Multi-frequency parallel ac method multi-scale perspective inversion method for coal mining face of coal mine

Abstract

The present application discloses a multi-frequency parallel alternating current method multi-scale perspective inversion method for coal mining face, which is suitable for detecting coal seam working face floor hidden disaster water source; first, set the working face floor as the detection area and establish a rectangular coordinate system; then, divide the detection area into large-scale cubic grids according to the collected low-frequency alternating current field data, and obtain the alternating resistivity values of all grid units by inversion; and take the alternating resistivity values as the initial model, gradually subdivide all large-scale cubic grids into small-scale cubic grids as the frequency increases, and obtain the alternating resistivity values in all small-scale cubic grids by inversion; wherein the grid length corresponding to adjacent frequencies satisfies the formula wherein 1<=i<=(N-1); thus, all transmission frequencies correspond to a grid scale, large-scale grids are used for low-frequency electric field signal inversion, and small-scale grids are used for high-frequency electric field signal inversion; thereby, the identification of different scale geological anomaly bodies is realized.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of coal seam working face floor hidden disaster water source detection, in particular to a multi-frequency parallel alternating current method multi-scale perspective inversion method for coal mining working face. BACKGROUND

[0002] With the continuous development of coal seam mining in China, the hydrogeological conditions of the mine become more and more complex, which makes the coal seam face the serious threat of pressure mining and floor water disaster. At present, the technologies for exploring the floor water disaster of the working face mainly include transient electromagnetic method, audio frequency electric perspective method and mine direct current resistivity method. Among them, the audio frequency electric perspective method has high signal-to-noise ratio and good plane resolution, and is suitable for detecting the water-bearing body of the working face floor, but the detection depth is controlled by frequency conversion. The frequency is less during the conventional audio frequency electric perspective observation, and the data interpretation mainly adopts the ray tracing algorithm, without considering the characteristic relationship between the data obtained by different frequency collection, which leads to poor scale resolution of the results to the water-bearing body. SUMMARY

[0003] In view of the problems existing in the prior art, the present application provides a multi-frequency parallel alternating current method multi-scale perspective inversion method for coal mining working face, to solve the problem of low resolution of the detection results of the traditional audio frequency electric perspective method, and aims to improve the detection accuracy of the geological anomaly body of the coal mining working face.

[0004] To achieve the above-mentioned purpose, the present application adopts the following technical scheme:

[0005] The present application provides a multi-frequency parallel alternating current method multi-scale perspective inversion method for coal mining working face, comprising the following steps:

[0006] (1) setting the floor of the coal mining working face as the detection area, and establishing a rectangular coordinate system;

[0007] (2) setting the observation system, matching the transmitted current and the received electric field; wherein the collected data is obtained based on the fan-shaped observation method and the double-lane interchanging measurement is implemented, realizing the two-way coverage of the alternating current field;

[0008] (3) sorting the N alternating current field data of different frequencies collected by each receiving point from low frequency to high frequency, and the sequential number is f1, f2, …, f N , wherein N≥6 and the frequency range is several hertz to several hundred hertz;

[0009] (4) for the alternating current field data of different frequencies, the detection area is divided into different scale cubic grids, and the frequencies f1, f2, …, f N The corresponding grid lengths are L1, L2, …, L N , wherein the grid lengths corresponding to adjacent frequencies satisfy formula (1);

[0010]

[0011] Where 1≤i≤(N-1);

[0012] (5) Set L1 = n × s, where 1 ≤ n ≤ 3, and s is the distance between adjacent measurement points; recursively calculate L2, ..., L according to formula (1). N , obtain the grid side length corresponding to the AC electric field collected by each frequency excitation;

[0013] (6) First, perform AC resistivity inversion on the grid corresponding to frequency f1 to obtain the AC resistivity R(f1) of all grid cells at this frequency; then, using R(f1) as the initial model, perform AC resistivity inversion on the AC electric field data corresponding to frequency f2 to obtain the AC resistivity R(f2) of all grid cells at frequency f2; and so on, gradually obtain the AC resistivity R(f3) of all grid cells at frequencies f3 to f4. N The corresponding grid cell AC resistivity R(f3) to R(f N ); When implementing AC resistivity inversion, the objective function is set as

[0014] S(m)=[dg(m)] T W d [dg(m)] (2)

[0015] Where g is the theoretical AC electric field data matrix, d is the measured AC electric field data matrix, m is the model AC resistivity matrix, and W d is the weight coefficient matrix; in order to make S(m) converge, the model AC resistivity m is modified several times during inversion, and the modified relationship is:

[0016] (J T W d J+λI)Δm=J T W d [dg(m)] (3)

[0017] Where J is the Jacobi matrix, J T is the transposed matrix of J, and λ is the damping factor. When S(m) meets the given constraints, the inversion is terminated and the AC resistivity values ​​of all grid cells are obtained.

[0018] (7) For R(f1), R(f2), ..., R(f N ) to perform three-dimensional imaging and form N AC resistivity cloud maps; use low-frequency AC resistivity cloud maps to determine large-scale electrical anomalies, and high-frequency AC resistivity cloud maps to determine small-scale electrical anomalies, thereby realizing the identification of geological anomalies of different scales.

