A method for pre-evaluating the effect of pre-fracturing anti-hammering and shock control of a ground horizontal well
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- 鄂尔多斯市国源矿业开发有限责任公司
- Filing Date
- 2026-04-07
- Publication Date
- 2026-07-21
Smart Images
Figure CN122432758A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of coal mining technology, and in particular to a method for pre-evaluation of the anti-shock and vibration control effect before fracturing horizontal wells on the surface. Background Technology
[0002] In recent years, coal mining depths have been continuously increasing, and mining operations have gradually entered more complex geological areas. Mine tremors and rockbursts are currently the main dynamic hazards in my country's mining industry. Thick, hard rock layers are commonly found above coal seams. With the expansion of underground mining areas, the movement of these thick, hard key strata easily triggers mine tremor loads, leading to underground rockbursts, which severely restrict safe mine production. Currently, the effective means of preventing rockbursts induced by low- to medium-level mine tremors is underground fracturing, while horizontal well surface fracturing technology is an effective means of preventing high-level mine tremors. Compared with underground directional drilling fracturing, surface horizontal well fracturing technology for managing rockbursts has advantages such as larger fracturing capacity (12-14 m³ / min) and longer fractures (radius > 150 m). Practice has shown that surface horizontal well fracturing can achieve the goals of pre-fracture of the working face roof, regional pressure relief, reducing the pressure step distance of the working face, and reducing the pressure intensity, while also protecting roadways and reducing roadway floor heave and spalling accidents. Currently, during the construction of surface hydraulic fracturing for the prevention and control of dynamic disasters in coal mines, there are problems such as unclear identification of the effect of overburden structure modification and the degree of change in regional stress environment. As a result, the anti-scour effect of some mines after adopting surface fracturing measures is difficult to achieve the expected goal, which directly affects the promotion and application of surface hydraulic fracturing technology in coal mine anti-scour work.
[0003] Microseismic monitoring technology is a key technology for evaluating fracturing effectiveness. It involves receiving seismic wave signals from fractured underground rocks and using this data to determine the spatial location and timing of rock fractures. In recent years, with the large-scale exploration and development of unconventional oil and gas resources such as tight oil and shale oil, the application of microseismic monitoring technology in oil and gas field fracturing has developed rapidly. Early microseismic analysis primarily utilized the spatial location information of events to interpret the length, width, height, and azimuth of fracturing fractures. Current microseismic monitoring interpretation techniques mainly combine parameters such as the magnitude, energy, and distribution characteristics of microseismic events to determine the orientation and location of natural fractures. Simultaneously, by calculating the reservoir stimulation volume (SRV), interpretation work is carried out on the spacing of fracturing clusters and the fracturing range. However, this method lacks sufficient depth in assessing fracturing effectiveness, lacks a quantitative system, and has low utilization of multi-source data, making it impossible to predict risks in advance. Summary of the Invention
[0004] The technical problem to be solved by the present invention is to provide a pre-evaluation method for the anti-surge and vibration control effect of surface horizontal well fracturing in view of the above-mentioned shortcomings. The method determines the size parameters of the fracturing rock section based on the on-site construction and monitoring, further obtains the evaluation parameters of the anti-surge effect of surface hydraulic fracturing, and uses comprehensive evaluation to quantitatively pre-evaluate the anti-surge and vibration control effect of surface hydraulic fracturing.
[0005] To solve the above-mentioned technical problems, the technical solution adopted by the present invention is: a method for pre-evaluation of the anti-shock and vibration control effect before fracturing of surface horizontal wells, comprising: Step 1: Obtain geological and mining data of the fracturing mine and on-site fracturing operation monitoring data; Step 2: Based on the obtained geological and mining data of the fractured mine and the on-site fracturing construction monitoring data, determine each fracturing section and the multiple evaluation parameters corresponding to each fracturing section; Step 3: Preprocess each evaluation parameter of each fracturing section, and based on the preprocessed evaluation parameters, use the CRITIC method to determine the weight of each evaluation parameter, and calculate the evaluation value of the shock and vibration control effect of each fracturing section by weighted summation method. Step 4: Classify the effectiveness of each fracturing section based on its anti-shock and seismic control performance evaluation value, and output a pre-evaluation report.
