A transient electromagnetic detection method for small pit goaf

Abstract

This application discloses a transient electromagnetic detection method for small-scale goaf areas, comprising the following steps: establishing different geophysical numerical models based on the geological and geophysical information of the survey area; performing forward modeling on the geophysical numerical models to obtain transient electromagnetic response characteristics under different parameters; determining the detection parameters of the survey area based on the simulation results; conducting detection experiments at typical measurement points in the survey area to determine the acquisition parameters; determining the distribution of survey lines in the survey area based on the acquisition parameters; detecting the transient feedback electromagnetic waves fed back from each survey line; performing inversion analysis on the feedback electromagnetic waves of each survey line to obtain the inversion resistivity and depth data of each survey line; determining the low-resistivity anomaly zone and the goaf anomaly zone within the small-scale goaf area; and determining the boundary location of the small-scale goaf area. Through the above-described scheme of this invention, accurate regional division results of small-scale goaf areas can be obtained.

Description

Technical Field

[0001] The present application belongs to the technical field of transient electromagnetic detection methods for geological exploration, and in particular, relates to a transient electromagnetic detection method for small pit goaf areas. Background Art

[0002] Effective detection of coal mine goafs has always been a difficult technical problem for the industry to overcome. Due to the different formation ages, burial depths, spatial structures, surrounding rock conditions, caving, filling and water accumulation in small cellar goafs, the physical properties of small cellar goafs show great differences. When the underground coal seams are mined, the stable coal-bearing strata are destroyed, the cracks between the rocks increase, and the surrounding rocks become loose, showing relatively high resistance characteristics. But at the same time, the small cellar goaf collapse area also forms a good water-rich and water-conducting area. If there is external water supply to cause the goaf to be filled with water, it will show low resistance characteristics. This makes the detection results difficult to interpret.

[0003] At present, the detection of goaf is mainly divided into seismic methods and electromagnetic methods. The seismic method is based on the velocity difference between the goaf and the surrounding rock, and the electromagnetic method is based on the electrical difference between the goaf and the surrounding rock. Seismic exploration is an important geophysical survey method that uses the elastic difference between strata and rocks to detect geological structures and find useful mineral resources. When seismic waves encounter elastic interfaces during propagation, they will produce reflection, refraction, and diffraction. The different properties of the received seismic waves and the different ways of sending and receiving form different seismic exploration methods. Although seismic methods have been widely used in goaf detection, due to the particularity of small cellar goafs, there is still no systematic method to solve the problem of fine detection of small cellar goafs. Summary of the invention

[0004] The present application aims to provide a transient electromagnetic detection method for small cellar goaf areas, which mainly uses the transient electromagnetic detection method to detect small cellar goaf areas, so as to solve the problem of low accuracy of small cellar goaf area detection results in the prior art.

[0005] In view of the above technical problems, some embodiments of the present application provide a method for transient electromagnetic detection of a small pit goaf, comprising the following steps:

[0006] Data simulation step: according to the geological and geophysical information of the survey area, different geophysical numerical models are established, and the transient electromagnetic response characteristics under different parameters are obtained by forward simulation of the geophysical numerical models; the detection parameters of the survey area are determined according to the simulation results;

[0007] Data test steps: conduct detection tests at typical measurement points in the measurement area, verify the selected detection parameters, and determine the acquisition parameters based on the verification results;

[0008] The data acquisition step is to determine the distribution of the survey lines in the survey area according to the acquisition parameters, emit transient electromagnetic waves to each survey line in the survey area, and detect the transient feedback electromagnetic waves fed back by each survey line;

[0009] The data processing steps are to invert and analyze the feedback electromagnetic waves of each survey line, and obtain the inversion resistivity and depth data of each survey line based on the inversion analysis results; determine the low-resistance abnormal area and goaf abnormal area in the small cellar goaf area based on the inversion resistivity and depth data of each survey line; determine the boundary position of the small cellar goaf area based on the low-resistance abnormal area and goaf abnormal area, combined with geological and geophysical information.

[0010] The technical solution of the present application has the following technical effects relative to the prior art: through transient electromagnetic forward calculation, the transient electromagnetic response characteristics of the goaf area in the survey area are obtained. Combined with the forward modeling results, the latest two-dimensional constrained inversion technology is further used to refine the information to more accurately define the scope of the goaf area. Before the formal data collection work is carried out, the observation parameter test is first carried out, and the observation parameters are optimized through the test. After the data collection is completed, for the collection results, starting from the basic characteristics of the goaf area of ​​the coal mine, the geophysical characteristics of the goaf are analyzed in detail, and finally an appropriate detection method is selected to detect the survey area. First, the survey area is scanned by transient electromagnetic method, the transient electromagnetic abnormal area is verified by high-density electrical method, and the spatial distribution of the goaf area is delineated in detail in combination with three-dimensional reflection seismic. Using the method in the present application, for the goaf area under the conditions of a gently inclined coal seam with a burial depth of less than 100m and a coal seam thickness of less than 10m, this combination of geophysical methods has the most significant effect. Through the above-mentioned scheme of the present invention, accurate regional division results of small pit goaf areas can be obtained. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] The preferred embodiments of the present application will be described in detail below with reference to the accompanying drawings, which will help to understand the purpose and advantages of the present application, wherein:

[0012] Figure 1 This is a flow chart of a transient electromagnetic detection method for a small cellar goaf area according to an embodiment of the present invention;

[0013] Figure 2 A schematic diagram of a one-dimensional layered model according to an embodiment of the present invention;

[0014] Figure 3 A schematic diagram of one-dimensional simulation results when the coal-bearing strata according to an embodiment of the present invention are coal seams, low-resistance voids (filled with water), and high-resistance voids (filled with air);

[0015] Figure 4 A schematic diagram of the relative error between the coal-bearing stratum in one embodiment of the present invention and the original coal stratum response when the coal-bearing stratum is mined out at low resistance (filled with water) and high resistance (filled with air);

[0016] Figure 5(a) and 5(b) The calculation results of the low-resistance and high-resistance goaf models when the caprock thickness is different according to an embodiment of the present invention, wherein FIG5(a) is the calculation result of the low-resistance goaf model (filled with water), and FIG5(b) is the calculation result of the high-resistance goaf model (filled with air);

