Coal body structure fine identification method based on logging data
By using single-well logging data and core well geological data, and combining Euclidean distance algorithm to identify the coal body structure, the problem of inaccurate identification of coal body structure in the existing technology is solved, and the production capacity of coalbed methane wells has been improved.
Patent Information
- Application Number
- CN202510219838.8
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-02-26
- Publication Date
- 2025-05-30
AI Technical Summary
The prior art is difficult to accurately identify the coal body structure, which affects the recovery rate and economic benefits of coalbed methane wells.
By using single well logging data and combining the core well geological data within a 1 square kilometer, coal core depth correction, statistical characteristic parameters of coal structure type, and Euclidean distance algorithm are used to identify coal structure structure.
The fine identification of the coal structure of the uncore-cut well was achieved, the fracturing layer was optimized, and the production capacity of the coalbed methane well was improved.
Smart Images
Figure CN120061824A_ABST
Abstract
Description
Technical Field
[0001] The present invention belongs to the technical field of coal seam gas well coal body structure analysis and stimulation research, and particularly relates to a fine identification method of coal body structure based on logging data. Background Art
[0002] With the in-depth development of coal seam gas exploitation, how to accurately identify the coal body structure and improve the productivity of coal seam gas wells has become an important technical problem in coal seam gas exploration and development. Traditional coal body structure identification methods mainly rely on drilling core analysis. However, core sampling is costly, time-consuming, and cannot comprehensively cover all well sections. In addition, due to the limited number of cored wells, the coal body structure of newly completed drilled wells cannot be accurately described, which restricts the optimization and implementation of stimulation measures.
[0003] With the rapid development of logging technology, single-well logging data has gradually become one of the important tools for identifying the coal body structure of coal seam gas wells. However, it is difficult to achieve fine identification of the coal body structure with single-well logging data without the support of core data, resulting in inaccurate selection of well section perforation, fracturing, and drilling horizons, which affects the recovery rate and economic benefits of coal seam gas wells. Summary of the Invention
[0004] The purpose of the present invention is to provide a fine identification method of coal body structure based on logging data applicable to coal seam gas wells. By using single-well logging data to finely identify the coal body structure of non-cored wells, efficient screening of high-quality coal body sections is achieved, fracturing horizons are optimized, and the wellbore stimulation effect is improved. This method is applicable to newly completed drilled wells with multiple cored wells in the area, especially suitable for coal seam gas wells that require optimized fracturing and drilling horizons.
[0005] The present invention adopts the following technical solutions. A fine identification method of coal body structure based on logging data includes the following steps: (a) Taking the target non-cored coal seam gas well as the center, obtaining geological data of at least 2 cored wells within a range of 1 square kilometer; (b) Correcting the coal core depth of the cored wells to match the coal seam interface in the logging data; (c) Counting the logging characteristic parameters of different coal body structure types and calculating the mean value range of each structure type parameter; (d) By using the Euclidean distance algorithm, calculating the comprehensive distance between the logging data of each depth point of the target well coal seam and the mean value of each coal body structure feature, and determining the coal body structure of this depth point as the structure type with the minimum distance; (e) According to the identification result, selecting the primary structure or fragmented structure coal body section as the fracturing target area or the horizontal well drilling trajectory.
[0006] Further, in the step (a), the geological data includes the analysis results of core samples, logging data, and the coal body structure type, core length, and depth.
[0007] Further, the depth correction method in the step (b) is to perform correction using the following formula: ; In the formula: h, h ’ —The coal seam thickness obtained from drilling core sampling and logging interpretation; d 1 、d 2 、d—the depths of the top and bottom interfaces of the coal seam drilled and the sampling depth; d ’ 1 、d ’ 2 、d ’ —The depths of the top and bottom interfaces of the coal seam obtained from logging interpretation and the corrected sampling depth.
[0008] Further, in the step (c), the logging characteristic parameters include well diameter, compensated density, acoustic travel time, and natural gamma.
[0009] Further, the coal body structure types in the step (c) include primary structure, fragmented structure, granular structure, and mylonitic structure.
[0010] Further, the coal body structure type includes fragmented-granular structure, and the fragmented-granular structure is between the fragmented structure and the granular structure.
[0011] Further, the Euclidean distance calculation formula in the step (d) is: , d represents the distance between two data points, represents the nth eigenvalue of a certain data point, represents the mean value of the nth feature, and n represents the total number of features.
