A method and system for guiding rapid excavation of a rock roadway of a coal mine by using three-dimensional seismic

Abstract

The application discloses a method and system for guiding rapid excavation of a coal mine rock roadway by using three-dimensional seismic data, and comprises the following steps: constraining by using well and roadway data, establishing a well and roadway constrained velocity model, performing pre-stack depth migration processing according to the well and roadway constrained velocity model to obtain depth domain data of the pre-stack depth migration processing; cross-plotting analysis is performed on the well logging curve, each lithology is calibrated, and the value threshold of each calibrated lithology is determined; the depth domain data of the pre-stack depth migration processing is subjected to well logging constrained depth domain wave impedance inversion to obtain a depth domain wave impedance inversion profile of the roadway, and the lithology of the roadway is interpreted by taking each calibrated lithology and the corresponding value threshold as a reference; the depth domain wave impedance inversion profile of the roadway is converted into a seismic and geological profile according to the value threshold of each calibrated lithology, and a roadway geological profile is drawn according to the depth domain wave impedance inversion profile of the roadway to guide the rapid excavation of the coal mine rock roadway. The application reduces the number of drilling in the excavation and improves the roadway excavation efficiency.

Description

Technical Field

[0001] This invention relates to the field of three-dimensional seismic data processing technology, specifically to a method and system for rapid tunneling in coal mine rock tunnels guided by three-dimensional seismic data. Background Technology

[0002] Currently, the design of coal mine roadways is mainly based on the undulation and structural development of the main coal seam interpreted by 3D seismic analysis, combined with the geological and hydrological characteristics of the mine field. Among these, the undulation and structural development of the main coal seam interpreted by 3D seismic analysis is still largely based on seismic data processed by pre-stack time migration.

[0003] In the construction of rock tunnels, drilling is often used for advance exploration. With the continuous improvement of mechanization and digitalization in coal mines, many mines have introduced tunnel boring machines (TBMs) for drilling. TBMs have a fast excavation speed, but the cutting blades need to be adjusted according to different rock types; otherwise, the progress will be affected, and the cutting blades are easily damaged. The adjustable slope of the TBM is also relatively small, so adjustments must be made with high precision. The existing rock tunnel design and drilling methods have the following drawbacks:

[0004] (1) The seismic data used is mostly pre-stack time migration processed seismic data, which is not accurate enough in interpreting the fault location and the undulation of coal seams.

[0005] (2) The interpretation results of seismic data based on pre-stack time migration processing need to be converted from time to depth in order to be converted into reference data for mine roadway design.

[0006] (3) The interpretation results of the main coal seam are referenced. There are no more direct results for the target layer that needs to be tunneled (generally a relatively stable sandstone / mudstone layer), and there is also a lack of data on the lithological changes of the target layer.

[0007] (4) Numerous inaccuracies require continuous advance drilling during tunnel excavation, which leads to easy damage to the shield machine's cutting blade. In addition, continuous advance drilling affects the construction progress, resulting in high construction costs, tight tunnel connection, and also increases the risk of abandoned tunnels. Summary of the Invention

[0008] To overcome the shortcomings of existing technologies, this invention provides a method and system for rapid tunneling in coal mine rock tunnels guided by three-dimensional seismic data. This method addresses technical problems in existing technologies, such as inaccurate interpretation, the need for time-to-depth conversion, lack of data on lithological variations, and the need for continuous drilling. The goal is to reduce the number of drilling operations, improve tunneling efficiency, reduce the risk of cutting tool damage, and avoid the risk of abandoned tunnels.

[0009] To solve the above problems, the technical solution adopted by the present invention is as follows:

[0010] A method for rapid tunneling in coal mine rock tunnels guided by 3D seismic data includes the following steps:

[0011] Using tunnel data as constraints, a tunnel constraint velocity model is established. Based on the tunnel constraint velocity model, pre-stack depth migration processing is performed to obtain pre-stack depth migration processed depth domain data.

[0012] Cross-plot analysis was performed on the logging curves to calibrate each lithology and determine the threshold values ​​for each calibrated lithology.

[0013] The depth domain data from the pre-stack depth migration processing is subjected to logging-constrained depth domain acoustic impedance inversion to obtain the depth domain acoustic impedance inversion profile of the tunnel.