[0017] Figure 6(a) and 6(b) The calculation results of the low-resistance and high-resistance goaf models when the goaf thickness is different according to an embodiment of the present invention, wherein FIG6(a) is the calculation result of the low-resistance goaf model, and FIG6(b) is the calculation result of the high-resistance goaf model;

[0018] Figure 7 A three-dimensional goaf model according to an embodiment of the present invention;

[0019] Figure 8(a) and 8(b) Based on Figure 7 The schematic diagram of the forward multi-channel response of the three-dimensional goaf model shown in FIG8(a) corresponds to the low-resistance goaf model, and FIG8(b) corresponds to the high-resistance goaf model;

[0020] Fig. 9 A schematic diagram of a test working device according to an embodiment of the present invention;

[0021] Fig.10 Observation curves of different superposition times according to an embodiment of the present invention;

[0022] Fig.11 Observation curves of three test points of one embodiment of the present invention;

[0023] Figures 12(a), (b) and (c) are representative test line resistivity-depth cross-sections of the A zone of the embodiment of the present invention, wherein Figures 12(a), (b) and (c) are resistivity-depth cross-sections of 8 lines, 38 lines and 58 lines respectively;

[0024] Figures 13(a) and (b) are resistivity-depth cross-section diagrams of the measurement line in the B area according to an embodiment of the present invention, wherein Figures 13(a) and (b) are resistivity-depth cross-section diagrams of the measurement line in the B1 area and the B2 area, respectively;

[0025] Figures 14(a), (b), and (c) are relative abnormal cross-section diagrams of representative survey lines in area A of an embodiment of the present invention, wherein Figures 14(a), (b), and (c) are relative abnormal cross-section diagrams of line 8, line 38, and line 58, respectively;

[0026] Figures 15(a) and (b) are relative abnormal cross-section diagrams of representative survey lines in area B of an embodiment of the present invention, wherein Figures 15(a) and (b) are relative abnormal cross-section diagrams of line B1 and line B2, respectively;

[0027] Fig. 16 (a), (b) and (c) are resistivity contour planes at different depths in the A zone according to an embodiment of the present invention, wherein Fig. 16 (a), (b) and (c) are resistivity contour planes at a depth of 30 m in the A zone, resistivity contour planes at a depth of 60 m in the A zone and resistivity contour planes at a depth of 90 m in the A zone, respectively;

[0028] Figures 17(a), (b) and (c) are relative anomaly plan views at different depths in zone A of an embodiment of the present invention, wherein Figures 17(a), (b) and (c) are relative anomaly plan views at a depth of 30m in zone A, relative anomaly plan views at a depth of 60m in zone A and relative anomaly plan views at a depth of 90m in zone A, respectively.

[0029] Fig.18 This is a low-resistance goaf distribution diagram of area A of an embodiment of the present invention;

[0030] Fig.19 This is a high-resistance goaf distribution diagram of area A of an embodiment of the present invention;

[0031] Fig. 20 This is a distribution diagram of the goaf area in zone A of an embodiment of the present invention;

[0032] Fig.21 This is a distribution diagram of the goaf area in zone B of an embodiment of the present invention. DETAILED DESCRIPTION

[0033] The technical features involved in the different embodiments of the present application described below can be combined with each other as long as they do not conflict with each other.

[0034] The present application embodiment provides a method for transient electromagnetic detection of a small pit goaf area, such as Figure 1 As shown, the following steps are included:

[0035] S101: Data simulation step, establishing different geophysical numerical models according to the geological and geophysical information of the survey area, and performing forward simulation on the geophysical numerical models to obtain transient electromagnetic response characteristics under different parameters; determining the detection parameters of the survey area according to the simulation results.

[0036] S102: Data test step, performing detection tests at typical measurement points in the measurement area, verifying the selected detection parameters, and determining acquisition parameters based on the verification results.

[0037] S103: Data collection step, determining the distribution of survey lines in the survey area according to the collection parameters, emitting transient electromagnetic waves to each survey line in the survey area, and detecting transient feedback electromagnetic waves fed back by each survey line.

[0038] S104: Data processing step, invert and analyze the feedback electromagnetic waves of each survey line, and obtain the inversion resistivity and depth data of each survey line according to the inversion analysis results; determine the low-resistance abnormal area and the goaf abnormal area in the small pit goaf area according to the inversion resistivity and depth data of each survey line; determine the boundary position of the small pit goaf area according to the low-resistance abnormal area and the goaf abnormal area, combined with geological and geophysical information.

[0039] The scheme in the above embodiment obtains the transient electromagnetic response characteristics of the goaf area in the survey area through transient electromagnetic forward calculation. Combined with the forward modeling results, the latest two-dimensional constrained inversion technology is further used to refine the information to more accurately define the scope of the goaf area. Before the formal execution of data collection, an observation parameter test is first carried out, and the observation parameters are optimized through the test. After the data collection is completed, for the collection results, starting from the basic characteristics of the goaf area of ​​the coal mine, the geophysical characteristics of the goaf are analyzed in detail, and finally an appropriate detection method is selected to detect the survey area. First, the survey area is scanned by transient electromagnetic method, the transient electromagnetic anomaly area is verified by high-density electrical method, and the spatial distribution of the goaf area is delineated in detail in combination with three-dimensional reflection seismic. Using the method in this application, for the goaf area under the conditions of a gently inclined coal seam with a burial depth of less than 100m and a coal seam thickness of less than 10m, this combination of geophysical prospecting methods has the most significant effect. Through the above scheme of the present invention, accurate regional division results of small pit goaf areas can be obtained.

[0040] In the above scheme, the steps of data simulation include: before formal data collection, different geophysical numerical models are established according to the geological and geophysical information of the survey area, forward simulation is performed using numerical simulation methods, and the numerical calculation results are analyzed to determine effective detection methods and select appropriate observation parameters. Among them, the numerical simulation method includes simulating the transient electromagnetic response characteristics under different parameters through one-dimensional forward simulation and three-dimensional forward modeling.

[0041] In the above scheme, the steps of data testing include: before formal data collection, observation tests are carried out at typical measuring points in the survey area to verify the effectiveness of the method and determine the optimal collection parameters. The test points for data testing are selected in areas with known geological conditions and less interference.

