Intelligent prediction method and system for coalbed methane exploitation quantity

Abstract

The invention relates to the field of coalbed methane exploitation, and particularly discloses a coalbed methane exploitation amount intelligent prediction method and system.The method comprises the steps that all sampling points are arranged in a coalbed methane exploitation area to be predicted and surveyed, geological information of the coalbed methane exploitation area to be predicted is obtained, and geological information of all coalbed methane exploited areas in the history is obtained; comparing the two regions, analyzing a comprehensive similarity index between each coalbed methane exploited region and the coalbed methane exploited region to be predicted in history, and screening each contrast coalbed methane exploited region; acquiring the coalbed methane exploitation quantity of each contrast coalbed methane exploitation area, and estimating the coalbed methane exploitation quantity of the coalbed methane exploitation area to be predicted; obtaining the coalbed methane yield trend of each control coalbed methane exploited area, and estimating the coalbed methane yield trend of the coalbed methane exploited area to be predicted; and the coal bed gas exploitation amount is predicted based on the exploitation data of the exploited coal bed gas area with similar geological conditions, so that the reliability of the prediction result is improved.

Description

Technical Field

[0001] The invention relates to the field of coalbed methane mining, and particularly to a method and system for intelligently predicting coalbed methane mining volume. Background Art

[0002] As an unconventional natural gas resource, coalbed methane is high-quality, efficient and clean, and can effectively replace highly polluting coal, and even other energy sources such as oil and minerals. The development and utilization of coalbed methane can not only increase energy supply, but also reduce environmental pollution and promote safe production in coal mines.

[0003] The development of coalbed methane development and utilization technology has made the demand for coalbed methane extraction volume prediction more and more urgent. Through scientific and reasonable division of coalbed methane accumulation units, improved coalbed methane content prediction and recovery rate determination methods, the recoverability of coalbed methane resources can be quantitatively evaluated, providing basic information and scientific basis for the formulation of medium- and long-term energy development plans and energy resource exploration and development plans.

[0004] However, the existing coalbed methane production prediction methods still have some limitations and shortcomings in practical applications.

[0005] For example, an existing Chinese patent with authorization announcement number CN117967252B discloses a coalbed methane extraction method for deep coal reservoirs based on gas volume prediction, including the following steps: S1: Conduct geological survey on the target coal reservoir to obtain its geological properties; S2: Divide the same coal reservoir into several mining areas according to different geological properties; S3: Predict the adsorbed gas volume for each mining area respectively; S4: Formulate different mining strategies for each mining area according to the predicted adsorbed gas volume of each mining area; S5: Mine the corresponding mining areas according to different mining strategies to obtain actual gas production, and compare the actual gas production with the corresponding predicted adsorbed gas volume to verify the accuracy of the prediction.

[0006] For example, the existing Chinese patent with the publication number CN115860197A discloses a coalbed methane production prediction method and system based on data-driven, firstly, obtaining the coalbed methane dynamic production history data of the production well to be predicted and the coalbed methane production prediction related data of the production well to be predicted; according to the coalbed methane dynamic production history data, determining the production well type to which the production well to be predicted belongs; then selecting the trained coalbed methane production prediction model corresponding to the production well type as the target model; finally, inputting the coalbed methane production prediction related data of the production well to be predicted into the target model to obtain the production data of the production well to be predicted. This invention obtains the most easily obtained and most valuable monitoring data at the coalbed methane mining site, and calculates the coalbed methane production based on this part of the data and the production prediction model trained by the machine learning method, thereby reducing the data acquisition time and improving the coalbed methane production prediction speed.

[0007] The above patent has the following deficiencies: First, it does not take into account that the insufficient representativeness of the relevant data collected for predicting coalbed methane production, such as geological data, may affect the accuracy of the coalbed methane production prediction results, thereby failing to improve the accuracy of the coalbed methane production prediction results from the source.

[0008] Secondly, only the cumulative coalbed methane production volume is predicted, without further prediction of the coalbed methane production process information, such as the coalbed methane production trend curve during the production process. This is not conducive to energy companies understanding the coalbed methane production situation at different stages in the future in advance, planning production activities more reasonably and better planning energy structure. Summary of the invention

[0009] In view of this, in order to solve the problems raised in the above background technology, a method and system for intelligent prediction of coalbed methane production is proposed.

[0010] The technical solution adopted by the present invention to solve its technical problems is: in the first aspect, the present invention provides a method for intelligent prediction of coalbed methane production, comprising the following steps: Step 1, collection of geological information of the coalbed methane production area: setting up sampling points in the coalbed methane production area to be predicted and conducting surveys to obtain geological information of the coalbed methane production area to be predicted, wherein the geological information includes coal seam geological information, gas content-related information, and hydrogeological information.

[0011] Step 2: Obtain geological information of historical coalbed methane exploited areas: Obtain geological information of historical coalbed methane exploited areas.

[0012] Step 3. Similarity analysis of historical coalbed methane mined areas: Compare the geological information of each historical coalbed methane mined area with the geological information of the coalbed methane mining area to be predicted, analyze the coal seam geological similarity coefficient, gas content similarity coefficient, and hydrogeological similarity coefficient of each historical coalbed methane mined area and the coalbed methane mining area to be predicted, and further analyze the comprehensive similarity index of each historical coalbed methane mined area and the coalbed methane mining area to be predicted.

[0013] Step 4. Estimation of coalbed methane production in coalbed methane production areas: Based on the comprehensive similarity index of each historical coalbed methane produced area and the coalbed methane production area to be predicted, obtain each reference coalbed methane produced area and the coalbed methane production of each reference coalbed methane produced area, further analyze the estimated coalbed methane production in the coalbed methane production area to be predicted, and provide feedback.

[0014] Step 5. Estimation of coalbed methane production trend in coalbed methane mining areas: Obtain the coalbed methane production trend curves of each reference coalbed methane mining area, further analyze the estimated coalbed methane production trend curve of the coalbed methane mining area to be predicted, and provide feedback.

