A directional drilling gas extraction optimization method based on coal seam permeability dynamic monitoring

Abstract

The present application relates to the technical field of gas extraction in coal mine, in particular to a directional drilling gas extraction optimization method based on dynamic monitoring of coal seam permeability, comprising the following steps: step 1: coal seam permeability dynamic monitoring system is built, S1.1 sensor arrangement: along the directional drilling trajectory of the target coal seam, distributed gas pressure sensor, gas flow sensor, and ground stress sensor are arranged at intervals of 1m; the present application adopts an underground distributed sensor array to realize dynamic and continuous monitoring of coal seam permeability, with a resolution of 1m, which can accurately capture the influence of mining disturbance and ground stress change on permeability and provide real-time data support for extraction optimization; based on the dynamic distribution model of permeability, the depth, spacing, inclination and branch angle of the directional drilling are adaptively adjusted to realize the accurate layout of "fewer drilling holes in high-permeability areas and more drilling holes in low-permeability areas", and the pure flow of gas extraction is improved by more than 30%, and the extraction standard period is shortened by 25%.

Description

Technical Field

[0001] This invention relates to the field of underground gas extraction technology in coal mines, specifically to an optimized method for directional borehole gas extraction based on dynamic monitoring of coal seam permeability. Background Technology

[0002] Coal seam gas drainage is a core technology for coal mine gas disaster prevention and clean energy utilization. Directional borehole drainage, due to its advantages of wide coverage and high drainage efficiency, has become the mainstream drainage technology for high-gas mines. However, traditional directional borehole gas drainage methods have significant technical drawbacks:

[0003] Permeability monitoring is static and cannot reflect the dynamic changes in coal seams: Traditional coal seam permeability testing mostly uses laboratory coal sample measurements or underground single-point static pressure tests, obtaining static data at a certain moment. However, during mining disturbances, changes in ground stress, and gas drainage, the permeability of coal seams undergoes significant spatiotemporal evolution, and static data cannot guide the dynamic adjustment of drainage parameters.

[0004] Drilling parameter design is based on experience and lacks specificity: parameters such as depth, spacing, dip angle, and branch angle of directional drilling are mostly determined based on geological exploration reports and engineering experience, without being coupled with the distribution characteristics of coal seam permeability. Areas with high permeability are prone to waste of negative pressure during extraction, while areas with low permeability result in substandard extraction, leading to low overall extraction efficiency.

[0005] Fixed extraction parameters and lack of dynamic control mechanisms: In traditional gas extraction processes, parameters such as extraction negative pressure and sealing hole length are not adjusted once set. As gas extraction progresses, coal seam gas pressure decreases and permeability changes. Fixed parameters will cause the extraction effect to decline and may even lead to local gas exceedances.

[0006] Lack of a closed-loop optimization system leads to delayed evaluation of gas extraction effectiveness: Traditional methods have not established a closed-loop system of "monitoring-analysis-optimization-control-feedback". The evaluation of gas extraction effectiveness is mostly carried out after the extraction is completed, and it is impossible to correct the borehole layout and extraction parameters in real time, resulting in a long gas extraction compliance cycle and high costs.

[0007] While existing technologies have made preliminary explorations into coal seam permeability monitoring and directional borehole extraction, they have not yet formed an integrated technical solution of "dynamic permeability monitoring - spatiotemporal evolution modeling - adaptive optimization of directional borehole parameters - real-time control of the extraction process." This makes it difficult to solve the core problems of low gas extraction efficiency and high safety risks in high-gas mines. Therefore, this paper proposes an optimization method for directional borehole gas extraction based on dynamic monitoring of coal seam permeability. Summary of the Invention

[0008] In view of this, the present invention provides an optimized method for directional borehole gas extraction based on dynamic monitoring of coal seam permeability, in order to solve or alleviate the technical problems existing in the prior art, and at least provide a beneficial option.

[0009] The technical solution of this invention is implemented as follows: an optimization method for directional borehole gas extraction based on dynamic monitoring of coal seam permeability, comprising the following steps:

[0010] Step 1: Establishment of a dynamic monitoring system for coal seam permeability

[0011] S1.1 Sensor Layout: Along the directional drilling trajectory of the target coal seam, distributed gas pressure sensors, gas flow sensors, and ground stress sensors are arranged at 1m intervals; extraction negative pressure sensors and gas concentration sensors are arranged at the borehole openings.