[0042] In the above scheme, the data collection process includes the following parts:

[0043] 3.1. Setting of transient electromagnetic instrument. In this embodiment, the Terra TEM transient electromagnetic instrument produced in Australia can be used, and the probe is the domestic TEM-7K magnetic probe. Terra TEM is an advanced transient electromagnetic instrument with a convex compact package that provides a certain range of measurement functions. With the installation of a medium-sized power transmitter and a high-speed digitizer, Terra TEM has the ability to detect shallow high-resistance rock masses to deep mineral targets. The large touch screen and intuitive menu make Terra TEM a transient electromagnetic system with a good user interface. Optional accessories further enhance the performance of the system, enabling the reduction, processing and visualization of timely collected data. The system provides timely quality control feedback for staff and subtle spatial and temporal differences.

[0044] 3.2. Control machine settings. The console includes a Pentium 3 processor, a 15-inch ultra-thin LCD display with a touch screen, a transient electromagnetic transmitter with an output energy of 10A, and a transient electromagnetic receiver with a fixed gain. Its built-in system can detect circuits and one to three flow channels. The receiving channel uses a fixed 500kHz, 16-bit A / D conversion while sampling. A built-in GPS module is optional. The processor chip includes a low-power Pentium series processor with a 1GB storage chip.

[0045] 3.3. Display settings. The ultra-thin display is a high-brightness display device that can be used well in sunlight. The brightness can be adjusted through the button below the display. When the lid is closed, its built-in switch can turn off the display and save power. If necessary, the user can turn off the display manually and use the high-brightness touch button. When the display directly reflects sunlight, its visibility will be reduced.

[0046] 3.4. Touch screen settings: You can quickly set and obtain (parameters) through the touch screen interface, and use a large number of options to adjust and manage system parameters without cumbersome nested menus. Most parameters can be (set) with only two or three touch operations. Only fingers are allowed to operate the screen. Never use hard objects such as pens, screwdrivers, etc. to operate, otherwise it will seriously damage the screen, reduce its service life, and reduce the visibility of the display;

[0047] 3.5. Graphical User Interface Settings The graphical user interface uses a user-friendly design. Tables and pop-up menus are used only when the user quickly overviews important parameters and wants to keep the interface tidy. The user always sets important system parameters to be visible.

[0048] 3.6.GPS settings. The built-in GPS is optional and is installed on the top of the bottom box. It has a 12-channel active antenna. Enter the GPS program through a special menu to view various parts related to the GPS system, such as satellite space distribution, NMEA traffic, etc. After the GPS is turned on, the system takes 2-5 minutes to initialize to determine the location, and then the GPS enters the dynamic mode; if the cover is closed, no GPS data will be received; the parameters obtained are the longitude and latitude of all parts of the world.

[0049] 3.7. Transmitter settings; within a period of one second, the transmitter's specified output power is 24V / 10A. The shutdown time is fixed and detectable for the loop self-inductance effect of the current. The short-circuit protection inside the circuit can stop the transmitter and alarm the operator. A high-power transmitter can be used. Its shutdown time is shorter than the previous layer exploration and 2.5 times faster than the transmitter's loop self-inductance. Users can also select the most appropriate current through the expansion package.

[0050] 3.8. Receiver settings: The receiver input signal comes from single-turn coil induction or multi-coil amplification. The effective power required by the receiver is 12V / 120mA. Each receiving channel is independent and has a separate storage address. Different gains can be set. Depending on the needs of the environment, you can choose whether to use Nyquist filtering, but you cannot set Nyquist filtering for a single channel.

[0051] 3.9. Set the optimal resonant frequency and induction intensity of the magnetic probe, set up the data acquisition part of the system, the signal transmission system and the central control console, and connect the three. At 7.2k, the magnetic probe has the best resonant induction value and the maximum induction intensity. The better the reception effect of the corresponding underground signal, the greater the intensity. Therefore, in order to achieve the detection depth, a 7K probe is used as the receiving device.

[0052] 3.10. After the above devices are connected into a system, the data acquisition part transmits the received electromagnetic signals to the central control console through the signal transmission system to complete the data collection work.

[0053] The system uses a direct access connection method, and can draw a stable transient attenuation curve as required. Users can use this to test the function of the system, evaluate the effectiveness of the gain and whether the Nyquist filter setting is appropriate; the resistance of the receiving coil can be measured by passing a very small current through the receiving coil, and the maximum resistance of the coil is 100 ohms. When the system is turned off, the protection circuit disconnects the connector and amplifier to protect the system. In addition to receiving signals, the receiving circuit can also detect other important system parameters, including internal temperature and battery voltage, and prompt the user when the system is in an abnormal state; the receiving device uses a magnetic rod instead of a hollow coil. When a magnetic probe is used instead of a receiving loop, the detection depth after data processing often becomes larger, and as the probe model changes, the detection depth from 250k-70k-18k-7k continues to increase. This is related to the receiving area of ​​different types of magnetic probes. The effective receiving area of ​​these four probes is 200m respectively. 2 , 2000m 2 , 10000m 2 , 40000m 2 The larger the receiving area, the greater the strength of the received signal, and the greater the signal-to-noise ratio, making it possible to process and interpret deep signals. At the same time, the probe model represents the resonant frequency of the probe. The TEM-7K magnetic probe is the magnetic probe with the lowest resonant frequency, which is only 7KHz, and the highest linear frequency is about 4KHz. The amplitude-frequency characteristic curve of the magnetic probe is very close to the 45° linear rise characteristic in the frequency band below the resonance point on the double logarithmic coordinate paper.

[0054] In the above scheme, the data processing process includes:

[0055] 4.1. Perform quasi-two-dimensional inversion on all pre-processed data of each survey line to obtain inverted resistivity and depth data, and draw resistivity-depth pseudo-section diagrams of each survey line to characterize the electrical structure within a certain depth of the survey area.

[0056] 4.2. According to the inversion results, the overall electrical property difference in the survey area is small, and it is difficult to divide the goaf abnormal area directly according to the resistivity value. For this reason, the average resistivity at the same depth of each survey line is taken, and then the relative error between the inverted resistivity at the corresponding depth of each survey line and the average resistivity at the depth is calculated, and a relative anomaly map is drawn to quantitatively delineate the low-resistance abnormal area.

[0057] 4.3. At 5-meter depth intervals, draw the apparent resistivity plane contour map and relative anomaly map within the 110-meter depth range, and circle the abnormal mining area on the plane.

