A multi-physics field data fusion imaging method based on tunnel excavation advance detection

Abstract

The present invention discloses a multi-physical field data fusion imaging method based on tunnel excavation advance detection. First, the respective result maps of seismic reflection wave advance detection, transient electromagnetic advance detection and direct current method advance detection in front of the tunnel are obtained for gridding, and the corresponding values ​​of each small grid on the three maps are determined. Then, the probability statistics are calculated in combination with the set prior judgment conditions and the previously verified seismic-electromagnetic advance detection data to obtain the probability of the presence / absence of geological anomalies corresponding to each prior judgment condition. Finally, the probability of the presence / absence of geological anomalies in each small grid after the three-value fusion is calculated; by judging that the probability of existence in each small grid is greater than the probability of non-existence, the geological anomaly area determined after the fusion of the seismic-electromagnetic three fields is obtained; while avoiding multiple solutions, the method effectively improves the accuracy of advance detection of the comprehensive geophysical method, and provides theoretical support for the subsequent service of geological anomaly identification in front of tunnel excavation and geological safety during tunnel excavation.

Description

Technical Field

[0001] The present invention relates to a multi-physical field data fusion imaging method based on tunnel excavation advance detection, specifically a method for normalizing the data of seismic reflection wave advance detection, transient electromagnetic advance detection and direct current method advance detection during tunnel excavation, fusing and imaging the normalized data of the three fields of seismic and electromagnetic, and then obtaining the imaging conditions of the geological anomaly body development in front of the tunnel, belonging to the field of advance detection technology. Background Art

[0002] Finding out the location and lithological characteristics of geological anomalies ahead of tunnel excavation is a key step to ensure the normal excavation of tunnels, and is crucial to ensuring the safe construction of underground space in my country. The seismic reflection wave advance detection method, the transient electromagnetic advance detection method, and the direct current advance detection method are the three main tunnel advance detection methods. Among them, the seismic reflection wave advance detection method is sensitive to the geological structure ahead of the tunnel, and the transient electromagnetic advance detection method and the direct current advance detection method are sensitive to the geological anomalies ahead of the tunnel.

[0003] However, geophysical methods have multiple solutions, and a single method is difficult to accurately describe the development of geological anomalies in front of the tunnel. Each method has a certain detection accuracy. If a single method is used, the detection accuracy will be low. There are also some results of advance detection by integrating seismic reflection waves, transient electromagnetic advance detection and direct current method, but they are only a way of mutual verification after separate detection, and the fusion and imaging of multiple physical field data have not been realized; therefore, how to construct a multi-physical field data fusion imaging method based on tunnel excavation advance detection, so that it can fuse and image multiple physical field data, and mark the geological anomaly area obtained by integrating multiple physical field data in the imaging, thereby avoiding multiple solutions while enhancing the geological structure perception ability and effectively improving the advance detection accuracy, is the research direction of the present invention. Summary of the invention

[0004] In view of the problems existing in the above-mentioned prior art, the present invention provides a multi-physical field data fusion imaging method based on tunnel excavation advance detection, so that it can fuse multiple physical field data with each other for imaging, and mark the geological anomaly areas obtained by integrating multiple physical field data in the imaging, thereby avoiding multiple solutions while enhancing the geological structure perception ability and effectively improving the accuracy of advance detection.

[0005] In order to achieve the above-mentioned purpose, the technical solution adopted by the present invention is: a multi-physical field data fusion imaging method based on tunnel excavation advance detection, the specific steps are:

[0006] Step 1: Seismic wave advance detection, transient electromagnetic advance detection and direct current advance detection are respectively carried out in the same range ahead of the tunnel excavation, so as to obtain seismic reflection wave advance detection result map, transient electromagnetic advance detection result map and direct current advance detection result map, and the three result maps are respectively meshed, and the horizontal axis and the vertical axis are respectively divided into m×n small grids, and each small grid formed after meshing each result map is respectively recorded as (i, j), where i=1~m, j=1~n;

