation indicators is scarce. When the number of evaluation indicators is abundant, the corresponding oil well evaluation method is the neural network evaluation method; when the number of evaluation indicators is limited, the corresponding oil well evaluation method is the weighted hierarchical analysis method; when the number of evaluation indicators is scarce, the corresponding oil well evaluation method is the grey relational analysis method.

[0044] Based on the matching relationship and the oil well evaluation influencing factors corresponding to the target oil well, determine the applicable data for each oil well evaluation influencing factor and pre-configure various oil well evaluation methods. For example, the applicable data for various pre-configured oil well evaluation methods can be determined by querying a database. The database stores the matching relationship between different oil well evaluation influencing factors and oil well evaluation methods, as well as the corresponding preset applicable data. The standard applicable data corresponding to the matching relationship with the target oil well is used as the applicable data for the pre-configured various oil well evaluation methods.

[0045] For example, for any oil well evaluation influencing factor, the applicable data for the oil well evaluation method corresponding to that oil well evaluation influencing factor is set to 1, and the applicable data for other oil well evaluation methods is set to 0.

[0046] By obtaining the pre-established matching relationship between influencing factors and oil well evaluation methods, and based on the matching relationship and the oil well evaluation influencing factors corresponding to the target oil well, the applicable data for each oil well evaluation influencing factor is determined, thereby improving the accuracy of the applicable data for each pre-configured oil well evaluation method.

[0047] S130. Determine an oil well evaluation strategy based on the applicable data of each oil well evaluation method for each oil well evaluation influencing factor, wherein the oil well evaluation strategy includes at least one oil well evaluation method.

[0048] In this embodiment, the oil well evaluation strategy is a scheme that comprehensively evaluates the target oil well using at least one oil well evaluation method. It may include one, two, or even three oil well evaluation methods, determined based on the applicable data for each oil well evaluation influencing factors. For example, by comparing the applicable data for each oil well evaluation influencing factors using each oil well evaluation method, the oil well evaluation method corresponding to the largest applicable data is selected as the oil well evaluation method for the target oil well, and this oil well evaluation method is used as the oil well evaluation strategy for the target oil well.

[0049] For each oil well evaluation method, based on the applicable data corresponding to each oil well evaluation influencing factor of that evaluation method, the comprehensive applicable data for each oil well evaluation influencing factor is determined. The comprehensive applicable data can be the sum or weighted sum of the applicable data corresponding to each oil well evaluation influencing factor. For example, the oil well evaluation method corresponding to the maximum comprehensive applicable data is determined as the target oil well evaluation method, which serves as the oil well evaluation strategy.

[0050] By determining the evaluation strategy for each oil well based on the applicable data of the influencing factors of each oil well evaluation method, data support is provided for the comprehensive evaluation of the target oil well, improving the accuracy of the oil well evaluation strategy determination, and thus helping to improve the accuracy of the evaluation results of the target oil well.

[0051] S140. The target oil well is evaluated based on the oil well evaluation strategy to obtain the evaluation results of the target oil well.

[0052] In this embodiment, the evaluation result is a conclusion reflecting the production status of the target oil well, which may include one or more of the target oil well's health status and evaluation indicators. The target oil well's health status includes healthy, sub-healthy, and unhealthy. The target oil well is evaluated according to an oil well evaluation strategy to obtain the evaluation result. For example, the evaluation indicators of the target oil well can be processed according to at least one oil well evaluation method in the oil well evaluation strategy to obtain the evaluation result.