[0006] Furthermore, the evaluation parameters include: geometric parameters, energy parameters, volumetric parameters, microseismic activity parameters, and stress state parameters.
[0007] Furthermore, the determination of the evaluation parameters includes: Geometric parameters: obtained directly from geological and mining data of the fracturing mine and on-site fracturing construction monitoring data; Energy parameters: calculated using a ground microseismic monitoring system based on on-site fracturing construction monitoring data; Volumetric parameters: Calculated using an octree algorithm based on on-site fracturing construction monitoring data; Microseismic activity parameters: calculated using a point cloud local adaptive density algorithm based on on-site fracturing construction monitoring data; Stress state parameters include the average stress concentration factor and pore pressure variation. The average stress concentration factor is obtained by inversion of the coupled numerical model of geomechanics and fracturing construction based on the on-site fracturing construction monitoring data. The pore pressure variation is obtained by estimating the injection influence range based on the fracturing pressure data based on the on-site fracturing construction monitoring data.
[0008] Furthermore, in step 3, the preprocessing of each evaluation parameter for each fracturing section includes: Data cleaning was performed on the various evaluation parameters of each fracturing section; After data cleaning, the evaluation parameters of each fracturing segment were normalized.
[0009] Furthermore, in step 3, the weight of each evaluation parameter is determined using the CRITIC method based on the preprocessed evaluation parameters, including: Construct the original data matrix X, we have
[0010] In the formula, each row of the original data matrix X corresponds to a fracturing segment, each column corresponds to an evaluation parameter, m is the total number of fracturing segments, and n is the total number of index parameters. For the j-th evaluation parameter, standardization is performed to obtain the standardized matrix. ,have
[0011] In the formula, z ij x is the standardized value of the j-th evaluation parameter in the i-th fracturing segment. ij Let j be the value of the evaluation parameter in the i-th fracturing segment, min(x ij ) represents the minimum value of the j-th evaluation parameter in each fracturing segment, max(x) ij ) represents the maximum value of the j-th evaluation parameter in each fracturing segment; Calculate the standard deviation of the j-th evaluation parameter. ,have
[0012] In the formula, The mean of the standardized values of the j-th evaluation parameter; Calculate the correlation coefficient matrix of each evaluation parameter. , where r jk The Pearson correlation coefficient between the j-th and k-th evaluation parameters is given by...
[0013] Based on the Pearson correlation coefficient between the j-th and k-th evaluation parameters, the conflict c of the j-th evaluation parameter is calculated. j ,have
[0014] The standard deviation of the j-th evaluation parameter Conflict c with the j-th evaluation parameter j By combining these, we can obtain the information content of the j-th evaluation parameter. C j ,have
[0015] Information content of the j-th evaluation parameter C j After normalization, the weight w of the j-th evaluation parameter is obtained. j ,have
[0016] In the formula, C k Let be the information content of the k-th evaluation parameter.
[0017] Furthermore, in step 3, the calculation of the shock and seismic control effect evaluation value of each fracturing section using the weighted summation method includes: The evaluation values of the shock and seismic control effects of each fracturing section are calculated using the following formula:
[0018] In the formula, CEI i It is the first i Evaluation values of the shock and seismic control effect of each fracturing section; w j It is the weight of the j-th evaluation parameter; X ij It is the first i The value of the j-th evaluation parameter of each fracturing segment.
[0019] Furthermore, in step 4, the effect grading based on the shock and vibration control effect evaluation values of each fracturing section includes: The range of the CEI value for judging the shock and seismic control effect is within CEI>=0.75, 0.5<=CEI<0.75, 0.25<=CEI<0.5, or CEI<0.25; The effect is excellent when CEI>=0.75, good when 0.5<=CEI<0.75, average when 0.25<=CEI<0.5, and poor when CEI<0.25.
