Electric field induced coal seam fracturing gas extraction method

Abstract

The application discloses a kind of electric field induced fracturing coal seam gas extraction methods for increasing permeability, belong to coal seam gas extraction field, comprising the following steps: S1, field reconnaissance;S2, generate three-dimensional geological model;S3, carry out electric field induced fracturing simulation, until the optimal fracturing path is obtained, the corresponding electric field parameter of optimal fracturing path is electric field initial parameter;S4, based on the three-dimensional coal seam image generated, in fracturing area distribution distributed stress sensor, strain sensor and displacement sensor, to monitor stress concentration factor, strain and crack length and width change in coal seam;S5, to coal seam with electric field initial parameter, and based on dynamic adjustment electric field parameter, to ensure that optimal fracturing path is reached;S6, extraction gas.The electric field induced fracturing coal seam gas extraction method for increasing permeability described above, based on real-time monitoring data dynamic adjustment electric field parameter, ensure that always along the optimal path fracturing, avoid unnecessary resource waste and security risks.

Description

Technical Field

[0001] This invention relates to the field of coal seam gas extraction, and more particularly to a method for gas extraction from coal seams with enhanced permeability caused by electric field fracturing. Background Technology

[0002] Coalbed methane (CBM), also known as coal seam gas, refers to hydrocarbon gases stored in coal seams. It is primarily composed of methane, mainly adsorbed on the surface of coal matrix particles, with some free space in coal pores or dissolved in coal seam water. It is a by-product of coal mining and belongs to unconventional natural gas. It has emerged as a clean and high-quality energy source and chemical feedstock internationally in the last one or two decades. When the concentration of CBM in the air reaches 5%-16%, it will explode upon contact with an open flame, leading to coal mine explosions. To address this problem, CBM is extracted before coal mining, reducing the coal mine CBM explosion rate to 70% to 85%.

[0003] There are currently various coal seam permeability enhancement technologies, such as high-pressure water fracturing, drilling, and electric field fracturing. Among them, the principle of electric fracturing of coal seams is mainly to use high-voltage electric pulse waves or plasma technology to generate physical effects such as stress waves, shock waves, or water shock waves in the coal seam, thereby inducing the propagation of internal cracks and the fracturing of the coal body, achieving the purpose of fracturing and permeability enhancement.

[0004] Existing electric field fracturing coal seam technologies are as follows:

[0005] CN202110158171.7 discloses a method for enhancing the permeability of coal seams by integrating electric pulse directional slotting and hydraulic blasting. The method involves first constructing positive and negative electrode directional boreholes at the end of a motor-driven borehole in the coal seam. Then, a conductive ion solution is injected into the positive and negative electrode directional boreholes. High-voltage electric pulse technology is used to impact the boreholes, and hydraulic slotting is performed. After slotting, the conductive ion solution in the electrode directional boreholes is discharged using a drainage pump. Finally, pulse blasting is performed on the electrode directional boreholes that have undergone electric pulse hydraulic slotting.

[0006] CN202310176030.7 discloses a device and method for enhanced gas drainage by combining controllable shock wave fracturing of coal seams with gas injection. The device includes a borehole fracturing component and a displacement drainage component. The borehole fracturing component includes a drilling rig, hollow drill rod, high-voltage electric pulse controller, high-voltage electric pulse controllable shock wave generator, multi-functional adapter, and multi-functional sealing plug. The displacement drainage component includes a CO2 gas permeability enhancement system, a CO2 gas injection pipe, a gas drainage pipe, a gas drainage system, and a CO2 gas separation system. The method is as follows: For low-permeability and difficult-to-desorb coal seams, firstly, a batch of boreholes are drilled at the marked locations in the gas drainage area within the coal seam. The boreholes are divided into conventional boreholes and permeability enhancement boreholes, which are alternately distributed. Then, a high-voltage electric pulse controllable shock wave is used to fracture and enhance the permeability of the coal seam, effectively increasing the degree of fracture development. Subsequently, carbon dioxide is used to displace the gas in the coal seam, effectively enhancing the drainage effect of difficult-to-desorb gas in the coal seam and further reducing the risk of gas outburst and gas explosion.