[0053] For example, in an oil well evaluation strategy, the evaluation method might be a neural network evaluation method. The evaluation indicators of the target oil well are input into a neural network model to obtain the evaluation results, which include the health status and evaluation indicators of the target oil well. Specifically, the neural network evaluation method is a method that uses a neural network model to comprehensively evaluate the target oil well. Optionally, the neural network model might include a back propagation (BP) neural network model. A BP neural network model includes an input layer, hidden layers, and an output layer. The number of nodes in the input layer can be determined based on the types of evaluation indicators. For example, if there are N different types of evaluation indicators, the number of nodes in the input layer can be set to N. The hidden layer can select a corresponding activation function as needed; for example, the sigmoid function can be chosen. The number of layers and nodes in the hidden layer can be set as needed and is not limited here. The output layer can select a corresponding activation function as needed; for example, the softmax function can be chosen. The number of nodes in the output layer can be set as needed, for example, it can be three or five. In the process of evaluating target oil wells using a BP neural network model, preprocessing operations can be performed on the evaluation indicators. For example, the evaluation indicators can be normalized, mapping them to the [0,1] interval. Data cleaning can also be performed on the evaluation indicators, including removing outliers and missing values. Before using the BP neural network model to evaluate the target oil well, an untrained BP neural network model can be trained. For example, by setting the maximum number of iterations, learning rate, and loss function, the untrained BP neural network model can be trained using gradient descent. The maximum number of iterations, learning rate, and loss function can be set empirically and are not restricted here. By training the untrained BP neural network model, a trained BP neural network model can be obtained.

[0054] For example, in an oil well evaluation strategy, the evaluation method used is grey relational analysis. The evaluation indicators of the target oil well are used as a comparison sequence, and the standard data corresponding to these indicators are used as a reference sequence. The evaluation indicators in the comparison sequence are dimensionless. The relationship coefficients between the comparison sequence and the reference sequence are calculated. These coefficients include, but are not limited to, the minimum difference between two levels, the maximum difference between two levels, and the resolution coefficient. The correlation coefficient between the comparison sequence and the reference sequence is calculated based on these coefficients. The degree of correlation between the comparison sequence and the reference sequence is calculated based on the correlation coefficients. A pre-defined correspondence between the standard correlation degree and the health status is established. The standard correlation degree corresponding to the degree of correlation between the comparison sequence and the reference sequence is determined. The health status corresponding to the standard correlation degree is used as the health status of the target oil well, thus obtaining the evaluation result of the target oil well.

[0055] Grey relational analysis is a method for comprehensively evaluating target oil wells by calculating the grey relational degree of evaluation indicators. The evaluation process is as follows: The evaluation indicators of the target oil well are used as a comparison sequence, and the corresponding standard data are used as a reference sequence. The evaluation indicators in the comparison sequence are dimensionless, for example, by using an initial value method. The relationship coefficient between the comparison sequence and the reference sequence is calculated. This relationship coefficient includes, but is not limited to, the minimum difference between two levels, the maximum difference between two levels, and the resolution coefficient. The resolution coefficient can be set empirically, for example, it can be set to 0.5; there is no restriction here. The correlation coefficient between the comparison sequence and the reference sequence is calculated based on the minimum difference between two levels, the maximum difference between two levels, and the resolution coefficient. The formula for calculating the correlation coefficient is as follows:

[0056]

[0057] Where, ξ i (k) represents the correlation coefficient between the i-th comparison sequence and the reference sequence at time k; ρ represents the resolution coefficient, ρ∈(0,1), and is usually set to 0.5; min i min k |x0(k)-x i (k)| represents the minimum difference between two levels; max i max k |x0(k)-x i (k)| represents the maximum difference between the two levels. The correlation coefficient is used to calculate the correlation between the comparison sequence and the reference sequence, using the following formula:

[0058]

[0059] Where, r i This represents the correlation between the i-th comparison sequence and the reference sequence; n represents the type of evaluation index. The comparison sequences are sorted according to the magnitude of the correlation. The greater the correlation, the closer the evaluation index in the comparison sequence is to the corresponding standard data in the reference sequence.