[0020] Furthermore, in step 1, the geological and mining data of the fracturing mine includes: coal seam occurrence conditions at the working face, coal mining methods, borehole columnar section and physical and mechanical parameters of each rock stratum.
[0021] Compared with the prior art, the present invention has the following advantages: This invention provides a method for pre-evaluating the anti-shock and vibration control effect before fracturing in surface horizontal wells, which has the following advantages compared to existing technologies: (1) Deep integration of geological parameters, engineering mechanics models and microseismic data to conduct joint analysis of multi-source data, realizes multi-dimensional analysis and effective evaluation of the internal transformation quality of the fracture network, completes in-depth data mining, guides the optimization of fracturing construction scheme, and improves the overall transformation effect.
[0022] (2) A quantitative fracturing effect evaluation method has been formed. A quantitative pre-evaluation system with multi-parameter fusion has been constructed based on the mathematical evaluation model. An objective prediction standard for the pre-mining anti-impact effect has been established, eliminating the bias of human experience.
[0023] (3) This scheme can monitor and accurately reflect the shock and vibration control effect after fracturing of horizontal wells on the ground in a timely manner, transforming the shock and vibration control assessment from "post-event interpretation" to "pre-event prescription", and quantitatively characterizing and evaluating the shock and vibration control effect in real time, so as to accurately locate high-risk sections and provide prevention and control suggestions.
[0024] 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
[0025] Figure 1 This is a schematic flowchart illustrating the overall process of the present invention. Detailed Implementation
[0026] like Figure 1 As shown, the present invention provides a method for pre-evaluation of the anti-shock and vibration control effect before fracturing of a surface horizontal well, comprising: Step 1: Obtain geological and mining data of the fracturing mine and on-site fracturing operation monitoring data; Step 2: Based on the obtained geological and mining data of the fractured mine and the on-site fracturing construction monitoring data, determine each fracturing section and the multiple evaluation parameters corresponding to each fracturing section; Step 3: Preprocess each evaluation parameter of each fracturing section, and based on the preprocessed evaluation parameters, use the CRITIC method to determine the weight of each evaluation parameter, and calculate the evaluation value of the shock and vibration control effect of each fracturing section by weighted summation method. Step 4: Classify the effectiveness of each fracturing section based on its anti-shock and seismic control performance evaluation value, and output a pre-evaluation report.
[0027] In step 1, geological and mining data of the fractured mine and on-site fracturing construction monitoring data are acquired. The geological and mining data of the fractured mine includes: coal seam occurrence conditions at the working face, mining methods, borehole columnar sections, and physical and mechanical parameters of each rock stratum.
[0028] In step 2, based on the obtained geological and mining data of the fractured mine and the on-site fracture construction monitoring data, each fractured section and the corresponding multiple evaluation parameters are determined.
[0029] The evaluation parameters include: geometric parameters, energy parameters, volumetric parameters, microseismic activity parameters, and stress state parameters.
[0030] Based on borehole columnar sections and rock mechanics parameters, key overburden layers were identified. Mechanical parameters such as fracture step distance, load, fracture energy release, and caving block size were calculated based on theoretical analysis of the key seismic layers. These parameters, i.e., the fracturing layers, were then comprehensively determined through theoretical analysis and on-site microseismic monitoring results. Using methods such as surface hydraulic fracturing segment spacing and microseismic monitoring during fracturing, parameters such as the length, number of segments, spacing between fracturing segments, and cluster spacing of the horizontal fracturing sections were determined. During real-time fracturing operations, construction parameters (fluid volume, sand volume, displacement, and pressure) were recorded. Real-time microseismic fracture monitoring was implemented to monitor fracture direction and length, and to obtain the time, location, and energy of microseismic events.
