Coal bed gas typical reservoir gas content evaluation method based on well logging information
Through the constrained multivariate linear regression model based on logging information combined with lithologic and physical properties, the problem of inaccurate assessment of coalbed methane reserves is solved, and more accurate evaluation of coalbed methane gas content is achieved, and scientific resource allocation and mining decisions are supported.
Patent Information
- Application Number
- CN202510967734.5
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-07-14
- Publication Date
- 2025-09-02
AI Technical Summary
The existing technology does not fully consider the impact of geological complexity, lithologic properties and physical properties on coalbed methane gas content, resulting in inaccurate assessment of coalbed methane reserves and lacks sufficient constraints in the regression model, which affects the accuracy and reliability of the assessment.
Based on logging information, a constrained multivariate linear regression model is constructed, combined with lithologic indication matrix and physical constraint characteristics, and through screening and normalizing the logging data, an accurate coalbed methane reservoir gas content evaluation method is established, including obtaining logging data and core data, constructing lithologic indication matrix and physical constraint characteristics, establishing a multivariate linear regression model and solving it, and obtaining the coalbed methane gas content value.
It improves the accuracy and reliability of coalbed methane reserve assessment, can conduct accurate analysis for specific target layers, provide quantitative mining basis, and ensure the rationality of resource allocation and accuracy during the mining process.
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Figure CN120575853A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the technical field of coalbed methane evaluation, and in particular to a method for evaluating the gas content of a typical coalbed methane reservoir based on well logging information. Background Art
[0002] In recent years, with the continuous development of coalbed methane resource development technology, coalbed methane reserve assessment and mining technology have gradually become the research focus in the field of coalbed methane exploration. However, traditional coalbed methane evaluation methods, especially laboratory testing methods based on core sampling, have certain limitations. For example, laboratory testing relies on core samples. However, the core sampling process often faces problems such as coal core vibration, mud contamination, and gas leakage, which leads to distortion and inaccuracy of core data, thereby affecting the assessment accuracy of coalbed methane gas content.
[0003] Among them, the limitations of existing technologies include at least the following problems: existing technologies do not fully consider the influence of geological complexity and lithology and physical properties on coalbed methane content, and lack sufficient constraints and optimization means for the establishment of regression models, resulting in low prediction accuracy of the final model, which affects the reliability of coalbed methane reserve assessment results and makes it difficult to accurately reflect the actual storage capacity and mining potential of coalbed methane, which in turn easily leads to over- or under-estimation of coalbed methane resources, thereby affecting coalbed methane development. Summary of the Invention
[0004] In response to the shortcomings of the existing technology, the present invention provides a method for evaluating the gas content of typical coalbed methane reservoirs based on well logging information, which solves the problem that the existing technology does not fully consider the geological complexity, resulting in inaccurate coalbed methane reserve assessment.
[0005] To achieve the above objectives, the present invention is implemented through the following technical solutions: a method for evaluating the gas content of a typical coalbed methane reservoir based on well logging information, comprising the following steps: obtaining well logging data and core data of a set area and performing preprocessing; screening and processing based on the well logging data of the set area after preprocessing to obtain a screening set of the set area; constructing a lithologic indicator matrix and physical property constraint characteristics of the set area based on the core data of the set area after preprocessing; constructing a constrained multiple linear regression model of the set area based on the screening set, the lithologic indicator matrix, and the physical property constraint characteristics of the set area; solving the constrained multiple linear regression model of the set area to obtain a logging coefficient set; and obtaining target logging data of the target layer section to be evaluated, analyzing in combination with the logging coefficient set, and obtaining the coalbed gas content value of the target layer section to be evaluated.
[0006] Furthermore, the logging data includes natural gamma value, volume density value, acoustic time difference value, neutron logging value, and resistivity value; the core data includes mud content value, sandstone content value, carbonate content value, porosity value, permeability value, and density value; the screening set includes screening natural gamma value, screening volume density value, screening acoustic time difference value, screening neutron logging value, and screening resistivity value.