[0007] It is known that the control parameters in the existing electric field fracturing process are mostly set based on experience and cannot be dynamically adjusted according to the on-site environment, resulting in poor anti-reflection effect. Summary of the Invention

[0008] The purpose of this invention is to provide a method for improving the permeability of coal seams through electric field fracturing and gas extraction, thereby solving the aforementioned technical problems.

[0009] To achieve the above objectives, the present invention provides a method for improving the permeability of coal seams through electric field fracturing and gas extraction, comprising the following steps:

[0010] S1. On-site reconnaissance: Collect coal seam lithology data, physical property data, boundary and internal structure data, initial stress, and historical fracturing test data;

[0011] S2. Modeling: Import the coal seam lithology data, physical property data, boundary and internal structure data, initial stress and historical fracturing test data obtained in step S1 into the 3D modeling software to generate a 3D geological model.

[0012] S3. Simulation Experiment: Based on the three-dimensional geological model generated in step S2, electric field fracturing simulation is performed using numerical simulation software until the optimal fracturing path is obtained. The electric field parameters corresponding to the optimal fracturing path are taken as the initial electric field parameters.

[0013] S4. Data monitoring: Based on the three-dimensional coal seam image generated in step S2, distributed stress sensors, strain sensors and displacement sensors are deployed in the fractured area to monitor the stress concentration factor, strain and crack length and width changes in the coal seam.

[0014] S5. Apply the initial electric field parameters determined in step S3 to the coal seam, and dynamically adjust the electric field parameters based on the crack width, stress change and temperature distribution collected in real time in step S4, so as to ensure that the optimal fracturing path described in step S3 is achieved.

[0015] S6. Use gas extraction equipment to extract gas at the inlet of the optimal fracturing path.

[0016] Preferably, in step S1, core samples of the coal seam are taken to obtain coal seam lithology data;

[0017] The method involves using ground-penetrating radar to emit electromagnetic waves into the coal seam and then obtaining the physical property data of the coal seam through the received reflected waves. The physical property data includes the dielectric constant, thickness, density and conductivity of the coal seam.

[0018] The seismic source is applied to the coal seam, and the boundary and internal structure data of the coal seam are determined by the received seismic waves. The internal structure data includes faults, joints, cracks and folds.

[0019] The initial stress field of the coal seam is obtained by borehole measurement.

[0020] Preferably, the 3D modeling software mentioned in step S2 is FLAC3D.

[0021] Preferably, the numerical simulation software mentioned in step S3 is ANSYS or COMSOL;

[0022] Furthermore, step S3 specifically includes the following steps:

[0023] S31. Set initial conditions: Set the initial electric field strength E0 and the initial frequency f0, and determine the boundary conditions of the simulation region;

[0024] S32. Define the following multi-objective function with the comprehensive evaluation index F as the optimization objective:

[0025] F=α1×L+α2×W+α3×D+α4×K t +α5×RII (1);

[0026] In the formula, L represents the crack length in meters (m); W represents the crack width in meters (m); D represents the crack density in cracks per meter (cracks / m²); K... t The stress concentration factor is represented by α1, α2, α3, α4, and α5, which represent the crack length L, crack width W, crack density D, and stress concentration factor K, respectively. t Weighting coefficients corresponding to the rock integrity index RII;

[0027] S33. Numerical Iterative Simulation: Perform numerical iterative simulations by changing the electric field strength E or frequency f, and record the electric field strength E, frequency f, crack length L, crack width W, crack density D, and stress concentration factor K for each simulation. t The iteration continues until the change in the comprehensive evaluation index F is less than a set threshold, along with the rock integrity index RII;

[0028] S34. Determine the optimal fracture path: Select the maximum comprehensive evaluation index F as the optimal fracture path from the iterative results obtained in step S33.

[0029] S35. Determine the electric field strength E and frequency f corresponding to the maximum comprehensive evaluation index F as the initial electric field strength E0 and initial frequency f0, respectively.

[0030] Preferably, in step S32, the weighting coefficient determination steps are as follows:

[0031] Step 1: Initialize the weight coefficients: α1, α2, α3, α4, and α5;

[0032] The second step is to calculate the comprehensive evaluation index F under the initial weight coefficients.

