Shale gas platform well test production prediction method and device based on gas production coefficient

Abstract

The present application relates to the technical field of oil and gas field development, and discloses a method and device for predicting the test production of shale gas platform wells based on the gas production coefficient. The present application utilizes the characteristic of slow changes in the shale gas marine sedimentary plane and introduces the gas production coefficient to simplify the complex geological conditions into the gas production capacity of the unit volume of the formation, thereby reducing the amount of calculation engineering. At the same time, the fitting target parameter is converted from the single well test production that is subject to greater inter-well interference to the platform average test production, so the error is smaller and the gas production capacity of the formation can be more truly reflected.

Description

Technical Field

[0001] The present application relates to the technical field of oil and gas field development, specifically to the production and development of shale gas, and in particular to a method and device for predicting the production of shale gas platform wells based on gas production coefficient. Background Art

[0002] Numerous studies have shown that the test yield of shale gas wells is positively correlated with their long-term stable production capacity. Accurately predicting the test yield of shale gas wells is a practical challenge facing shale gas exploration and development.

[0003] Current shale gas horizontal well test production predictions primarily rely on regression prediction based on single-well test production. The most widely used method involves statistically analyzing the correlation between various data types and test production, then selecting parameters for correlation regression. Similarly, test production predictions have also been developed using algorithms such as machine learning, grayscale prediction, and random forests. However, single-well test production alone cannot fully reflect the underlying reservoir geology. During the testing of wells on a shale gas platform, varying fracturing sequences often lead to later-fractured wells interfacing with earlier-fractured wells or wells already in production, affecting the test production data of earlier-fractured or interlinked wells. Therefore, regression prediction methods based on single-well test production struggle to eliminate the influence of this error. Furthermore, in shale gas exploration practice, four wells on the same platform and branch, under similar geological and reservoir conditions, have been observed to exhibit abnormally high production in one well while the other three have relatively low production. This resulting test error often negatively impacts the development of regression formulas, ultimately resulting in significant errors in the prediction of well test production on shale gas platforms, failing to accurately reflect the gas production capacity of the formation. Summary of the Invention

[0004] In order to solve the problems and shortcomings existing in the above-mentioned prior art, the present application proposes a shale gas platform well test production prediction method and device based on the gas production coefficient. By utilizing the characteristic that the shale gas marine sedimentary plane changes slowly, the gas production coefficient is introduced to simplify the complex geological conditions into the problem of gas production capacity per unit volume of formation, thereby reducing the amount of engineering calculations. At the same time, the fitting target parameter is converted from the single well test production that is subject to greater inter-well interference to the platform average test production, so the error is smaller and it can more truly reflect the gas production capacity of the formation.

[0005] In order to achieve the above-mentioned invention objectives, the technical solutions of this application are as follows:

[0006] A shale gas platform well test production prediction method based on gas production coefficient, comprising:

[0007] Obtaining implementation data for shale gas platform well projects;

[0008] Define the gas production coefficient;

[0009] The location of the tunnel encountered by each single well in the platform well is counted, and the horizontal section of each single well is divided into n different lithofacies sections according to the location of the tunnel encountered;

[0010] Assuming that the gas production coefficients of the same lithofacies section of each well in the same platform well are the same, the gas production coefficients of each lithofacies section of the platform well are calculated based on the test production of each well and the rock parameters of each lithofacies section;

[0011] According to the obtained gas production coefficient, a plane distribution diagram of gas production coefficient of different lithofacies in different platform wells is established;

[0012] Obtain the gas production coefficients of different lithofacies sections of a newly drilled single well based on the gas production coefficient plane distribution map, and calculate the test production of the newly drilled single well;

[0013] Based on the test production of each single well in the platform well, the predicted test production of the entire platform well is calculated.

[0014] Furthermore, the engineering implementation data includes well logging data, mud logging data, drilling data and fracturing segmentation data.

[0015] Furthermore, the gas production coefficient refers to the ability of a unit volume of gas-bearing rock to provide converted daily test production after undergoing standard fracturing and testing procedures in the area.

[0016] Furthermore, the rock parameters include the gas content per unit volume of the lithofacies section, the rock density, and the rock volume affected by fracturing.