[0007] Step 2: Assign values ​​to the individual small grids after the seismic reflection wave advance detection result map is divided. The value of the individual small grid is S (i,j) is the average value of all earthquake amplitudes in the grid; find the maximum value of all single small grids S (i,j) max ; The single small grid value obtained by the above subdivision is normalized, and the processed small grid value is A(i,j);

[0008] Step 3: Assign values ​​to the individual small grids after the transient electromagnetic advance detection result map is divided. The value of the individual small grid is R TEM (i, j) is the average value of all transient electromagnetic resistivity values ​​in the grid; the maximum value of all single small grids obtained by segmentation is obtained R TEM (i,j) max ; The single small grid value obtained by the above subdivision is normalized, and the processed small grid value is B(i,j);

[0009] Step 4: Assign values ​​to the individual small grids after the DC electrical advance detection. R DC (i, j) is the average value of all DC resistivity values ​​in the grid; the maximum value of all the individual small grids obtained by segmentation is obtained R DC (i,j) max ; The single small grid value obtained by the above subdivision is normalized, and the processed small grid value is C(i,j);

[0010] Step 5: Set the prior judgment conditions for whether there is an anomaly ahead of the tunnel excavation. The specific settings are as follows: for the seismic reflection wave advance detection data, if A(i,j)≥α, it is considered that there is a geological anomaly, and if A(i,j)<α, it is determined that there is no geological anomaly; for the transient electromagnetic advance detection data, if B(i,j)>β or <γ, it is determined that there is a geological anomaly, and if γ≤B(i,j)≤β, it is determined that there is no geological anomaly; for the direct current method advance detection data, if C(i,j)>β or <γ, it is determined that there is a geological anomaly, and if γ≤C(i,j)≤β, it is determined that there is no geological anomaly;

[0011] Step 6. Calculate the probability statistics based on the previously verified seismo-electromagnetic advance detection data. P(Y) represents the probability of the existence of geological anomalies, and P(-Y) represents the probability of the absence of geological anomalies. The following are calculated: P[A(i,j)≥α|Y], P[A(i,j)<α|Y], P[B(i,j)>β|Y], P[B(i,j)<γ |Y], P[γ≤B(i,j)≤β |Y], P[C(i,j)>β|Y], P[C(i,j)<γ |Y], P[γ≤C(i,j)≤β |Y] and P[A(i,j)≥α|-Y], P[A(i,j)<α|-Y], P[B(i,j)>β|-Y], P[B(i,j)<γ |-Y], P[γ≤B(i,j)≤β |Y] |-Y], P[C(i,j)>β|-Y], P[C(i,j)<γ |-Y], P[γ≤C(i,j)≤β |-Y]; that is, in the historical excavation process, three types of advance detection, seismic and electromagnetic, will be carried out and corresponding result maps will be obtained respectively. Then, after the excavation in the later stage, the previous detection can be verified to see whether there is a real geological anomaly. The data will be subjected to probability statistics. When there is a geological anomaly, the values ​​of A(i,j), B(i,j) and C(i,j) of the three result maps corresponding to the geological anomaly area during the advance detection will be calculated according to the size of the small grid, so as to obtain the A(i,j), B(i,j) and C(i,j) values ​​of each small grid corresponding to the geological anomaly area of ​​the three result maps in each historical geological anomaly area. Similarly, the A(i,j), B(i,j) and C(i,j) values ​​of each small grid corresponding to the geological anomaly area of ​​the three result maps in the advance detection when there is no geological anomaly area can be obtained. Subsequently, each value will be compared with its own judgment threshold to obtain the corresponding geological anomaly probability and the probability of no geological anomaly. Taking A(i,j) as an example,