[0033] Step 3: Calculate the partial derivative F′ of the objective function with respect to each weight coefficient:

[0034]

[0035] In the formula, α i where i is the weighting coefficient, and i = 1, 2, 3, 4, 5;

[0036] Step 4: Update the weight coefficients using the gradient descent formula:

[0037]

[0038] In the formula, η represents the learning rate;

[0039] Step 5: Repeat steps 1 through 4 until convergence or the maximum number of iterations is reached;

[0040] Step 6: Output α' after iteration i As the final weighting coefficient.

[0041] Preferably, step S5 specifically includes the following steps:

[0042] S51. Apply an electric field to the coal seam using an electric field application device according to the initial electric field parameters, and monitor the stress concentration factor, strain, and crack length and width changes in the coal seam in real time.

[0043] S52. Based on real-time acquisition of stress concentration factor, strain, and crack length and width variations, the electric field parameters are dynamically adjusted using an adaptive control algorithm.

[0044]

[0045] In the formula, α (t+1) α represents the electric field parameter at the (t+1)th iteration. (t) K represents the electric field parameters at the t-th iteration. p K i and K d These represent the proportional gain, integral gain, and differential gain, respectively; e(t) represents the difference between the current fracturing path and the optimal fracturing path.

[0046] S53. Evaluate the crack propagation and determine whether the crack grows along the optimal crack initiation path. If so, maintain the current electric field parameters; otherwise, return to step S52.

[0047] Therefore, the above-mentioned electric field-induced fracturing coal seam permeability enhancement gas extraction method of the present invention has the following beneficial effects:

[0048] 1. Multi-source data fusion: Through core samples, ground-penetrating radar, seismic waves and borehole measurements, a variety of key data, including coal seam lithology, physical properties, boundary and internal structure, and initial stress, were obtained, providing a foundation for subsequent processing;

[0049] 2. A comprehensive evaluation index is introduced, taking into account multiple factors such as crack length, width, density, stress concentration factor and rock integrity. The weight coefficients are continuously optimized through the gradient descent method to finally determine the optimal crack initiation path, making the results more consistent with reality.

[0050] 3. An adaptive control algorithm is used to fine-tune the electric field parameters, making the whole process more intelligent and flexible, and better able to cope with uncertainties under complex geological conditions;

[0051] 4. By monitoring the stress, strain, and crack propagation in the crack-causing area in real time, problems can be identified and corresponding adjustments can be made in a timely manner, thereby improving the safety and success rate of the operation.

[0052] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0053] Figure 1 This is a flowchart of a method for improving the permeability of coal seams and extracting gas by electric field fracturing according to the present invention. Detailed Implementation

[0054] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the embodiments of the present invention will be further described in detail below with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are merely illustrative of the embodiments of the present invention and are not intended to limit the embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of this application. Examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout.

[0055] It should be noted that the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion, such as a process, method, system, product, or server that includes a series of steps or units, not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such process, method, product, or device.

[0056] The embodiments of the present invention will now be described in detail with reference to the accompanying drawings.

[0057] like Figure 1 As shown, a method for improving the permeability of coal seams through electric field fracturing and gas extraction includes the following steps:

[0058] S1. On-site reconnaissance: Collect coal seam lithology data, physical property data, boundary and internal structure data, initial stress, and historical fracturing test data;

[0059] In step S1, core samples of the coal seam are taken to obtain coal seam lithology data;

[0060] The method involves using ground-penetrating radar to emit electromagnetic waves into the coal seam and then obtaining the physical property data of the coal seam through the received reflected waves. The physical property data includes the dielectric constant, thickness, density and conductivity of the coal seam.

[0061] The seismic source is applied to the coal seam, and the boundary and internal structure data of the coal seam are determined by the received seismic waves. The internal structure data includes faults, joints, cracks and folds.

[0062] The initial stress field of the coal seam is obtained by borehole measurement.

[0063] S2. Modeling: Import the coal seam lithology data, physical property data, boundary and internal structure data, initial stress and historical fracturing test data obtained in step S1 into the 3D modeling software to generate a 3D geological model.