[0012] Further, the logging data is continuously recorded by taking values at depths.
[0013] Further, the depth interval distance is not greater than 0.05 meters.
[0014] This method is a method for finely identifying the coal body structure using single-well logging data. By analyzing the characteristics of core sampling and logging data around a non-cored well, the purpose of finely identifying the coal body structure of the non-cored well using its logging data is achieved. This method is applicable to areas within 1 Km in the same region. 2Fine identification of the coal body structure of newly completed drilled wells with more than 2 coring wells. When perforating and fracturing newly completed vertical and directional wells, this method can be used to find high-quality coal body structure sections to optimize the fracturing intervals and increase production; analyze the coal body structure of the horizontal well pilot hole to guide the drilling interval of the horizontal section and increase production. Description of the Drawings
[0015] Figure 1 It is a schematic diagram of the coal core depth correction of the present invention. Detailed Implementation Modes
[0016] To better understand the purpose, structure and function of the present invention, the following further describes in detail a method for fine identification of coal body structure based on logging data of the present invention with reference to the drawings.
[0017] A method for fine identification of coal body structure based on logging data includes the following steps: (a) For a certain coalbed methane well that has been newly drilled, not cored, and logged, obtain the geological data of more than 2 other cored wells within 1 Km centered on it. 2 within.
[0018] (b) Correct the coal core depth to match the logging data.
[0019] (c) Statistically analyze the logging data characteristics of the coal cores. The logging characteristic parameters mainly include well diameter (mm), compensated density (g / cm3), acoustic travel time (μs / m), and natural gamma (API). Obtain the numerical ranges and means of well diameter, compensated density, acoustic travel time, and natural gamma for different coal body structures (generally primary structure, fragmented structure, granular structure, and mylonite structure).
[0020] (d) Through the Euclidean distance algorithm, use the above-mentioned logging characteristic means as eigenvalues. Calculate the comprehensive distance between the logging data of the newly completed drilled well coal seam and different eigenvalues. The smaller the distance, the closer the data point is to the characteristic mean of the coal body structure, and the more likely it belongs to this structure, thereby judging the coal body structure of coal seams at different depths.
[0021] (e) According to the identification results, select the primary structure or fragmented structure coal body section as the fracturing target area or the horizontal well drilling trajectory.
[0022] Specifically, step (a) is the collation of existing cored well data. According to the position and distance relationship, select more than 2 existing cored wells within the range of 1 Km of the newly completed drilled well, collect the analysis results of core samples, logging data (well diameter, acoustic travel time, compensated density, etc.), and coal body structure types (such as massive, powdery, etc.) of the surrounding cored wells, and record the coal core length and depth. 2 range.
[0023] Analyze and summarize the geological information such as the strata, coal seam thickness, and coal body structure of each coring well to comprehensively understand the characteristics of the coal body in the area.
[0024] In step (b), there are certain errors in the depth, thickness of the coal seam, and sampling depth obtained by drilling and coring, and they often do not match the results of well logging interpretation. Therefore, it is necessary to correct the sampling depth of drilling. In order to accurately count the well logging data of the coal core and analyze the characteristics, this method uses Figure 1 the coal core depth correction method shown in the figure, and its calculation formula is as follows: ; The meanings of each symbol: h, h ’ —The thickness of the coal seam obtained by drilling and coring and well logging interpretation; d 1 、d 2 、d—The depths of the top and bottom interfaces of the coal seam drilled and the sampling depth; d ’ 1 、d ’ 2 、d ’ —The depths of the top and bottom interfaces of the coal seam obtained by well logging interpretation and the corrected sampling depth.
[0025] In step (c), it is for well logging data comparison. By comparing and analyzing the well logging data of the coring well with the actual core information, the typical characteristics of different coal body structures in the well logging data are summarized, which is convenient for identifying and calibrating the data of the non-coring well.
[0026] By sorting out the data of the coring well, a clear and systematic regional coal body characteristic database can be formed, thus providing a more reliable basis for the selection of fracturing horizons and horizontal section drilling of subsequent coalbed methane wells.