[0012] S1.2 Data Acquisition System Debugging: Connect the sensor to the downhole data acquisition substation and the ground monitoring center, and set the data acquisition frequency to 5 minutes / time to ensure real-time data transmission;

[0013] Step 2: Dynamic data acquisition and preprocessing of coal seam permeability

[0014] S2.1 Real-time data acquisition: Acquire data on gas pressure, gas flow rate, ground stress, extraction negative pressure, and gas concentration of the target coal seam;

[0015] S2.2 Data Preprocessing: Wavelet denoising algorithm is used to eliminate sensor noise and remove outlier data; the real-time coal seam permeability coefficient is calculated based on Darcy's law, using the following formula:

[0016] In the formula, The air permeability coefficient, For gas flow, For gas dynamic viscosity, The length of the borehole section. To determine the area affected by the extraction, For gas pressure difference;

[0017] Step 3: Construction of a spatiotemporal evolution model for coal seam permeability

[0018] S3.1 Data Modeling: The pre-processed permeability coefficient is coupled with geological parameters (coal seam depth, coal body structure) and mining disturbance parameters (working face advance distance), and a BP neural network is used to construct a spatiotemporal evolution model of coal seam permeability;

[0019] S3.2 Model Validation: The accuracy of the model is verified using field measurement data to ensure that the model prediction error is ≤5%;

[0020] Step 4: Adaptive optimization of directional drilling parameters

[0021] S4.1 Permeability Zoning: Based on the spatiotemporal evolution model, the target coal seam is divided into high permeability zones. Medium breathability zone Low air permeability area ;

[0022] S4.2 Drilling parameter optimization: The drilling spacing in the high permeability zone is set to 20-25m, the drilling spacing in the low permeability zone is set to 8-12m, and the drilling spacing in the medium permeability zone is set to 15-20m; adjust the drilling inclination angle and branch angle to ensure that the drilling trajectory covers the low permeability zone.

[0023] Step 5: Dynamic Control of Gas Drainage Process

[0024] S5.1 Extraction negative pressure control: The extraction negative pressure in the high permeability zone is set to 15~20kPa, in the medium permeability zone to 20~25kPa, and in the low permeability zone to 25~30kPa; the negative pressure value is automatically adjusted according to the real-time changes in permeability.

[0025] S5.2 Sealing parameter optimization: The sealing length in the low permeability zone is set to 8-10m, and the sealing length in the high permeability zone is set to 4-6m to enhance the sealing performance.

[0026] Step 6: Evaluation of Sampling Results and Closed-Loop Feedback

[0027] S6.1 Effectiveness Evaluation: The pure gas extraction flow rate, gas concentration, and residual gas pressure in the coal seam are used as evaluation indicators, and the evaluation period is 24 hours.

[0028] S6.2 Closed-loop feedback: If the extraction effect does not meet the standard, the drilling parameters and extraction parameters are re-optimized based on the latest air permeability data until the extraction meets the standard.

[0029] Further optimized modules include downhole monitoring, data processing, model analysis, parameter optimization, extraction control, and performance evaluation. These modules are interconnected via industrial Ethernet to form a closed-loop optimization system.

[0030] (1) Downhole monitoring module: including distributed gas pressure sensor, gas flow sensor, ground stress sensor and extraction negative pressure sensor, used to collect dynamic parameters of coal seam in real time;

[0031] (2) Data processing module: including downhole data acquisition substation and ground data server, used for data noise reduction, outlier removal and permeability coefficient calculation;

[0032] (3) Model analysis module: Based on the BP neural network algorithm, a spatiotemporal evolution model of coal seam permeability is constructed to predict the permeability distribution;

[0033] (4) Parameter optimization module: Based on the permeability zoning results, adaptively generate optimization schemes for directional drilling spacing, inclination angle, and branch angle;

[0034] (5) Extraction control module: including negative pressure automatic regulating valve and sealing material injection system, used to dynamically adjust extraction negative pressure and sealing parameters;

[0035] (6) Effect evaluation module: evaluate the sampling effect in real time based on the sampling indicators and generate feedback optimization instructions.