[0058] 4.4. Based on the cross-sectional and plan views of resistivity and relative anomalies, combined with geological information and on-site surveys, a joint analysis is conducted to determine the boundary position of the goaf and provide guidance on the location of the drilling holes.

[0059] Among them, in the data simulation step, the forward modeling method of one-dimensional forward modeling includes:

[0060] In the case of non-zero offset, the frequency domain vertical magnetic field induction intensity component generated by the loop source is:

[0061]

[0062] It can be seen that in a one-dimensional layered medium, under non-zero bias conditions, the vertical magnetic field response of the loop source is expressed as a double integral, where the inner integral is a double Bessel function integral and the outer integral is a cosine integral. The integral kernel in equation (1) is It increases monotonically with the increase of λ. Therefore, in the Hankel transform of equation (1), many filter coefficients and convolution calculation times are required, which affects the calculation speed. In order to ensure the convergence speed of the integral of the above equation and reduce the number of convolution calculations, the integral kernel is transformed into So the Hankel transformation becomes:

[0063]

[0064] because As λ increases, it appears as a single-peak curve of finite width. Therefore, when calculating, it is only necessary to perform convolution calculation within the finite width where the integral kernel is not zero, which can greatly reduce the filter coefficient and the number of convolutions and improve the calculation speed. At the same time, in order to further improve the calculation speed, the cubic spline interpolation function is introduced into the calculation, that is, the linear digital filtering method is first used to calculate a sufficient number of BZ(b), and then the cubic spline interpolation function method is used to obtain the required kernel function value, thereby replacing the linear mathematical filtering method to directly calculate the kernel function BZ(b), which greatly speeds up the calculation speed.

[0065] After obtaining the frequency domain response, the time domain response can be obtained by Fourier transform:

[0066]

[0067] The simulation results of one-dimensional forward modeling are:

[0068] The geological and drilling information of the survey area revealed that the coal seams in this area are shallowly buried and the geological conditions are simple. Figure 2The simplified one-dimensional layered model is shown in Figure 1. Among them, ρ1 is the resistivity of the surrounding rock (background), and the value is set to 100Ω.m; h1 is the thickness of the cap rock, and the value varies according to different situations; ρ2 and h2 represent the resistivity and thickness of the coal-bearing strata, and their values ​​will vary according to the different situations of the layer being a coal seam, a low-resistance goaf (filled with water), and a high-resistance goaf (filled with air). Based on previous experience and the overall resistivity level of the survey area, while considering work efficiency and detection effect, we used a 300m×300m central loop device for simulation, the current was taken as the normalized value (1A), the calculation time range was 0.006ms~20ms, and included 40 time windows.

[0069] First, the response characteristics of coal-bearing strata under different conditions are analyzed. At this time, the cover thickness is set to h1 = 50m, the coal-bearing strata thickness is set to h2 = 20m, and the resistivity of the coal-bearing strata when they are coal seams, low-resistance goaf (filled with water), and high-resistance goaf (filled with air) are ρ2 = 1000Ω.m, 10Ω.m, and 10000Ω.m, respectively. The calculation results are shown in 3. It can be seen that the attenuation curve of the low-resistance goaf is significantly different from that of the unmined coal-bearing strata, while the difference between the high-resistance goaf and the coal-bearing strata is very small. This is related to the insensitivity of the vertical magnetic field component of the loop source to high-resistance strata. In order to better quantitatively analyze the differences between the two goaf conditions and the original coal-bearing strata signals, we plot the relative anomaly curves of the two and the coal-bearing strata as shown in Figure 3. Figure 4 As shown in the figure, it can be seen that the maximum relative error between the low-resistance goaf area and the original coal formation response can reach more than 300%, while the maximum value of the high-resistance goaf area is only about 4%. This shows that in actual field detection, the transient electromagnetic method can easily identify the low-resistance goaf area, but it is difficult to effectively detect the high-resistance goaf area.

[0070] Next, we study the effect of different cover thicknesses on the simulation results. According to the survey area information, the burial depth of the main coal seam (12 coal) ranges from 20 to 80 m. The responses of low-resistance goaf and high-resistance goaf with different cover thicknesses were simulated at 20 m intervals. Other parameters were consistent with the previous ones. The results are shown in Figure 5 (a) and Figure 5 (b). It can be seen that the response curves of different thickness models will show great differences in the early stage, especially the low-resistance goaf model, which indicates that the detection device can obtain corresponding response characteristics for goafs with different burial depths.

[0071] Finally, in order to solve the problem of goaf size, the response characteristics under different goaf thickness conditions were simulated. At this time, the burial depth of the top interface of the coal series is fixed at 50 meters, and the goaf thickness is considered to be 5 meters, 10 meters, 20 meters, 25 meters, and 30 meters respectively. Other parameters remain unchanged. The calculation results are shown in Figure 6 (a) and Figure 6 (b). The numerical results show that the change of goaf thickness will also have a great impact on the response, and the impact on the low-resistance goaf is more obvious.

[0072] The forward modeling methods of the three-dimensional forward modeling in the above scheme include:

[0073] The underground electrical structure is actually three-dimensional. Establishing a three-dimensional geological-geophysical model of the goaf and performing three-dimensional forward simulation can obtain signals that are closer to actual field observations. The time-domain finite-difference method is the main method for numerical simulation of transient electromagnetic fields. In recent years, it has been widely used in transient electromagnetic field simulation. The Maxwell equations under quasi-static conditions are used in transient electromagnetic field calculations:

[0074]

[0075]

[0076] Where: B is the magnetic induction intensity, E is the electric field intensity, H is the magnetic field intensity, σ is the dielectric conductivity, and γ is the virtual dielectric constant.

[0077] In the region where the emission source is located, equation (5) needs to be modified to

[0078]

[0079] Among them J s is the source current density.

[0080] By performing differential discretization on equations (4)-(6), the electromagnetic field differential equations of the passive and active regions can be obtained.

[0081] Simulation results:

[0082] Design as Figure 7 The three-dimensional goaf model shown in the figure has a resistivity of 100Ω.m for the surrounding rock formation, a thickness of 50m for the caprock, a resistivity of 500Ω.m for the coal seam, and a thickness of 5m. There is a goaf in the coal-bearing stratum, and its size is fixed at 20×20×5m (length, width, and height). By changing the resistivity value of the goaf, the characteristics of the transient electromagnetic three-dimensional response when the low-resistance and high-resistance goaf are abnormal are studied respectively.