[0060] For example, in an oil well evaluation strategy, the evaluation method used is the weighted analytic hierarchy process (AHP). A judgment matrix is ​​constructed based on multiple evaluation indicators of the target oil well. The eigenvalues ​​and eigenvectors of the judgment matrix are calculated, and the eigenvectors are normalized to obtain the weight vectors of the evaluation indicators. Standard scores for multiple evaluation indicators are pre-set. Based on these standard scores, the corresponding score data for the target oil well's multiple score indicators is set. The multiple score indicators of the target oil well are weighted and summed to obtain the final score of the target oil well. A pre-set correspondence between the oil well score and its health status is established to determine the oil well score corresponding to the final score of the target oil well. The health status corresponding to the oil well score is then used as the health status of the target oil well, thus obtaining the evaluation result of the target oil well.

[0061] The Weighted Hierarchical Analysis (WHP) is a method for comprehensively evaluating target oil wells using the Analytic Hierarchy Process (AHP) and a weighted comprehensive evaluation method. The WHP process is as follows: First, a judgment matrix is ​​constructed based on multiple evaluation indicators of the target oil well. This can be done through a judgment matrix construction model, where multiple evaluation indicators are input into a pre-trained model for processing. Such models include, but are not limited to, neural network models, such as convolutional neural network models and transformer models. Alternatively, the judgment matrix can be constructed manually, for example, by setting preset input regions for multiple evaluation indicators. Inputting these indicators into their corresponding regions yields the complete judgment matrix. Next, the eigenvalues ​​and eigenvectors of the judgment matrix are calculated. This can be done using eigenvalue methods or by using eigenvalue and eigenvector extraction models. For example, the judgment matrix can be input into a pre-trained eigenvalue and eigenvector extraction model for processing. These models include, but are not limited to, neural network models. Finally, the eigenvectors are normalized to obtain the weight vectors of the evaluation indicators.

[0062] By evaluating target oil wells using oil well evaluation strategies, evaluation results are obtained, achieving a comprehensive evaluation of target oil wells and improving the accuracy of the evaluation results.

[0063] Optionally, the method may also include: displaying the evaluation results and generating prompts based on the evaluation results.

[0064] Specifically, the prompts are targeted suggestions summarized from the evaluation results. These prompts can be generated based on the evaluation results, such as the health status and evaluation indicators. For example, if the target oil well is in a sub-healthy state, and the three-phase voltage and current data of the pumping equipment are abnormal, the corresponding prompt would include the possibility of increased wear and tear on the pumping equipment, suggesting a check of the power supply line and the pumping equipment. The evaluation results can be displayed on a screen, either as text or via voice announcement. By displaying the evaluation results and generating prompts based on them, a basis is provided for staff to perform oil well maintenance.

[0065] Optionally, the method further includes: identifying anomalies in the evaluation index data of the target oil well, determining abnormal evaluation index data, and displaying the abnormal evaluation index data.

[0066] Specifically, abnormal evaluation index data refers to evaluation index data that exceeds the normal or preset range among the various evaluation index data of the target oil well, and can be identified through anomaly identification. For example, corresponding preset ranges are set for different evaluation index data. The evaluation index data of the target oil well is compared with the corresponding preset ranges. When the evaluation index data of the target oil well is within the corresponding preset range, it indicates that the evaluation index data of the target oil well is not abnormal; when the evaluation index data of the target oil well exceeds the corresponding preset range, it indicates that the evaluation index data of the target oil well is abnormal, and the evaluation index data exceeding the corresponding preset range is identified as abnormal evaluation index data. Abnormal evaluation index data can be displayed through display devices. For example, it can be displayed as text on the screen of the display device, or it can display the abnormal evaluation index data and its corresponding preset range, or it can be displayed through voice broadcast. By identifying and displaying abnormal evaluation index data of the target oil well, data support is provided for management personnel to make decisions.

[0067] Optionally, the method further includes: displaying the evaluation results and generating prompt information based on the evaluation results; identifying anomalies in the evaluation index data of the target oil well and determining abnormal evaluation index data; and displaying the abnormal evaluation index data.

[0068] Specifically, the evaluation results of the target oil well are displayed through the display device, and corresponding prompts are generated based on the evaluation results. Anomalies in the evaluation index data of the target oil well are identified, and evaluation index data that exceeds the corresponding preset range are identified as abnormal evaluation index data and displayed. This helps to effectively prevent the occurrence of safety accidents and provides oil well managers with accurate and detailed decision-making basis.

