CN-121998221-A - Method, medium and electronic equipment for determining productivity evaluation model and evaluating productivity

CN121998221ACN 121998221 ACN121998221 ACN 121998221ACN-121998221-A

Abstract

The application discloses a method, a medium and electronic equipment for determining and evaluating productivity evaluation models, wherein the method comprises the steps of obtaining at least two reservoir physical parameters before casting at least two old wells and obtaining production dynamic information, wherein the production dynamic information comprises recoverable reserves and at least two types of productivity data; the method comprises the steps of acquiring capacity evaluation data for evaluating capacity from at least two kinds of capacity data according to the recoverable reserves, acquiring sensitive parameters affecting the capacity evaluation data from at least two kinds of reservoir physical parameters according to the capacity evaluation data, determining a first target relation between the capacity evaluation data and the sensitive parameters, and determining a second target relation between the capacity evaluation data and the recoverable reserves. The application can evaluate the productivity of the new well according to the productivity evaluation data of the new well.

Inventors

JI LIANG
Xing Xuejie
CAO JINGTIAN
YANG HONGTAO
ZHANG TONG
WANG YUAN
WANG DEZHI
SHI JUNTAI
HUANG HONGXING
YI WEI
ZHANG ZHENGCHAO

Assignees

中国石油天然气股份有限公司
中石油煤层气有限责任公司
中联煤层气国家工程研究中心有限责任公司

Dates

Publication Date: 20260508
Application Date: 20241104

Claims (10)

1. The productivity evaluation model determining method is characterized by being applied to a deep coal bed gas well and comprising the following steps of: Acquiring at least two reservoir physical parameters before casting of at least two old wells, and acquiring production dynamic information, wherein the production dynamic information comprises recoverable reserves and at least two productivity data; Acquiring capacity evaluation data for evaluating capacity from the at least two kinds of capacity data according to the recoverable reserves; According to the productivity evaluation data, sensitive parameters influencing the productivity evaluation data are obtained from the at least two reservoir physical parameters; Determining a first target relationship between the capacity evaluation data and the sensitive parameter, and determining a second target relationship between the capacity evaluation data and the recoverable reserves, wherein the first target relationship is used for determining the capacity evaluation data of a new well in the same block as the at least two old wells, and the second target relationship is used for determining the recoverable reserves of the new well in the same block as the at least two old wells.
2. The method of claim 1, wherein the reservoir property parameters include a first property parameter and a second property parameter, and the obtaining at least two reservoir property parameters prior to production in at least two old wells comprises: testing the at least two old wells to obtain the first physical parameters; Acquiring historical bottom hole flow pressure data, historical casing pressure data and historical productivity data of the at least two old wells, and acquiring initial values of the second physical parameters; And inputting the historical bottom hole flow pressure data, the historical casing pressure data, the historical capacity data and the initial value of the second characteristic parameter into a pre-established production dynamic prediction model, and performing history fitting through the production dynamic prediction model to obtain the second characteristic parameter.
3. The method according to claim 2, further comprising, after said history-fitting based on a pre-established production dynamic prediction model to obtain said second performance parameter: According to the change trend of the historical bottom hole flow pressure data and the historical casing pressure data, the historical bottom hole flow pressure data and the historical casing pressure data are prolonged, and bottom hole flow pressure data and casing pressure data are obtained; And inputting the bottom hole flow pressure data, the casing pressure data, the first physical property parameter and the second physical property parameter into the production dynamic prediction model, and predicting to obtain the at least two production capacity data through the production dynamic prediction model, wherein the first physical property parameter and the second physical property parameter change according to a preset rule.
4. The method according to claim 1, wherein the obtaining capacity evaluation data for evaluating capacity from the at least two kinds of capacity data based on the recoverable reserves includes: Determining, for the at least two types of capacity data, a first factor of influence of the type of capacity data on the recoverable reserves, wherein the first factor characterizes the magnitude of the influence of the type of capacity data on the recoverable reserves; and selecting the capacity data with the largest first factor from the at least two capacity data as the capacity evaluation data.
5. The method according to claim 1, wherein the step of obtaining sensitive parameters affecting the capacity evaluation data from the at least two reservoir physical parameters based on the capacity evaluation data comprises: Determining a second factor of the reservoir physical property parameters affecting the productivity evaluation data for the at least two reservoir physical property parameters, wherein the second factor characterizes the magnitude of the influence of the reservoir physical property parameters on the productivity evaluation value; And selecting the reservoir physical property parameter with the second factor larger than a first threshold value from the at least two reservoir physical property parameters as the sensitive parameter.
6. The method of claim 1, wherein when the sensitive parameter is at least two reservoir physical parameters, the determining the first target relationship between the capacity evaluation data and the sensitive parameter comprises: Constructing a first combination function of the sensitive parameters; And determining a third factor of the first combination function affecting the productivity evaluation data, if the third factor is larger than a second threshold, performing linear fitting on the first combination function and the productivity evaluation data to obtain the first target relation, and if the third factor is smaller than or equal to the second threshold, eliminating the sensitive parameter with the smallest second factor, and returning to the step of executing the first combination function for constructing the sensitive parameter, wherein the third factor characterizes the influence of the first combination function on the productivity evaluation value.
7. The method of claim 1, wherein when the sensitive parameter is a reservoir property parameter, the determining a first target relationship between the capacity evaluation data and the sensitive parameter comprises: And performing linear fitting on the productivity evaluation data and the sensitive parameters to obtain the first target relation.
8. The productivity evaluation method is characterized by being applied to a deep coal-bed gas well and comprising the following steps of: The productivity evaluation model determination method according to any one of claims 1 to 7, wherein the first target relationship and the second target relationship are obtained; Acquiring sensitive parameters of a new well; Determining productivity evaluation data of the new well according to the first target relation and the sensitive parameters of the new well, wherein the new well and the at least two old wells are positioned in the same block; and determining the recoverable reserves of the new well according to the productivity evaluation data of the new well and the second target relation.
9. A computer readable storage medium, having stored thereon a computer program comprising executable instructions which, when executed by a processor, implement the method of any of claims 1-7.
10. An electronic device comprising one or more processors and memory storing executable instructions for the processors that, when executed by the one or more processors, cause the one or more processors to implement the method of any of claims 1-7.

