Coal mine roof water inflow monitoring method based on well-ground combined resistivity method

Abstract

The invention relates to a coal mine roof water inflow monitoring method based on a well-ground combined resistivity method, and the method comprises the steps: designing a ground and underground resistivity method monitoring scheme, and obtaining ground and underground resistivity monitoring data of a coal seam roof rock stratum in a working face recovery process according to the resistivity method monitoring scheme; analyzing the monitoring data through forward numerical simulation and inversion imaging to obtain a resistivity profile cloud picture; resistivity change characteristics in the resistivity profile cloud picture are extracted to determine distribution characteristics of the water guide channels, and the underground water migration process under the mining influence is dynamically monitored; the resistivity change characteristics and the working face water inflow change characteristics are comprehensively compared and analyzed, the incidence relation between the water inflow and the resistivity change characteristics is established, and the change of the water inflow of the stope working face in the next stage is predicted. According to the method, dynamic monitoring of working face roof overlying strata damage and underground water migration rules and prediction and early warning of water inrush disasters in the recovery process are achieved.

Description

Technical Field

[0001] The invention relates to the technical field of coal mine roof water hazard monitoring, and in particular to a coal mine roof water inflow monitoring method based on a well-ground combined resistivity method. Background Art

[0002] During the coal mining process, cracks caused by deformation and collapse of the roof due to coal seam excavation form water-conducting fracture zones in the process of developing toward the ground. When the water-conducting fracture zone develops to the aquifer or even the ground, one or more water-conducting channels are formed that connect the coal mining face with the aquifer or the ground. Water will flow into the goaf along the water-conducting channels, often leading to water disasters. Once a water disaster occurs, it will cause great threats and losses to the safety of life and property of coal mines and miners due to its suddenness and destructiveness. Coal mine water disasters have become one of the major issues affecting coal mine safety production. The formation and occurrence of mine water hazards have a stage from gestation, development to occurrence. Different stages of this change process have corresponding precursors. If in the daily water prevention and control work of coal mines, the hydrogeological conditions of each aquifer in the mine and the mining conditions of the working face are monitored in real time, the hydrological dynamics of the mine are grasped in time, dangerous signs are discovered in time and corresponding preventive measures are taken, it is possible to achieve early detection, early prediction and early prevention of mine water hazard accidents and ensure safe and efficient production of coal mines.

[0003] The microseismic monitoring and electrical monitoring currently widely used in China are to monitor water inrush from the roof and floor of key working faces. Sensors are mainly buried around the target working face to capture the development process of mining cracks in the roof and floor of the working face and the changing rules of the low-resistance abnormal area. At present, there is little research on roof water hazard monitoring technology for high-exploitation working faces in China, and the existing microseismic and resistivity monitoring technologies cannot be simply applied. Summary of the invention

[0004] In order to solve the problems existing in the above-mentioned prior art, the purpose of the present invention is to propose a coal mine roof water inrush monitoring method based on the joint well-ground resistivity method, so as to realize the monitoring and early warning of the working face roof overburden damage and groundwater migration law during the mining process.

[0005] To achieve the above object, the present invention provides the following solutions:

[0006] A method for monitoring water inflow from coal mine roof based on well-ground joint resistivity method, comprising:

[0007] Acquire monitoring data during the mining process of the working face, analyze the monitoring data through forward numerical simulation and inversion imaging, and obtain a resistivity profile cloud map;

[0008] Extracting resistivity variation characteristics from the resistivity profile cloud map, determining distribution characteristics of the water channel based on the resistivity variation characteristics, and monitoring the water channel according to the distribution characteristics;

[0009] The water inflow variation characteristics of the current stage in the working face mining process are obtained, the resistivity variation characteristics and the water inflow variation characteristics are compared, and the water inflow variation in the next stage is predicted.

[0010] Optionally, obtaining monitoring data during the mining process of the working face includes:

[0011] Setting a target number of ground measuring lines, setting ground measuring points with a first preset point distance on the ground measuring lines, and setting monitoring devices on the ground measuring points;

[0012] Setting a target number of downhole measuring lines, setting downhole measuring points with a second preset point distance on the downhole measuring lines, and setting monitoring devices on the downhole measuring points;

[0013] Wherein, the monitoring device comprises: AMN and MNB three-pole devices;

[0014] The monitoring data is collected by the monitoring device.