[0007] Furthermore, the specific steps for obtaining the screening set of the set area are as follows: normalizing the pre-processed logging data of the set area; obtaining the gas content value of the set area, and based on the gas content value of the set area and the normalized logging data of the set area, analyzing the natural gamma mutual information entropy value, volume density mutual information entropy value, acoustic time difference mutual information entropy value, neutron logging mutual information entropy value, and resistivity mutual information entropy value of the set area, and performing judgment analysis with the preset mutual information entropy value respectively to obtain the screening set of the set area.
[0008] Furthermore, the specific steps of the judgment analysis are as follows: if the natural gamma mutual information entropy value of the set area is higher than the preset mutual information entropy value, it is marked as the screening natural gamma value; if the natural gamma mutual information entropy value of the set area is lower than or equal to the preset mutual information entropy value, it is not marked.
[0009] Furthermore, the specific steps for constructing the lithologic indicator matrix and physical property constraint characteristics of the set area are as follows: based on the mud content value, sandstone content value, and carbonate rock content value of the set area, the lithologic indicator matrix of the set area is constructed; based on the porosity value, permeability value, and density value of the set area, the physical property constraint characteristics of the set area are constructed.
[0010] Furthermore, the logging coefficient set includes natural gamma coefficient, volume density coefficient, acoustic wave time difference coefficient, screened neutron logging coefficient, and resistivity coefficient, and the target logging data includes target natural gamma value, target volume density value, target acoustic wave time difference value, target neutron logging value, and target resistivity value.
[0011] Furthermore, the specific steps for obtaining the coal seam gas content value of the target layer to be evaluated are as follows: based on the target logging data and logging coefficient set of the target layer to be evaluated, analyzing the target interaction set of the target layer to be evaluated; based on the target interaction set of the target layer to be evaluated, analyzing the coal seam gas content value of the target layer to be evaluated.
[0012] Furthermore, the constrained multiple linear regression model of the set region is specifically: ;in, is the regression intercept term; The first The logging coefficient of the parameter, , is the total number of parameters in the screening set, To set the physical property constraint characteristics of the region, is the constraint coefficient of the physical property constraint feature of the set area.
[0013] The present invention has the following beneficial effects: (1) This method for evaluating the gas content of typical coalbed methane reservoirs based on well logging information makes the assessment of coalbed methane reserves more accurate by combining a multivariate regression model with a lithologic indicator matrix and physical property constraint characteristics. Specifically, by effectively combining and processing well logging data with core data, a constrained regression model is established, which enables in-depth analysis of the multi-dimensional characteristics of coal seams such as lithology and physical properties, and thus more accurately assesses the gas content of coalbed methane, thereby improving the accuracy and reliability of the assessment results and providing more scientific data support for subsequent coalbed methane development and resource allocation.
[0014] (2) This method for evaluating the gas content of typical coalbed methane reservoirs based on well logging information can accurately analyze a specific target layer segment and predict the coalbed methane gas content value of the layer segment by combining the target well logging data and the well logging coefficient set, thereby providing a quantitative basis for coalbed methane extraction at different depths. The well logging data is normalized and important parameters are screened out using the mutual information entropy value, thereby effectively improving the spatial distribution capability of coalbed methane evaluation and ensuring the rational allocation of resources during the coalbed methane development process.
[0015] Of course, any product implementing the present invention does not necessarily need to achieve all of the advantages described above at the same time. BRIEF DESCRIPTION OF THE DRAWINGS
[0016] Figure 1 This is a flow chart of a method for evaluating the gas content of a typical coalbed methane reservoir based on well logging information according to the present invention.