[0015] In the second aspect, the present invention also provides an intelligent prediction system for coalbed methane production, including: a coalbed methane production area geological information collection module: used to deploy various sampling points in the coalbed methane production area to be predicted and conduct surveys to obtain geological information of the coalbed methane production area to be predicted, wherein the geological information includes coal seam geological information, gas content-related information, and hydrogeological information.

[0016] The module for acquiring geological information of historical coalbed methane exploited areas is used to acquire geological information of historical coalbed methane exploited areas.

[0017] Similarity analysis module for historical coalbed methane mined areas: used to compare the geological information of historical coalbed methane mined areas with the geological information of coalbed methane mined areas to be predicted, analyze the coal seam geological similarity coefficient, gas content similarity coefficient, and hydrogeological similarity coefficient of historical coalbed methane mined areas and coalbed methane mined areas to be predicted, and further analyze the comprehensive similarity index of historical coalbed methane mined areas and coalbed methane mined areas to be predicted.

[0018] Coalbed methane production volume estimation module for coalbed methane production areas: used to obtain each reference coalbed methane produced area and the coalbed methane production volume of each reference coalbed methane produced area based on the comprehensive similarity index of each historical coalbed methane produced area and the coalbed methane production area to be predicted, further analyze the estimated coalbed methane production volume of the coalbed methane production area to be predicted, and provide feedback.

[0019] Coalbed methane production trend estimation module in coalbed methane mining area: used to obtain the coalbed methane production trend curve of each reference coalbed methane mined area, further analyze the estimated coalbed methane production trend curve of the coalbed methane mining area to be predicted, and provide feedback.

[0020] Database: used to store geological information and production records of each historical coalbed methane mining area.

[0021] Compared with the prior art, the beneficial effects of the present invention are as follows: 1. When conducting geological exploration in the predicted coalbed methane mining area, the sampling points arranged by the present invention cover the entire exploration area in the horizontal direction to avoid being concentrated in a certain local area. In the vertical direction, the thickness change of the coal seam is considered, and layered sampling is carried out from the top plate to the bottom plate of the coal seam, which is conducive to comprehensively reflecting the spatial characteristics of the coal seam, improving the representativeness of the collected geological data, and thus improving the accuracy of the predicted coalbed methane mining volume results based on geological data.

[0022] 2. The present invention evaluates the similarity between historical coalbed methane mined areas and coalbed methane mined areas to be predicted through multiple indicators in multiple dimensions such as coal seam geology, gas content, hydrogeology, etc., screens coalbed methane mined areas with similar geological conditions and high reference value, and predicts the coalbed methane mining volume of the coalbed methane mining areas based on their coalbed methane mining volume, thereby improving the reliability of the coalbed methane mining volume prediction results.

[0023] 3. The present invention estimates the coalbed methane production trend of the coalbed methane mining area to be predicted based on the coalbed methane production trend of each coalbed methane mining area with similar geological conditions to the coalbed methane mining area to be predicted, so that energy companies can understand the coalbed methane production situation at different stages in the future in advance, thereby planning production activities more reasonably and better planning energy structure. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for describing the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0025] Figure 1 It is a schematic diagram of the method flow of the present invention.

[0026] Figure 2 This is a system module connection diagram of the present invention.

[0027] Figure 3 It is a structural frame diagram of the present invention for evaluating the similarity between each historical coalbed methane exploitation area and the coalbed methane exploitation area to be predicted. DETAILED DESCRIPTION

[0028] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0029] See also Figure 1 and Figure 3 As shown, the first aspect of the present invention provides a method for intelligently predicting coalbed methane production, comprising the following steps: Step 1, collecting geological information of the coalbed methane production area: setting up sampling points in the coalbed methane production area to be predicted and conducting surveys to obtain geological information of the coalbed methane production area to be predicted, wherein the geological information includes coal seam geological information, gas content-related information, and hydrogeological information.

[0030] Exemplarily, the specific analysis process of step one is: obtaining a regional division method for the coalbed methane production area to be predicted and dividing it to obtain sub-areas of the coalbed methane production area to be predicted.

[0031] The center point of each sub-area in the coalbed methane production area to be predicted is recorded as a first-class sampling point.

[0032] According to the preset equal depth principle, sampling points are arranged vertically between the top and bottom plates of the coal seams at the center points of each sub-area in the predicted coalbed methane mining area, and they are recorded as Class II sampling points.

[0033] The first-class sampling points and the second-class sampling points are summarized to obtain the sampling points of the coalbed methane mining area to be predicted and conduct surveys to obtain the coal seam geological information, gas content-related information, and hydrogeological information of the coalbed methane mining area to be predicted.

[0034] As a preferred solution, a regional division method for the coalbed methane mining area to be predicted is obtained. The specific method is: obtain the shape and scale of the coalbed methane mining area to be predicted, set the regional division methods corresponding to each shape and scale of the coalbed methane mining area, and screen the regional division methods for the coalbed methane mining area to be predicted.

[0035] As a preferred solution, the shape and scale of the coalbed methane production area to be predicted refers to the shape and area of ​​the area enclosed by the boundary line of the coalbed methane production area to be predicted.

[0036] As a preferred solution, the area division method includes but is not limited to: grid division or regular geometric figure division.

[0037] In a specific embodiment, the predicted coalbed methane production area is divided into a grid according to a preset equal area principle.

[0038] As a preferred solution, the survey data of each sampling point in the coalbed methane mining area to be predicted is processed and analyzed in a series of processes to obtain the geological information of the coalbed methane mining area to be predicted.