[0015] Optionally, analyzing the monitoring data by forward numerical simulation and inversion imaging includes:

[0016] The preset underground electrical distribution is calculated through forward numerical simulation to obtain the apparent resistivity response characteristics at each electrode position, analyze the apparent resistivity response characteristics at each electrode position, that is, the positive and negative change characteristics of the apparent resistivity difference at different times, obtain the electrical properties of the mined-out water, and determine the abnormal change area;

[0017] The electrode coordinates of the AMN three-pole device are obtained, the potential difference and current between two points MN are measured according to the electrode coordinates, the electrode coordinates and the potential difference and current between two points MN are inverted and imaged, and the underground electrical distribution is reconstructed.

[0018] Optionally, obtaining the resistivity profile cloud map includes:

[0019] Step 1, obtain the initial model;

[0020] Step 2, calculate the Jacobian matrix based on the singular decomposition method to obtain the model parameter correction;

[0021] Step 4, updating the model parameters of the initial model based on the model parameter correction amount;

[0022] Step 5, based on the corrected initial model, obtain the new apparent resistivity response characteristics, and compare them with the measured apparent resistivity, and judge whether the error is reduced, whether the accuracy threshold is met, and whether the maximum number of iterations is reached. If the judgment conditions are met, the final resistivity model is output. If the judgment conditions are not met, repeat step 2;

[0023] Step 6: Based on the final resistivity model, obtain the resistivity profile cloud map.

[0024] Optionally, the method for updating the model parameters of the initial model is:

[0025] m i+1 =m i +Δm

[0026] Among them, m i+1 is the updated model parameter, m i is the model parameter of the initial model, and Δm is the model parameter correction amount.

[0027] Optionally, monitoring the water channel according to the distribution characteristics includes:

[0028] The resistivity variation characteristics in the resistivity profile cloud map are extracted at preset intervals along the inclination of the working face, the resistivity variation characteristics over the monitoring time in the extracted resistivity profile cloud map are analyzed, the distribution characteristics of the water conducting channel during the mining process are obtained, and the abnormal conditions of the water conducting channel are monitored according to the distribution characteristics.

[0029] Optionally, predicting the change in water inflow in the next stage includes:

[0030] Obtain the water inflow change characteristics of the current stage during the working face mining process, compare the resistivity change characteristics with the water inflow change characteristics, analyze the time and space relationship between the resistivity change characteristics and the water inflow change characteristics, and predict the water inflow change in the next stage.

[0031] The beneficial effects of the present invention are:

[0032] The present invention can realize accurate monitoring and early warning of the damage of the working face roof overburden and the movement of groundwater during the mining process, reduce the multi-solution of the commonly used electrical method, improve the accuracy of the prediction results, optimize the location of drainage holes and drilling targets, improve the drainage effect, ensure the safe production of coal mines, and improve the major safety hazards of coal mining. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0034] Figure 1 This is a flow chart of a method for monitoring water inflow from coal mine roof based on a well-ground combined resistivity method according to an embodiment of the present invention;

[0035] Figure 2 A flow chart of obtaining a resistivity profile cloud map according to an embodiment of the present invention;

[0036] Figure 3 A schematic diagram of a three-pole device according to an embodiment of the present invention;

[0037] Figure 4 A schematic diagram of a ground survey line arrangement scheme according to an embodiment of the present invention;

[0038] Figure 5 A schematic diagram of a downhole survey line arrangement scheme according to an embodiment of the present invention;

[0039] Figure 6 The apparent resistivity cross-section diagrams of two adjacent monitorings; among them, (a) is the apparent resistivity cross-section diagram of Line 1 on October 8, 2023, (b) is the apparent resistivity cross-section diagram of Line 1 on October 16, 2023, (c) is the apparent resistivity cross-section diagram of Line 2 on October 11, 2023, (d) is the apparent resistivity cross-section diagram of Line 2 on October 16, 2023, (e) is the apparent resistivity cross-section diagram of Line 3 on October 10, 2023. Surface map, (f) apparent resistivity cross-section map of Line 3 on October 15, 2023, (g) apparent resistivity cross-section map of Line 4 on October 10, 2023, (h) apparent resistivity cross-section map of Line 4 on October 15, 2023, (i) apparent resistivity cross-section map of Line 5 on October 10, 2023, (j) apparent resistivity cross-section map of Line 5 on October 15, 2023, (k) apparent resistivity value color code;