[0017] Figure 2 The present invention is a flowchart of the specific steps for obtaining the coal seam gas content value of the target layer to be evaluated in a typical coal seam gas reservoir gas content evaluation method based on well logging information. DETAILED DESCRIPTION
[0018] See also Figure 1 The embodiment of the present invention provides a technical solution: a method for evaluating the gas content of a typical coalbed methane reservoir based on well logging information, comprising the following steps: obtaining well logging data and core data of a set area, and performing preprocessing (i.e., using a B-spline interpolation algorithm to eliminate the depth difference between the well logging data and the core data, i.e., obtaining the core sampling depth). The specific formula is as follows: ,in, is the corrected logging depth; is the core sampling depth; is a cubic B-spline interpolation function); based on the pre-processed well logging data of the set area, a screening set of the set area is obtained; based on the pre-processed core data of the set area, a lithologic indicator matrix and physical property constraint characteristics of the set area are constructed; based on the screening set, the lithologic indicator matrix, and the physical property constraint characteristics of the set area, a constrained multiple linear regression model of the set area is constructed (i.e., a multiple linear regression model is established based on the screening set, and the lithologic indicator matrix and physical property constraint characteristics are added to the multiple linear regression model as model constraints to ensure that the model prediction conforms to physical reality, and finally a constrained multiple linear regression model is obtained); the constrained multiple linear regression model of the set area is solved (using the Lagrange multiplier method) to obtain a logging coefficient set, and the model is validated in three stages: cross-validation, blind well test set prediction, and virtual well disturbance test to test the spatial generalization and noise resistance of the model. Finally, gas content is predicted and a gas content planar distribution map is drawn; target logging data of the target layer to be evaluated are obtained, and analyzed in combination with the logging coefficient set to obtain the coal seam gas content value of the target layer to be evaluated.
[0019] The constrained multiple linear regression model of the set area is specifically: ;in, is the regression intercept term; The first The logging coefficient of the parameter, , is the total number of parameters in the screening set, To set the physical property constraint characteristics of the region, is the constraint coefficient of the physical property constraint characteristics of the set area, , is the constraint coefficient matrix, is the constraint boundary vector.
[0020] Well logging data include natural gamma value (obtained by direct measurement using gamma ray detection instruments during drilling and uploaded to the database), volume density value (obtained by gamma ray density logging tools, which calculate the volume density value of the rock formation by measuring the change in electron density in the rock formation and uploaded to the database), acoustic time difference value (obtained by acoustic logging tools, which calculate the value by emitting sound waves and recording the time it takes for the sound waves to propagate in the formation and uploaded to the database), neutron logging value (obtained by neutron logging tools and uploaded to the database), resistivity value (obtained by resistivity logging tools, which calculate the resistivity value of the rock formation by measuring the propagation resistance of current in the formation and uploaded to the database), and the core data include mud quality. Content value (obtained through core analysis, such as X-ray diffraction analysis, and the results are uploaded to the data), sandstone content value (obtained through core analysis, using X-ray diffraction analysis, and the results are uploaded to the data), carbonate rock content value (obtained through core analysis, using X-ray diffraction analysis, and the results are uploaded to the data), porosity value (obtained through laboratory gas displacement method, water saturation method, or through neutron logging and density logging, and the results are uploaded to the data), permeability value (obtained through laboratory gas permeability test, pressure decay method, and the results are uploaded to the data), density value (obtained through laboratory mass and volume determination method, or through gamma-ray density logging, and the results are uploaded to the data).
[0021] The specific steps for constructing the lithologic indicator matrix and physical property constraint characteristics of the set area are as follows: Based on the mud content value, sandstone content value, and carbonate rock content value of the set area, the lithologic indicator matrix of the set area is constructed, which is specifically: ,in, is the lithologic indicator matrix of the set area, is the mud content value of the set area, is the sandstone content value of the set area, is the carbonate rock content value of the set area; based on the porosity value, permeability value, and density value of the set area, the physical property constraint characteristics of the set area are constructed, which are specifically: .
[0022] Specifically, the screening set includes screening natural gamma values, screening volume density values, screening acoustic time difference values, screening neutron logging values, and screening resistivity values.