[0012] Step 7. Assuming that there is no connection between the seismic reflection wave advance detection results, transient electromagnetic advance detection results and direct current advance detection results, calculate the probability statistics of geological anomalies in each small grid (i,j): P[Y| A(i,j),B(i,j),C(i,j)] = P(Y)·P[A(i,j)|Y]·P[B(i,j)|Y]·P[C(i,j)|Y], where P[A(i,j)|Y] = P[A(i,j)≥α|Y], P[B(i,j)|Y] = P[B(i,j)>β|Y] + P[B(i,j)<γ|Y], and P[C(i,j)|Y] = P[C(i,j)>β|Y] + P[C(i,j)<γ |Y]; Probability statistics when there is no geological anomaly P[-Y|A(i,j),B(i,j),C(i,j)]= P(-Y)·P[A(i,j)|-Y]·P[B(i,j)|-Y]·P[C(i,j)|-Y], where P[A(i,j)|-Y]= P[A(i,j)<α|-Y], P[B(i,j)|-Y]= P[γ≤B(i,j)≤β|-Y], P[C(i,j)|-Y]= P[γ≤C(i,j)≤β|-Y];

[0013] If P[Y| A(i,j), B(i,j), C(i,j)]>P[-Y|A(i,j), B(i,j), C(i,j)] of a small grid, it is determined that there is a geological anomaly in the small grid and it is marked; if P[Y|A(i,j), B(i,j), C(i,j)]≤P[-Y|A(i,j), B(i,j), C(i,j)] of a small grid, it is determined that there is no geological anomaly in the small grid; after all the small grids are biased, the area covered by the small grid that is finally marked is the geological anomaly area determined after the fusion of the seismic and electromagnetic fields.

[0014] Furthermore, the calculation formula of A(i,j) is: A(i,j)= S (i,j) / S (i,j) max ; The calculation formula of B(i,j) is: B(i,j)= R TEM (i,j) / R TEM (i,j) max ; The calculation formula of C(i,j) is: C(i,j)= R DC (i,j) / R DC (i,j) max .

[0015] Furthermore, in step 5, α is 0.8, β is 0.9, and γ is 0.1. The above parameter values ​​can be used or optimized and adjusted according to the specific geological conditions on site to meet the required detection requirements.

[0016] Furthermore, in step 7, each small grid is initially filled with white, and if a small grid is marked, the small grid is filled with red. This method facilitates direct observation of geological abnormal areas after fusion imaging.

[0017] Compared with the prior art, the present invention first obtains the seismic reflection wave advance detection result map, transient electromagnetic advance detection result map and direct current method advance detection result map in front of the tunnel, and then performs gridding, and determines the A(i,j), B(i,j) and C(i,j) values ​​of each small grid through normalized data processing, then sets the prior judgment conditions, and calculates the probability statistics based on the previously verified seismic electromagnetic advance detection data, so as to obtain the probability of the existence of geological anomalies and the probability of the absence of geological anomalies corresponding to each prior judgment condition, and finally calculates the probability of the existence of geological anomalies after the fusion of the A(i,j), B(i,j) and C(i,j) values ​​of each small grid. , and the probability of no geological anomaly; if the probability of the existence of geological anomaly in any small grid is greater than the probability of no geological anomaly, the grid will be marked, and after processing all small grids, the geological anomaly area determined after the fusion of seismic, electromagnetic and three fields is obtained; this method realizes the imaging perception of the geological anomaly body ahead of tunnel excavation by fusing seismic, electromagnetic and three-field data, and marks the geological anomaly area obtained by integrating multiple physical field data in the imaging, thereby avoiding multiple solutions while enhancing the geological structure perception ability, effectively improving the accuracy of advanced detection of the comprehensive geophysical method, and providing theoretical support for the subsequent service of geological anomaly identification ahead of tunnel excavation and geological safety during tunnel excavation. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 It is a schematic diagram of meshing the result graph in the present invention;

[0019] Figure 2 It is a schematic diagram of the fusion of the three seismic and electromagnetic fields in the present invention. DETAILED DESCRIPTION

[0020] The present invention will be further described below.