[0017] Furthermore, the gas production coefficient of each lithofacies section of the entire platform well is obtained based on the test production of each single well and the rock parameters of each lithofacies section, including:

[0018] According to the meaning of gas production coefficient, the test production of a single platform well is

[0019] Formula (1);

[0020] in, represents the daily test output, Indicates the gas production coefficient of the corresponding lithofacies section of the well; Indicates the gas content per unit mass of rock in the corresponding lithofacies section of the well; Indicates the rock density of the lithofacies section corresponding to the well; It indicates the rock volume affected by fracturing in the corresponding lithofacies section of the well;

[0021] Based on the test production of each single well in the platform well and the rock parameters of each lithofacies section of the single well, an equation group is established. By solving the equation group, the gas production coefficient of each lithofacies section of the entire platform well is obtained.

[0022] Furthermore, the test production of a newly drilled single well is the sum of the test production of each lithofacies section of the single well.

[0023] Furthermore, the predicted test production of the entire platform well is the sum of the test production of each single well.

[0024] A shale gas platform well test production prediction device based on gas production coefficient, comprising:

[0025] The first data acquisition module is used to obtain shale gas platform well project implementation data;

[0026] Data definition module, used to define gas production coefficient;

[0027] The first data processing module is used to count the location of the tunnel encountered by each single well in the platform well, and divide the horizontal section of each single well into different n lithofacies sections according to the location of the tunnel encountered;

[0028] The second data processing module is used to calculate the gas production coefficient of each lithofacies section of the entire platform well based on the test production of each single well and the rock parameters of each lithofacies section;

[0029] A third data processing module is used to establish a plane distribution map of gas production coefficients of different lithofacies in different platform wells according to the gas production coefficients;

[0030] The second data acquisition module is used to obtain the gas production coefficients of different lithofacies sections of a newly drilled single well based on the gas production coefficient plane distribution map;

[0031] The fourth data processing module is used to calculate the test production of a newly drilled single well based on the gas production coefficients of different lithofacies sections of the newly drilled single well;

[0032] The fifth data processing module is used to obtain the predicted test production of the entire platform wells based on the test production of each single well.

[0033] A computer device includes a memory, a processor, and a computer program stored in the memory and executable in the processor. When the processor executes the computer program, the above-mentioned shale gas platform well test production prediction method based on gas production coefficient is implemented.

[0034] A computer-readable storage medium stores a computer program, which, when executed in a computer processor, implements the above-mentioned shale gas platform well test production prediction method based on gas production coefficient.

[0035] Beneficial effects of this application:

[0036] (1) This application utilizes the characteristic of slow changes in the shale gas marine sedimentary plane and introduces the gas production coefficient to simplify the complex geological conditions into the gas production capacity per unit volume of the formation, thereby reducing the amount of engineering calculations.

[0037] (2) Since the test production of shale gas wells is affected by many factors such as the construction sequence and the drainage of adjacent wells, the test production of a single well fluctuates greatly. Therefore, this application converts the single well test production prediction into the platform average test production, which minimizes the influence of the aforementioned engineering parameters and can more truly reflect the gas production capacity of the formation.

[0038] (3) This application can predict the test production of shale gas wells in advance, and then predict the economic and feasibility of deploying platforms in the region, thereby improving the benefits of shale gas exploration and development. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] The foregoing and following detailed description of the present application will become more apparent when read in conjunction with the following drawings, in which:

[0040] Figure 1 This is a flow chart of the application method;

[0041] Figure 2 This is a structural diagram of the device of this application;

[0042] Figure 3 This is a correlation analysis chart of the actual test production and the fitted calculated test production in an operating area in the Sichuan Basin;

[0043] Figure 4 This is a planar distribution map of the gas production coefficient of shale gas platform wells in an operating area in the Sichuan Basin. DETAILED DESCRIPTION

[0044] In order to enable those skilled in the art to better understand the technical solutions in this application, the following will further illustrate the technical solutions for achieving the invention purpose of this application through several specific embodiments. It should be noted that the technical solutions claimed for protection in this application include but are not limited to the following embodiments. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without making any creative work should fall within the scope of protection of this application.

[0045] Example 1

[0046] Broadly speaking, the most widely used method for predicting shale gas well test yield is to statistically analyze the correlation between various data and test yield, then perform regression analysis on selected parameters. Similarly, other methods for predicting test yield include machine learning, grayscale prediction, and random forest algorithms.

[0047] However, the above prediction methods cannot truly reflect the gas production capacity of the formation, and the calculation amount of the entire project is also very large during the prediction.