[0083] Assume that the resistivity of the low-resistance goaf area is 10Ω.m, and the resistivity of the high-resistance goaf area is 10000Ω.m. The three-dimensional forward modeling of the two models is performed to obtain the multi-channel response profiles shown in Figure 8(a) and Figure 8(b).

[0084] In addition, in the above scheme, the data test steps include:

[0085] Before formal data collection, observation tests need to be conducted at typical measuring points in the survey area. The main purpose is to verify the effectiveness of the method and determine the optimal acquisition parameters. The test points should be selected in areas with known geological conditions and less interference. According to the existing drilling revelations, this embodiment selects a test area in a certain area. There is a goaf area with verified drilling in the area, and the coordinates are (484060.5, 5473735.3). With this point as the center, a 300×300m transmission wireframe is laid out, and the responses of three measuring points are observed in the central area of ​​the frame, such as Fig. 9 The three measuring points are distributed in the east-west direction with a spacing of 20m, among which S2 is the verified mined-out area (filled with water), and S1 and S3 are unmined-out areas.

[0086] The acquisition parameters of transient electromagnetic mainly include: emission source size, emission voltage, emission current intensity, observation time range (emission fundamental frequency), number of superpositions and effective area of ​​the probe. Combined with the above forward simulation conclusions, the emission source size is selected as 300×300m, which can meet the detection needs and can better balance the construction efficiency and detection effect. The probe is selected as a 7k model with an effective area of ​​40,000㎡. The rated emission voltage of the Terra TEM instrument is 24V, so the emission current intensity can be determined according to the line resistance. The transmission wire frame used in this transmission is 6mm 2 The multi-core copper wire has a resistivity level of about 0.4Ω.m / 100m, and the overall resistivity of the emission source is about 4.8Ω.m, so the emission current intensity is about 5A. The two parameters that need to be determined are the emission base frequency and the number of superpositions. The emission base frequency determines the decay time range of the secondary field signal, thereby determining the range of the detection depth. The number of superpositions is related to signal quality and work efficiency. Under the premise of meeting the signal smoothness, minimizing the number of superpositions can ensure higher measurement efficiency.

[0087] In summary, the two parameters of the transmission base frequency and the number of superpositions were mainly selected and studied in the experimental work. According to the detection depth estimation formula of the central loop device (t is in ms), the latest estimated time is t=d 2 / 500ρ. The goaf in the survey area is shallowly buried, and the target detection depth does not exceed 100m. However, in order to better characterize the deep electrical structure, the maximum detection depth is taken as 200 meters. The resistivity in the formula needs to use the average resistivity value within the 200-meter depth range of the survey area. According to the existing information, the minimum and maximum values ​​of the average resistivity are set to 5Ω.m and 500Ω.m, respectively. Based on the above parameters, it can be estimated that at extremely low and extremely high resistivity levels, the latest time channel required to reach a detection depth of 200 meters is 16ms and 0.16ms, respectively. Therefore, in order to ensure that the detection depth can meet the requirements under any electrical conditions, the latest observation delay in actual work cannot be later than 16ms. According to the built-in time series of Terra TEM, the selected transmission base frequency is 12.5Hz, and the latest time channel is 20ms at this time.

[0088] The overall interference level in the measurement area is low, and there are high-voltage wires and drilling rigs under construction at some measurement points. In areas without obvious interference, a good attenuation curve can be obtained by selecting 128 times of superposition. At this time, increasing the number of superpositions will not significantly improve the data quality. Fig.10 The observation curves for the S1 measurement point when 128, 256 and 512 times of superposition are used respectively. It can be seen that with the increase of the number of superpositions, the observed signal has not been significantly improved. Therefore, in order to ensure the measurement efficiency, the number of superpositions is mainly 128 times during operation. When the interference is more serious or the observation curve has a large oscillation, the number of superpositions is appropriately increased.

[0089] At this point, the parameters for field data collection have all been determined and can be summarized as follows: Working device: center loop, emission source size: 300m×300m, emission voltage: 24V, emission current: 5A, emission base frequency: 12.5Hz, number of superpositions: 128 times, probe effective area: 40000m 2 .

[0090] According to the above acquisition parameters, the signals of the three test points are collected in sequence, such as Fig.11 As shown in the figure, it can be seen that the curve of the S2 measuring point with a low-resistance goaf is significantly different from the curves of the other two measuring points without goaf. The low-resistance goaf significantly enhances the response amplitude of the S2 measuring point. Therefore, the experimental work shows that transient electromagnetic detection can effectively identify goaf under the selected working parameters.

[0091] In this embodiment, in the data collection step, a total of 63 central loop transient electromagnetic measurement lines and 2 overlapping loop measurement lines are arranged in the measurement area A, and 1 central loop and 1 overlapping loop transient electromagnetic measurement line are arranged in the measurement area B. The specific work arrangement is as shown in the actual material. Figure 3-21The exploration process: 64 central loop transient electromagnetic survey lines, with a total profile length of 47740m, 2447 physical points, 141 quality inspection points, 30 test points, and a total of 2618 physical points; 3 overlapping loop transient electromagnetic profiles, with a total profile length of 4360m, 221 survey points, 13 quality inspection points, 10 test points, and a total of 244 physical points.

[0092] Specifically, the data processing includes the four steps 4.1-4.4 as mentioned above. The above four steps of this embodiment are explained one by one below.

[0093] 1. Apparent resistivity-depth profile interpretation

[0094] First, the data of all survey lines are subjected to quasi-two-dimensional inversion to obtain resistivity-depth data and draw cross-section diagrams. The inversion adopts the OCCAM method, with a maximum depth of 110 meters, a total of 22 layers, and a fixed thickness of 5 meters for each layer. Due to the large number of survey lines, only a few representative survey line profile results are selected for analysis.

[0095] In the working area A1, A2 and A3, 8 lines, 38 lines and 58 lines were selected for analysis, and the inversion results are shown in Figures 12-15. From the resistivity-depth section, it can be seen that the electrical structure revealed by the three survey lines generally shows a medium-high-low-high-low change trend within the depth range of 110m. Among them, the medium-high resistivity (resistivity 35-45Ω.m) layer shallower than 30m is speculated to be related to the Holocene strata and backfill soil on the surface; there is a low-resistivity layer (resistivity 20-30Ω.m) within the depth range of 30-50 meters, which is speculated to be a reflection of the Quaternary sedimentary layer; the overall resistivity of the survey line within the depth range of 50-90m is relatively high, which is a display of the coal-bearing strata; when the depth is greater than 90m, the stratum resistivity becomes very low, only about 10Ω.m, which is speculated to be related to the low-resistance mudstone and sandstone in the underlying strata of the coal-bearing strata.