[0036] More preferably, the distributed sensor in step 1 is a mine explosion-proof sensor with an IP68 protection rating, which can work stably in underground environments with 95% humidity and temperatures ranging from -20 to 60°C.

[0037] More preferably, the wavelet denoising algorithm in step 2 is based on the db4 wavelet base and has a decomposition layer of 3, which can effectively eliminate power frequency interference and electromagnetic interference from the sensor.

[0038] More preferably, the input layer nodes of the BP neural network in step 3 are gas pressure, ground stress, and coal seam burial depth, the number of hidden layer nodes is 12, and the output layer nodes are permeability coefficient.

[0039] More preferably, the directional drilling in step 4 is carried out using a tracked directional drilling rig, with a drilling depth of up to 500m and a drilling trajectory deviation of ≤0.5°.

[0040] More preferably, the regulating accuracy of the extraction negative pressure automatic regulating valve in step 5 is ±0.5kPa, which can be adjusted in real time according to the instructions of the ground monitoring center.

[0041] Preferably, the ground monitoring center adopts a PLC programmable controller, which supports remote control and data visualization, and can display the coal seam permeability distribution cloud map and extraction parameters in real time.

[0042] More preferably, the extraction standards in step 6 are: residual gas pressure in the coal seam ≤ 0.74 MPa, and gas extraction rate ≥ 60%.

[0043] Furthermore, this method is applicable to all types of high-gas mines, especially coal seams that are significantly affected by mining disturbances and have drastic spatial and temporal variations in permeability.

[0044] The embodiments of the present invention have the following advantages due to the adoption of the above technical solutions:

[0045] I. This invention employs a distributed sensor array in the well to achieve dynamic and continuous monitoring of coal seam permeability with a resolution of 1m. It can accurately capture the impact of mining disturbances and changes in ground stress on permeability, providing real-time data support for drainage optimization. Based on a dynamic permeability distribution model, it adaptively adjusts the depth, spacing, inclination angle, and branch angle of directional boreholes to achieve a precise layout of "fewer boreholes in high permeability areas and more dense boreholes in low permeability areas." This increases the pure flow rate of gas drainage by more than 30% and shortens the drainage compliance period by 25%.

[0046] Second, this invention dynamically adjusts parameters such as extraction negative pressure and sealing hole length based on real-time permeability monitoring data, avoiding waste of negative pressure in high permeability areas and insufficient extraction in low permeability areas, reducing the number of times underground gas concentration exceeds the limit by 80%; it establishes a closed-loop system of "monitoring-modeling-optimization-control-evaluation-feedback", shortening the extraction effect evaluation cycle to 24 hours, and can correct parameters in real time based on the evaluation results to adapt to dynamic changes in the coal seam.

[0047] Third, the present invention integrates automated modules for data acquisition, modeling analysis, and parameter control, reducing the workload of manual on-site surveying and adjustment, lowering labor costs by 40%, and avoiding the safety risks of personnel working underground.

[0048] The above overview is for illustrative purposes only and is not intended to be limiting in any way. In addition to the illustrative aspects, embodiments, and features described above, further aspects, embodiments, and features of the invention will become readily apparent from the accompanying drawings and the following detailed description. Attached Figure Description

[0049] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0050] Figure 1 This is a structural diagram of the present invention. Detailed Implementation

[0051] In the following description, only certain exemplary embodiments are briefly described. As those skilled in the art will recognize, the described embodiments can be modified in various ways without departing from the spirit or scope of the invention. Therefore, the drawings and description are considered to be exemplary in nature and not restrictive.

[0052] The embodiments of the present invention will now be described in detail with reference to the accompanying drawings.

[0053] like Figure 1 As shown, this embodiment of the invention provides an optimized method for directional borehole gas extraction based on dynamic monitoring of coal seam permeability, comprising the following steps:

[0054] Step 1: Establishment of a dynamic monitoring system for coal seam permeability

[0055] S1.1 Sensor Layout: Along the directional drilling trajectory of the target coal seam, distributed gas pressure sensors, gas flow sensors, and ground stress sensors are arranged at 1m intervals; extraction negative pressure sensors and gas concentration sensors are arranged at the borehole openings.