[0069] The technical solution of this embodiment obtains the oil well evaluation influencing factors corresponding to the target oil well. These factors include at least two of the following: the number of evaluation indicators, the oil well production stage, geological conditions, and production management requirements. This allows for the acquisition of oil well evaluation influencing factors from multiple dimensions, providing comprehensive data support for subsequent task analysis and processing. Based on each oil well evaluation influencing factor, pre-configured applicable data for various oil well evaluation methods is determined. This applicable data characterizes the matching degree between the oil well evaluation method and the oil well evaluation influencing factors, improving the accuracy of the applicable data and providing a basis for subsequent task analysis and processing. Based on the applicable data for each oil well evaluation influencing factor, an oil well evaluation strategy is determined for each oil well evaluation method. This strategy includes at least one oil well evaluation method, improving the accuracy of the strategy determination and thus improving the accuracy of the target oil well evaluation results. The target oil well is then evaluated based on the evaluation strategy to obtain the evaluation results, achieving a comprehensive evaluation of the target oil well and improving the utilization rate of oil well production data and the accuracy of the oil well evaluation results.

[0070] Example 2

[0071] Figure 2 This is a flowchart of a comprehensive oil well evaluation method provided in Embodiment 2 of the present invention. This embodiment is an optimization of the above embodiment. Figure 2 As shown, the method includes:

[0072] S210. Obtain the oil well evaluation influencing factors corresponding to the target oil well. The oil well evaluation influencing factors include at least two of the following: the number of evaluation indicators, the oil well development stage, geological condition information, and production management requirements information.

[0073] S220. Based on each oil well evaluation influencing factor, determine the applicable data for various oil well evaluation methods. The applicable data characterizes the matching degree between the oil well evaluation method and the oil well evaluation influencing factor.

[0074] S230. Based on the applicable data of each oil well evaluation method for each oil well evaluation influencing factors, determine the comprehensive applicable data of each oil well evaluation method for the target oil well.

[0075] In this embodiment, the comprehensive applicable data reflects the degree of matching between each oil well evaluation method and the target oil well. This can be determined based on the applicable data of each oil well evaluation method for each oil well evaluation influencing factor. For example, a scoring system can be used, scoring each oil well evaluation method according to each oil well evaluation influencing factor using a percentage system. The score for each oil well evaluation method is then used as the comprehensive applicable data for the corresponding oil well evaluation method for the target oil well. Alternatively, the weights of different oil well evaluation influencing factors for each oil well evaluation method can be pre-set, and the weighted sum of each oil well evaluation method can be calculated. This weighted sum is then used as the comprehensive applicable data for each oil well evaluation method for the target oil well. By using the applicable data of each oil well evaluation method for each oil well evaluation influencing factor, the comprehensive applicable data for each oil well evaluation method for the target oil well is determined, improving the accuracy of the comprehensive applicable data and providing data support for subsequent analysis and research.

[0076] S240. Based on the comprehensive applicable data corresponding to each oil well evaluation method, determine the target oil well evaluation method. Accordingly, the oil well evaluation strategy includes the target oil well evaluation method.

[0077] In this embodiment, the target oil well evaluation method is an oil well evaluation method applicable to the target oil well, including one or more of the following: neural network evaluation method, grey relational analysis method, and weighted hierarchical analysis method. Optionally, the target oil well evaluation method is the oil well evaluation method corresponding to the maximum value of the comprehensive applicable data. The target oil well evaluation method is determined based on the comprehensive applicable data corresponding to each oil well evaluation method. The numerical values ​​of the comprehensive applicable data corresponding to each oil well evaluation method can be compared to determine the oil well evaluation method corresponding to the maximum value of the comprehensive applicable data. This oil well evaluation method corresponding to the maximum value of the comprehensive applicable data is then used as the target oil well evaluation method. Determining the target oil well evaluation method through the comprehensive applicable data corresponding to each oil well evaluation method improves the accuracy of the target oil well evaluation method, thereby contributing to the accuracy of the target oil well evaluation results.