[0021] Embodiment: The specific steps of the present invention are:

[0022] Step 1: Seismic wave advance detection, transient electromagnetic advance detection and direct current method advance detection are respectively carried out in the same range ahead of tunnel excavation, so as to obtain seismic reflection wave advance detection result map, transient electromagnetic advance detection result map and direct current method advance detection result map. The three result maps are respectively meshed, and the horizontal and vertical axes are respectively divided into the same number of m×n small grids, such as Figure 1 As shown in the figure, each small grid formed after gridding each result map is recorded as (i, j), where i=1~m, j=1~n;

[0023] Step 2: Assign values ​​to the individual small grids after the seismic reflection wave advance detection result map is divided. The value of the individual small grid is S (i,j) is the average value of all earthquake amplitudes in the grid; find the maximum value of all single small grids S (i,j) max ; The single small grid value obtained by the above subdivision is normalized, and the processed small grid value is A(i,j), A(i,j)= S (i,j) / S (i,j) max ;

[0024] Step 3: Assign values ​​to the individual small grids after the transient electromagnetic advance detection result map is divided. The value of the individual small grid is R TEM (i, j) is the average value of all transient electromagnetic resistivity values ​​in the grid; the maximum value of all single small grids obtained by segmentation is obtained R TEM (i,j) max ; The single small grid value obtained by the above subdivision is normalized, and the processed small grid value is B(i,j), B(i,j)= R TEM (i,j) / R TEM (i,j) max ;

[0025] Step 4: Assign values ​​to the individual small grids after the DC electrical advance detection. R DC (i, j) is the average value of all DC resistivity values ​​in the grid; the maximum value of all the individual small grids obtained by segmentation is obtained R DC (i,j) max ; The single small grid value obtained by the above subdivision is normalized, and the processed small grid value is C(i,j), C(i,j)= R DC (i,j) / RDC (i,j) max ;

[0026] Step 5: Set the prior judgment conditions for whether there is an anomaly ahead of the tunnel excavation. The specific settings are as follows: for the seismic reflection wave advance detection data, if A(i,j)≥0.8, it is considered that there is a geological anomaly. If A(i,j) is less than 0.8, it is determined that there is no geological anomaly; for the transient electromagnetic advance detection data, if B(i,j)>0.9 or less than 0.1, it is determined that there is a geological anomaly. If 0.1≤B(i,j)≤0.9, it is determined that there is no geological anomaly; for the direct current method advance detection data, if C(i,j)>0.9 or less than 0.1, it is determined that there is a geological anomaly. If 0.1≤C(i,j)≤0.9, it is determined that there is no geological anomaly;

[0027] Step 6. Calculate the probability statistics based on the previously verified seismo-electromagnetic advance detection data. P(Y) represents the probability of the existence of geological anomalies, and P(-Y) represents the probability of the absence of geological anomalies. The following are calculated: P[A(i,j)≥0.8|Y], P[A(i,j)<0.8 |Y], P[B(i,j)>0.9|Y], P[B(i,j)<0.1 |Y], P[0.1≤B(i,j)≤0.9 |Y], P[C(i,j)>0.9|Y], P[C(i,j)<0.1 |Y], P[0.1≤C(i,j)≤0.9 |Y] and P[A(i,j)≥0.8|-Y], P[A(i,j)<0.8|-Y], P[B(i,j)>0.9|-Y], P[B(i,j)<0.1 |-Y], P[0.1≤B(i,j)≤0.9 |-Y], P[C(i,j)>0.9|-Y], P[C(i,j)<0.1 |-Y], P[0.1≤C(i,j)≤0.9 |-Y]; that is, in the historical excavation process, three types of advance detections will be carried out by seismic and electromagnetic and the corresponding result maps will be obtained respectively. Then, after the excavation in the later stage, the previous detection can be verified to see whether there is a real geological anomaly. These data will be subjected to probability statistics. When there is a geological anomaly, the values ​​of A(i,j), B(i,j) and C(i,j) of the three result maps corresponding to the position of the geological anomaly area in the advance detection will be calculated according to the size of the small grid. Thus, the values ​​of A(i,j), B(i,j) and C(i,j) of each small grid in the three result maps corresponding to the position of the geological anomaly area in each historical geological anomaly area can be obtained. Similarly, the values ​​of A(i,j), B(i,j) and C(i,j) of the three result maps corresponding to the position of the geological anomaly area in the historical geological anomaly area can be obtained. The three types of advance detection results maps of normal areas correspond to the A(i,j), B(i,j) and C(i,j) values ​​of each small grid in the location of the geological anomaly area. Subsequently, each value is compared with its own judgment threshold to obtain the corresponding geological anomaly probability and the probability of no geological anomaly. Taking A(i,j) as an example, all A(i,j) values ​​in the geological anomaly area are compared with the threshold of 0.8, and the proportion of A(i,j) values ​​≥0.8 to the total number is counted, that is, P[A(i,j)≥0.8|Y], the probability of the existence of geological anomalies. Similarly, the probability of the existence of other geological anomalies and the probability of no geological anomalies can be calculated;