[0064] The 3D modeling software mentioned in step S2 is FLAC3D.

[0065] S3. Simulation Experiment: Based on the three-dimensional geological model generated in step S2, electric field fracturing simulation is performed using numerical simulation software until the optimal fracturing path is obtained. The electric field parameters corresponding to the optimal fracturing path are taken as the initial electric field parameters.

[0066] The numerical simulation software mentioned in step S3 is ANSYS or COMSOL;

[0067] Furthermore, step S3 specifically includes the following steps:

[0068] S31. Set initial conditions: Set the initial electric field strength E0 and the initial frequency f0, and determine the boundary conditions of the simulation region;

[0069] S32. Define the following multi-objective function with the comprehensive evaluation index F as the optimization objective:

[0070] F=α1×L+α2×W+α3×D+α4×K t +α5×RII (1);

[0071] In the formula, L represents the crack length in meters (m); W represents the crack width in meters (m); D represents the crack density in cracks per meter (cracks / m²); K... t The stress concentration factor is represented by α1, α2, α3, α4, and α5, which represent the crack length L, crack width W, crack density D, and stress concentration factor K, respectively. t Weighting coefficients corresponding to the rock integrity index RII;

[0072] In step S32, the weighting coefficients are determined as follows:

[0073] Step 1: Initialize the weight coefficients: α1, α2, α3, α4, and α5;

[0074] The second step is to calculate the comprehensive evaluation index F under the initial weight coefficients.

[0075] Step 3: Calculate the partial derivative F of the objective function with respect to each weight coefficient:

[0076]

[0077] In the formula, α i Let i be the weighting coefficient, and i = 1, 2, 3, 4, 5;

[0078] Step 4: Update the weight coefficients using the gradient descent formula:

[0079]

[0080] In the formula, η represents the learning rate;

[0081] Step 5: Repeat steps 1 through 4 until convergence or the maximum number of iterations is reached;

[0082] Step 6: Output α′ after iteration i As the final weighting coefficient.

[0083] S33. Numerical Iterative Simulation: Perform numerical iterative simulations by changing the electric field strength E or frequency f, and record the electric field strength E, frequency f, crack length L, crack width W, crack density D, and stress concentration factor K for each simulation. t The iteration continues until the change in the comprehensive evaluation index F is less than a set threshold, along with the rock integrity index RII;

[0084] S34. Determine the optimal fracture path: Select the maximum comprehensive evaluation index F as the optimal fracture path from the iterative results obtained in step S33.

[0085] S35. Determine the electric field strength E and frequency f corresponding to the maximum comprehensive evaluation index F as the initial electric field strength E0 and initial frequency f0, respectively.

[0086] S4. Data monitoring: Based on the three-dimensional coal seam image generated in step S2, distributed stress sensors, strain sensors and displacement sensors are deployed in the fractured area to monitor the stress concentration factor, strain and crack length and width changes in the coal seam.

[0087] S5. Apply the initial electric field parameters determined in step S3 to the coal seam, and dynamically adjust the electric field parameters based on the crack width, stress change and temperature distribution collected in real time in step S4, so as to ensure that the optimal fracturing path described in step S3 is achieved.

[0088] Step S5 specifically includes the following steps:

[0089] S51. Apply an electric field to the coal seam using an electric field application device according to the initial electric field parameters, and monitor the stress concentration factor, strain, and crack length and width changes in the coal seam in real time.

[0090] S52. Based on real-time acquisition of stress concentration factor, strain, and crack length and width variations, the electric field parameters are dynamically adjusted using an adaptive control algorithm.

[0091]

[0092] In the formula, α (t+1) α represents the electric field parameter at the (t+1)th iteration. (t) K represents the electric field parameters at the t-th iteration. p K i and K dThese represent the proportional gain, integral gain, and differential gain, respectively; e(t) represents the difference between the current fracturing path and the optimal fracturing path.

[0093] S53. Evaluate the crack propagation and determine whether the crack grows along the optimal crack initiation path. If so, maintain the current electric field parameters; otherwise, return to step S52.