[0039] In this embodiment, when the present invention conducts geological exploration in the predicted coalbed methane extraction area, the arranged sampling points cover the entire exploration area in the horizontal direction to avoid being concentrated in a certain local area, and consider the thickness change of the coal seam in the vertical direction, and perform layered sampling from the top plate to the bottom plate of the coal seam, which is conducive to comprehensively reflecting the spatial characteristics of the coal seam, improving the representativeness of the collected geological data, and thus improving the accuracy of the predicted coalbed methane extraction results based on geological data.

[0040] Exemplarily, the coal seam geological information of the coalbed methane mining area to be predicted in step one includes coal rock type, coal seam thickness, coal seam burial depth, coal quality characteristic information, and coal seam structural information, wherein the coal quality characteristic information includes porosity, permeability, and the content of various chemical components in coal; the coal seam structural information includes the type, axial direction, and dip angle of folds, as well as the type, fault distance, and combination of faults; the gas content-related information includes the original gas content of the coal seam and the content of various gas components in coalbed methane; the hydrogeological information includes the groundwater level, water flow direction, and flow rate.

[0041] As a preferred solution, the coal type includes but is not limited to: bright coal, semi-bright coal, semi-dark coal and dark coal, etc. The coal type can be determined by observing the content and morphology of the microscopic components of the coal sample under a microscope.

[0042] As a preferred solution, the coal seam thickness refers to the vertical distance between the top and bottom of the coal seam. The coal seam thickness can be obtained by drilling, geophysical logging, tunneling, three-dimensional seismic exploration, and other methods.

[0043] As a preferred solution, the coal seam burial depth refers to the vertical distance between the coal seam and the ground surface. The coal seam burial depth can be obtained by geological exploration drilling method, geophysical exploration method, inference method using existing geological data, and other methods.

[0044] As a preferred solution, the types of chemical components in the coal in the coal quality characteristic information include but are not limited to: moisture, ash, volatile matter, fixed carbon, etc. The coal quality characteristic information can be obtained by laboratory analysis of coal samples or on-site rapid detection equipment.

[0045] As a preferred solution, the fold types in the coal seam structural information include anticlines and synclines, the fault types include normal faults, reverse faults, and strike-slip faults, and the fault combinations include parallel arrangement, echelon arrangement, and grid arrangement. The coal seam structural information can be obtained through on-site geological surveying or geophysical exploration methods such as seismic exploration and electrical exploration.

[0046] As a preferred solution, the original gas content of the coal seam can be obtained by conducting an on-site desorption experiment on the coal core taken out from underground during the drilling process.

[0047] As a preferred solution, the various gas components of the coalbed methane include but are not limited to: methane, carbon dioxide, nitrogen, etc. The gas samples collected from the borehole can be measured or analyzed by a gas analyzer or a gas chromatograph to obtain the contents of various gas components of the coalbed methane.

[0048] As a preferred solution, the groundwater level, flow direction and flow rate can be obtained through on-site hydrogeological drilling and water level monitoring.

[0049] Step 2: Obtain geological information of historical coalbed methane exploited areas: Obtain geological information of historical coalbed methane exploited areas.

[0050] As a preferred solution, the method for obtaining geological information of each historical coalbed methane mining area is: extracting geological information of each historical coalbed methane mining area stored in the database. It should be noted that the geological information of each historical coalbed methane mining area is consistent with the geological information of the coalbed methane mining area to be predicted.

[0051] As a preferred solution, geological information of each historical coalbed methane exploited area is obtained during the exploration stage of each historical coalbed methane exploited area.

[0052] Step 3. Similarity analysis of historical coalbed methane mined areas: Compare the geological information of each historical coalbed methane mined area with the geological information of the coalbed methane mining area to be predicted, analyze the coal seam geological similarity coefficient, gas content similarity coefficient, and hydrogeological similarity coefficient of each historical coalbed methane mined area and the coalbed methane mining area to be predicted, and further analyze the comprehensive similarity index of each historical coalbed methane mined area and the coalbed methane mining area to be predicted.

[0053] Exemplarily, the specific analysis process of step three includes: S1: based on the geological information of each coalbed methane exploited area in history, obtain the coal seam geological information of each coalbed methane exploited area in history, and further obtain the coal rock type, coal seam thickness, coal seam burial depth, coal quality characteristics information, and coal seam structure information of each coalbed methane exploited area in history.

[0054] S2: Compare the coal rock types of each coalbed methane mining area in history with the coal rock types of the coalbed methane mining area to be predicted, set the coal rock type similarity factors corresponding to the same and different coal rock types, and screen out the coal rock type similarity factors of each coalbed methane mining area in history, which are recorded as , Indicates the history The number of the coal-bed methane mining area, .

[0055] In a specific embodiment, the coal rock type similarity factor corresponding to the same coal rock type is 1, and the coal rock type similarity factor corresponding to different coal rock types is 0.

[0056] S3: Compare the coal seam thickness of each coal seam gas mining area in history with the coal seam thickness of the coal seam gas mining area to be predicted, obtain the relative deviation of the coal seam thickness of each coal seam gas mining area in history, substitute it into the preset relationship function between the relative deviation of the coal seam thickness and the coal seam thickness similarity factor, and obtain the coal seam thickness similarity factor of each coal seam gas mining area in history, which is recorded as .

[0057] As a preferred solution, the relative deviation of the coal seam thickness in each historical coal seam methane exploited area refers to the absolute value of the difference between the coal seam thickness in each historical coal seam methane exploited area and the coal seam thickness in the coal seam methane exploitation area to be predicted.

[0058] As a preferred solution, the relationship function between the preset relative deviation of coal seam thickness and the coal seam thickness similarity factor is a negative correlation function, that is, the larger the relative deviation of coal seam thickness, the smaller the coal seam thickness similarity factor.

[0059] S4: Compare the coal seam depths of each historical coal seam gas mining area with the coal seam depths of the coal seam gas mining area to be predicted, analyze the similarity factors of the coal seam depths of each historical coal seam gas mining area, and record them as .