[0023] The specific steps for obtaining the screening set of the set area are as follows: normalize the pre-processed well logging data of the set area (Tukey weighting function can be used for normalization, and the specific formula is as follows: , is a certain logging parameter in the logging data of the set area after normalization; is the median of the logging parameters in the logging data of the set area, The first and third quartiles of the logging parameters in the logging data of the set area are obtained respectively; the gas content value of the set area is obtained (obtained through core experiments, in which the core samples are heated to release gas, and the total desorption gas content of the core is measured, which is used as the actual gas content), and the sliding window is defined (i.e. , is the center depth, is a multiple of the window radius, As the benchmark step length), based on the gas content value of the set area in the window and the normalized logging data of the set area, analyze the natural gamma mutual information entropy value (i.e. the mutual information entropy of natural gamma and gas content), volume density mutual information entropy value, acoustic time difference mutual information entropy value, neutron logging mutual information entropy value, resistivity mutual information entropy value of the set area (calculate the natural gamma information entropy value, volume density information entropy value, acoustic time difference information entropy value, neutron logging information entropy value, resistivity information entropy value, and gas content information entropy value based on the information entropy formula, and then calculate the natural gamma information entropy value , volume density information entropy value, acoustic wave time difference information entropy value, neutron logging information entropy value, resistivity information entropy value and gas content information entropy value are analyzed to obtain corresponding joint entropy value), and are judged and analyzed with preset mutual information entropy value to obtain the screening set of the set area. The specific formulas of natural gamma mutual information entropy value, volume density mutual information entropy value, acoustic wave time difference mutual information entropy value, neutron logging mutual information entropy value, and resistivity mutual information entropy value are logically consistent. Here, taking natural gamma mutual information entropy value as an example, the specific formula of natural gamma mutual information entropy value of the set area is as follows: ,in is the natural gamma mutual information entropy value of the set area, They are the natural gamma information entropy value and gas content information entropy value of the set area respectively; is the natural gamma joint entropy of the set area.
[0024] The specific steps of judgment and analysis are as follows (here the judgment and analysis steps of the natural gamma mutual information entropy value are taken as an example): if the natural gamma mutual information entropy value of the set area is higher than the preset mutual information entropy value (such as 0.35), it is marked as a screening natural gamma value; if the natural gamma mutual information entropy value of the set area is lower than or equal to the preset mutual information entropy value, it is not marked.
[0025] In this implementation plan, normalization processing and mutual information entropy analysis are used to effectively screen out logging parameters that are closely related to coalbed methane content, and the accuracy of coalbed methane reserve assessment is improved. Secondly, Tukey weighted function normalization eliminates the dimensional differences between different logging parameters, so that the influence of each parameter can be compared equally. The mutual information entropy value is calculated through a sliding window, and the correlation strength between each logging parameter and coalbed methane content is further quantified to ensure the scientific nature of the screening process, so that logging data that have a greater impact on gas content can be accurately screened out, thereby significantly improving the reliability and accuracy of the assessment results.
[0026] Specifically, the logging coefficient set includes the natural gamma coefficient, volume density coefficient, acoustic wave time difference coefficient, screened neutron logging coefficient, and resistivity coefficient; the target logging data includes the target natural gamma value, target volume density value, target acoustic wave time difference value, target neutron logging value, and target resistivity value.
[0027] like Figure 2 As shown, the specific steps for obtaining the coal seam gas content value of the target layer to be evaluated are as follows: based on the target logging data and logging coefficient set of the target layer to be evaluated, the target interaction set of the target layer to be evaluated is analyzed, specifically: the target natural gamma value, target volume density value, target acoustic wave time difference value, target neutron logging value, and target resistivity value are multiplied with the natural gamma coefficient, volume density coefficient, acoustic wave time difference coefficient, screened neutron logging coefficient, and resistivity coefficient respectively to obtain the target natural gamma interaction value, target volume density interaction value, target acoustic wave time difference interaction value, target neutron logging interaction value, and target resistivity interaction value; based on the target interaction set of the target layer to be evaluated, the coal seam gas content value of the target layer to be evaluated is analyzed, specifically: the target natural gamma interaction value, target volume density interaction value, target acoustic wave time difference interaction value, target neutron logging interaction value, and target resistivity interaction value of the target layer to be evaluated are summed, and the result obtained is the coal seam gas content value.
[0028] In this implementation scheme, the target logging data and the logging coefficient set are interactively analyzed to accurately calculate the coalbed gas content of the target layer to be evaluated, and each logging parameter is multiplied by the corresponding coefficient to quantify the contribution of each logging parameter to the coalbed methane content. By summing the interactive values and combining the influence of multiple parameters, a comprehensive coalbed methane content is obtained, thereby fully considering the influence of different logging parameters on the gas content, and improving the precision and accuracy of the evaluation through interactive analysis.