[0019] The present invention has the following beneficial effects:

[0020] (1) Through multi-scale inversion of multi-frequency parallel alternating current field perspective data, the spatial resolution of the water-bearing abnormal body of the coal mining face floor is significantly improved, and the problem of low determination accuracy of the water-bearing abnormal body in the detection result of the conventional audio frequency electric perspective method is overcome.

[0021] (2) The multi-scale imaging result can effectively identify water-bearing abnormal bodies of different scales, and combined with geological condition analysis, it is helpful to classify and divide the abnormal amplitude of the water-bearing body, thereby improving the precision of the coal mine stope water disaster prevention level. BRIEF DESCRIPTION OF DRAWINGS

[0022] Figure 1 is the layout diagram of the observation system of the present application;

[0023] Figure 2 is the schematic diagram of the cube grid division in the inversion of the present application;

[0024] Figure 3 is the alternating current resistivity three-dimensional solid figure of the present application;

[0025] Figure 4 is the 50m depth section figure in the three-dimensional solid figure of the present application;

[0026] Figure 5 is the comparison figure of the low-resistance abnormal area and the drilling water yield in the embodiment of the present application. DETAILED DESCRIPTION

[0027] The present application will be described in detail below in combination with the drawings, but the present application can be implemented in various different ways limited and covered by the claims.

[0028] Embodiment:

[0029] There is a limestone aquifer in the floor of the 1021 coal seam working face of a certain mine. According to the ground drilling, the maximum thickness of the stratum is 135m, and there are 15 layers of limestone. Among them, the thickness of 3 limestone and 4 limestone is 11m and 11.6m respectively, and the karst fissure is developed and the heterogeneity is strong, which is the main water-bearing layer. The existing hydrological observation data shows that the static water head of the water-bearing layer is-110m, while the lowest elevation of the working face is-393m, the maximum water pressure is 2.83Mpa, and the maximum water inflow is 117m 3 / h, therefore, the working face faces the problem of pressure mining. The water-bearing layer is the disaster-causing water source of the working face mining.

[0030] (1) According to the field layout principle of the electric field perspective method, the floor of the coal seam working face is set as the detection area, and a rectangular coordinate system is established.

[0031] (2) Set the observation system to match the transmitted current and received electric field; wherein the collected data is obtained based on a fan-shaped observation method and double-lane reciprocal measurement is implemented to achieve bidirectional coverage of the alternating current electric field, such as Figure 1 During actual measurement, 96 and 101 receiving points 96 and 101 are arranged in the double lane of the working face, with a point distance of 10 m, and 20 and 21 power supply points, with a point distance of 50 m, each power supply point corresponding to 21 receiving points.

[0032] (3) Sort the 8 different frequency alternating current electric field data of 1 Hz, 8 Hz, 16 Hz, 32 Hz, 64 Hz, 128 Hz, 256 Hz and 512 Hz of each receiving point from low frequency to high frequency, and the order number is f1, f2, …, f8.

[0033] (4) For alternating current electric field data of different frequencies, the detection area is divided into different scale cubic grids, and a cubic grid division schematic diagram is as shown in Figure 2 The grid side lengths corresponding to the frequencies f1, f2, …, f8 are L1, L2, …, L8 respectively, wherein the grid side lengths corresponding to adjacent frequencies satisfy formula (1);

[0034]

[0035] Wherein 1≤i≤7.

[0036] (5) Set L1=n×s, wherein 1≤n≤3, and s is the distance between adjacent measurement points; L2, …, L8 are recursively calculated according to formula (1) to obtain the grid side length corresponding to the alternating current electric field collected at each frequency.

[0037] (6) First, the grid corresponding to the frequency f1 is subjected to alternating current resistivity inversion to obtain the alternating current resistivity R(f1) of all grid units at this frequency. Then, taking R(f1) as the initial model, the alternating current resistivity inversion is performed on the alternating current electric field data corresponding to the frequency f2 to obtain the alternating current resistivity R(f2) of all grid units at the frequency f2. In this way, the alternating current resistivity R(f3) to R(f8) of the grid units corresponding to the frequencies f3 to f N are gradually obtained. Wherein, when the alternating current resistivity inversion is implemented, the objective function is set as

[0038] S(m)=[d-g(m)] T W d [d-g(m)] (2)

[0039] In the formula, g is the theoretical alternating current electric field data matrix, d is the measured alternating current electric field data matrix, m is the model alternating current resistivity matrix, and W d is the weight coefficient matrix. In order to make S(m) converge, the model alternating current resistivity m is modified multiple times during inversion, and the modification relationship is

[0040] (J T W d J+λI)Δm=J T W d [d-g(m)] (3)

[0041] In the formula, J is Jacobi matrix, J T is the transpose matrix of J, and λ is damping factor. When S(m) meets the given constraint condition, the inversion is terminated, and the AC resistivity value of all grid cells is obtained.