[0078] In some embodiments, the oil well evaluation method with comprehensive applicable data exceeding a set threshold is determined as the target oil well evaluation method. The target oil well evaluation method includes two or more oil well evaluation methods, and the oil well evaluation strategy also includes the weights corresponding to the two or more oil well evaluation methods respectively.

[0079] For example, see Figure 3 , Figure 3This is a schematic diagram of an oil well evaluation method selection method provided by an embodiment of the present invention. The influencing factors for oil well evaluation include data availability, production stage, geological conditions, and production management requirements. Data availability includes three scenarios: abundant and high-quality data, limited or inconsistent data quality, and limited and incomplete data. Production stage includes initial, mid-term, and late-term production stages. Geological conditions include complex and stable geological conditions. Production management requirements include in-depth analysis and prediction, daily rapid assessment, and comprehensive consideration of subjective experience. Oil well evaluation methods include neural network evaluation, grey relational analysis, and a combination of hierarchical analysis and weighted comprehensive analysis. Grey relational analysis is also known as grey relational evaluation. Different oil well evaluation influencing factors correspond to different oil well evaluation methods. Abundant and high-quality data corresponds to the neural network evaluation method; limited or inconsistent data corresponds to the hierarchical analysis combined with weighted comprehensive analysis; and limited and incomplete data corresponds to the grey relational analysis method. The evaluation method for oil wells in the mid-term production stage is the neural network evaluation method; the evaluation method for the initial production stage is the analytic hierarchy process (AHP) combined with weighted comprehensive analysis; and the evaluation method for the later production stage is the grey relational analysis method. For oil wells with complex geological conditions, the neural network evaluation method is used; for oil wells with stable geological conditions, the grey relational analysis method, the AHP, and the weighted comprehensive analysis method are combined.

[0080] S250. The target oil well is evaluated based on the oil well evaluation strategy to obtain the evaluation results of the target oil well.

[0081] When the target oil well evaluation method includes one oil well evaluation method, the evaluation result corresponding to the target oil well evaluation method can be used as the evaluation result of the target oil well.

[0082] Optionally, the method further includes: evaluating the target oil well based on the target oil well evaluation method in the oil well evaluation strategy to obtain the evaluation result corresponding to the target oil well evaluation method; and using the evaluation result corresponding to the target oil well evaluation method as the evaluation result of the target oil well.

[0083] Specifically, the oil well evaluation strategy includes an oil well evaluation method. The target oil well is evaluated using this method, resulting in an evaluation result. This result may include numerical data and one or more aspects of the target oil well's health status. This evaluation result is then used as the final evaluation result for the target oil well. By evaluating the target oil well using the target oil well evaluation method within the strategy, and obtaining the corresponding evaluation result, a comprehensive evaluation of the target oil well is achieved.

[0084] When the evaluation method for the target oil well includes two or more evaluation methods, the evaluation results corresponding to each evaluation method can be weighted to obtain the evaluation result of the target oil well.

[0085] Optionally, the method further includes: evaluating the target oil well based on the target oil well evaluation method in the oil well evaluation strategy to obtain the evaluation result corresponding to the target oil well evaluation method; and weighting the evaluation results corresponding to each target oil well evaluation method to obtain the evaluation result of the target oil well.

[0086] Specifically, the oil well evaluation strategy includes one or more evaluation methods. Different target oil well evaluation methods within the strategy are used to evaluate the target oil wells separately, yielding evaluation results for each method. These results include numerical data. The evaluation results for each method are weighted according to their respective weights within the strategy; for example, a weighted sum can be calculated and used as the final evaluation result. By evaluating the target oil wells using the target evaluation methods within the strategy, and then weighting these results, the accuracy of the target oil well evaluation is improved.