[0096] According to the above analysis, the integrity of the coal-bearing strata will be destroyed after the coal seam is mined. If the goaf maintains a relatively stable spatial form and is not filled with water, the electrical characteristics will show a relatively high-resistance anomaly; if the goaf is filled with water, the resistivity will drop significantly, showing a relatively low-resistance anomaly. However, due to the low detection sensitivity of the transient electromagnetic method for high-resistance targets, it is difficult to obtain accurate relatively high-resistance anomalies. Therefore, we only focus on the low-resistance anomaly area here. Based on this principle, the electrical characteristics of the above three lines within the depth range of the coal seam can be analyzed, and the 0-120, 360-400, 520-620, 620-680 measuring points of the 8th line, the 60-100 point area of ​​the 38th line, and the 40-100, 560-700 point area of ​​the 58th line can be roughly delineated. The resistivity shows obvious lateral discontinuity and there are many low-resistance barriers. These resistivity anomaly areas may be related to underground water-rich goafs. However, due to the overall small electrical differences in the survey area, coupled with the averaging effect brought about by the resistivity data difference, it is difficult to accurately delineate the abnormal area by relying solely on the amplitude change of the resistivity. As shown in Figure 12, the resistivity-depth cross-section diagram of the representative survey lines in Area A is shown, which are the resistivity-depth cross-section diagrams of 8 lines, 38 lines and 58 lines respectively. Figure 13 shows the inversion results of two survey lines B1 and B2 in Area B. Among them, B1 is the survey line on the north side of the conveyor belt, and B2 is the survey line on the south side. It can be seen that the inversion results of the survey lines on both sides are basically the same, and the electrical characteristics show a high-low-high change trend. However, the resistivity of the two survey lines in this area is generally low, which is quite different from the structure of Area A. This is most likely because the measuring point is close to the conveyor belt. The low-resistance conveyor belt of the metal causes the signal to attenuate slowly and the response value to increase, making the inversion resistivity overall low. Therefore, the depth and resistivity values ​​in the inversion results of these two lines are not reliable. However, it can be explained from the lateral changes in the electrical structure. It is obvious that the resistivity of these two lines shows more mutations in the lateral direction, which reveals that the stability of the underground strata may have been destroyed, forming a larger area of ​​mined-out area.

[0097] Figures 12(a), 12(b), 12(c) and 13(a), 13(b) are explanations of the resistivity-depth cross-section diagrams for typical survey lines. The interpretation of other survey lines can refer to the above criteria, and the cross-section diagrams of all survey lines can be found in the attached figure. It can be seen that from the resistivity-depth cross-section diagram, only the vertical and horizontal variation trends of the formation resistivity can be obtained, but it is difficult to accurately identify the abnormal goaf area. Therefore, we will use the concept of relative anomaly to identify and delineate the goaf area.

[0098] 2. Interpretation of relative abnormal cross-section diagram

[0099] Geological and drilling information show that the strata in this area are stably distributed and have gentle inclinations. Therefore, it can be assumed that at a fixed depth in the entire survey area, the resistivity of the strata tends to a stable value. When there is a goaf at this depth, the resistivity will increase or decrease within a certain range. Therefore, the concept of relative anomaly can be used to divide high-resistance and low-resistance goaf areas. That is, first calculate the average resistivity of the entire area at a fixed depth, then calculate the relative error between the resistivity value of each measuring point at this depth and the average value, and finally judge the low-resistance goaf and high-resistance goaf based on the given relative low anomaly and high anomaly thresholds. The formula for calculating relative anomaly is:

[0100]

[0101] In the formula, is the resistivity value at the jth depth at the ith measuring point, is the average resistivity in the whole area at depth j.

[0102] According to the above ideas, the relative anomaly values ​​of all survey lines can be calculated. The key issue here is to determine the thresholds of high and low anomalies. Combined with the analysis of the resistivity-depth cross-section diagram and the verification of the measuring points with known geological conditions, we set the threshold of low-resistance anomalies to -20% and the threshold of high-resistance anomalies to 20%. That is, when the relative anomaly is less than or equal to -20%, it is judged as a low-resistance goaf filled with water; when the relative anomaly is greater than or equal to 20%, it is judged as a high-resistance goaf filled with air.

[0103] First, the average resistivity of the whole area within a depth of 110 meters is calculated at a spacing of 5 meters, and the calculation results are shown in Table 1. It can be seen that the change trend of the average resistivity of the whole area with depth is consistent with the change of each survey line.

[0104] Table 1 Average resistivity at different depths in A1 area

[0105]

[0106] Figures 14(a), 14(b) and 14(c) are the relative abnormal cross sections of lines 8, 38 and 58. It can be seen that the resistivity anomaly range in each measuring line can be clearly identified by using the relative abnormal cross sections, and its high and low resistance characteristics can also be judged.

[0107] Figures 15(a) and 15(b) are the relative anomaly cross-sections of the two survey lines in Area B. Since this area is far away from Area A and the resistivity results are distorted by the influence of the conveyor belt, we calculate the average value of the resistivity values ​​of the two lines at the same depth. Figure 12(a) , 12(b)The resistivity-depth cross-section diagrams shown in Figures 12(c)-13(a) and 13(b) can provide more details, depict the lateral resistivity mutation more accurately, and provide more direct evidence for delineating high and low resistivity abnormal areas.