[0031] The determination of the evaluation parameters includes: Geometric parameters: obtained directly from geological and mining data of the fracturing mine and on-site fracturing construction monitoring data; Energy parameters: calculated using a ground microseismic monitoring system based on on-site fracturing construction monitoring data; Volumetric parameters: Calculated using an octree algorithm based on on-site fracturing construction monitoring data; Microseismic activity parameters: calculated using a point cloud local adaptive density algorithm based on on-site fracturing construction monitoring data; Stress state parameters include the average stress concentration factor and pore pressure variation. The average stress concentration factor is obtained by inversion of the coupled numerical model of geomechanics and fracturing construction based on the on-site fracturing construction monitoring data. The pore pressure variation is obtained by estimating the injection influence range based on the fracturing pressure data based on the on-site fracturing construction monitoring data.
[0032] Specifically, during fracturing operations, parameters for evaluating the anti-scour effect of surface hydraulic fracturing are collected segment by segment, including: 1) Geometric parameters: side length L, width W (fracture influence width / fracture network expansion width), and height H (fracture influence height / fracture network expansion height) of the microseismic event set. 2) Energy parameter: Energy E released by the cumulative seismic moment calculated by the ground microseismic monitoring system. 3) Volume Parameters: The modified volume (SRV) is calculated based on the seismic deformation of microseismic events. 90% of the effective fracture geometry depends on the modified volume resulting from seismic deformation and fracture propagation. Areas with high seismic deformation indicate high fracture density, thus contributing more to the modified volume. This method uses an octree algorithm to calculate the modified volume SRV. An octree is a geometric data structure that recursively divides a set of points in three-dimensional space into eight equal regions, generating tree structures of different levels until the tree reaches a certain depth or meets certain requirements. The specific calculation process is as follows: First, set the target density threshold. t At the thresholdt In the case of dividing microseismic event points, n Let there be non-empty child nodes, and the maximum tree depth be... h m Then we have the set of microseismic events for a certain grid. M :
[0033] In the formula, m i For the division of the first i A set of event points within a non-empty node and , The coordinates of the microseismic point set are... L Let be the side length of the set of microseismic events.
[0034] Create a global index set for all non-empty nodes. B :
[0035] b i Each node is assigned a global index number. Then, based on the index and the parent-child relationships between nodes, a spatial lookup function is used. H(x) Calculate the hierarchy of non-empty nodes:
[0036] For each node along x , y , z Set of side lengths along the coordinate axes L 0:
[0037] In the formula, l 0 j For the first i Layer nodes along j The length of the side in the direction.
[0038] Each iteration of the algorithm yields an octet, which results in a bisection for the three dimensions. Therefore, the digit can be obtained as follows: i Layer nodes along j Side length in the direction:
[0039] Therefore, we can obtain the first... i Volume of a single non-empty node in a layer V i :
[0040] The crack volume can be obtained by summing the volumes of all non-empty nodes. V :
[0041] 4) Microseismic Activity Parameters: The density attribute of microseismic events can intuitively reflect the degree of fracturing at various locations within the fracture network. The higher the density value, the more thorough the reservoir stimulation. This method uses a point cloud-based local adaptive density algorithm to obtain the microseismic density value. This method increases the density in dense areas and decreases the density in sparse areas, thus increasing the density difference between them. This better reflects the density differences within the fracture network and evaluates the fracturing effect at different locations. The specific calculation process is as follows: First, regarding microseismic event clouds P any point in P i The calculation radius is r neighborhood N r ( P i )middle P i Local density at the location d ( P i ):
[0042] Secondly, calculation N r ( P i The average density in ) m r ( P i ):
[0043] In the formula: n The number of points in the neighborhood; d ( P j ) is any point within the neighborhood. P j Local density at a given location.
[0044] Then, determine the local standard deviation. :
[0045] Finally, the magnification factor G is set, and the local adaptive density of the event is obtained using the local density mean and local standard deviation. :
[0046] 5) Stress state parameters: including mean stress concentration factor And the change in pore pressure ΔP.
[0047] Mean stress concentration factor Based on theoretical calculations, combined with geomechanical models (geomechanical field, rock mechanics parameters) and fracturing construction parameters (net pressure, fracture morphology), a refined numerical model is established to inversely calculate the stress field after fracturing, and the stress concentration coefficients of key target areas such as flexural zones, faults, section coal pillars, and areas where mining has not yet been completed are extracted. These are the core mechanical indicators for evaluating the pressure relief effect.