Description

Method, medium and electronic equipment for determining productivity evaluation model and evaluating productivity Technical Field The application relates to the technical field of coalbed methane, in particular to a method, a device, a medium and electronic equipment for determining a deep coalbed methane productivity evaluation model. Background The deep coal bed gas reservoir has the characteristics of low holes, low permeability, high stress and high free gas, the adsorbed gas gradually becomes desorbed gas in the production process, the original free gas and desorbed gas, water in the coal bed and coal dust can generate gas-water-coal dust three-phase seepage, the conventional oil gas well productivity equation with dynamic change of the permeability of the coal reservoir is difficult to contain the mechanism, and the method is not suitable for evaluating and predicting the productivity of the deep coal bed gas. At present, when evaluating the productivity of the coal-bed gas well, on one hand, the productivity potential of the coal-bed gas well can be evaluated according to static geological parameters, but the evaluation accuracy is poor, on the other hand, a horizontal well simulation geometric model of the coal-bed gas well can be established, productivity evaluation data of the horizontal well simulation geometric model are calculated first, and then final productivity evaluation data are obtained through fitting the productivity evaluation data in actual production, so that the productivity of the coal-bed gas well is evaluated, but the horizontal well simulation geometric model needs to be re-established in each evaluation of the productivity, the workload is heavy, and the method is not suitable for a new well because a new well does not have actual production data. Disclosure of Invention The embodiment of the application provides a method, a device, a medium and electronic equipment for determining a deep coal bed methane productivity evaluation model, which are used for solving the technical problem that the existing productivity evaluation data cannot be applied to the productivity prediction of a new well. Other features and advantages of the application will be apparent from the following detailed description, or may be learned by the practice of the application. According to a first aspect of the application, there is provided a productivity evaluation model determination method applied to a deep coal-bed gas well, comprising: Acquiring at least two reservoir physical parameters before casting of at least two old wells, and acquiring production dynamic information, wherein the production dynamic information comprises recoverable reserves and at least two productivity data; Acquiring capacity evaluation data for evaluating capacity from the at least two kinds of capacity data according to the recoverable reserves; According to the productivity evaluation data, sensitive parameters influencing the productivity evaluation data are obtained from the at least two reservoir physical parameters; Determining a first target relationship between the capacity evaluation data and the sensitive parameter, and determining a second target relationship between the capacity evaluation data and the recoverable reserves, wherein the first target relationship is used for determining the capacity evaluation data of a new well in the same block as the at least two old wells, and the second target relationship is used for determining the recoverable reserves of the new well in the same block as the at least two old wells. In some embodiments of the application, based on the foregoing aspects, the reservoir property parameters include a first property parameter and a second property parameter, and the obtaining at least two reservoir property parameters prior to the production of the at least two old wells includes: testing the at least two old wells to obtain the first physical parameters; Acquiring historical bottom hole flow pressure data, historical casing pressure data and historical productivity data of the at least two old wells, and acquiring initial values of the second physical parameters; And inputting the historical bottom hole flow pressure data, the historical casing pressure data, the historical capacity data and the initial value of the second characteristic parameter into a pre-established production dynamic prediction model, and performing history fitting through the production dynamic prediction model to obtain the second characteristic parameter. In some embodiments of the present application, based on the foregoing solution, after the performing history fitting according to the pre-established production dynamic prediction model, the obtaining the second performance parameter further includes: According to the change trend of the historical bottom hole flow pressure data and the historical casing pressure data, the historical bottom hole flow pressure data and the historical casing pressure