[0108] 3. Interpretation of the apparent resistivity contour map

[0109] The influence range of goaf may be from the surface to the interface of coal seam floor. In order to analyze the changes of stratum electrical properties at different depths in the survey area and the distribution of goaf, we drew resistivity plane distribution maps at 23 depths ranging from 0 to 110 meters with a spacing of 5 meters. Since there are only two survey lines in area B, this work is only carried out for the data of area A. Here, the resistivity contour plane distribution map of all survey points in area A at three depths of 30 meters, 60 meters and 90 meters is selected as an example for analysis, as shown in Figure 16. The resistivity plane distribution map of other depths is shown in the attached figure. It can be seen that the resistivity anomaly area can be easily divided by the resistivity contour plane map. According to the above-mentioned goaf interpretation criteria, we can interpret the relatively low-resistance and relatively high-resistance areas in the figure as water-filled and water-supplemented goaf. In addition, according to the actual field survey, the location of the collapse area on the surface is marked in the figure (as shown in the square in the figure). It can be seen that where there is surface collapse (it is believed that there is underground goaf), it does not necessarily show absolute low-resistance or high-resistance characteristics in terms of electrical properties. It is also worth noting that the resistivity anomalies in some areas of the figure may also be related to the interference of power transmission lines on the surface, such as the obvious high-resistance anomaly belt running nearly north-south in the southwest of the survey area.

[0110] 4. Relative anomaly plan view interpretation

[0111] Similar to the cross-sectional diagram, it is difficult to accurately delineate and distinguish the range of high-resistance and low-resistance goaf areas using only the resistivity plane distribution map. Therefore, the concept of relative anomaly is continued to be used to draw relative anomaly distribution maps of each depth plane, as shown in Figure 17(a), Figure 17(b) and Figure 17(c). Obviously, the relative anomaly plane distribution map can clearly delineate the relatively low-resistance and relatively high-resistance anomaly areas at each depth, providing very direct evidence for the subsequent goaf interpretation. It can also be found that the areas shown as low-resistance or high-resistance anomalies in the resistivity contour lines at the same depth are not displayed in the relative anomaly map, which is also the advantage of using quantitative thresholds for division.

[0112] 5. Summary of transient electromagnetic interpretation results for the 1st to 4th

[0113] The data of each depth in the A survey area are integrated to form a three-dimensional relative anomaly distribution map, as shown in the following figure. Fig.18 and 19The spatial distribution of relatively low-resistance and relatively high-resistance anomalies is shown. It can be seen that the low-resistance relative anomaly area is mainly distributed in the southern part of the A survey area, the high-resistance relative anomaly is more widely distributed in the A area, and the distribution of resistivity anomalies in the middle of the survey area is relatively scattered. It should be noted that in some survey point areas, relatively low-resistance and relatively high-resistance anomalies exist at different depths at the same time. For this situation, we count both high and low-resistance anomalies.

[0114] Finally, the scope of the goaf in this work area was delineated based on the apparent resistivity cross-section diagram, relative anomaly cross-section diagram, resistivity plane diagram, relative anomaly cross-section diagram, relative anomaly three-dimensional diagram, field survey, and existing information. Fig. 20 As shown. From the interpretation results map, it can be seen that the distribution range of goaf areas in the survey area is random and disordered, which is consistent with the characteristics of small coal pits that coal is mined whenever it is seen. Therefore, when dividing the goaf area, we use the TEM measurement points with abnormalities as statistics, that is, each measurement point corresponds to a goaf area. At the same time, we plot the location points of goaf areas with a thickness greater than 5 meters revealed by the implemented drilling and the location points of ground collapse obtained by field surveys in the figure to verify the reliability of the interpretation results. It can be seen that the locations of the revealed goaf areas and ground collapse areas are basically consistent with the interpreted goaf abnormal areas. According to statistics, there are a total of 117 goaf areas greater than 5 meters revealed by drilling and recorded ground collapse points, and there are 102 points that are consistent with the interpretation results. Therefore, it is estimated that the accuracy of this detection result can reach about 87%.

[0115] The interpretation results of area B are shown in the figure Fig.21 As shown in the figure, it can be seen that there are large areas of suspected goaf areas on both sides of the conveyor belt in Area B, and the goaf areas are relatively continuous. According to the statistical results, there are 149 low-resistance goaf areas in Area B.

[0116] Finally, the results of the interpretation of low-resistance goaf are as follows: 679 low-resistance anomaly areas were identified in Area A, including 175 in Area A1, 369 in Area A2, and 135 in Area A3; 149 low-resistance anomaly areas were identified in Area B, as shown in Table 2. It should be noted that the abnormal belt ( Fig. 20 There is a north-south transmission line here, which has a certain impact on the measured data and reduces the reliability of the interpretation results.

[0117] Table 2 Statistical information of delineated goaf areas

[0118]

[0119] Methods A comprehensive geophysical exploration of goaf was carried out using 3D seismic, transient electromagnetic, high-density electrical method and elastic wave inter-hole CT method. First, transient electromagnetic method was used to scan the study area, high-density electrical method was used to verify the transient electromagnetic anomaly area, and the spatial distribution of goaf was delineated in detail in combination with 3D reflection seismic. The results showed that this geophysical exploration method is applicable to goaf in gently dipping coal seams with a burial depth of less than 100m and a coal seam thickness of less than 10m.

[0120] The method adopted in the above embodiments of the present application has at least the following advantages:

[0121] (1) Based on the collection of geological information of the working area and previous work results, transient electromagnetic method, high-density resistivity method, three-dimensional seismic method and elastic wave inter-hole CT method were used to detect the inter-hole distribution of collapse pits with a diameter greater than 5m in the small pit goaf area of ​​the working area. A large amount of real and reliable geophysical data was obtained, which is important information for this study on goaf collapse and an important reference for future geological prospecting and coal mining work in the area.

[0122] (2) The distribution characteristics and impact range of the collapse pits with a diameter greater than 5 m in Areas A and B were identified, and the spatial connections within the collapse pits were analyzed. Among them, 28 mining collapse pits were identified in Area A1, 44 in Area A2, 9 in Area A3, and 5 in Area B.

[0123] (3) Based on the comprehensive interpretation and inference results, the morphological characteristics of the mining subsidence areas in areas A1 and A3 were further inferred and their distribution volumes were estimated in combination with the drilling information of areas A1 and A3. Based on the results of areas A1 and A3, the distribution characteristics of mining subsidence in areas A2 and B were inferred and classified, which provided a basis for the later geological drilling layout.

[0124] (4) The technical characteristics of four geophysical methods for detecting goafs were summarized, the advantages and problems of each method were analyzed, and corresponding countermeasures and solutions were proposed for the problems. A combination of geophysical technical methods for detecting subsidence areas in small pit goafs was proposed, which provided a reference for goaf detection in areas with similar geological conditions.