[0048] Based on this, the present embodiment provides a shale gas platform well test production prediction method and device based on gas production coefficient, which can reduce errors in the prediction process, more realistically reflect the gas production capacity of the formation, and also reduce the amount of calculation engineering.

[0049] In order to facilitate understanding of this embodiment, a shale gas platform well test production prediction method based on gas production coefficient disclosed in an embodiment of the present application is first introduced in detail.

[0050] The embodiment of the present application discloses a method for predicting the production of shale gas platform wells based on the gas production coefficient. Figure 1 , the method specifically comprises the following steps:

[0051] Step S101: Collect and obtain engineering implementation data such as well logging data, mud logging data, drilling data, and fracturing stage data of shale gas platform wells.

[0052] Step S102: define the gas production coefficient as the capacity of a unit volume of gas-bearing rock to provide converted daily test production after undergoing the standard fracturing and testing process in the region.

[0053] Step S103: Count the locations of the tunnels encountered by each single well in the platform well, and then divide the horizontal section of each single well into n different lithofacies sections according to the locations of the tunnels encountered.

[0054] Step S104: Due to variations in parameters such as sedimentary facies and mineral composition, wells drilled on different platforms may encounter different gas production coefficients for the same lithofacies. However, marine shale gas deposits change relatively slowly laterally, so it can be assumed that different wells on the same platform have the same gas production coefficients in the same lithofacies section. Therefore, it is assumed that the gas production coefficients of all wells on the same platform are the same in the same lithofacies section. Furthermore, due to factors such as brittleness, porosity, and clay mineral content, different lithofacies have different gas production capacities, and their parameters such as gas content and rock density are also different. Based on the definition of the gas production coefficient, the expression for calculating the test production of a single well is as follows:

[0055] Formula (1);

[0056] in, Indicates daily test output in units of , It indicates the gas production coefficient of the corresponding lithofacies section of the single well, with the unit being 1; Indicates the gas content per unit mass of rock in the lithofacies section of the single well, in units of ; Indicates the rock density of the lithofacies section corresponding to the single well, in units of ; It indicates the rock volume affected by fracturing in the lithofacies section of the single well, in units of ;

[0057] From the above calculation expression, we can know that the test production of a single well is equal to the sum of the test production of each lithofacies section of the single well;

[0058] According to the test production calculation expressions of each single platform well, a corresponding set of equations is established. By solving the set of equations, the gas production coefficient of each lithofacies section of a single platform well can be obtained.

[0059] Step S105: Repeat the above steps to respectively obtain the gas production coefficients of various lithofacies sections of several different platform wells, and establish a plane distribution map of the gas production coefficients of different lithofacies in different platform wells based on the obtained gas production coefficients.

[0060] Step S106: Obtain the gas production coefficients of different lithofacies sections of the newly drilled single well according to the established gas production coefficient plane distribution map, and calculate the test production of the newly drilled single well using the above-mentioned single well test production calculation expression.

[0061] Step S107: summing the obtained test production of each single well to obtain the test production of the entire platform well, and finally completing the prediction of the test production of the platform well.

[0062] The shale gas platform well test production prediction method described in this embodiment is applicable to platform wells where the number of single wells is greater than or equal to the number of lithofacies sections in the platform wells.

[0063] In this embodiment, in step S5, when calculating the gas production coefficient of each lithofacies section of a single platform well, when the number of platform wells is equal to the number of lithofacies sections, the number of equations in the established equation group is equal to the number of unknowns (gas production coefficients). Therefore, the gas production coefficient of each lithofacies section of the platform well can be directly obtained by solving the above equation group. However, when the number of platform wells is greater than the number of lithofacies sections of the platform well, the number of equations in the equation group established based on the calculation expression of the test production of each platform well is greater than the number of unknowns (gas production coefficients). Therefore, when obtaining the gas production coefficient of each lithofacies section of a single platform well, a verification step needs to be added, as follows:

[0064] First, several equations are established based on the test production calculation expression of a single platform well. Then, some of the equations are randomly selected to establish a system of equations. The number of equations should be equal to the number of unknowns (gas production coefficients). The system of equations is solved to obtain the initial values ​​of the gas production coefficients of each lithofacies section of the platform well. The initial values ​​are then substituted into the remaining equations for verification. If the error between the calculated test production and the known test production is less than 5%, then the initial values ​​are considered to be the values ​​of the gas production coefficients. If the error between the calculated test production and the known test production is greater than 5%, then some of the equations are reselected, the system of equations is reestablished, and the system of equations is solved. Similarly, the initial values ​​of the gas production coefficients obtained by solving the system of equations are substituted into the remaining equations for verification. If the error between the calculated test production and the known test production is less than 5%, then the requirements are considered to be met and the initial values ​​are the values ​​of the gas production coefficients. If the error is still greater than 5%, the above steps are repeated. If all solutions cannot make the final error less than 5%, the set of solutions with the smallest overall error is selected as the optimal solution.