[0048] Pore pressure variation ΔP: Fracturing fluid injection significantly alters the local pore pressure field, affecting effective stress and rock mass strength. Increased pore pressure reduces effective stress and is a crucial mechanism for inducing microseismic / shock events, representing a key aspect of the impact of fracturing. The average pressure variation is obtained by estimating the injection impact range using fracturing pressure data.
[0049] In step 3, the evaluation parameters of each fracturing segment are preprocessed, and based on the preprocessed evaluation parameters, the weight of each evaluation parameter is determined by the CRITIC method, and the evaluation value of the shock and vibration control effect of each fracturing segment is calculated by the weighted summation method.
[0050] This involves preprocessing various evaluation parameters for each fracturing section, including: Data cleaning was performed on the various evaluation parameters of each fracturing section; After data cleaning, the evaluation parameters of each fracturing segment were normalized.
[0051] Specifically, data cleaning involves removing outliers and microseismic events with excessively large positioning errors. Normalization is also performed because the dimensions and numerical ranges of various parameters differ greatly. For example, SRV is a volume, which is dimensionless. Therefore, all parameters must be normalized to make them comparable. The range method is used for data normalization.
[0052] In step 3, when determining the weights of the evaluation parameters, the CRITIC method is used to objectively determine the relative importance of each parameter in the comprehensive evaluation index. The CRITIC method considers both the contrast strength (standard deviation) and conflict (negative correlation with other parameters) of the parameters.
[0053] The weights of each evaluation parameter are determined using the CRITIC method based on the preprocessed evaluation parameters, including: Construct the original data matrix X, we have
[0054] In the formula, each row of the original data matrix X corresponds to a fracturing segment, each column corresponds to an evaluation parameter, m is the total number of fracturing segments, and n is the total number of index parameters. For the j-th evaluation parameter, standardization is performed to obtain the standardized matrix. ,have
[0055] In the formula, z ij x is the standardized value of the j-th evaluation parameter in the i-th fracturing segment. ij Let j be the value of the evaluation parameter in the i-th fracturing segment, min(x ij ) represents the minimum value of the j-th evaluation parameter in each fracturing segment, max(x) ij ) represents the maximum value of the j-th evaluation parameter in each fracturing segment; Calculate the standard deviation of the j-th evaluation parameter. ,have
[0056] In the formula, The mean of the standardized values of the j-th evaluation parameter; Calculate the correlation coefficient matrix of each evaluation parameter. , where r jk The Pearson correlation coefficient between the j-th and k-th evaluation parameters is given by...
[0057] Based on the Pearson correlation coefficient between the j-th and k-th evaluation parameters, the conflict c of the j-th evaluation parameter is calculated. j ,have
[0058] The standard deviation of the j-th evaluation parameter Conflict c with the j-th evaluation parameter j By combining these, we can obtain the information content of the j-th evaluation parameter. C j ,have
[0059] Information content of the j-th evaluation parameter C j After normalization, the weight w of the j-th evaluation parameter is obtained. j ,have
[0060] In the formula, C k Let be the information content of the k-th evaluation parameter.
[0061] The seismic control and shock mitigation effectiveness evaluation value is obtained based on weights, and information from multiple dimensions is integrated into a single, quantifiable score for intuitive comparison of the seismic control and shock mitigation effectiveness of different fracturing sections or the overall project. The weighted summation method is used to calculate the seismic control and shock mitigation effectiveness evaluation value (CEI) for each fracturing section.
[0062] Step 3, which involves calculating the shock and seismic control effect evaluation value of each fracturing section using a weighted summation method, includes: The evaluation values of the shock and seismic control effects of each fracturing section are calculated using the following formula:
[0063] In the formula, CEI i It is the first i Evaluation values of the shock and seismic control effect of each fracturing section; w j It is the weight of the j-th evaluation parameter; X ij It is the first i The value of the j-th evaluation parameter of each fracturing segment.