[0014] Based on the depth domain impedance inversion profile of the tunnel, and with reference to each calibrated lithology and its corresponding threshold value, the lithology of the tunnel is interpreted.

[0015] Based on the threshold values ​​of each calibrated lithology, the depth domain impedance inversion profile of the tunnel is converted into a seismic geological profile, and the tunnel geological profile is drawn based on the depth domain impedance inversion profile of the tunnel.

[0016] Combining the interpretation of roadway lithology, the aforementioned seismic geological profile, and the aforementioned roadway geological profile, we can guide the rapid excavation of rock roadways in coal mines.

[0017] As a preferred embodiment of the present invention, when using tunnel data for constraint, the method includes:

[0018] The elevation information of the target layer seen in the boreholes and tunnels is extracted from the shaft and tunnel data, and the (X,Y,Z) information of each borehole and each tunnel observation point is extracted from the elevation information.

[0019] The (X,Y,Z) information of each borehole and each tunnel observation point is used for constrained velocity modeling.

[0020] In a preferred embodiment of the present invention, when using the (X,Y,Z) information of each point for constrained velocity modeling, the following is included:

[0021] The depth information of each point is obtained from the (X,Y,Z) information of each borehole and each tunnel observation point;

[0022] Based on the tunnel data, pre-stack time migration processing is performed to obtain a pre-stack time migration profile, and the two-way travel time is read from the pre-stack time migration profile;

[0023] The depth information of each point and the two-way travel time are used to constrain the velocity model, as shown in Formula 1:

[0024] S = 1 / 2 * C * V (1);

[0025] In the formula, S represents the depth information of each point, C represents the two-way travel time, and V represents the speed.

[0026] In a preferred embodiment of the present invention, the pre-stack depth migration processing based on the tunnel constraint velocity model includes:

[0027] Kirchoff integration method is used for Kirchoff pre-stack depth migration, as shown in Equation 2:

[0028]

[0029] In the formula, ∑ represents the observation line, and C D C, C H σ represents the spatial location of the source point, imaging point, and receiver point. D σ H For the travel time from the source to the imaging point and from the imaging point to the receiver, B is the geometric diffusion factor, m is the outward normal direction of the observation surface, ν is the recorded wave field, and T is the reflection coefficient.

[0030] In a preferred embodiment of the present invention, when performing pre-stack depth migration processing based on the tunnel constraint velocity model, the method further includes:

[0031] After dividing the seismic signal frequency in the tunnel data into multiple narrow frequency bands using the reflectance spectral imaging method, Kirchhoff pre-stack depth migration processing is performed on each narrow frequency band.

[0032] In a preferred embodiment of the present invention, determining the threshold values ​​for each calibrated lithology includes:

[0033] Determine the density threshold, acoustic threshold, and wave impedance threshold for each of the calibrated lithologies.

[0034] As a preferred embodiment of the present invention, the process of performing well logging-constrained depth domain acoustic impedance inversion includes:

[0035] The depth domain data processed by the pre-stack depth migration is used to pick up the stratigraphic data, and the determined target stratigraphic layer is checked, corrected, interpolated and smoothed to obtain more effective stratigraphic data.

[0036] Based on the tunnel data, the depth-domain acoustic curve and density curve are obtained;

[0037] Based on the depth domain data from the pre-stack depth migration processing and the more effective stratigraphic data, the acoustic and density curves of the depth domain are used to generate the wave impedance curves of the depth domain in the well, and seismic wavelets are extracted from the seismic traces near the well to form a synthetic seismic record of the depth domain.

[0038] An initial wave impedance model is generated based on the more effective stratigraphic data and the wave impedance curve in the depth domain.

[0039] The depth domain data and the seismic wavelet processed by the pre-stack depth migration process are normalized to obtain the normalized depth domain data and the normalized seismic wavelet processed by the pre-stack depth migration process.

[0040] The reflection coefficient sequence is obtained by inversion based on the normalized pre-stack depth migration data, the normalized seismic wavelet, and the initial wave impedance model.

[0041] The reflection coefficient sequence is converted into a wave impedance sequence to obtain the wave impedance inversion result. Based on the wave impedance inversion result, the depth domain wave impedance inversion profile of the tunnel is obtained.