[0060] As an optimal solution, the similarity factors of coal seam burial depths in various historical coal seam methane mined areas are analyzed. The specific method is: obtain the absolute value of the difference between the coal seam burial depths in various historical coal seam methane mined areas and the coal seam burial depths in the coal seam methane mining area to be predicted, and record it as the relative deviation of the coal seam burial depths in various historical coal seam methane mined areas; substitute the relative deviation of the coal seam burial depths in various historical coal seam methane mined areas into the preset relationship function between the relative deviation of the coal seam burial depth and the coal seam burial depth similarity factor, and obtain the coal seam burial depth similarity factor in various historical coal seam methane mined areas.

[0061] As a preferred solution, the relationship function between the preset relative deviation of coal seam burial depth and the coal seam burial depth similarity factor is a negative correlation function, that is, the greater the relative deviation of coal seam burial depth, the smaller the coal seam burial depth similarity factor.

[0062] S5: Based on the coal quality characteristics information of each coalbed methane mining area in history, the porosity, permeability, and various chemical components in the coal of each coalbed methane mining area in history are obtained, and the porosity, permeability, and various chemical components in the coal of the coalbed methane mining area to be predicted are compared one by one, and the coal quality characteristics similarity factors of each coalbed methane mining area in history are analyzed and recorded as .

[0063] As a preferred solution, the similarity factors of coal quality characteristics of each coalbed methane mining area in history are analyzed. The specific method is: the porosity, permeability, and various chemical components in the coal of each coalbed methane mining area in history are recorded as , Indicates the first The number of the chemical component, .

[0064] The porosity, permeability, and various chemical components in the coal in the predicted coalbed methane mining area are recorded as .

[0065] By analyzing the formula Obtain the similarity factors of coal quality characteristics of each coalbed methane mining area in history ,in represents a natural constant, Respectively represent the preset porosity relative deviation, permeability relative deviation, The threshold value of relative deviation of chemical component content.

[0066] S6: Based on the coal seam structural information of each coal seam gas mining area in history, the types, axes, dip angles, fault types, fault distances, and combination methods of the folds in each coal seam gas mining area in history are obtained, and the types, axes, dip angles, fault types, fault distances, and combination methods of the folds in the coal seam gas mining area to be predicted are compared one by one, and the coal seam structural similarity factors of each coal seam gas mining area in history are analyzed and recorded as .

[0067] S7: By analyzing the formula Obtain the coal seam geological similarity coefficient between the historical coal seam gas mining areas and the coal seam gas mining areas to be predicted ,in They represent the weights of the similarity factors of the preset coal rock type, coal seam thickness, coal seam burial depth, coal quality characteristics, and coal seam structure. .

[0068] As a preferred solution, the coal seam structural similarity factors of each historical coalbed methane exploited area are analyzed. The specific method is: the fold type, fold axis, fault type, and fault combination mode of each historical coalbed methane exploited area are compared with the fold type, fold axis, fault type, and fault combination mode of the coalbed methane exploitation area to be predicted, and the fold type similarity factors with the same and different corresponding fold types, the fold axis similarity factors with the same and different corresponding fold axes, the fault type similarity factors with the same and different corresponding fault types, and the fault combination mode similarity factors with the same and different corresponding fault combinations are set respectively, and the fold type similarity factors, fold axis similarity factors, fault type similarity factors, and fault combination mode similarity factors of each historical coalbed methane exploited area are screened and recorded as .

[0069] The inclination angles of each coalbed methane mining area in history are compared with the inclination angles of the coalbed methane mining area to be predicted, and the relative deviations of the inclination angles of each coalbed methane mining area in history are obtained. The relative deviations are substituted into the relationship function between the preset relative deviations of the inclination angles and the similarity factors of the inclination angles, and the similarity factors of the inclination angles of each coalbed methane mining area in history are obtained, which are recorded as .

[0070] The fault distance of each coalbed methane mining area in history is compared with the fault distance of the coalbed methane mining area to be predicted, and the relative deviation of the fault distance of each coalbed methane mining area in history is obtained. It is substituted into the relationship function between the preset relative deviation of the fault distance and the fault distance similarity factor to obtain the fault distance similarity factor of each coalbed methane mining area in history, which is recorded as .

[0071] By analyzing the formula Obtain the coal seam structural similarity factor of each coal seam gas mining area in history .

[0072] As a preferred scheme, the threshold values ​​of the relative deviation of porosity, the relative deviation of permeability, and the relative deviation of the contents of various chemical components in coal are set based on the actual needs when evaluating the similarity in coal quality characteristics between historical coalbed methane mining areas and the coalbed methane mining areas to be predicted.

[0073] In a specific embodiment, the fold type similarity factors corresponding to the same and different fold types are 1 and 0 respectively.

[0074] In a specific embodiment, the axial similarity factors of the folds corresponding to the same and different axial directions of the folds are 1 and 0 respectively.

[0075] In a specific embodiment, the fault type similarity factors corresponding to the same and different fault types are 1 and 0 respectively.

[0076] In a specific embodiment, the similarity factors of the fault combinations corresponding to the same and different fault combinations are 1 and 0 respectively.

[0077] As a preferred solution, the relative deviation of the inclination angle of each historical coalbed methane exploited area refers to the absolute value of the difference between the inclination angle of each historical coalbed methane exploited area and the inclination angle of the coalbed methane exploitation area to be predicted.

[0078] As a preferred solution, the relationship function between the relative deviation of the pitch angle and the similarity factor of the pitch angle is a negative correlation function, that is, the larger the relative deviation of the pitch angle, the smaller the similarity factor of the pitch angle.

[0079] As a preferred solution, the relative deviation of the fault distance of each historical coalbed methane exploited area refers to the absolute value of the difference between the fault distance of each historical coalbed methane exploited area and the fault distance of the coalbed methane exploitation area to be predicted.

[0080] As a preferred solution, the relationship function between the relative deviation of the fault distance and the fault distance similarity factor is a negative correlation function, that is, the larger the relative deviation of the fault distance is, the smaller the fault distance similarity factor is.