[0064] CEI i A higher CEI value indicates a better expected shock and vibration control effect in the pre-mining assessment of the fracturing section, signifying greater pressure relief, more uniform energy release, significantly reduced stress concentration, and effective modification of hazardous areas. The overall effectiveness evaluation index for the entire fracturing project is obtained by summing and averaging the CEI values of all fracturing sections.
[0065] In step 4, the effect is graded according to the evaluation value of the anti-shock and seismic control effect of each fracturing section, and a pre-evaluation report is output.
[0066] The method of classifying the effectiveness of shock and vibration control based on the evaluation values of each fracturing section includes: The range of the CEI value for judging the shock and seismic control effect is within CEI>=0.75, 0.5<=CEI<0.75, 0.25<=CEI<0.5, or CEI<0.25; The effect is excellent when CEI>=0.75, good when 0.5<=CEI<0.75, average when 0.25<=CEI<0.5, and poor when CEI<0.25.
[0067] Based on the calculated CEI value, combined with engineering experience and target requirements, a threshold range was set to classify the effectiveness, forming a quantitative evaluation method. Overall, a CEI >= 0.75 indicates excellent shock and vibration control, with sufficient expected pressure relief and a significant reduction in mine tremors and impact risks; a CEI <= 0.5 <= 0.75 indicates good shock and vibration control; a CEI <= 0.25 <= 0.5 indicates moderate effectiveness, requiring attention to localized areas; and a CEI < 0.25 indicates poor shock and vibration control, requiring in-depth analysis of the causes and supplementary pressure relief measures.
[0068] When outputting the pre-assessment report, this invention outputs the report based on the aforementioned monitoring and model calculation results. This mainly includes the assessment parameters used, their data sources and processing methods, weight calculation results, parameter values and CEI values for each fracturing section, and the CEI value for the overall engineering effect. Simultaneously, a spatial distribution map of key parameters is visualized, resulting in a three-dimensional visualization of the modified volume SRV and a comparison diagram of the impact hazard area before and after modification. Finally, the pre-assessment conclusions and recommendations are given, clearly indicating the expected shock and seismic control effect level, identifying potential risk sections, and providing early warnings and suggestions for subsequent mining operations, such as strengthening monitoring in a certain area, adjusting the mining sequence, and considering supplementary pressure relief.
[0069] The above description is merely a preferred embodiment of the present invention and does not constitute any limitation on the present invention. Any simple modifications, alterations, or equivalent structural changes made to the above embodiments based on the technical essence of the present invention shall still fall within the protection scope of the present invention.
Claims
1. A method for pre-evaluating the anti-shock and vibration control effect before fracturing in surface horizontal wells, characterized in that, include: Step 1: Obtain geological and mining data of the fracturing mine and on-site fracturing operation monitoring data; Step 2: Based on the obtained geological and mining data of the fractured mine and the on-site fracturing construction monitoring data, determine each fracturing section and the multiple evaluation parameters corresponding to each fracturing section; Step 3: Preprocess each evaluation parameter of each fracturing section, and based on the preprocessed evaluation parameters, use the CRITIC method to determine the weight of each evaluation parameter, and calculate the evaluation value of the shock and vibration control effect of each fracturing section by weighted summation method. Step 4: Classify the effectiveness of each fracturing section based on its anti-shock and seismic control performance evaluation value, and output a pre-evaluation report.
2. The method for pre-evaluation of anti-shock and vibration control effect before fracturing of a horizontal well on the surface according to claim 1, characterized in that, The evaluation parameters include: geometric parameters, energy parameters, volumetric parameters, microseismic activity parameters, and stress state parameters.