[0087] The technical solution of this embodiment obtains the oil well evaluation influencing factors corresponding to the target oil well. These factors include at least two items: the number of evaluation indicators, the oil well production stage, geological condition information, and production management requirements. This allows for the acquisition of oil well evaluation influencing factors from multiple dimensions, providing comprehensive data support for subsequent task analysis and processing. Based on each oil well evaluation influencing factor, pre-configured applicable data for various oil well evaluation methods is determined. This applicable data characterizes the matching degree between the oil well evaluation method and the oil well evaluation influencing factors, improving the accuracy of the applicable data and providing a basis for subsequent task analysis and processing. Based on each oil well evaluation method, specific data is used for each oil well evaluation... By analyzing applicable data on price influencing factors, the comprehensive applicable data for each oil well evaluation method is determined for the target oil well, improving the accuracy of the comprehensive applicable data and providing data support for subsequent analysis and research. Based on the comprehensive applicable data corresponding to each oil well evaluation method, the target oil well evaluation method is determined. Consequently, the oil well evaluation strategy includes the target oil well evaluation method, improving the accuracy of the target oil well evaluation method and thus contributing to the accuracy of the target oil well evaluation results. Based on the oil well evaluation strategy, the target oil well is evaluated and processed to obtain the evaluation results of the target oil well, realizing the comprehensive evaluation of the target oil well and improving the utilization rate of oil well production data and the accuracy of oil well evaluation results.

[0088] Example 3

[0089] Figure 4 This is a schematic diagram of the structure of an oil well comprehensive evaluation device provided in Embodiment 3 of the present invention. Figure 4 As shown, the device includes:

[0090] The oil well evaluation influencing factor acquisition module 310 is used to acquire the oil well evaluation influencing factors corresponding to the target oil well. The oil well evaluation influencing factors include at least two of the following: the number of evaluation indicators, the oil well development stage, geological condition information, and production management demand information.

[0091] The applicable data determination module 320 is used to determine the applicable data for various pre-configured oil well evaluation methods based on each oil well evaluation influencing factor. The applicable data characterizes the matching degree between the oil well evaluation method and the oil well evaluation influencing factor.

[0092] The oil well evaluation strategy determination module 330 is used to determine the oil well evaluation strategy based on the applicable data of each oil well evaluation method for each oil well evaluation influencing factor. The oil well evaluation strategy includes at least one oil well evaluation method.

[0093] The evaluation result acquisition module 340 is used to evaluate the target oil well based on the oil well evaluation strategy and obtain the evaluation result of the target oil well.

[0094] Based on the above embodiments, optional pre-configured oil well evaluation methods include neural network evaluation method, grey relational evaluation method and weighted hierarchical analysis method.

[0095] Optionally, the applicable data determination module 320 is also used to: obtain the pre-established matching relationship between influencing factors and oil well evaluation methods; and determine the applicable data for each oil well evaluation influencing factor based on the matching relationship and the oil well evaluation influencing factors corresponding to the target oil well.

[0096] Optionally, the oil well evaluation strategy determination module 330 is also used to: determine the comprehensive applicable data of each oil well evaluation method for the target oil well based on the applicable data of each oil well evaluation method for each oil well evaluation influencing factor; and determine the target oil well evaluation method based on the comprehensive applicable data corresponding to each oil well evaluation method. Accordingly, the oil well evaluation strategy includes the target oil well evaluation method.

[0097] Optionally, the target oil well evaluation method is the oil well evaluation method corresponding to the maximum value of the comprehensive applicable data.

[0098] Optionally, the target oil well evaluation method may include two or more oil well evaluation methods, and the oil well evaluation strategy may also include the weights corresponding to the two or more oil well evaluation methods respectively.

[0099] Optionally, the evaluation result acquisition module 340 is further configured to: evaluate the target oil well based on the target oil well evaluation method in the oil well evaluation strategy, and obtain the evaluation result corresponding to the target oil well evaluation method; and use the evaluation result corresponding to the target oil well evaluation method as the evaluation result of the target oil well.