[0065] Furthermore, based on the same inventive concept, the embodiments of the present application also provide a shale gas platform well test production prediction device based on gas production coefficient, as described in the following embodiments. As used below, the term "unit" or "module" can be a combination of software and / or hardware that implements a predetermined function. Although the device described in the following embodiments is preferably implemented in software, it is also possible and conceivable to implement it in hardware, or a combination of software and hardware. Figure 2 Specifically, the device may include: a first data acquisition module 201, a data definition module 202, a first data processing module 203, a second data processing module 204, a third data processing module 205, a second data acquisition module 206, a fourth data processing module 207 and a fifth data processing module 208.

[0066] The structure is described in detail below.

[0067] The first data acquisition module 201 is used to acquire shale gas platform well engineering implementation data;

[0068] The data definition module 202 is used to define the gas production coefficient;

[0069] The first data processing module 203 is used to count the location of the tunnel encountered by each single well in the platform well, and divide the horizontal section of each single well into n different lithofacies sections according to the location of the tunnel encountered;

[0070] The second data processing module 204 is used to calculate the gas production coefficient of each lithofacies section of the entire platform well based on the test production of each single well and the rock parameters of each lithofacies section;

[0071] The third data processing module 205 is used to establish a planar distribution map of gas production coefficients of different lithofacies in different platform wells according to the gas production coefficients;

[0072] The second data acquisition module 206 is used to obtain the gas production coefficients of different lithofacies sections of a newly drilled single well according to the gas production coefficient plane distribution map;

[0073] The fourth data processing module 207 is used to calculate the test production of a newly drilled single well based on the gas production coefficients of different lithofacies sections of the newly drilled single well;

[0074] The fifth data processing module 208 is used to obtain the predicted test production of the entire platform wells based on the test production of each individual well.

[0075] It should be noted that the systems, devices, models, or units described in the above embodiments can be implemented by computer chips or physical devices, or by products with certain functions. For ease of description, in this specification, the above devices are described in various units according to their functions. Of course, when implementing this application, the functions of each unit can be implemented in the same or multiple software and / or hardware.

[0076] Furthermore, in this specification, adjectives such as first and second may be used merely to distinguish one element or action from another, without necessarily or implying any actual such relationship or order.

[0077] From the above description, it can be seen that the embodiment of the present application provides a shale gas platform well test production prediction device based on gas production coefficient. It takes advantage of the slow change of the shale gas marine sedimentary plane, introduces the concept of gas production coefficient, establishes the relationship between specific parameters and test production, and thus obtains the gas production coefficient of different lithofacies sections in different platform wells, and finally establishes a plane distribution map of gas production coefficients of different lithofacies in different platform wells based on the obtained gas production coefficients. Then, the test production of the newly drilled single well is calculated based on the established plane distribution map of gas production coefficients, and finally the test production of the entire platform well is predicted. Therefore, when predicting the test production of the platform well, the amount of engineering calculations is reduced by simplifying the complex geological conditions into the problem of gas production capacity per unit volume of the formation. At the same time, the fitting target parameter is converted from the single well test production that is subject to greater interference between wells to the platform average test production, which has smaller errors and can more truly reflect the gas production capacity of the formation.

[0078] Furthermore, an embodiment of the present application also provides a computer device, which includes a memory, a processor, and a computer program stored in the memory and executable in the processor. When the processor executes the computer program, the steps of any of the above methods are implemented.

[0079] Furthermore, an embodiment of the present application also provides a computer-readable storage medium, which stores a computer program. When the computer program is executed in a computer processor, it implements the steps of any of the above methods.

[0080] Example 2

[0081] This embodiment takes a certain operating area in the Sichuan Basin as an example to further explain the shale gas platform well test production prediction method based on gas production coefficient in this application.