[0040] Figure 7 It is a cross-section diagram of the difference in apparent resistivity between two adjacent monitorings; among them, (a) is a cross-section diagram of the relative change in apparent resistivity of Line 1 between October 16 and October 8, (b) is a cross-section diagram of the relative change in apparent resistivity of Line 2 between October 16 and October 10, (c) is a cross-section diagram of the relative change in apparent resistivity of Line 3 between October 15 and October 10, (d) is a cross-section diagram of the relative change in apparent resistivity of Line 4 between October 15 and October 10, (e) is a cross-section diagram of the relative change in apparent resistivity of Line 5 between October 15 and October 10, and (f) is a color code for the difference in apparent resistivity;

[0041] Figure 8 The plane diagrams of apparent resistivity difference of each aquifer monitoring; among them, (a) is the cross-section diagram of apparent resistivity change of Salawusu Formation, (b) is the cross-section diagram of apparent resistivity change of the middle part of Baode Formation, (c) is the cross-section diagram of apparent resistivity change of the bottom of bedrock weathering layer, (d) is the cross-section diagram of apparent resistivity change of the middle part of Anding Formation, (e) is the cross-section diagram of apparent resistivity change of the middle part of Zhiluo Formation, (f) is the cross-section diagram of apparent resistivity change of the bottom boundary of Zhiluo Formation, and (g) is the color code of apparent resistivity difference;

[0042] Fig. 9 The cross-section diagram of the apparent resistivity near the nose and the difference between the apparent resistivity on October 10; (a) is the cross-section diagram of the apparent resistivity change at 3770m (the nose position), (b) is the cross-section diagram of the apparent resistivity change at 3760m, (c) is the cross-section diagram of the apparent resistivity change at 3750m, and (d) is the color code of the apparent resistivity difference;

[0043] Fig.10 The cross-section diagram of the difference between the apparent resistivity near the nose and the apparent resistivity on October 6; (a) is the cross-section diagram of the apparent resistivity change at 3770m (the nose position), (b) is the cross-section diagram of the apparent resistivity change at 3760m, and (c) is the cross-section diagram of the apparent resistivity change at 3750m;

[0044] Fig.11 Figure 1: Results of underground monitoring; (a) is the resistivity cross-section diagram of the auxiliary transport chute monitored on October 14, (b) is the lateral distribution curve of the resistivity near the bottom boundary of the Zhiluo group of the auxiliary transport chute on October 14, (c) is the resistivity cross-section diagram of the return air chute monitored on October 14, (d) is the lateral distribution curve of the resistivity near the bottom boundary of the Zhiluo group of the return air chute on October 14, (e) is the resistivity cross-section diagram of the auxiliary transport chute monitored on October 16, (f) is the resistivity cross-section diagram of the auxiliary transport chute monitored on October 16 (g) is the resistivity cross-section diagram of the return air chute monitored on October 16, (h) is the lateral resistivity distribution curve near the bottom boundary of the Zhiluo group of the return air chute on October 16, (i) is the resistivity cross-section diagram of the paving chute monitored on October 17, (j) is the lateral resistivity distribution curve near the bottom boundary of the Zhiluo group of the auxiliary chute on October 17, (k) is the resistivity cross-section diagram of the return air chute monitored on October 17, (l) is the lateral resistivity distribution curve near the bottom boundary of the Zhiluo group of the return air chute on October 17. DETAILED DESCRIPTION

[0045] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0046] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0047] like Figure 1 As shown, the present embodiment discloses a method for monitoring water inflow from the roof of a coal mine based on a combined well-ground resistivity method, comprising: designing a resistivity monitoring scheme above and below the well, and acquiring monitoring data during the working face mining process according to the resistivity monitoring scheme; analyzing the monitoring data through forward numerical simulation and inversion imaging to acquire a resistivity profile cloud map; extracting resistivity change characteristics from the resistivity profile cloud map, determining the distribution characteristics of the water conducting channel based on the resistivity change characteristics, and monitoring the water conducting channel according to the distribution characteristics; acquiring the water inflow change characteristics at the current stage during the working face mining process, comparing the resistivity change characteristics with the water inflow change characteristics, and predicting the water inflow change in the next stage.