[0027] In step (d), the "Euclidean distance" method is used to calculate the characteristic values of different coal body structures. The Euclidean distance is a commonly used distance measurement method for calculating the straight-line distance between two points in a multi-dimensional space. This method is especially suitable for the similarity measurement and clustering analysis of data points in space. The formula for calculating the Euclidean distance is: , d represents the distance between two data points, represents the nth characteristic value of a certain data point, It represents the mean of the nth feature, where n represents the total number of features. To accurately identify the coal seam structure, four parameters, namely well diameter (mm), compensated density (g / cm³), acoustic travel time (μs / m), and natural gamma (API), are selected as the eigenvalue for calculating the Euclidean distance. The reasons for choosing these parameters are that the coal seam has characteristics such as low radioactive content, high resistivity, high organic matter content, low density, and relatively low hardness compared to the surrounding rock. Calculate the comprehensive distance between the logging data of the newly completed drilled coal seam and different eigenvalues. The smaller the distance, the closer the data point is to the mean value of the coal seam structure characteristics, and the more likely it belongs to this structure, thereby determining the coal seam structure at different depths.
[0028] Step (e) guides the drilling and fracturing operations. For vertical wells and directional wells, select hard coal (primary structure coal or fragmented coal) for perforating and fracturing, which can effectively reduce the filtration loss of fracturing fluid, increase the fracture creation scale, and reduce the influence of coal powder. For horizontal wells, select hard coal (primary structure coal or fragmented coal) to drill the horizontal section, which can lay a good foundation for the subsequent fracturing operations.
[0029] This method can achieve the purpose of accurately identifying the coal seam structure of newly completed drilled wells by analyzing the logging data characteristics of non-cored wells and comparing and analyzing them with the data of cored wells around the well. This method is particularly applicable to areas where there are more than two cored wells within a range of 2 1 Km. It has broad application prospects in the design and operation of newly completed vertical wells, directional wells, and horizontal wells, and can be used to optimize the fracturing intervals, guide the drilling of horizontal sections, and improve the productivity of coalbed methane wells.
[0030] Taking the WXN-04H-D1 well in the southern block of Wuxiang as an example, this method is introduced. WXN-04H-D1 is a directional well with a completed well depth of 1313 m and is completed with casing. The production casing is a Q125 casing with an outer diameter of φ139.7 mm and a wall thickness of 10.54 mm. There are WXN-U-04H (22 m), WXN-U-01V (466 m), and WXN-U-04V (905 m) around the WXN-04H-D1 well that have undergone coring work. Statistical analysis is carried out on the logging data of these 3 wells (the logging data is continuously recorded at intervals of 0.05 m in depth), and the results are shown in Appendices 1 - 3. There is no mylonite structure in the wells in the southern block of Wuxiang. The fragmented - granular structure is a structure between the fragmented structure and the granular structure and is classified separately. Analyze the logging data corresponding to different coal seam structures, and the results are shown in Appendix 4.
[0031] Appendix 1 Statistical Table of Coal Core Logging Data of WXN-U-04H Appendix 2 Statistical Table of Coal Core Logging Data of WXN-U-01V Statistical Table of Coal Core Logging Data for WXN-U-04V Statistical Table of Calculation Results of Characteristic Values of Different Coal Body Structures Statistical Table of Logging Data for WXN-04H-D1 Based on the characteristic values of logging data of different coal body structures in Table 4 and Table 5, the coal body structures of coal seams No. 3 上 #, No. 3 and No. 15 -1 #, No. 15 -2 # and No. 15 -3 # in Well WXN-04H-D1 can be obtained. The specific results are as follows: No. 3 上 # coal is located at 1120.00 - 1122.65m, with a total thickness of 2.65m. Among them, the interval from 1120.00 - 1122.60m (2.60m) is judged as fragmented - granular structure, and the interval from 1122.60 - 1122.65m (0.05m) is judged as primary structure. It is recommended to select the perforation and fracturing positions in the middle and lower parts of the coal seam.
[0032] No. 3# coal is located at 1126.10 - 1127.95m, with a total thickness of 1.85m. Among them, the interval from 1126.1 - 1126.15m (0.05m) is judged as fragmented - granular structure, the interval from 1126.15 - 1126.3m (0.15m) is judged as fragmented structure, the interval from 1126.3 - 1127m (0.7m) is judged as fragmented - granular structure, the interval from 1127 - 1127.35m (0.35m) is judged as primary structure, the interval from 1127.35 - 1127.55m (0.2m) is judged as fragmented - granular structure, the interval from 1127.55 - 1127.7m (0.15m) is judged as primary structure, the interval from 1127.7 - 1127.8m (0.1m) is judged as fragmented - granular structure, and the interval from 1127.8 - 1127.95m (0.15m) is judged as primary structure. It is recommended to select the perforation and fracturing positions near the coal with primary structure.