[0094] S6. Use gas extraction equipment to extract gas at the inlet of the optimal fracturing path.

[0095] Example:

[0096] In order to verify the effectiveness of the electric field-induced fracturing coal seam permeability enhancement gas extraction method described in this invention at a coal mine site, the following steps were implemented:

[0097] 1. On-site reconnaissance and data collection: By taking core samples from the coal seam, lithological data of the coal seam were obtained, including the hardness and brittleness of the coal.

[0098] By using ground-penetrating radar to emit electromagnetic waves into the coal seam and receiving the reflected waves, physical property data of the coal seam were obtained, specifically including the dielectric constant, thickness (average 5m), and density (average 1.4g / cm³). 3 ) and conductivity.

[0099] By applying seismic sources to the coal seam and receiving seismic waves, the boundaries and internal structure data of the coal seam were determined, including the distribution of faults, joints, cracks and folds.

[0100] The initial stress field data of the coal seam were obtained through borehole measurements, which provided a basis for subsequent simulation experiments.

[0101] 2. Construction of 3D geological model: All data obtained from the on-site reconnaissance were imported into FLAC3D 3D modeling software to generate a high-precision 3D geological model, providing an accurate physical basis for electric field-induced fracturing simulation.

[0102] 3. Electric field-induced fracturing simulation and optimization: Electric field-induced fracturing simulation was performed in ANSYS numerical simulation software based on the generated three-dimensional geological model. The initial electric field strength and frequency were set, and the boundary conditions of the simulation area were determined.

[0103] Through multi-objective function optimization, taking into account crack length, crack width, crack density, stress concentration factor (averaged to 0.5), and rock integrity index, the optimal crack initiation path and corresponding initial electric field parameters were determined.

[0104] 4. Data monitoring and electric field parameter adjustment: Distributed stress sensors, strain sensors and displacement sensors were deployed in the fracturing area to monitor the stress concentration factor, strain and crack length and width changes in the coal seam in real time.

[0105] 5. Apply an electric field to the coal seam using an electric field application device according to the optimized initial electric field parameters, and dynamically adjust the electric field parameters based on real-time monitoring data to ensure that the cracks grow along the optimal crack initiation path.

[0106] 6. Gas drainage: Gas drainage equipment was installed at the entrance of the optimal fracturing path, and gas drainage operations were carried out.

[0107] The average fracture length obtained using the above method reached 25m, effectively increasing the permeability of the coal seam. The average fracture width was 0.025m, providing a good channel for gas drainage. Furthermore, after fracturing, the fracture density of the coal seam increased to an average of 5 fractures / m, further improving the permeability of the coal seam.

[0108] Stress concentration factor: Through electric field fracturing, the average stress concentration factor of the coal seam was reduced to 0.5, which effectively alleviated the stress concentration phenomenon in the coal seam.

[0109] Gas extraction efficiency: Compared with coal seams that have not undergone electric field fracturing, the gas extraction efficiency has increased by more than 55%, significantly improving the safety level of coal mine production.

[0110] In summary, the implementation of the electric field-induced fracturing method for gas extraction in coal seams not only effectively increases the permeability and infiltration rate of the coal seam, but also significantly improves the gas extraction efficiency, providing a strong guarantee for the safe production of coal mines.

[0111] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the technical solutions of the present invention, and these modifications or equivalent substitutions cannot cause the modified technical solutions to deviate from the spirit and scope of the technical solutions of the present invention.