[0048] Specifically, the ground three-pole electrical sounding method is used for downward detection, and the underground roof three-pole electrical sounding method is used for upward detection to achieve the joint well-ground detection of the overburden rock damage of the working face roof and the migration of groundwater during the mining process, including the following steps:

[0049] Step 1: Determine monitoring methods such as ground three-pole electrical depth sounding method and underground top plate three-pole electrical depth sounding method by consulting literature and conducting on-site investigation;

[0050] Step 2: Design underground and surface electrical monitoring systems and plans: Line layout plan such as Figure 4-5 ,The monitoring period is during the entire working face mining process;

[0051] Step 3: Analyze the monitoring data through forward numerical simulation and inversion imaging to obtain the resistivity profile cloud map;

[0052] Step 4: Observe the distribution characteristics of the abnormal range of the resistivity of the formation above the roof before and after mining, delineate the abnormal water-rich area, and determine the distribution characteristics of the water-conducting channel by analyzing the time series change characteristics of the resistivity during the mining process, so as to realize the monitoring of the water-filled channel;

[0053] Step five, compare the resistivity change characteristics obtained through electrical monitoring with the water inflow change characteristics, analyze the temporal and spatial relationship between the resistivity change and the water inflow change, and predict the water inflow change in the next stage.

[0054] Furthermore, the design of the resistivity monitoring scheme above and below the ground includes: setting a target number of ground survey lines, setting ground survey points at a first preset point distance on the ground survey lines, and setting monitoring devices on the ground survey points; setting a target number of downhole survey lines, setting downhole survey points at a second preset point distance on the downhole survey lines, and setting monitoring devices on the downhole survey points; wherein the monitoring devices include: AMN and MNB three-pole devices.

[0055] Furthermore, the monitoring data are analyzed by forward numerical simulation and inversion imaging, including: calculating the preset underground electrical distribution by forward numerical simulation, obtaining the apparent resistivity response characteristics at each electrode position, analyzing the apparent resistivity response characteristics at each electrode position, that is, the positive and negative change characteristics of the apparent resistivity difference at different times, obtaining the electrical properties of the mined-out water, and determining the abnormal change area;

[0056] The electrode coordinates of the AMN three-pole device are obtained, the potential difference and current between two points MN are measured according to the electrode coordinates, the electrode coordinates and the potential difference and current between two points MN are inverted and imaged, and the underground electrical distribution is reconstructed.

[0057] The electrode coordinates and the voltage and current under the electrode coordinates are obtained by field measurements with a DC current meter. The acquisition device is an AMN three-pole device, where B is an infinite power supply electrode, forming a pair of power supply electrodes with A; MN is a measuring electrode, which can measure the potential difference and current between the two points MN. The MN spacing in this scheme is 30m.

[0058] Specifically, (1) the finite element method is used to simulate the electrical properties of typical water-bearing (conducting) geological anomalies such as the goaf above the coal seam roof, the "upper three zones", and faults, summarize the geoelectric anomaly response characteristics, and identify the abnormal changes by the changes in apparent resistivity at different times. The effectiveness of time-lapse resistivity imaging technology in monitoring water migration in the coal seam roof is verified, providing data for subsequent inversion research and theoretical guidance for actual data processing and interpretation. By analyzing the positive and negative change characteristics of the apparent resistivity difference at different times, the changes in water accumulation in the goaf are inferred, and the areas with drastic changes are focused on, timely prediction and warning are made, and the occurrence of serious accidents is avoided as much as possible. (2) The data at each monitoring time is inverted to reconstruct the underground resistivity distribution. Water accumulation in the goaf of the working face is a "dynamic" process in which the water from the roof aquifer gradually flows into the goaf during the mining of the working face. The traditional resistivity inversion method is time-consuming and cannot meet the needs of real-time processing and interpretation of mine water inrush monitoring data.

[0059] The significance of forward modeling: (1) Forward modeling can be used to understand the response patterns of different geoelectric anomalies; (2) According to the forward modeling results of the preset geoelectric model, the surface and underground observation systems can be optimized; (3) Inversion is carried out on the basis of forward modeling, which can provide an initial underground medium resistivity model that fits the actual situation for inversion.