[0082] The method of this application is used to predict the test production of shale gas platform wells in the region, including the following steps:

[0083] S101. Collect engineering implementation data. Taking an operating area in the Sichuan Basin as an example, collect engineering implementation data such as well logging data, mud logging data, drilling data, and fracturing segmentation data from 85 shale gas horizontal wells in the operating area.

[0084] S102. Define a parameter gas production coefficient, which is the converted daily test production that a unit volume of rock can provide after undergoing the standard fracturing and testing process in the area, with a unit of 1.

[0085] S103. Count the locations of the tunnels encountered by the wells in the operation area. Based on the locations of the tunnels encountered, the lithofacies encountered in the area can be divided into three lithofacies sections.

[0086] S104. Since the shale gas formations in this area belong to marine strata, the variations in parameters such as sedimentary facies and mineral composition are small. It can be assumed that the gas production coefficients of different wells in the same lithofacies section at the same platform are the same. Therefore, it is assumed that the gas production coefficients of all wells in the same lithofacies section at the same platform are the same. Based on the definition of gas production coefficient, the expression for calculating the tested production of a single well is as follows:

[0087] Formula (1);

[0088] Among them, among them, Indicates daily test output in units of , It indicates the gas production coefficient of the corresponding lithofacies section of the single well, with the unit being 1; Indicates the gas content per unit mass of rock in the lithofacies section of the single well, in units of ; Indicates the rock density of the lithofacies section corresponding to the single well, in units of ; It indicates the rock volume affected by fracturing in the lithofacies section of the single well, in units of .

[0089] Step S105: Based on the test production calculation expressions of each single platform well, a corresponding set of equations is established to solve the gas production coefficients of different lithofacies of a single platform well.

[0090] Step S106: Repeat the above steps to obtain the gas production coefficient of each lithofacies section at different platforms, refer to the attached manual. Figure 1 The calculation results show that in this area, the gas production coefficient of lithofacies 1 ranges from 1 to 1.5, the gas production coefficient of lithofacies 2 ranges from 0.1 to 0.4, and the gas production coefficient of lithofacies 3 ranges from 0.2 to 0.6. Then, the results are substituted into the test production calculation formula for inspection. The overall error of the result is small. Then, based on the obtained gas production coefficient, a plane distribution map of the gas production coefficient of different lithofacies in different platform wells is established. The plane distribution map of the gas production coefficient of lithofacies 1 in this area is shown as follows: Figure 2 shown.

[0091] Step S107: Based on the established gas production coefficient planar distribution map, the gas production coefficients of different lithofacies sections of the newly drilled HZ platform are obtained. The test production of the newly drilled platform is calculated using the above-mentioned single-well test production calculation expression. The formula estimates the test production of the four wells on the newly drilled HZ platform to be 2.2647 million cubic meters per day. The actual test production of the four wells totaled 2.1441 million cubic meters, with a prediction error of 5.624%, indicating good prediction results.

[0092] In the description of this application, it should be understood that the terms "center", "longitudinal", "lateral", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", etc., indicating the orientation or position relationship, are based on the orientation or position relationship shown in the accompanying drawings, and are only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation. Therefore, it should not be understood as limiting the scope of protection of this application.

[0093] It should also be noted that, in the description of this application, unless otherwise expressly specified or limited, the terms "disposed," "installed," and "connected" should be understood broadly. For example, they can refer to fixed connections, detachable connections, or integral connections; mechanical connections or electrical connections; direct connections or indirect connections through an intermediate medium; and internal connections between two components. Those skilled in the art will understand the specific meanings of the above terms in this application based on the specific circumstances.

[0094] The devices or modules illustrated in the above embodiments can be specifically implemented by computer chips or entities, or by products with certain functions. For the convenience of description, the above devices are described in terms of functions and are divided into various modules and described separately. Of course, when implementing this application, the functions of each module can be implemented in the same or multiple software and / or hardware, or the module that implements the same function can be implemented by a combination of multiple sub-modules, etc. The device embodiments described above are merely schematic. For example, the division of the modules is only a logical function division. In actual implementation, there may be other division methods, such as multiple modules or components can be combined or integrated into another system, or some features can be ignored or not executed.