3. A method for pre-evaluation of the anti-shock and vibration control effect before fracturing in a surface horizontal well according to claim 2, characterized in that, The determination of the evaluation parameters includes: Geometric parameters: obtained directly from geological and mining data of the fracturing mine and on-site fracturing construction monitoring data; Energy parameters: calculated using a ground microseismic monitoring system based on on-site fracturing construction monitoring data; Volumetric parameters: Calculated using an octree algorithm based on on-site fracturing construction monitoring data; Microseismic activity parameters: calculated using a point cloud local adaptive density algorithm based on on-site fracturing construction monitoring data; Stress state parameters include the average stress concentration factor and pore pressure variation. The average stress concentration factor is obtained by inversion of the coupled numerical model of geomechanics and fracturing construction based on the on-site fracturing construction monitoring data. The pore pressure variation is obtained by estimating the injection influence range based on the fracturing pressure data based on the on-site fracturing construction monitoring data.
4. A method for pre-evaluation of the anti-shock and vibration control effect before fracturing in a horizontal well on the surface, as described in claim 1, is characterized in that... Step 3, which involves preprocessing the evaluation parameters of each fracturing section, includes: Data cleaning was performed on the various evaluation parameters of each fracturing section; After data cleaning, the evaluation parameters of each fracturing segment were normalized.
5. A method for pre-evaluation of the anti-shock and vibration control effect before fracturing in a surface horizontal well according to claim 1, characterized in that, In step 3, the weights of each evaluation parameter are determined using the CRITIC method based on the preprocessed evaluation parameters, including: Construct the original data matrix X, we have In the formula, each row of the original data matrix X corresponds to a fracturing segment, each column corresponds to an evaluation parameter, m is the total number of fracturing segments, and n is the total number of index parameters. For the j-th evaluation parameter, standardization is performed to obtain the standardized matrix. ,have wherein z ij is the normalized value of the jth evaluation parameter in the ith fracture segment, x ij is the value of the jth evaluation parameter in the ith fracture segment, min(x ij ) is the minimum value of the jth evaluation parameter in each fracture segment, and max(x ij ) is the maximum value of the jth evaluation parameter in each fracture segment. Calculate the standard deviation of the j-th evaluation parameter. ,have In the formula, The mean of the standardized values of the j-th evaluation parameter; Calculate the correlation coefficient matrix of each evaluation parameter. , where r jk The Pearson correlation coefficient between the j-th and k-th evaluation parameters is given by... Based on the Pearson correlation coefficient between the j-th and k-th evaluation parameters, the conflict c of the j-th evaluation parameter is calculated. j ,have The standard deviation of the j-th evaluation parameter Conflict c with the j-th evaluation parameter j By combining these, we can obtain the information content of the j-th evaluation parameter. C j ,have Information content of the j-th evaluation parameter C j After normalization, the weight w of the j-th evaluation parameter is obtained. j ,have In the formula, C k Let be the information content of the k-th evaluation parameter.
6. A method for pre-evaluation of the anti-shock and vibration control effect before fracturing in a surface horizontal well according to claim 5, characterized in that, Step 3, which involves calculating the shock and seismic control effect evaluation value of each fracturing section using a weighted summation method, includes: The evaluation values of the shock and seismic control effects of each fracturing section are calculated using the following formula: In the formula, CEI i It is the first i Evaluation values of the shock and seismic control effect of each fracturing section; w j It is the weight of the j-th evaluation parameter; X ij It is the first i The value of the j-th evaluation parameter of each fracturing segment.
7. A method for pre-evaluation of the anti-shock and vibration control effect before fracturing in a surface horizontal well according to claim 1, characterized in that, In step 4, the effect grading based on the shock and vibration control effect evaluation values of each fracturing section includes: The CEI (ceiling isolation index) value for assessing the effectiveness of shock and seismic control is within the range of CEI>=0.75, 0.5<=CEI<0.75, 0.25<=CEI<0.5, or CEI<0.25; The effect is excellent when CEI>=0.75, good when 0.5<=CEI<0.75, moderate when 0.25<=CEI<0.5, and poor when CEI<0.
25.
8. A method for pre-evaluation of the anti-shock and vibration control effect before fracturing in a horizontal well on the surface, as described in claim 1, is characterized in that... In step 1, the geological and mining data of the fracturing mine includes: coal seam occurrence conditions of the working face, coal mining methods, borehole columnar section and physical and mechanical parameters of each rock stratum.