[0060] Furthermore, if Figure 2 As shown in the figure, obtaining the resistivity profile cloud map includes:

[0061] Step 1, obtain the initial model;

[0062] Step 2, calculate the Jacobian matrix based on the singular decomposition method to obtain the model parameter correction;

[0063] Step 4, updating the model parameters of the initial model based on the model parameter correction amount;

[0064] Step 5, based on the corrected initial model, obtain the new apparent resistivity response characteristics, and compare them with the measured apparent resistivity, and judge whether the error is reduced, whether the accuracy threshold is met, and whether the maximum number of iterations is reached. If the judgment conditions are met, the final resistivity model is output. If the judgment conditions are not met, repeat step 2;

[0065] Step 6: Based on the final resistivity model, obtain the resistivity profile cloud map.

[0066] Specifically, forward numerical simulation is to calculate the apparent resistivity response characteristics at each electrode position according to the preset underground electrical distribution; inversion imaging is to reconstruct the corresponding underground electrical distribution according to the voltage and current response of each coordinate electrode measured on site (the apparent resistivity can be calculated). Forward modeling is the basis of inversion. Each time the initial resistivity model is corrected, it is forward modeled again, and the corresponding forward modeling result is compared with the measured apparent resistivity until the error between the two after comparison is extremely small. In this case, this model is considered to be the electrical distribution of the real underground medium corresponding to the measured response.

[0067] Furthermore, the method for updating the model parameters of the initial model is:

[0068] m i+1 =m i +Δm

[0069] Among them, m i+1 is the updated model parameter, m i is the model parameter of the initial model, and Δm is the model parameter correction amount.

[0070] Furthermore, monitoring the water conducting channel according to the distribution characteristics includes: extracting resistivity change characteristics in the resistivity profile cloud map at preset intervals along the inclination of the working face, analyzing the resistivity change characteristics over the monitoring time in the extracted resistivity profile cloud map, obtaining the distribution characteristics of the water conducting channel during the mining process, and monitoring abnormal conditions of the water conducting channel according to the distribution characteristics.

[0071] Specifically, (1) the resistivity variation characteristics in the resistivity cross-section diagram of each surface-underground survey line are extracted; (2) the resistivity variation characteristics in the resistivity cross-section diagram are extracted at 10-m intervals along the working face inclination; (3) by analyzing the variation characteristics of each cross-section diagram over the monitoring time (the resistivity at a certain position becomes lower or higher), the distribution characteristics of the suspected water-conducting channels during the mining process are obtained, and they are tracked and observed to realize the monitoring of the water-filled channels.

[0072] Furthermore, predicting the change in water inflow in the next stage includes: obtaining the change characteristics of water inflow in the current stage of the working face mining process, comparing the resistivity change characteristics with the water inflow change characteristics, analyzing the time and space relationship corresponding to the resistivity change characteristics and the water inflow change characteristics, and predicting the change in water inflow in the next stage.

[0073] Specifically, (1) observe the daily changes in water inflow during the mining process of the working face; (2) compare the resistivity change characteristics obtained through monitoring with the water inflow change characteristics, analyze the temporal and spatial relationship between the resistivity change and the water inflow change, and predict the water inflow change in the next stage.

[0074] The present invention is further illustrated by the following examples, but is not limited to the following examples:

[0075] Caojiatan Mine 12 Pan Area West Wing 2 -2 The coal seam is buried at a depth of about 300 to 350 meters. During coal seam mining, the main sources of direct water are the water from the Yan'an Formation sandstone confined aquifer, the water from the Zhiluo Formation sandstone confined aquifer, and the water from the bedrock weathering layer. Due to the weak areas in the red soil layer, there is a potential for the water from the Quaternary Salawusu Formation aquifer to enter the mine through the weak areas. The bedrock weathering layer and the Quaternary Salawusu Formation aquifer have relatively developed fissures, strong connectivity, and good recharge. -2 Aquifers that are the focus of prevention and control during coal mining.

[0076] According to the analysis of the hydrogeological data of the mine, there is a weak red soil area in the west wing of the 12th panel area of ​​Caojiatan Coal Mine, and the red soil layer of the Baode Formation is missing in the top plate of the cut-eye section of some working faces. During the mining period, the water of the Quaternary Salawusu Formation aquifer may directly recharge the goaf through the "skylight", and water inrush and sand collapse accidents may occur in the mine, threatening the safety of the working face mining. The coal mining height of the 122107 and 122105 working faces currently being mined is 5.8m, the top coal height is 6m, and the water-conducting fracture zone is about 200 meters high, which will be led to the weathered bedrock layer (167 to 254m from the top plate of the working face). Because the observation boreholes currently arranged for the loose layer and weathered bedrock aquifer in the mine are far away and the monitoring area is large, the monitoring and early warning functions cannot be played in time. In order to ensure safety during mining, it is necessary to monitor the water in the roof aquifer (especially the bedrock weathering layer and the Salawusu Formation) during the mining of the working face so that water prevention and control measures can be taken in advance to eliminate the threat of water hazards in the bud.