[0056] S1.2 Data Acquisition System Debugging: Connect the sensor to the downhole data acquisition substation and the ground monitoring center, and set the data acquisition frequency to 5 minutes / time to ensure real-time data transmission;

[0057] Step 2: Dynamic data acquisition and preprocessing of coal seam permeability

[0058] S2.1 Real-time data acquisition: Acquire data on gas pressure, gas flow rate, ground stress, extraction negative pressure, and gas concentration of the target coal seam;

[0059] S2.2 Data Preprocessing: Wavelet denoising algorithm is used to eliminate sensor noise and remove outlier data; the real-time coal seam permeability coefficient is calculated based on Darcy's law, using the following formula:

[0060] In the formula, The air permeability coefficient, For gas flow, For gas dynamic viscosity, The length of the borehole section. To determine the area affected by the extraction, For gas pressure difference;

[0061] Step 3: Construction of a spatiotemporal evolution model for coal seam permeability

[0062] S3.1 Data Modeling: The pre-processed permeability coefficient is coupled with geological parameters (coal seam depth, coal body structure) and mining disturbance parameters (working face advance distance), and a BP neural network is used to construct a spatiotemporal evolution model of coal seam permeability;

[0063] S3.2 Model Validation: The accuracy of the model is verified using field measurement data to ensure that the model prediction error is ≤5%;

[0064] Step 4: Adaptive optimization of directional drilling parameters

[0065] S4.1 Permeability Zoning: Based on the spatiotemporal evolution model, the target coal seam is divided into high permeability zones. Medium breathability zone Low air permeability area ;

[0066] S4.2 Drilling parameter optimization: The drilling spacing in the high permeability zone is set to 20-25m, the drilling spacing in the low permeability zone is set to 8-12m, and the drilling spacing in the medium permeability zone is set to 15-20m; adjust the drilling inclination angle and branch angle to ensure that the drilling trajectory covers the low permeability zone.

[0067] Step 5: Dynamic Control of Gas Drainage Process

[0068] S5.1 Extraction negative pressure control: The extraction negative pressure in the high permeability zone is set to 15~20kPa, in the medium permeability zone to 20~25kPa, and in the low permeability zone to 25~30kPa; the negative pressure value is automatically adjusted according to the real-time changes in permeability.

[0069] S5.2 Sealing parameter optimization: The sealing length in the low permeability zone is set to 8-10m, and the sealing length in the high permeability zone is set to 4-6m to enhance the sealing performance.

[0070] Step 6: Evaluation of Sampling Results and Closed-Loop Feedback

[0071] S6.1 Effectiveness Evaluation: The pure gas extraction flow rate, gas concentration, and residual gas pressure in the coal seam are used as evaluation indicators, and the evaluation period is 24 hours.

[0072] S6.2 Closed-loop feedback: If the extraction effect does not meet the standard, the drilling parameters and extraction parameters are re-optimized based on the latest air permeability data until the extraction meets the standard.

[0073] In one embodiment, the system includes a downhole monitoring module, a data processing module, a model analysis module, a parameter optimization module, a pumping control module, and an effect evaluation module. These modules are interconnected via an industrial Ethernet network to form a closed-loop optimization system.

[0074] (1) Downhole monitoring module: including distributed gas pressure sensor, gas flow sensor, ground stress sensor and extraction negative pressure sensor, used to collect dynamic parameters of coal seam in real time;

[0075] (2) Data processing module: including downhole data acquisition substation and ground data server, used for data noise reduction, outlier removal and permeability coefficient calculation;

[0076] (3) Model analysis module: Based on the BP neural network algorithm, a spatiotemporal evolution model of coal seam permeability is constructed to predict the permeability distribution;

[0077] (4) Parameter optimization module: Based on the permeability zoning results, adaptively generate optimization schemes for directional drilling spacing, inclination angle, and branch angle;

[0078] (5) Extraction control module: including negative pressure automatic regulating valve and sealing material injection system, used to dynamically adjust extraction negative pressure and sealing parameters;

[0079] (6) Effect evaluation module: evaluate the sampling effect in real time based on the sampling indicators and generate feedback optimization instructions.