[0028] Step 7. Assuming that there is no connection between the seismic reflection wave advance detection results, transient electromagnetic advance detection results and direct current advance detection results, calculate the probability statistics of geological anomalies in each small grid (i,j): P[Y| A(i,j),B(i,j),C(i,j)] = P(Y)·P[A(i,j)|Y]·P[B(i,j)|Y]·P[C(i,j)|Y], where P[A(i,j)|Y] = P[A(i,j)≥0.8|Y], P[B(i,j)|Y] = P[B(i,j)> 0.9|Y]+ P[B(i,j)<0.1Y], and P[C(i,j)|Y] = P[C(i,j)> 0.9|Y]+ P[C(i,j)<0.1 |Y]; Probability statistics when there is no geological anomaly P[-Y|A(i,j),B(i,j),C(i,j)]= P(-Y)·P[A(i,j)|-Y]·P[B(i,j)|-Y]·P[C(i,j)|-Y], where P[A(i,j)|-Y]= P[A(i,j)<0.8|-Y], P[B(i,j)|-Y]= P[0.1≤B(i,j)≤0.9 |-Y], P[C(i,j)|-Y]=P[0.1≤C(i,j)≤0.9 |-Y];

[0029] Initially, each small grid is filled with white. If P[Y| A(i,j), B(i,j), C(i,j)]>P[-Y|A(i,j), B(i,j), C(i,j)] of a small grid, it is determined that there is a geological anomaly in the small grid and it is filled with red. If P[Y|A(i,j), B(i,j), C(i,j)]≤P[-Y|A(i,j), B(i,j), C(i,j)] of a small grid, it is determined that there is no geological anomaly in the small grid. After all the small grids are biased, if Figure 2 As shown, the final red coverage area is the geological anomaly area determined after the fusion of seismic and electromagnetic fields.