[0077] Therefore, in order to find out the seepage change law of the overlying aquifer during the mining process of the working face in the weak red soil area, the "Research and Application of Water Filling Monitoring Technology for the Roof of the Fully Mechanized Caving Working Face under Complex Geoelectric Conditions" was carried out to study a set of fine water filling monitoring technologies up and down the well to achieve real-time monitoring of the water filling source, water filling channel, and water accumulation in the goaf of the mining working face. This will provide water hazard warning to ensure the safe mining of the working face in the weak red soil area in the west wing of the 12th plate area, and provide a basis for the later water hazard control in the skylight area.

[0078] There are 5 ground survey lines, with a line distance of 91m and each line length of 1200m. The point distance of the survey points is 10m, with a total of 605 points. The monitoring devices are AMN and MNB three-pole devices, such as Figure 3 MN spacing is 30m; detection depth is 260m. Two underground survey lines are arranged along the top plates of the two trenches of the working face, each measuring line is 1200m long, and monitoring is carried out in two stages, with each stage measuring line length of 600m. Figure 5 ,; The measuring point spacing is 10m, with a total of 605 points; the AMN three-pole device is used, the MN spacing is 30m, and the maximum detection depth is 200m.

[0079] Monitoring and analysis:

[0080] 1) The resistivity monitoring task is to monitor the change of the resistivity of the roof rock during the mining of the 122105 working face, and to warn the development of the roof water channel. The ground monitoring system is designed at the surface position corresponding to the working face. The monitoring system arranges 5 measuring lines with a length of 1200m and a line distance of 91m; an electrode is arranged every 10m, and a total of 605 electrodes are arranged. The monitoring area is divided into 3 sections for monitoring, and the monitoring section this time is 4180~3590m.

[0081] 2) The resistivity monitoring result is the apparent resistivity distribution of 0-260m below the surface. Generally, when the stratum distribution is stable and the lithology is relatively uniform, the electrical distribution is stable, the apparent resistivity contour lines are evenly distributed and change gently. If there is a water-conducting structure, the uniform electrical distribution law is broken, which is reflected in the map as a decrease in the apparent resistivity value, and the apparent resistivity contour lines are twisted and deformed into traps or dense strips. In the color result map, the apparent resistivity abnormal area is blue, and the better the conductivity, the darker the blue.

[0082] 3) From the monitoring apparent resistivity profile results ( Figure 6 (a)-(k)) It can be seen that the apparent resistivity of the monitoring area is distributed in the range of 30 to 400 Ω·m, but there is a relatively low-resistance area in the section of mileage 3960 to 3720 m, which indicates that the aquifer in this area is relatively rich in water.

[0083] 4) Monitoring results map ( Figure 7 (a)-(f)) are the differences in apparent resistivity between the monitoring results of the day and the previous monitoring results, which are used to describe the changes in the resistivity of the working face. The blue-green color represents a decrease in apparent resistivity compared with the previous one (increased water-richness), named “low abnormal area”; the white color represents an area with a small difference in apparent resistivity, named “normal area”; the yellow-red color represents an increase in apparent resistivity (weakened water-richness or fracture zone), named “high abnormal area”.

[0084] Abnormal characteristics of ground monitoring profiles ( Figure 6 ):

[0085] Survey line 1: There are continuous high anomaly areas at 4180-3590m horizontally and near -15--30m vertically; there are 5 low anomaly areas at 4180-4100m, 4060-4040m, 4000-3970m, 3940-3880m and 3700-3680m horizontally, and they develop to near -100m (210m on the top plate) vertically; there are 5 high anomaly areas at 4090-4070m, 4040-4000m, 3960-3940m, 3880-3850m and 3740-3710m horizontally, and they develop to near -50m (260m on the top plate) vertically.

[0086] Survey Line 2: There are continuous low anomaly areas at 4180-3970m horizontally and near -15--50m vertically; there are continuous high anomaly areas at 3950-3590m horizontally and near -15--30m vertically; there is one low anomaly area at 4180-4100m horizontally, which develops to near -100m (210m on the top plate) vertically; there are two high anomaly areas at 4020-3900m and 3860-3800m horizontally, which develop to near -130m (180m on the top plate) vertically.