[0081] As a preferred solution, the weights of the similarity factors of coal rock type, coal seam thickness, coal seam burial depth, coal quality characteristics, and coal seam structure are set according to their importance in evaluating the similarity of coal seam geology between historical coal seam gas mining areas and the coal seam gas mining areas to be predicted. In a specific embodiment, the weights of the similarity factors of coal rock type, coal seam thickness, coal seam burial depth, coal quality characteristics, and coal seam structure are 0.2, 0.2, 0.2, 0.2, and 0.2, respectively.

[0082] For example, the specific analysis process of step three also includes: obtaining relevant information about the gas content of each historical coalbed methane mining area based on the geological information of each historical coalbed methane mining area, and further obtaining the original gas content of the coal seam and the content of various gas components of the coalbed methane in each historical coalbed methane mining area, and recording them as , Indicates The number of the gas component, .

[0083] The original gas content of the coal seam and the content of various gas components of the coal seam gas in the coal seam gas mining area to be predicted are recorded as .

[0084] By analyzing the formula Obtain the gas content similarity coefficient of each coalbed methane mining area in history and the coalbed methane mining area to be predicted ,in represents a natural constant, They represent the preset relative deviation of the original gas content of coal seams, the The threshold value of relative deviation of gas component content.

[0085] As a preferred scheme, the threshold values ​​of the relative deviation of the original gas content of the coal seam and the relative deviation of the contents of various gas components in the coalbed methane are set based on the actual needs when evaluating the similarity in gas content between the historical coalbed methane exploited areas and the coalbed methane exploitation areas to be predicted.

[0086] Exemplarily, the specific analysis process of step three also includes: obtaining hydrogeological information of each historical coalbed methane exploited area based on the geological information of each historical coalbed methane exploited area, further obtaining the water level, flow direction and flow velocity of groundwater in each historical coalbed methane exploited area, and comparing them one by one with the water level, flow direction and flow velocity of groundwater in the coalbed methane exploitation area to be predicted, analyzing the similarity factors of groundwater level, groundwater flow velocity and groundwater flow direction of each historical coalbed methane exploited area, and performing weighted average calculation to obtain the hydrogeological similarity coefficient between each historical coalbed methane exploited area and the coalbed methane exploitation area to be predicted.

[0087] As a preferred solution, the similarity factors of groundwater level, groundwater flow velocity and groundwater flow direction in each historical coalbed methane exploited area are analyzed. The specific method is: compare the groundwater level in each historical coalbed methane exploited area with the groundwater level in the coalbed methane exploitation area to be predicted, obtain the relative deviation of the groundwater level in each historical coalbed methane exploited area, substitute it into the preset relationship function between the relative deviation of the groundwater level and the groundwater level similarity factor, and obtain the groundwater level similarity factor in each historical coalbed methane exploited area.

[0088] The groundwater flow rate of each historical coalbed methane exploited area is compared with the groundwater flow rate of the coalbed methane exploitation area to be predicted, and the relative deviation of the groundwater flow rate in each historical coalbed methane exploited area is obtained. The relative deviation is substituted into the preset relationship function between the relative deviation of the groundwater flow rate and the groundwater flow rate similarity factor, and the groundwater flow rate similarity factor of each historical coalbed methane exploited area is obtained.

[0089] The flow direction of groundwater in each historical coalbed methane exploited area is compared with the flow direction of groundwater in the coalbed methane exploitation area to be predicted, and the flow direction similarity factors corresponding to the same and different flow directions are set, and the groundwater flow direction similarity factors of each historical coalbed methane exploited area are screened.

[0090] As a preferred solution, the relative deviation of groundwater levels in historical coalbed methane exploited areas refers to the absolute value of the difference between the groundwater levels in historical coalbed methane exploited areas and the groundwater levels in the coalbed methane exploitation area to be predicted.

[0091] As a preferred solution, the relationship function between the relative deviation of the groundwater level and the groundwater level similarity factor is a negative correlation function, that is, the larger the relative deviation of the groundwater level, the smaller the groundwater level similarity factor.

[0092] As a preferred solution, the relative deviation of groundwater flow rate in historical coalbed methane exploited areas refers to the absolute value of the difference between the groundwater flow rate in historical coalbed methane exploited areas and the groundwater flow rate in the coalbed methane exploitation area to be predicted.

[0093] As a preferred solution, the relationship function between the relative deviation of groundwater velocity and the similarity factor of groundwater velocity is a negative correlation function, that is, the larger the relative deviation of groundwater velocity, the smaller the similarity factor of groundwater velocity.

[0094] In a specific embodiment, the water flow direction similarity factors corresponding to the same and different water flow directions are 1 and 0 respectively.

[0095] As a preferred solution, the weights of the groundwater level similarity factor, the groundwater velocity similarity factor, and the groundwater flow direction similarity factor are set values, and the cumulative sum is 1. In a specific embodiment, the weights of the groundwater level similarity factor, the groundwater velocity similarity factor, and the groundwater flow direction similarity factor are 0.3, 0.35, and 0.35, respectively.

[0096] Exemplarily, the specific analysis process of step three also includes: calculating the weighted average of the coal seam geological similarity coefficient, gas content similarity coefficient, and hydrogeological similarity coefficient between the historical coal seam methane mined areas and the coal seam methane mined areas to be predicted, to obtain a comprehensive similarity index between the historical coal seam methane mined areas and the coal seam methane mined areas to be predicted.

[0097] As a preferred solution, the weights of the coal seam geological similarity coefficient, the gas content similarity coefficient, and the hydrogeological similarity coefficient are set values, and the cumulative sum is 1.