[0100] Optionally, the evaluation result acquisition module 340 is further configured to: evaluate the target oil well based on the target oil well evaluation method in the oil well evaluation strategy, and obtain the evaluation result corresponding to the target oil well evaluation method; and perform weighted processing on the evaluation results corresponding to each target oil well evaluation method to obtain the evaluation result of the target oil well.

[0101] Optionally, the device also includes a prompt message generation module for displaying evaluation results and generating prompt messages based on the evaluation results.

[0102] Optionally, the prompt information generation module is also used to: identify anomalies in the evaluation index data of the target oil well, determine abnormal evaluation index data, and display the abnormal evaluation index data.

[0103] Optionally, the prompt information generation module is also used to: display the evaluation results and generate prompt information based on the evaluation results; identify anomalies in the evaluation index data of the target oil well and determine the abnormal evaluation index data; and display the abnormal evaluation index data.

[0104] The oil well comprehensive evaluation device provided in this embodiment of the invention can execute the oil well comprehensive evaluation method provided in any embodiment of the invention, and has the corresponding functional modules and beneficial effects of the method.

[0105] Example 4

[0106] Figure 5 This is a schematic diagram of the structure of an electronic device provided in Embodiment 4 of the present invention. The electronic device 10 is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices (such as helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0107] like Figure 5 As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12 or a random access memory (RAM) 13, communicatively connected to the at least one processor 11. The memory stores computer programs executable by the at least one processor. The processor 11 can perform various appropriate actions and processes based on the computer program stored in the ROM 12 or loaded from storage unit 18 into the RAM 13. The RAM 13 may also store various programs and data required for the operation of the electronic device 10. The processor 11, ROM 12, and RAM 13 are interconnected via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0108] Multiple components in electronic device 10 are connected to input / output (I / O) interface 15, including: input unit 16, such as keyboard, mouse, etc.; output unit 17, such as various types of monitors, speakers, etc.; storage unit 18, such as disk, optical disk, etc.; and communication unit 19, such as network card, modem, wireless transceiver, etc. Communication unit 19 allows electronic device 10 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0109] Processor 11 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 11 include, but are not limited to, central processing unit (CPU), graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, digital signal processors (DSPs), and any suitable processor, controller, microcontroller, etc. Processor 11 performs the various methods and processes described above, such as the integrated evaluation method for oil wells.

[0110] In some embodiments, the comprehensive well evaluation method may be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on electronic device 10 via read-only memory (ROM) 12 and / or communication unit 19. When the computer program is loaded into random access memory (RAM) 13 and executed by processor 11, one or more steps of the comprehensive well evaluation method described above may be performed. Alternatively, in other embodiments, processor 11 may be configured to perform the comprehensive well evaluation method by any other suitable means (e.g., by means of firmware).

[0111] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), system-on-a-chip (SoCs), computed-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0112] Computer programs used to implement the integrated oil well evaluation method of the present invention can be written in any combination of one or more programming languages. These computer programs can be provided to the processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the functions / operations specified in the flowcharts and / or block diagrams are implemented. The computer programs can be executed entirely on a machine, partially on a machine, as a standalone software package partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0113] Example 5

[0114] Embodiment 5 of the present invention also provides a computer-readable storage medium storing computer instructions for causing a processor to execute an oil well comprehensive evaluation method, the method comprising:

[0115] The process involves: acquiring the influencing factors for well evaluation corresponding to the target oil well, including at least two of the following: the number of evaluation indicators, the oil well development stage, geological conditions, and production management requirements; determining applicable data for various pre-configured well evaluation methods based on each influencing factor, whereby the applicable data characterizes the matching degree between the well evaluation method and the influencing factor; determining an oil well evaluation strategy based on the applicable data for each influencing factor for each well evaluation method, whereby the oil well evaluation strategy includes at least one well evaluation method; and evaluating the target oil well based on the oil well evaluation strategy to obtain the evaluation result of the target oil well.