[0030] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principle of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A multi-physics field data fusion imaging method based on tunnel excavation advance detection, characterized in that: The specific steps are: Step 1: Seismic wave advance detection, transient electromagnetic advance detection and direct current advance detection are respectively carried out in the same range ahead of the tunnel excavation, so as to obtain seismic reflection wave advance detection result map, transient electromagnetic advance detection result map and direct current advance detection result map, and the three result maps are respectively meshed, and the horizontal axis and the vertical axis are respectively divided into m×n small grids, and each small grid formed after meshing each result map is respectively recorded as (i, j), where i=1~m, j=1~n; Step 2: Assign values ​​to the individual small grids after the seismic reflection wave advance detection result map is divided. The value of the individual small grid is S (i,j) is the average value of all earthquake amplitudes in the grid; find the maximum value of all single small grids S (i,j) max ; The single small grid value obtained by the above subdivision is normalized, and the processed small grid value is A(i,j); Step 3: Assign values ​​to the individual small grids after the transient electromagnetic advance detection result map is divided. The value of the individual small grid is R TEM (i, j) is the average value of all transient electromagnetic resistivity values ​​in the grid; the maximum value of all single small grids obtained by segmentation is obtained R TEM (i,j) max ; The single small grid value obtained by the above subdivision is normalized, and the processed small grid value is B(i,j); Step 4: Assign values ​​to the individual small grids after the DC electrical advance detection. R DC (i, j) is the average value of all DC resistivity values ​​in the grid; the maximum value of all the individual small grids obtained by segmentation is obtained R DC (i,j) max ; The single small grid value obtained by the above subdivision is normalized, and the processed small grid value is C(i,j); Step 5: Set the prior judgment conditions for whether there is an anomaly ahead of the tunnel excavation. The specific settings are as follows: for the seismic reflection wave advance detection data, if A(i,j)≥α, it is considered that there is a geological anomaly, and if A(i,j)<α, it is determined that there is no geological anomaly; for the transient electromagnetic advance detection data, if B(i,j)>β or <γ, it is determined that there is a geological anomaly, and if γ≤B(i,j)≤β, it is determined that there is no geological anomaly; for the direct current method advance detection data, if C(i,j)>β or <γ, it is determined that there is a geological anomaly, and if γ≤C(i,j)≤β, it is determined that there is no geological anomaly; Step 6. Calculate the probability statistics based on the previously verified seismo-electromagnetic advance detection data. P(Y) represents the probability of the existence of geological anomalies, and P(-Y) represents the probability of the absence of geological anomalies. The following are calculated: P[A(i,j)≥α|Y], P[A(i,j)<α|Y], P[B(i,j)> β|Y], P[B(i,j)<γ |Y], P[γ≤B(i,j)≤β |Y], P[C(i,j)> β|Y], P[C(i,j)<γ |Y], P[γ≤C(i,j)≤β |Y] and P[A(i,j)≥α|-Y], P[A(i,j)<α|-Y], P[B(i,j)> β|-Y], P[B(i,j)<γ |-Y], P[γ≤B(i,j)≤β |Y] |-Y], P[C(i,j)> β|-Y], P[C(i,j)<γ |-Y], P[γ≤C(i,j)≤β|-Y]; Step 7. Assuming that there is no connection between the seismic reflection wave advance detection results, transient electromagnetic advance detection results and direct current advance detection results, calculate the probability statistics of geological anomalies in each small grid (i,j): P[Y| A(i,j),B(i,j),C(i,j)] = P(Y)·P[A(i,j)|Y]·P[B(i,j)|Y]·P[C(i,j)|Y], where P[A(i,j)|Y] = P[A(i,j)≥α|Y], P[B(i,j)|Y] = P[B(i,j)> β|Y] + P[B(i,j)<γ |Y], P[C(i,j)|Y] = P[C(i,j)> β|Y] + P[C(i,j)<γ |Y]; Probability statistics when there is no geological anomaly P[-Y|A(i,j),B(i,j),C(i,j)]= P(-Y)·P[A(i,j)|-Y]·P[B(i,j)|-Y]·P[C(i,j)|-Y], where P[A(i,j)|-Y]= P[A(i,j)<α|-Y], P[B(i,j)|-Y]= P[γ≤B(i,j)≤β|-Y], P[C(i,j)|-Y]= P[γ≤C(i,j)≤β|-Y]; If P[Y| A(i,j), B(i,j), C(i,j)]>P[-Y|A(i,j), B(i,j), C(i,j)] of a small grid, it is determined that there is a geological anomaly in the small grid and it is marked; if P[Y|A(i,j), B(i,j), C(i,j)]≤P[-Y|A(i,j), B(i,j), C(i,j)] of a small grid, it is determined that there is no geological anomaly in the small grid; after all the small grids are biased, the area covered by the small grid that is finally marked is the geological anomaly area determined after the fusion of the seismic and electromagnetic fields.

2. The multi-physics field data fusion imaging method based on tunneling advance detection according to claim 1 is characterized in that: The calculation formula of A(i,j) is: A(i,j)= S (i,j) / S (i,j) max ; The calculation formula of B(i,j) is: B(i,j)= R TEM (i,j) / R TEM (i,j) max ; The calculation formula of C(i,j) is: C(i,j)= R DC (i,j) / R DC (i,j) max .

3. The multi-physics field data fusion imaging method based on tunneling advance detection according to claim 1 is characterized in that: In the step 5, α is 0.8, β is 0.9, and γ is 0.

1.

4. The multi-physics field data fusion imaging method based on tunneling advance detection according to claim 1 is characterized in that: In step seven, each small grid is initially filled with white, and if a small grid is marked, the small grid is filled with red.

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