[0098] As a preferred solution, the weights of the coal seam geological similarity coefficient, gas content similarity coefficient, and hydrogeological similarity coefficient are set according to their importance in evaluating the similarity between each historical coal seam gas mining area and the coal seam gas mining area to be predicted. In a specific embodiment, the weights of the coal seam geological similarity coefficient, gas content similarity coefficient, and hydrogeological similarity coefficient are 0.6, 0.2, and 0.2, respectively.

[0099] Step 4. Estimation of coalbed methane production in coalbed methane production areas: Based on the comprehensive similarity index of each historical coalbed methane produced area and the coalbed methane production area to be predicted, obtain each reference coalbed methane produced area and the coalbed methane production of each reference coalbed methane produced area, further analyze the estimated coalbed methane production in the coalbed methane production area to be predicted, and provide feedback.

[0100] Exemplarily, the specific analysis process of step four is: compare the comprehensive similarity index of each historical coalbed methane mined area and the coalbed methane mined area to be predicted with a preset comprehensive similarity index threshold; if the comprehensive similarity index of a historical coalbed methane mined area and the coalbed methane mined area to be predicted is greater than or equal to the preset comprehensive similarity index threshold, then the historical coalbed methane mined area is recorded as the reference coalbed methane mined area, and statistics are collected on each reference coalbed methane mined area.

[0101] As a preferred solution, the setting of the comprehensive similarity index threshold is set based on the actual demand when selecting the reference coalbed methane mined area for the coalbed methane mined area to be predicted from various historical coalbed methane mined areas.

[0102] Extract the production records of each coalbed methane mining area stored in the database, obtain the coalbed methane mining volume of each coalbed methane mining area in history, screen the coalbed methane mining volume of each control coalbed methane mining area, and record it as , Indicates The number of the coal-bed methane mining area is compared. , and the comprehensive similarity index of each control coalbed methane mining area and the coalbed methane mining area to be predicted is recorded as .

[0103] By analyzing the formula Get the estimated coalbed methane production volume in the coalbed methane production area to be predicted ,in .

[0104] In this embodiment, the present invention evaluates the similarity between historical coalbed methane mined areas and coalbed methane mined areas to be predicted by multiple indicators in multiple dimensions such as coal seam geology, gas content, and hydrogeology, screens coalbed methane mined areas with similar geological conditions and high reference value, and predicts the coalbed methane mining volume of the coalbed methane mining areas based on their coalbed methane mining volume, thereby improving the reliability of the coalbed methane mining volume prediction results.

[0105] Step 5. Estimation of coalbed methane production trend in coalbed methane mining areas: Obtain the coalbed methane production trend curves of each reference coalbed methane mining area, further analyze the estimated coalbed methane production trend curve of the coalbed methane mining area to be predicted, and provide feedback.

[0106] Exemplarily, the specific analysis process of step five is: extracting the production records of each historical coalbed methane mined area stored in the database, screening the production records of each reference coalbed methane mined area, obtaining the actual coalbed methane production of each reference coalbed methane mined area in each time period during the mining process, and drawing a trend curve of the actual coalbed methane production over time during the mining process of each reference coalbed methane mined area, and recording it as the coalbed methane production trend curve of each reference coalbed methane mined area.

[0107] As a preferred solution, a trend curve of the actual coalbed methane production changing with time during the mining process of each control coalbed methane mined area is drawn. The specific method is: a coordinate system is established with the time period as the horizontal axis and the actual coalbed methane production as the vertical axis, and the corresponding data points are marked in the coordinate system according to the actual coalbed methane production in each time period during the mining process of each control coalbed methane mined area, and the trend curve of the actual coalbed methane production changing with time during the mining process of each control coalbed methane mined area is drawn by using the method of establishing a mathematical model.

[0108] The curve fitting technology is used to fit the coalbed methane production trend curve of each reference coalbed methane mining area to obtain the estimated coalbed methane production trend curve of the coalbed methane mining area to be predicted.

[0109] As a preferred solution, the curve fitting technology is an existing relatively mature technology and will not be described in detail here.

[0110] In this embodiment, the present invention estimates the coalbed methane production trend of the coalbed methane mining area to be predicted based on the coalbed methane production trend of each coalbed methane mining area with similar geological conditions to the coalbed methane mining area to be predicted, so that energy companies can understand the coalbed methane production situation at different stages in the future in advance, thereby planning production activities more reasonably and better planning energy structure.

[0111] See also Figure 2 As shown, the second aspect of the present invention provides an intelligent prediction system for coalbed methane production, including a coalbed methane production area geological information collection module, a historical coalbed methane produced area geological information acquisition module, a historical coalbed methane produced area similarity analysis module, a coalbed methane production volume estimation module in the coalbed methane production area, a coalbed methane production trend estimation module in the coalbed methane mining area, and a database.

[0112] The historical coalbed methane mined area geological information acquisition module is respectively connected to the coalbed methane mining area geological information collection module and the historical coalbed methane mined area similarity analysis module; the coalbed methane mining area coalbed methane production volume estimation module is respectively connected to the historical coalbed methane mined area similarity analysis module and the coalbed methane mining area coalbed methane production trend estimation module; the database is respectively connected to the historical coalbed methane mined area geological information acquisition module, the coalbed methane mining area coalbed methane production volume estimation module and the coalbed methane mining area coalbed methane production trend estimation module.

[0113] The coalbed methane mining area geological information acquisition module is used to arrange various sampling points and conduct surveys in the coalbed methane mining area to be predicted to obtain geological information of the coalbed methane mining area to be predicted, wherein the geological information includes coal seam geological information, gas content related information, and hydrogeological information.

[0114] The module for acquiring geological information of historical coalbed methane exploited areas is used to acquire geological information of historical coalbed methane exploited areas.

[0115] The historical coalbed methane mined area similarity analysis module is used to compare the geological information of each historical coalbed methane mined area with the geological information of the coalbed methane mined area to be predicted, analyze the coal seam geological similarity coefficient, gas content similarity coefficient, and hydrogeological similarity coefficient of each historical coalbed methane mined area and the coalbed methane mined area to be predicted, and further analyze the comprehensive similarity index of each historical coalbed methane mined area and the coalbed methane mined area to be predicted.