[0080] In one embodiment, the distributed sensor in step 1 is a mine explosion-proof sensor with an IP68 protection rating, which can work stably in an underground environment with 95% humidity and a temperature of -20 to 60°C.

[0081] In one embodiment, the wavelet denoising algorithm in step 2 is based on the db4 wavelet base and has 3 decomposition layers, which can effectively eliminate power frequency interference and electromagnetic interference from the sensor.

[0082] In one embodiment, the input layer nodes of the BP neural network in step 3 are gas pressure, ground stress, and coal seam burial depth, the number of hidden layer nodes is 12, and the output layer nodes are permeability coefficient.

[0083] In one embodiment, the directional drilling in step 4 is carried out using a tracked directional drilling rig, with a drilling depth of up to 500m and a drilling trajectory deviation of ≤0.5°.

[0084] In one embodiment, the control accuracy of the automatic negative pressure regulating valve in step 5 is ±0.5 kPa, which can be adjusted in real time according to the instructions of the ground monitoring center.

[0085] In one embodiment, the ground monitoring center uses a PLC programmable controller, which supports remote control and data visualization, and can display the coal seam permeability distribution cloud map and extraction parameters in real time.

[0086] In one embodiment, the extraction compliance standard in step 6 is: residual gas pressure in the coal seam ≤ 0.74 MPa, and gas extraction rate ≥ 60%.

[0087] In one embodiment, the method is applicable to various types of high-gas mines, especially coal seams that are significantly affected by mining disturbances and have drastic spatial and temporal variations in permeability.

[0088] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any person skilled in the art can easily conceive of various variations or substitutions within the technical scope disclosed in the present invention, and these should all be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. An optimized method for directional borehole gas extraction based on dynamic monitoring of coal seam permeability, characterized in that: Includes the following steps: Step 1: Establishment of a dynamic monitoring system for coal seam permeability S1.1 Sensor Layout: Along the directional drilling trajectory of the target coal seam, distributed gas pressure sensors, gas flow sensors, and ground stress sensors are arranged at 1m intervals; extraction negative pressure sensors and gas concentration sensors are arranged at the borehole openings. S1.2 Data Acquisition System Debugging: Connect the sensor to the downhole data acquisition substation and the ground monitoring center, and set the data acquisition frequency to 5 minutes / time to ensure real-time data transmission; Step 2: Dynamic data acquisition and preprocessing of coal seam permeability S2.1 Real-time data acquisition: Acquire data on gas pressure, gas flow rate, ground stress, extraction negative pressure, and gas concentration of the target coal seam; S2.2 Data Preprocessing: Wavelet noise reduction algorithm is used to eliminate sensor noise and remove abnormal data; The formula for calculating the real-time coal seam permeability coefficient based on Darcy's law is as follows: In the formula, The air permeability coefficient, For gas flow, For gas dynamic viscosity, The length of the borehole section. To determine the area affected by the extraction, For gas pressure difference; Step 3: Construction of a spatiotemporal evolution model for coal seam permeability S3.1 Data Modeling: The pre-processed permeability coefficient is coupled with geological parameters (coal seam depth, coal body structure) and mining disturbance parameters (working face advance distance), and a BP neural network is used to construct a spatiotemporal evolution model of coal seam permeability; S3.2 Model Validation: The accuracy of the model is verified using field measurement data to ensure that the model prediction error is ≤5%; Step 4: Adaptive optimization of directional drilling parameters S4.1 Permeability Zoning: Based on the spatiotemporal evolution model, the target coal seam is divided into high permeability zones. Medium breathability zone Low air permeability area ; S4.2 Drilling parameter optimization: The drilling spacing in the high permeability zone is set to 20-25m, the drilling spacing in the low permeability zone is set to 8-12m, and the drilling spacing in the medium permeability zone is set to 15-20m; adjust the drilling inclination angle and branch angle to ensure that the drilling trajectory covers the low permeability zone. Step 5: Dynamic Control of Gas Drainage Process S5.1 Extraction negative pressure control: The extraction negative pressure in the high permeability zone is set to 15~20kPa, in the medium permeability zone to 20~25kPa, and in the low permeability zone to 25~30kPa; the negative pressure value is automatically adjusted according to the real-time changes in permeability. S5.2 Sealing parameter optimization: The sealing length in the low permeability zone is set to 8-10m, and the sealing length in the high permeability zone is set to 4-6m to enhance the sealing performance. Step 6: Evaluation of Sampling Results and Closed-Loop Feedback S6.1 Effectiveness Evaluation: The pure gas extraction flow rate, gas concentration, and residual gas pressure in the coal seam are used as evaluation indicators, and the evaluation period is 24 hours. S6.2 Closed-loop feedback: If the extraction effect does not meet the standard, the drilling parameters and extraction parameters are re-optimized based on the latest air permeability data until the extraction meets the standard.