[0116] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0117] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0118] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or computing systems that include middleware components (e.g., application servers), or computing systems that include frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0119] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0120] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0121] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A comprehensive evaluation method for oil wells, characterized in that, include: Obtain the oil well evaluation influencing factors corresponding to the target oil well. The oil well evaluation influencing factors include at least two of the following: the number of evaluation indicators, the oil well development stage, geological condition information, and production management requirements information. Based on each oil well evaluation influencing factor, pre-configured applicable data for various oil well evaluation methods are determined, and the applicable data characterizes the matching degree between the oil well evaluation method and the oil well evaluation influencing factor; An oil well evaluation strategy is determined based on the applicable data of each oil well evaluation influencing factor according to each oil well evaluation method, wherein the oil well evaluation strategy includes at least one oil well evaluation method. The target oil well is evaluated based on the oil well evaluation strategy to obtain the evaluation result of the target oil well.

2. The method according to claim 1, characterized in that, The method for determining the applicable data for pre-configured oil well evaluation methods based on each oil well evaluation influencing factor includes: Obtain the pre-established matching relationship between influencing factors and oil well evaluation methods; Based on the matching relationship and the oil well evaluation influencing factors corresponding to the target oil well, the applicable data for each oil well evaluation influencing factor is determined and pre-configured for various oil well evaluation methods.

3. The method according to claim 1, characterized in that, The process of determining an oil well evaluation strategy based on applicable data for each oil well evaluation influencing factor according to each oil well evaluation method includes: Based on the applicable data of each oil well evaluation method for each oil well evaluation influencing factor, determine the comprehensive applicable data of each oil well evaluation method for the target oil well; Based on the comprehensive applicable data corresponding to each oil well evaluation method, the target oil well evaluation method is determined, and the oil well evaluation strategy includes the target oil well evaluation method.

4. The method according to claim 3, characterized in that, The target oil well evaluation method is the oil well evaluation method corresponding to the maximum value of the comprehensive applicable data; Alternatively, the target oil well evaluation method may include two or more oil well evaluation methods, and the oil well evaluation strategy may also include the weights corresponding to the two or more oil well evaluation methods respectively.

5. The method according to claim 4, characterized in that, The evaluation process based on the oil well evaluation strategy to obtain the evaluation result of the target oil well includes: The target oil well is evaluated based on the target oil well evaluation method in the oil well evaluation strategy to obtain the evaluation result corresponding to the target oil well evaluation method. The evaluation result corresponding to the evaluation method of the target oil well is used as the evaluation result of the target oil well, or the evaluation results corresponding to each evaluation method of the target oil well are weighted to obtain the evaluation result of the target oil well.

6. The method according to claim 1, characterized in that, The pre-configured evaluation methods for various oil wells include neural network evaluation method, grey relational evaluation method, and weighted hierarchical analysis method.

7. The method according to claim 1, characterized in that, The method further includes: Display the evaluation results and generate prompt information based on the evaluation results; And / or, identify anomalies in the evaluation index data of the target oil well, determine abnormal evaluation index data, and display the abnormal evaluation index data.

8. A comprehensive evaluation device for oil wells, characterized in that, include: The oil well evaluation influencing factor acquisition module is used to acquire the oil well evaluation influencing factors corresponding to the target oil well. The oil well evaluation influencing factors include at least two of the following: the number of evaluation indicators, the oil well development stage, geological condition information, and production management demand information. The applicable data determination module is used to determine the applicable data for various pre-configured oil well evaluation methods based on each oil well evaluation influencing factor. The applicable data represents the degree of matching between the oil well evaluation method and the oil well evaluation influencing factor. An oil well evaluation strategy determination module is used to determine an oil well evaluation strategy based on applicable data of each oil well evaluation method for each oil well evaluation influencing factor, wherein the oil well evaluation strategy includes at least one oil well evaluation method. The evaluation result acquisition module is used to evaluate the target oil well based on the oil well evaluation strategy and obtain the evaluation result of the target oil well.

9. An electronic device, characterized in that, The electronic device includes: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform the oil well comprehensive evaluation method according to any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that cause a processor to execute the oil well comprehensive evaluation method according to any one of claims 1-7.

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