[0116] The coalbed methane production volume estimation module of the coalbed methane production area is used to obtain each reference coalbed methane produced area and the coalbed methane production volume of each reference coalbed methane produced area based on the comprehensive similarity index of each historical coalbed methane produced area and the coalbed methane production area to be predicted, further analyze the estimated coalbed methane production volume of the coalbed methane production area to be predicted, and provide feedback.

[0117] The coalbed methane production trend estimation module in the coalbed methane mining area is used to obtain the coalbed methane production trend curves of each reference coalbed methane mined area, further analyze the estimated coalbed methane production trend curve of the coalbed methane mining area to be predicted, and provide feedback.

[0118] The database is used to store geological information and production records of each coalbed methane mining area in history.

[0119] The above contents are merely examples and explanations of the concept of the present invention. Those skilled in the art may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the concept of the invention or exceed the scope defined by the present invention, they shall all fall within the protection scope of the present invention.

Claims

1. A method for intelligently predicting coalbed methane production, characterized in that: The steps include: Step 1: Collect geological information of coalbed methane mining area: Set up sampling points in the coalbed methane mining area to be predicted and conduct surveys to obtain geological information of the coalbed methane mining area to be predicted, where the geological information includes coal seam geological information, gas content related information, and hydrogeological information; Step 2: Acquisition of geological information of historical coalbed methane exploited areas: Acquisition of geological information of historical coalbed methane exploited areas; Step 3: Similarity analysis of historical coalbed methane mined areas: compare the geological information of each historical coalbed methane mined area with the geological information of the coalbed methane mined area to be predicted, analyze the coal seam geological similarity coefficient, gas content similarity coefficient, and hydrogeological similarity coefficient of each historical coalbed methane mined area and the coalbed methane mined area to be predicted, and further analyze the comprehensive similarity index of each historical coalbed methane mined area and the coalbed methane mined area to be predicted; Step 4: Estimation of coalbed methane production in coalbed methane production areas: Based on the comprehensive similarity index of each coalbed methane production area in history and the coalbed methane production area to be predicted, obtain each reference coalbed methane production area and obtain the coalbed methane production volume of each reference coalbed methane production area, further analyze the estimated coalbed methane production volume of the coalbed methane production area to be predicted, and provide feedback; Step 5. Estimation of coalbed methane production trend in coalbed methane mining areas: Obtain the coalbed methane production trend curves of each reference coalbed methane mining area, further analyze the estimated coalbed methane production trend curve of the coalbed methane mining area to be predicted, and provide feedback.

2. The method for intelligently predicting coalbed methane production according to claim 1, characterized in that: The specific analysis process of step 1 is as follows: Obtaining a regional division method for the coalbed methane mining area to be predicted and dividing it to obtain sub-areas of the coalbed methane mining area to be predicted; The center point of each sub-area in the coalbed methane mining area to be predicted is recorded as each first-class sampling point; According to the preset equal depth principle, each sampling point is arranged vertically between the top and bottom plates of the coal seam at the center point of each sub-area of ​​the coal seam gas mining area to be predicted, and is recorded as each second-class sampling point; The first-class sampling points and the second-class sampling points are summarized to obtain the sampling points of the coalbed methane mining area to be predicted and conduct surveys to obtain the coal seam geological information, gas content-related information, and hydrogeological information of the coalbed methane mining area to be predicted.

3. The method for intelligently predicting coalbed methane production according to claim 1, characterized in that: The coal seam geological information of the coal seam methane mining area to be predicted in step one includes coal rock type, coal seam thickness, coal seam burial depth, coal quality characteristic information, and coal seam structural information, wherein the coal quality characteristic information includes porosity, permeability, and the content of various chemical components in coal; the coal seam structural information includes the type, axial direction, and dip angle of folds, as well as the type, fault distance, and combination of faults; the gas content-related information includes the original gas content of the coal seam and the content of various gas components in coal seam methane; the hydrogeological information includes the groundwater level, water flow direction, and flow rate.

4. The method for intelligently predicting coalbed methane production according to claim 3 is characterized in that: The specific analysis process of step three includes: S1: Based on the geological information of each coalbed methane mining area in the past, the coal seam geological information of each coalbed methane mining area in the past is obtained, and the coal rock type, coal seam thickness, coal seam burial depth, coal quality characteristics information, and coal seam structure information of each coalbed methane mining area in the past are further obtained; S2: Compare the coal rock types of each coalbed methane mining area in history with the coal rock types of the coalbed methane mining area to be predicted, set the coal rock type similarity factors corresponding to the same and different coal rock types, and screen out the coal rock type similarity factors of each coalbed methane mining area in history, which are recorded as , Indicates the history The number of the coal-bed methane mining area, ; S3: Compare the coal seam thickness of each coal seam gas mining area in history with the coal seam thickness of the coal seam gas mining area to be predicted, obtain the relative deviation of the coal seam thickness of each coal seam gas mining area in history, substitute it into the preset relationship function between the relative deviation of the coal seam thickness and the coal seam thickness similarity factor, and obtain the coal seam thickness similarity factor of each coal seam gas mining area in history, which is recorded as ; S4: Compare the coal seam depths of each historical coal seam gas mining area with the coal seam depths of the coal seam gas mining area to be predicted, analyze the similarity factors of the coal seam depths of each historical coal seam gas mining area, and record them as ; S5: Based on the coal quality characteristics information of each coalbed methane mining area in history, the porosity, permeability, and various chemical components in the coal of each coalbed methane mining area in history are obtained, and the porosity, permeability, and various chemical components in the coal of the coalbed methane mining area to be predicted are compared one by one, and the coal quality characteristics similarity factors of each coalbed methane mining area in history are analyzed and recorded as ; S6: Based on the coal seam structural information of each coal seam gas mining area in history, the types, axes, dip angles, fault types, fault distances, and combination methods of the folds in each coal seam gas mining area in history are obtained, and the types, axes, dip angles, fault types, fault distances, and combination methods of the folds in the coal seam gas mining area to be predicted are compared one by one, and the coal seam structural similarity factors of each coal seam gas mining area in history are analyzed and recorded as ; S7: By analyzing the formula Obtain the coal seam geological similarity coefficient between the historical coal seam gas mining areas and the coal seam gas mining areas to be predicted ,in They represent the weights of the similarity factors of the preset coal rock type, coal seam thickness, coal seam burial depth, coal quality characteristics, and coal seam structure. .