[0087] Survey Line 3: There are alternating low anomaly areas at 4180-3880m laterally and -15--50m vertically; there are two high anomaly areas at 4180-4080m, 4040-3900m and 3800-3760m laterally, and the vertical height reaches around -100m (210m on the top plate).

[0088] Survey Line 4: There is one continuous low anomaly area at 4180-3900m horizontally and near -15--50m vertically; there is one continuous high anomaly area at 3900-3590m horizontally and near -15--40m vertically; there is one low anomaly area at 4180-4100m horizontally, which develops to near -200m (110m on the top plate) vertically; there are three low anomaly areas at 3960-3920m, 3880-3840m and 3800-3780m horizontally, which develop to near -150m (160m on the top plate) vertically.

[0089] Survey Line 5: There is one continuously distributed low anomaly area at 4020-3590m laterally and at -15--30m vertically; there is one low anomaly area at 4180-4110m laterally, which develops to around -100m (210m on the top plate) vertically; there are two low anomaly areas at 4100-4070m and 3880-3840m laterally, which develop to around -150m (160m on the top plate) vertically.

[0090] Abnormal characteristics of ground monitoring plane ( Figure 8 (a)-(g)):

[0091] Salawusu Formation: The low anomaly area is mainly distributed in the section of mileage 4180-3840m, and it is inferred that it is caused by local water accumulation after mining; the high anomaly areas distributed in other areas are inferred to be caused by the downward recharge of aquifer water due to surface cracks.

[0092] Baode Formation: The low anomaly areas are mainly distributed in the sections of mileage 4180-4020m and 3920-3830m. It is inferred that they are caused by local water accumulation after mining.

[0093] Bedrock weathering layer: The resistivity change in the monitored section is not obvious.

[0094] Anding Group: The low anomaly areas are mainly distributed in the sections of 4180-4150m and 3880-3800m. It is inferred that they are caused by local water accumulation after mining.

[0095] Zhiluo Formation: There are two low anomaly areas in the sections of mileage 4180-4080m and 4040-3900m, which are inferred to be caused by cracks in the goaf and their water content; there are two high anomaly areas in the sections of mileage 4050-3900m and 3840-3660m, which are inferred to be caused by the development of cracks in the goaf.

[0096] Abnormal features near the nose of the ground monitoring:

[0097] Fig. 9 (a)-(d) are cross-sectional diagrams of the difference between the apparent resistivity near the nose and the apparent resistivity on October 10. There is a low anomaly area 50-200m away from the tail, with a development height of -190m (120m on the top plate). The distribution range of this anomaly area gradually decreases from mileage 3770-3750m, and the development range gradually decreases; there is a high anomaly area 250-350m away from the tail, with a development height of -190m (120m on the top plate). The distribution range of this anomaly area gradually decreases from mileage 3770-3750m, and the development range gradually decreases. Fig.10 (a)-(c) are cross-sectional diagrams of the difference between the apparent resistivity near the nose and the apparent resistivity on October 6. There is a low abnormal area 140-220m away from the tail, with a development height of -150m (160m on the top plate). The distribution range of this abnormal area gradually increases from mileage 3770-3750m, and the development range gradually increases; there is a high abnormal area 270-350m away from the tail, with a development height of -130m (180m on the top plate). The distribution range of this abnormal area gradually decreases from mileage 3770-3750m, and the development range gradually decreases.

[0098] Downhole monitoring resistivity section characteristics:

[0099] (1) The vertical distribution of resistivity above the working face roof shows a "high-low-high" pattern ( Fig.11 (a)-(l)), the corresponding stratigraphic structure is "top coal-Yan'an formation-Zhiluo formation", and the resistivity distribution is well stratified; from October 14 to October 17, the resistivity of the return air chute monitoring near the tail first increased and then decreased.

[0100] (2) Water inflow prediction: Through the above analysis, ground monitoring found that in the cross-section diagram of mileage 3770-3750m, the distribution range of the low abnormal area near the nose gradually increased, the development range gradually increased, and the distribution range of the high abnormal area gradually decreased, and the development range gradually decreased. Therefore, it is estimated that the water dripping above the support will gradually increase in the next two days, and the water inflow at the nose and tail will gradually decrease.