2. The system for optimizing directional borehole gas extraction based on dynamic monitoring of coal seam permeability according to claim 1, characterized in that: It includes a downhole monitoring module, a data processing module, a model analysis module, a parameter optimization module, a pumping control module, and an effect evaluation module. These modules are interconnected via an industrial Ethernet network to form a closed-loop optimization system. (1) Downhole monitoring module: including distributed gas pressure sensor, gas flow sensor, ground stress sensor and extraction negative pressure sensor, used to collect dynamic parameters of coal seam in real time; (2) Data processing module: including downhole data acquisition substation and ground data server, used for data noise reduction, outlier removal and permeability coefficient calculation; (3) Model analysis module: Based on the BP neural network algorithm, a spatiotemporal evolution model of coal seam permeability is constructed to predict the permeability distribution; (4) Parameter optimization module: Based on the permeability zoning results, adaptively generate optimization schemes for directional drilling spacing, inclination angle, and branch angle; (5) Extraction control module: including negative pressure automatic regulating valve and sealing material injection system, used to dynamically adjust extraction negative pressure and sealing parameters; (6) Effect evaluation module: evaluate the sampling effect in real time based on the sampling indicators and generate feedback optimization instructions.

3. The optimized method for directional borehole gas extraction based on dynamic monitoring of coal seam permeability according to claim 1, characterized in that: The distributed sensor mentioned in step 1 is a mine-use explosion-proof sensor with an IP68 protection rating, which can work stably in underground environments with 95% humidity and temperatures ranging from -20 to 60°C.

4. The optimized method for directional borehole gas extraction based on dynamic monitoring of coal seam permeability according to claim 1, characterized in that: The wavelet denoising algorithm described in step 2 is based on the db4 wavelet base and has a decomposition layer of 3, which can effectively eliminate power frequency interference and electromagnetic interference from the sensor.

5. The optimized method for directional borehole gas extraction based on dynamic monitoring of coal seam permeability according to claim 1, characterized in that: The input layer nodes of the BP neural network described in step 3 are gas pressure, ground stress, and coal seam burial depth, the number of hidden layer nodes is 12, and the output layer nodes are permeability coefficient.

6. The optimized method for directional borehole gas extraction based on dynamic monitoring of coal seam permeability according to claim 1, characterized in that: The directional drilling described in step 4 is carried out using a tracked directional drilling rig, with a drilling depth of up to 500m and a drilling trajectory deviation of ≤0.5°.

7. The optimized method for directional borehole gas extraction based on dynamic monitoring of coal seam permeability according to claim 1, characterized in that: The automatic regulating valve for extraction negative pressure mentioned in step 5 has a regulation accuracy of ±0.5 kPa and can be adjusted in real time according to the instructions of the ground monitoring center.

8. The system for optimizing directional borehole gas extraction based on dynamic monitoring of coal seam permeability according to claim 2, characterized in that: The ground monitoring center uses a PLC programmable controller, which supports remote control and data visualization, and can display the coal seam permeability distribution cloud map and extraction parameters in real time.

9. The optimized method for directional borehole gas extraction based on dynamic monitoring of coal seam permeability according to claim 1, characterized in that: The extraction standards mentioned in step 6 are: residual gas pressure in the coal seam ≤ 0.74 MPa, and gas extraction rate ≥ 60%.

10. The method for optimizing directional borehole gas extraction based on dynamic monitoring of coal seam permeability according to claim 1, characterized in that: This method is applicable to all types of high-gas mines, especially coal seams that are significantly affected by mining disturbances and have drastic spatial and temporal variations in permeability.

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