[0029] Although the preferred embodiments of the present invention have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.
[0030] Obviously, those skilled in the art may make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if such changes and modifications fall within the scope of the claims and their equivalents, the present invention is intended to include such changes and modifications.
Claims
1. A method for evaluating the gas content of a typical coalbed methane reservoir based on well logging information, characterized in that: The following steps are involved: Obtain well logging data and core data in the set area and perform preprocessing; Performing screening processing based on the pre-processed well logging data of the set area to obtain a screening set of the set area; Based on the pre-processed core data of the set area, the lithology indicator matrix and physical property constraint characteristics of the set area are constructed; Construct a constrained multiple linear regression model for the set area based on the screening set, lithologic indicator matrix, and physical property constraint characteristics of the set area; Solve the constrained multiple linear regression model of the set area to obtain the logging coefficient set; The target logging data of the target layer to be evaluated is obtained, and the coal seam gas content value of the target layer to be evaluated is obtained by combining the logging coefficient set for analysis.
2. The method for evaluating the gas content of a typical coalbed methane reservoir based on well logging information according to claim 1, characterized in that: The logging data includes natural gamma value, volume density value, acoustic wave time difference value, neutron logging value, and resistivity value; the core data includes mud content value, sandstone content value, carbonate rock content value, porosity value, permeability value, and density value; the screening set includes screening natural gamma value, screening volume density value, screening acoustic wave time difference value, screening neutron logging value, and screening resistivity value.
3. The method for evaluating the gas content of a typical coalbed methane reservoir based on well logging information according to claim 2, characterized in that: The specific steps to obtain the filter set of the set area are as follows: Normalize the pre-processed well logging data of the set area; The gas content value of the set area is obtained. Based on the gas content value of the set area and the normalized logging data of the set area, the natural gamma ray mutual information entropy value, volume density mutual information entropy value, acoustic wave time difference mutual information entropy value, neutron logging mutual information entropy value, and resistivity mutual information entropy value of the set area are analyzed, and judgment and analysis are performed on them respectively compared with the preset mutual information entropy value to obtain the screening set of the set area.
4. The method for evaluating the gas content of a typical coalbed methane reservoir based on well logging information according to claim 3, characterized in that: The specific steps of judgment analysis are as follows: If the natural gamma mutual information entropy value of the set area is higher than the preset mutual information entropy value, it is marked as a screening natural gamma value; If the natural gamma mutual information entropy value of the set area is lower than or equal to the preset mutual information entropy value, it will not be marked.
5. The method for evaluating the gas content of a typical coalbed methane reservoir based on well logging information according to claim 2, characterized in that: The specific steps for constructing the lithologic indicator matrix and physical property constraint characteristics of the set area are as follows: Based on the mud content value, sandstone content value, and carbonate rock content value of the set area, a lithology indicator matrix of the set area is constructed; Based on the porosity, permeability, and density values of the set area, the physical property constraint characteristics of the set area are constructed.
6. The method for evaluating the gas content of a typical coalbed methane reservoir based on well logging information according to claim 2, characterized in that: The logging coefficient set includes the natural gamma coefficient, volume density coefficient, acoustic wave transit time coefficient, screened neutron logging coefficient, and resistivity coefficient. The target logging data includes the target natural gamma value, target volume density value, target acoustic wave transit time value, target neutron logging value, and target resistivity value.
7. The method for evaluating the gas content of a typical coalbed methane reservoir based on well logging information according to claim 6, characterized in that: The specific steps to obtain the coal seam gas content value of the target layer to be evaluated are as follows: Analyze the target interaction set of the target layer to be evaluated based on the target logging data and logging coefficient set of the target layer to be evaluated; Based on the target interaction set of the target layer to be evaluated, the coal seam gas content value of the target layer to be evaluated is analyzed.
8. The method for evaluating the gas content of a typical coalbed methane reservoir based on well logging information according to claim 1, characterized in that: The constrained multiple linear regression model of the set area is specifically: ； in, is the regression intercept term; The first The logging coefficient of the parameter, , is the total number of parameters in the screening set, To set the physical property constraint characteristics of the region, is the constraint coefficient of the physical property constraint feature of the set area.
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