[0095] Those skilled in the art will also appreciate that, in addition to implementing the controller in pure computer-readable program code, it is entirely possible to implement the same functionality by logically programming the method steps in the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers, embedded microcontrollers, and the like. Therefore, such a controller can be considered a hardware component, and the devices included therein for implementing various functions can also be considered structures within the hardware component. Alternatively, the devices for implementing various functions can be considered both software modules implementing the method and structures within the hardware component.

[0096] The above description is merely a preferred embodiment of the present application and does not constitute any form of limitation to the present application. Any simple modification or equivalent change made to the above embodiment based on the technical essence of the present application shall fall within the scope of protection of the present application.

Claims

1. A shale gas platform well test production prediction method based on gas production coefficient, characterized in that: include: Obtaining implementation data for shale gas platform well projects; Define the gas production coefficient, which refers to the ability of a unit volume of gas-bearing rock to provide converted daily test production after undergoing the standard fracturing and testing process in the region; The location of the tunnel encountered by each single well in the platform well is counted, and the horizontal section of each single well is divided into n different lithofacies sections according to the location of the tunnel encountered; Assuming that the gas production coefficients of the same lithofacies section for each well in the same platform well are the same, the gas production coefficients of each lithofacies section of the platform well are calculated based on the test production of each well and the rock parameters of each lithofacies section; the rock parameters include the gas content per unit volume of the lithofacies section, the rock density, and the rock volume affected by fracturing; The gas production coefficient of each lithofacies section of the entire platform well is obtained based on the test production of each single well and the rock parameters of each lithofacies section, including: According to the meaning of gas production coefficient, the test production of a single platform well is Formula (1); in, represents the daily test output, Indicates the gas production coefficient of the corresponding lithofacies section of the well; Indicates the gas content per unit mass of rock in the corresponding lithofacies section of the well; Indicates the rock density of the lithofacies section corresponding to the well; It indicates the rock volume affected by fracturing in the corresponding lithofacies section of the well; Based on the test production of each single well in the platform well and the rock parameters of each lithofacies section of the single well, a set of equations is established and solved to obtain the gas production coefficient of each lithofacies section of the entire platform well; According to the obtained gas production coefficient, a plane distribution diagram of gas production coefficient of different lithofacies in different platform wells is established; Obtain the gas production coefficients of different lithofacies sections of a newly drilled single well based on the gas production coefficient plane distribution map, and calculate the test production of the newly drilled single well; Based on the test production of each single well in the platform well, the predicted test production of the entire platform well is calculated.

2. The shale gas platform well test production prediction method based on gas production coefficient according to claim 1 is characterized in that: The engineering implementation data includes well logging data, mud logging data, drilling data and fracturing segmentation data.

3. The method for predicting shale gas platform well test production based on gas production coefficient according to claim 1, characterized in that: The test production of a newly drilled single well is the sum of the test production of each lithofacies section of the single well.

4. The method for predicting shale gas platform well test production based on gas production coefficient according to claim 1, characterized in that: The predicted test production of the entire platform well is the sum of the test production of each single well.

5. A shale gas platform well test production prediction device based on gas production coefficient, characterized in that: The shale gas platform well test production prediction device based on gas production coefficient is used to implement the shale gas platform well test production prediction method based on gas production coefficient according to any one of claims 1 to 4, comprising: The first data acquisition module is used to obtain shale gas platform well project implementation data; Data definition module, used to define gas production coefficient; The first data processing module is used to count the location of the tunnel encountered by each single well in the platform well, and divide the horizontal section of each single well into n different lithofacies sections according to the location of the tunnel encountered; The second data processing module is used to calculate the gas production coefficient of each lithofacies section of the entire platform well based on the test production of each single well and the rock parameters of each lithofacies section; A third data processing module is used to establish a planar distribution map of gas production coefficients of different lithofacies in different platform wells according to the gas production coefficients; The second data acquisition module is used to obtain the gas production coefficients of different lithofacies sections of a newly drilled single well based on the gas production coefficient plane distribution map; The fourth data processing module is used to calculate the test production of a newly drilled single well based on the gas production coefficients of different lithofacies sections of the newly drilled single well; The fifth data processing module is used to obtain the predicted test production of the entire platform wells based on the test production of each single well.

6. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable in the processor, wherein: When the processor executes the computer program, the method steps described in any one of claims 1 to 4 are implemented.

7. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, and when the computer program is executed in a computer processor, the method according to any one of claims 1 to 4 is implemented.

Images