[0125] Obviously, the above embodiments are merely examples for the purpose of clear explanation, and are not intended to limit the implementation methods. For those skilled in the art, other different forms of changes or modifications can be made based on the above description. It is not necessary and impossible to list all the implementation methods here. The obvious changes or modifications derived therefrom are still within the scope of protection of this application.

Claims

1. A transient electromagnetic detection method for small pit goaf, characterized in that: The steps include: Data simulation step: different geophysical numerical models are established according to the geological and geophysical information of the survey area, and the transient electromagnetic response characteristics under different parameters are obtained by forward simulation of the geophysical numerical models; Determine the detection parameters of the survey area according to the simulation results; Data test steps: conduct detection tests at typical measurement points in the measurement area, verify the selected detection parameters, and determine the acquisition parameters based on the verification results; The data acquisition step is to determine the distribution of the survey lines in the survey area according to the acquisition parameters, emit transient electromagnetic waves to each survey line in the survey area, and detect the transient feedback electromagnetic waves fed back by each survey line; The data processing step is to invert and analyze the feedback electromagnetic waves of each survey line, and obtain the inversion resistivity and depth data of each survey line according to the inversion analysis results; determine the low-resistance abnormal area and the goaf abnormal area in the small pit goaf area according to the inversion resistivity and depth data of each survey line; determine the boundary position of the small pit goaf area according to the low-resistance abnormal area and the goaf abnormal area, combined with geological and geophysical information; In the data simulation step: Conduct one-dimensional and three-dimensional forward modeling on geophysical numerical models to simulate transient electromagnetic response characteristics under different parameters; The simulation results of the one-dimensional forward modeling include: the response characteristics of different coal-bearing strata; the influence of different caprock thicknesses on the simulation results; the response characteristics of different goaf thicknesses; wherein: the one-dimensional forward modeling method includes: In the case of non-zero offset, the frequency domain vertical magnetic field induction intensity component generated by the loop source is expressed as formula (1): The integral kernel in formula (1) is Deformation After that, the formula (1) is transformed into formula (2): The vertical magnetic field induction intensity component in the frequency domain is transformed by Fourier transform to obtain the vertical magnetic field induction intensity component in the time domain, which is formula (3): In the three-dimensional forward simulation, the time-domain finite difference method is used to perform numerical simulation of transient electromagnetic fields. The simulation results of the three-dimensional forward simulation are expressed in the form of multi-channel response profiles; specifically, the following are included: The Maxwell equations under quasi-static conditions are used in transient electromagnetic field calculations: Where: B is the magnetic induction intensity, E is the electric field intensity, H is the magnetic field intensity, σ is the dielectric conductivity, and γ is the virtual dielectric constant; In the region where the emission source is located, equation (5) needs to be modified as follows: Among them J s is the source current density; Differentiate and discretize equations (4)-(6) to obtain the electromagnetic field differential equations in the passive and active regions; By changing the resistivity value of the goaf, the characteristics of transient electromagnetic three-dimensional response when low-resistance and high-resistance goaf are studied respectively. Assume that the resistivity of the low-resistance goaf area is 10Ω.m, and the resistivity of the high-resistance goaf area is 10000Ω.m; perform three-dimensional forward modeling on the two models to obtain multi-channel response profiles.

2. The transient electromagnetic detection method for small pit goaf according to claim 1 is characterized in that: In the data test step, the acquisition parameters include: emission source size, emission voltage, emission current intensity, observation time range, emission fundamental frequency, number of superpositions and probe effective area.

3. The transient electromagnetic detection method for small pit goaf according to claim 1 or 2 is characterized in that: In the data test steps: The typical measuring points include three, and detection signals of the three typical measuring points are collected in sequence; According to the distinguishing parameters shown by the detection signal of the existing goaf measuring point and the other two detection signals of the non-existent goaf measuring points, the acquisition parameters of transient electromagnetic detection for identifying the goaf area under the selected working parameters are used.

4. The transient electromagnetic detection method for small pit goaf according to claim 3 is characterized in that: The data collection step is implemented by a data collection system: The data acquisition system includes a control machine and a transient electromagnetic instrument connected to the control machine for communication, a high-brightness display device, a touch screen, a GPS, a transmitter and a receiver; wherein: The transient electromagnetic instrument is equipped with a magnetic probe; the high-brightness display device is equipped with a brightness adjustment button and a switch; the touch screen is used to display a graphical user interface for users to set and obtain parameters; the GPS is used to obtain the longitude and latitude coordinates of the data acquisition system; the transmitter has an output power of 24V / 10A per unit time; the input signal of the receiver comes from a single-turn coil induction signal or a multi-coil amplified signal, and its effective power is 12V / 120mA; the magnetic probe of the transient electromagnetic instrument is pre-set with a resonant frequency and an induction intensity.

5. The transient electromagnetic detection method for small pit goaf according to claim 4 is characterized in that: In the data collection step: The data acquisition system further comprises: a temperature detector for acquiring system temperature and a voltage detector for acquiring system battery voltage; the temperature detector and the voltage detector send the acquired data to the control machine; The data acquisition system also includes an alarm circuit. When the system temperature or battery voltage is abnormal, the control machine controls the alarm circuit to send an alarm signal.

6. The transient electromagnetic detection method for small pit goaf according to claim 1 or 2 is characterized in that: In the data processing step: The OCCAM method is used to invert and analyze the feedback electromagnetic waves of each survey line; According to the inversion analysis results, the high-resistance goaf area and the low-resistance goaf area are divided; The resistivity anomaly area is divided by the resistivity contour plane map, and the relatively low-resistance goaf area is determined as the water-filled goaf area, and the relatively high-resistance goaf area is determined as the air-filled goaf area; A relative anomaly plane distribution map is obtained according to the resistivity contour plane map, and the relative anomaly plane distribution map is used to delineate relatively low-resistance goaf areas and relatively high-resistance goaf areas at various depths.

7. The transient electromagnetic detection method for small pit goaf according to claim 6 is characterized in that: The steps of dividing the high-resistance goaf area and the low-resistance goaf area according to the inversion analysis results include: Calculate the average resistivity of the whole area at a fixed depth; Obtain the relative error between the resistivity value of each measuring point at the depth and the average value; The relatively low-resistance goaf area and the relatively high-resistance goaf area are determined according to the relative error and the given relatively low abnormal threshold and relatively high abnormal threshold.

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