[0042] (7) Three-dimensional imaging of AC resistivity is performed to obtain the three-dimensional result of AC resistivity, as shown in Figure 3 .

[0043] According to the statistics of sample mean and variance, the resistivity anomaly threshold is determined to be 110 Ω·m, and the value less than the threshold is a low resistivity anomaly area. The water content analysis is performed on the 4 gray bottom interface depth (50 m) section result, as shown in Figure 4 . The low resistivity anomaly area is mainly located in the 0-300 m and 550-950 m sections along the working face, and the latter has more obvious low resistivity anomaly. Since the coal seam in the working face is stable and the tectonic geological conditions are simple, based on the geological data of the nearby mined working face, it is determined that the above two areas contain water, and the 550-950 m section is rich in water, which is the key area for water prevention and control.

[0044] Figure 5 The comparison chart of different drilling water yield and low value area of AC resistivity is given. According to the statistics, there are 22 small-scale anomaly areas and 41 large-scale anomaly areas, which are in a discrete distribution state. According to the drilling exposure, there are 12 small-scale anomaly areas with water yield of 0-5 m 3 / h, 10 with water yield of 5-10 m 3 / h, 13 with water yield of 10-20 m 3 / h, and 28 with water yield of more than 20 m 3 / h in the large-scale anomaly area. It shows that the overall limestone layer in the working face floor is in a water-bearing state, and the heterogeneity is strong. If the water yield greater than 10 m 3 / h is used as the standard to determine the water-rich rock layer, 34 of the 41 drillings are located in the low value area of AC resistivity and on the boundary thereof, and the remaining 7 are located outside the low value area of AC resistivity, but they are relatively close to the boundary of the low value area of AC resistivity, which shows that the accuracy of the detection result is more than 82.93%. In addition, according to the statistics of the drillings with water yield greater than 10 m 3 / h, the average water yield in the 0-300 m low resistance area is 21.78 m 3 / h, and the average water yield in the 550-950 m section is 33.7 m 3 / h.

[0045] The implementation case effect shows the accuracy of detecting the resistivity distribution characteristics, and further verifies the effectiveness and reliability of the method.

[0046] It should be clear that the above only describes the preferred embodiments of the present application and is not intended to limit the present application. Although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or equivalently replace some technical features thereof. Any modification, equivalent replacement, improvement, etc. made within the spirit and principles of the present application shall be included in the protection scope of the present application.

Claims

1. A multi-scale perspective inversion method using a multi-frequency parallel alternating current method for a coal mining face, characterized in that: The following steps are involved: (1) Set the bottom plate of the coal mining face as the detection area and establish a rectangular coordinate system; (2) Setting up an observation system to match the transmitting current with the receiving electric field; the data collected is required to be obtained based on a sector observation method and to implement double-lane interchange measurement to achieve bidirectional coverage of the AC electric field; (3) Sort the N AC electric field data of different frequencies collected at each receiving point from low frequency to high frequency, and number them in sequence as f1, f2, ..., f N , where N ≥ 6 and the frequency range is from a few Hz to several hundred Hz; (4) For AC electric field data of different frequencies, the detection area is divided into cube grids of different scales, with frequencies f1, f2, ..., f N The corresponding grid side lengths are L1, L2, ..., L N , where the grid side lengths corresponding to adjacent frequencies satisfy formula (1); Where 1≤i≤(N-1); (5) Set L1 = n × s, where 1 ≤ n ≤ 3, and s is the distance between adjacent measurement points; recursively calculate L2, ..., L according to formula (1). N , obtain the grid side length corresponding to the AC electric field collected by each frequency excitation; (6) First, perform AC resistivity inversion on the grid corresponding to frequency f1 to obtain the AC resistivity R(f1) of all grid cells at this frequency; then, using R(f1) as the initial model, perform AC resistivity inversion on the AC electric field data corresponding to frequency f2 to obtain the AC resistivity R(f2) of all grid cells at frequency f2; and so on, gradually obtain the AC resistivity R(f3) of all grid cells at frequencies f3 to f4. N The corresponding grid cell AC resistivity R(f3) to R(f N ); When implementing AC resistivity inversion, the objective function is set as S(m)=[d-g(m)] T W d [d-g(m)] (2) Where g is the theoretical AC electric field data matrix, d is the measured AC electric field data matrix, m is the model AC resistivity matrix, and W d is the weight coefficient matrix; in order to make S(m) converge, the model AC resistivity m is modified several times during inversion, and the modified relationship is: (J T W d J+λI)Δm=J T W d [d-g(m)] (3) Where J is the Jacobi matrix, J T is the transposed matrix of J, and λ is the damping factor. When S(m) meets the given constraints, the inversion is terminated and the AC resistivity values ​​of all grid cells are obtained. (7) For R(f1), R(f2), ..., R(f N ) to perform three-dimensional imaging and form N AC resistivity cloud maps; use low-frequency AC resistivity cloud maps to determine large-scale electrical anomalies, and high-frequency AC resistivity cloud maps to determine small-scale electrical anomalies, thereby realizing the identification of geological anomalies of different scales.

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