Claims

1. A method for improving the permeability of coal seams and extracting gas using electric field-induced fracturing, characterized in that: Includes the following steps: S1. On-site reconnaissance: Collect coal seam lithology data, physical property data, boundary and internal structure data, initial stress, and historical fracturing test data; S2. Modeling: Import the coal seam lithology data, physical property data, boundary and internal structure data, initial stress and historical fracturing test data obtained in step S1 into the 3D modeling software to generate a 3D geological model. S3. Simulation Experiment: Based on the three-dimensional geological model generated in step S2, electric field fracturing simulation is performed using numerical simulation software until the optimal fracturing path is obtained. The electric field parameters corresponding to the optimal fracturing path are taken as the initial electric field parameters. S4. Data monitoring: Based on the three-dimensional coal seam image generated in step S2, distributed stress sensors, strain sensors and displacement sensors are deployed in the fractured area to monitor the stress concentration factor, strain and crack length and width changes in the coal seam. S5. Apply the initial electric field parameters determined in step S3 to the coal seam, and dynamically adjust the electric field parameters based on the crack width, stress change and temperature distribution collected in real time in step S4, so as to ensure that the optimal fracturing path described in step S3 is achieved. S6. Use gas extraction equipment to extract gas at the inlet of the optimal fracturing path; The numerical simulation software mentioned in step S3 is ANSYS or COMSOL; Furthermore, step S3 specifically includes the following steps: S31. Set initial conditions: Set the initial electric field strength. and initial frequency And determine the boundary conditions of the simulation region; S32, using comprehensive evaluation indicators The following multi-objective function is defined as the optimization objective: （1）； In the formula, This indicates the crack length, in meters (m). This indicates the crack width, in meters (m). This indicates the crack density, expressed in cracks / m. Indicates the stress concentration factor; Indicators representing rock integrity; , , , and These are the crack lengths. Crack width Crack density Stress concentration factor and rock integrity index The corresponding weighting coefficients; S33. Numerical Iterative Simulation: Changing the Electric Field Intensity or frequency Perform numerical iterative simulations and record the electric field intensity in each simulation. ,frequency Crack length Crack width Crack density Stress concentration factor and rock integrity index Until the comprehensive evaluation indicators If the change is less than a set threshold, the iteration stops. S34. Determine the optimal fracturing path: Select the maximum comprehensive evaluation index from the iterative results obtained in step S33. As the optimal fracture-inducing path; S35. Determine the maximum comprehensive evaluation index. corresponding electric field strength and frequency As the initial electric field strength and initial frequency .

2. The method for improving the permeability of coal seams and extracting gas according to claim 1, characterized in that: In step S1, core samples of the coal seam are taken to obtain coal seam lithology data; The method involves using ground-penetrating radar to emit electromagnetic waves into the coal seam and then obtaining the physical property data of the coal seam through the received reflected waves. The physical property data includes the dielectric constant, thickness, density and conductivity of the coal seam. The seismic source is applied to the coal seam, and the boundary and internal structure data of the coal seam are determined by the received seismic waves. The internal structure data includes faults, joints, cracks and folds. The initial stress field of the coal seam is obtained by borehole measurement.

3. The method for improving the permeability of coal seams and extracting gas according to claim 2, characterized in that: The 3D modeling software mentioned in step S2 is FLAC3D.

4. The method for improving the permeability of coal seams and extracting gas according to claim 3, characterized in that: In step S32, the weighting coefficients are determined as follows: Step 1: Initialize weight coefficients: , , , and ; Step 2: Calculate the comprehensive evaluation index under the initial weight coefficients. ; Step 3: Calculate the partial derivative of the objective function with respect to each weight coefficient. : （2）； In the formula, These are the weighting coefficients, and ; Step 4: Update the weight coefficients using the gradient descent formula: （3）； In the formula, Indicates the learning rate; Step 5: Repeat steps 1 through 4 until convergence or the maximum number of iterations is reached; Step 6: Output the results after iteration. As the final weighting coefficient.

5. The method for improving the permeability of coal seams and extracting gas according to claim 4, characterized in that: Step S5 specifically includes the following steps: S51. Apply an electric field to the coal seam using an electric field application device according to the initial electric field parameters, and monitor the stress concentration factor, strain, and crack length and width changes in the coal seam in real time. S52. Based on real-time acquisition of stress concentration factor, strain, and crack length and width variations, the electric field parameters are dynamically adjusted using an adaptive control algorithm. （4）； In the formula, Indicates the first Electric field parameters at the next iteration; Indicates the first Electric field parameters at the next iteration; , and These represent proportional gain, integral gain, and derivative gain, respectively. This represents the difference between the current fracturing path and the optimal fracturing path; S53. Evaluate the crack propagation and determine whether the crack grows along the optimal crack initiation path. If so, maintain the current electric field parameters; otherwise, return to step S52.

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