[0101] The embodiments described above are only descriptions of the preferred embodiments of the present invention and are not intended to limit the scope of the present invention. Without departing from the design spirit of the present invention, various modifications and improvements made to the technical solutions of the present invention by ordinary technicians in this field should all fall within the protection scope determined by the claims of the present invention.

Claims

1. A method for monitoring water inflow from coal mine roof based on well-ground joint resistivity method, characterized in that: include: Acquire monitoring data during the mining process of the working face, analyze the monitoring data through forward numerical simulation and inversion imaging, and obtain a resistivity profile cloud map; Extracting resistivity variation characteristics from the resistivity profile cloud map, determining distribution characteristics of the water channel based on the resistivity variation characteristics, and monitoring the water channel according to the distribution characteristics; The water inflow variation characteristics of the current stage in the working face mining process are obtained, the resistivity variation characteristics and the water inflow variation characteristics are compared, and the water inflow variation in the next stage is predicted.

2. The method for monitoring water inflow from coal mine roof based on well-ground joint resistivity method according to claim 1 is characterized in that: The monitoring data obtained during the mining process of the working face include: Setting a target number of ground measuring lines, setting ground measuring points with a first preset point distance on the ground measuring lines, and setting monitoring devices on the ground measuring points; Setting a target number of downhole measuring lines, setting downhole measuring points with a second preset point distance on the downhole measuring lines, and setting monitoring devices on the downhole measuring points; Wherein, the monitoring device comprises: AMN and MNB three-pole devices; The monitoring data is collected by the monitoring device.

3. The method for monitoring water inflow from coal mine roof based on well-ground joint resistivity method according to claim 1 is characterized in that: The monitoring data are analyzed through forward numerical simulation and inversion imaging, including: The preset underground electrical distribution is calculated through forward numerical simulation to obtain the apparent resistivity response characteristics at each electrode position, analyze the apparent resistivity response characteristics at each electrode position, that is, the positive and negative change characteristics of the apparent resistivity difference at different times, obtain the electrical properties of the mined-out water, and determine the abnormal change area; The electrode coordinates of the AMN three-pole device are obtained, the potential difference and current between two points MN are measured according to the electrode coordinates, the electrode coordinates and the potential difference and current between two points MN are inverted and imaged, and the underground electrical distribution is reconstructed.

4. The method for monitoring water inflow from coal mine roof based on well-ground joint resistivity method according to claim 1 is characterized in that: Obtaining the resistivity profile cloud map includes: Step 1, obtain the initial model; Step 2, calculate the Jacobian matrix based on the singular decomposition method to obtain the model parameter correction; Step 4, updating the model parameters of the initial model based on the model parameter correction amount; Step 5, based on the corrected initial model, obtain the new apparent resistivity response characteristics, and compare them with the measured apparent resistivity, and judge whether the error is reduced, whether the accuracy threshold is met, and whether the maximum number of iterations is reached. If the judgment conditions are met, the final resistivity model is output. If the judgment conditions are not met, repeat step 2; Step 6: Based on the final resistivity model, obtain the resistivity profile cloud map.

5. The method for monitoring water inflow from coal mine roof based on well-ground joint resistivity method according to claim 4 is characterized in that: The method for updating the model parameters of the initial model is: Among them, m i+1 is the updated model parameter, m i is the model parameter of the initial model, and Δm is the model parameter correction amount.

6. The method for monitoring water inflow from coal mine roof based on well-ground joint resistivity method according to claim 1, characterized in that: Monitoring the water channel according to the distribution characteristics includes: The resistivity variation characteristics in the resistivity profile cloud map are extracted at preset intervals along the inclination of the working face, the resistivity variation characteristics over the monitoring time in the extracted resistivity profile cloud map are analyzed, the distribution characteristics of the water conducting channel during the mining process are obtained, and the abnormal conditions of the water conducting channel are monitored according to the distribution characteristics.

7. The method for monitoring water inflow from coal mine roof based on well-ground joint resistivity method according to claim 1, characterized in that: The predicted changes in water inflow in the next stage include: Obtain the water inflow change characteristics of the current stage during the working face mining process, compare the resistivity change characteristics with the water inflow change characteristics, analyze the time and space relationship between the resistivity change characteristics and the water inflow change characteristics, and predict the water inflow change in the next stage.

Images