[0033] No. 15 -1 # coal is located at 1267.50 - 1268.15m, with a total thickness of 0.65m. Among them, the interval from 1267.50 - 1268.00m (0.50m) is judged as fragmented - granular structure, and the interval from 1268.00 - 1268.15m (0.15m) is judged as primary structure. It is recommended to select the perforation and fracturing positions in the middle and lower parts of the coal seam.
[0034] 15 -2 # The coal seam is at 1269.65 - 1270.85 m, with a total thickness of 1.20 m. Among them, the section from 1269.65 - 1270.60 m (0.95 m) is judged to be a fragmented - granular structure, and the section from 1270.60 - 1270.85 m (0.25 m) is judged to be a primary structure. It is recommended to select the middle - lower part of the coal seam for perforation and fracturing.
[0035] 15 -3 # The coal seam is at 1274.25 - 1274.55 m, with a total thickness of 0.30 m. Among them, the section from 1274.25 - 1274.40 m (0.15 m) is judged to be a fragmented structure, the section from 1274.40 - 1274.50 m (0.10 m) is judged to be a fragmented - granular structure, and the section from 1274.50 - 1274.55 m (0.05 m) is judged to be a primary structure. It is recommended to select the middle - lower part of the coal seam for perforation and fracturing.
[0036] It can be understood that the present invention is described through some embodiments. Those skilled in the art know that, without departing from the spirit and scope of the present invention, various changes or equivalent substitutions can be made to these features and embodiments. Additionally, under the teaching of the present invention, these features and embodiments can be modified to adapt to specific situations and materials without departing from the spirit and scope of the present invention. Therefore, the present invention is not limited by the specific embodiments disclosed herein, and all embodiments falling within the scope of the claims of this application belong to the scope protected by the present invention.
Claims
1. A method for fine identification of coal structure based on well logging data, characterized in that: The following steps are involved: (a) Taking the target uncored CBM well as the center, obtain geological data of at least two cored wells within an area of 1 square kilometer; (b) correcting the coal core depth of the cored well to match the coal seam interface in the well logging data; (c) Count the logging characteristic parameters of different coal body structure types and calculate the mean range of the parameters of each structure type; (d) Using the Euclidean distance algorithm, the comprehensive distance between the well logging data at each depth point of the target well coal seam and the mean value of each coal body structure characteristic is calculated, and the structure type with the smallest distance is determined as the coal body structure at that depth point; (e) Based on the identification results, select the original structure or fragmented structure coal layer as the fracturing target area or horizontal well drilling trajectory.
2. The method for fine identification of coal structure based on well logging data according to claim 1 is characterized in that: In the step (a), the geological data includes core sample analysis results, well logging data, coal body structure type, coal core length and depth.
3. The method for fine identification of coal structure based on well logging data according to claim 2 is characterized in that: The depth correction method in step (b) is to use the following formula for correction: ; Where: h, h ’ — Coal seam thickness obtained from drilling coring and logging interpretation; d1, d2, d—depth of top and bottom interfaces of the coal seam and sampling depth; d ’ 1.d ’ 2.d ’ —The depth of the top and bottom interfaces of the coal seam obtained from logging interpretation and the corrected sampling depth.
4. The method for fine identification of coal structure based on well logging data according to claim 3 is characterized in that: In the step (c), the logging characteristic parameters include well diameter, compensated density, acoustic wave time difference and natural gamma.
5. The method for fine identification of coal structure based on well logging data according to claim 4 is characterized in that: The coal body structure types in step (c) include primary structure, fragmentation structure, granular structure and mylonitic structure.
6. The method for fine identification of coal structure based on well logging data according to claim 5 is characterized in that: The coal body structure types include fragmentation-granular structure, which is between fragmentation structure and granular structure.
7. The method for fine identification of coal structure based on well logging data according to claim 1, characterized in that: The Euclidean distance calculation formula in step (d) is: , d represents the distance between two data points, represents the nth eigenvalue of a data point, represents the mean of the nth feature, and n represents the total number of features.
8. The method for finely identifying coal structure based on well logging data according to any one of claims 1 to 7, characterized in that: Well logging data are recorded continuously at depth.
9. The method for fine identification of coal structure based on well logging data according to claim 8, characterized in that: The depth interval is no more than 0.05 meters.