5. The method for intelligently predicting coalbed methane production according to claim 4, characterized in that: The specific analysis process of step three also includes: According to the geological information of each coalbed methane mining area in history, the gas content information of each coalbed methane mining area in history is obtained, and the original gas content of the coal seam and the content of various gas components of coalbed methane in each coalbed methane mining area in history are further obtained, which are recorded as , Indicates The number of the gas component, ; The original gas content of the coal seam and the content of various gas components of the coal seam gas in the coal seam gas mining area to be predicted are recorded as ; By analyzing the formula Obtain the gas content similarity coefficient of each coalbed methane mining area in history and the coalbed methane mining area to be predicted ,in represents a natural constant, They represent the preset relative deviation of the original gas content of coal seams, the The threshold value of relative deviation of gas component content.

6. The method for intelligently predicting coalbed methane production according to claim 3, characterized in that: The specific analysis process of step three also includes: Based on the geological information of each coalbed methane exploited area in history, the hydrogeological information of each coalbed methane exploited area in history is obtained, and the groundwater level, flow direction and flow velocity of each coalbed methane exploited area in history are further obtained, and compared with the groundwater level, flow direction and flow velocity of the coalbed methane exploitation area to be predicted, the similarity factors of the groundwater level, groundwater flow velocity and groundwater flow direction of each coalbed methane exploited area in history are analyzed, and the weighted average value is calculated to obtain the hydrogeological similarity coefficient between each coalbed methane exploited area in history and the coalbed methane exploitation area to be predicted.

7. The method for intelligently predicting coalbed methane production according to claim 1, characterized in that: The specific analysis process of step three also includes: The weighted average values ​​of the coal seam geological similarity coefficient, gas content similarity coefficient and hydrogeological similarity coefficient of each historical coal seam methane exploited area and the coal seam methane exploitation area to be predicted are calculated to obtain the comprehensive similarity index of each historical coal seam methane exploited area and the coal seam methane exploitation area to be predicted.

8. The method for intelligently predicting coalbed methane production according to claim 1, characterized in that: The specific analysis process of step 4 is as follows: Compare the comprehensive similarity index of each historical coalbed methane mined area and the coalbed methane mined area to be predicted with the preset comprehensive similarity index threshold; if the comprehensive similarity index of a historical coalbed methane mined area and the coalbed methane mined area to be predicted is greater than or equal to the preset comprehensive similarity index threshold, then the historical coalbed methane mined area is recorded as the reference coalbed methane mined area, and statistics are collected on each reference coalbed methane mined area; Extract the production records of each coalbed methane mining area stored in the database, obtain the coalbed methane mining volume of each coalbed methane mining area in history, screen the coalbed methane mining volume of each control coalbed methane mining area, and record it as , Indicates The number of the coal-bed methane mining area is compared. , and the comprehensive similarity index of each control coalbed methane mining area and the coalbed methane mining area to be predicted is recorded as ; By analyzing the formula Get the estimated coalbed methane production volume in the coalbed methane production area to be predicted ,in .

9. The method for intelligently predicting coalbed methane production according to claim 1, characterized in that: The specific analysis process of step five is as follows: Extract the production records of each historical coalbed methane mined area stored in the database, screen the production records of each reference coalbed methane mined area, obtain the actual coalbed methane production in each time period during the mining process of each reference coalbed methane mined area, draw the trend curve of the actual coalbed methane production over time during the mining process of each reference coalbed methane mined area, and record it as the coalbed methane production trend curve of each reference coalbed methane mined area; The curve fitting technology is used to fit the coalbed methane production trend curve of each reference coalbed methane mining area to obtain the estimated coalbed methane production trend curve of the coalbed methane mining area to be predicted.

10. An intelligent prediction system for coalbed methane production, characterized in that: include: Coalbed methane mining area geological information acquisition module: used to arrange sampling points and conduct surveys in the coalbed methane mining area to be predicted, and obtain geological information of the coalbed methane mining area to be predicted, where the geological information includes coal seam geological information, gas content related information, and hydrogeological information; The module for obtaining geological information of historical coal-bed methane exploited areas is used to obtain geological information of historical coal-bed methane exploited areas. Similarity analysis module of historical coalbed methane mined areas: used to compare the geological information of each historical coalbed methane mined area with the geological information of the coalbed methane mined area to be predicted, analyze the coal seam geological similarity coefficient, gas content similarity coefficient, and hydrogeological similarity coefficient of each historical coalbed methane mined area and the coalbed methane mined area to be predicted, and further analyze the comprehensive similarity index of each historical coalbed methane mined area and the coalbed methane mined area to be predicted; Coalbed methane production volume estimation module for coalbed methane production areas: used to obtain each reference coalbed methane production area and the coalbed methane production volume of each reference coalbed methane production area based on the comprehensive similarity index of each historical coalbed methane production area and the coalbed methane production area to be predicted, further analyze the estimated coalbed methane production volume of the coalbed methane production area to be predicted, and provide feedback; CBM production trend estimation module in CBM mining area: used to obtain the CBM production trend curve of each CBM mining area, further analyze the estimated CBM production trend curve of the CBM mining area to be predicted, and provide feedback; Database: used to store geological information and production records of each historical coalbed methane mining area.

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