[0042] In a preferred embodiment of the present invention, the process of obtaining the reflection coefficient sequence through inversion includes:

[0043] The inversion is performed based on the relative wave impedance value at the sampling point, the wavelet convolution matrix, and the initial wave impedance model constraint factor, as shown in Equation 3:

[0044] d=(H T H+ωW mm +τV T V) -1 (H T f+τV T ψ m (3);

[0045] In the formula, f = [f1, f2, ..., f N ] T This is depth-domain seismic data processed by pre-stack depth migration; N is the total number of sampling points in the depth-domain seismic data; d = [d1, d2, ..., d N ] T is the reflection coefficient sequence; H is an N×N dimensional wavelet convolution matrix, with the superscript T representing the matrix transpose; ω is the sparsity constraint factor, used to control the sparsity of the reflection coefficients; τ is the initial wave impedance model constraint factor, used to control the dependence of the inversion results on the initial wave impedance model; V is the integral operator matrix; the diagonal elements of matrix W are: W mmLet ρ represent the value of the element in the m-th row and m-th column of matrix W, where m is the row and column index of matrix W. All elements of matrix W except for the diagonal elements are zero. r E represents the standard deviation of the noise. m It is the initial reflection coefficient at the location of the m-th sampling point, calculated from the initial wave impedance model; Z is the relative wave impedance value at the m-th sampling point, and Z0 is the initial wave impedance value corresponding to the first sampling point within the inversion time window. m The wave impedance value at the m-th sampling point within the inversion window, d i Let ln be the reflection coefficient value at the i-th sampling point within the inversion window, and ln be the sign of the natural logarithm. This is a summation operation for m sampling points.

[0046] In a preferred embodiment of the present invention, converting the reflection coefficient sequence into a wave impedance sequence includes:

[0047] Based on the initial wave impedance value corresponding to the first sampling point within the inversion time window and the reflection coefficient value of the sampling point, the wave impedance value of the sampling point is obtained, as shown in formula (4):

[0048]

[0049] In the formula, Z m Zm is the wave impedance value at the m-th sampling point within the inversion window, Z0 is the initial wave impedance value corresponding to the first sampling point within the inversion window, and dm is the initial wave impedance value. i Let be the reflection coefficient value at the i-th sampling point within the inversion window, and let e represent the base of the natural logarithm. This is a summation operation for m sampling points.

[0050] A system for rapid tunneling in coal mine rock tunnels guided by 3D seismic data includes:

[0051] Migration processing module: Used to constrain tunnel data, establish a fine velocity model, and perform pre-stack depth migration processing based on the velocity model to obtain pre-stack depth migration processed depth domain data;

[0052] Cross-plot analysis module: used to perform cross-plot analysis on well logging curves, calibrate various lithologies, and determine the threshold values ​​for each calibrated lithology;

[0053] Wave impedance inversion module: used to perform well logging-constrained depth domain wave impedance inversion on the depth domain data of the pre-stack depth migration processing to obtain the depth domain wave impedance inversion profile of the tunnel.

[0054] Results Acquisition Unit: Used to interpret the lithology of the tunnel based on the depth domain impedance inversion profile of the tunnel, with reference to each calibrated lithology and its corresponding threshold value; convert the depth domain impedance inversion profile of the tunnel into a seismic geological profile based on the threshold value of each calibrated lithology; and draw the tunnel geological profile based on the depth domain impedance inversion profile of the tunnel.

[0055] Analysis unit: Used to combine roadway lithology interpretation, the seismic geological profile, and the roadway geological profile to guide the rapid excavation of coal mine rock roadways.

[0056] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0057] (1) The method provided by this invention provides a basis for the formulation of a precise tunneling scheme for coal mine roadways and for the adjustment of the scheme during the tunneling process;

[0058] (2) The method provided by the present invention reduces the number of drilling operations during tunneling, improves the tunneling efficiency, reduces the frequency of construction plan adjustments, saves labor costs, reduces the risk of blade damage, and avoids the risk of abandoned tunnels.

[0059] The present invention will now be described in further detail with reference to the accompanying drawings and specific embodiments. Attached Figure Description

[0060] Figure 1 - This is a distribution diagram of the actual observation points of each borehole and each tunnel in an embodiment of the present invention;

[0061] Figure 2 - is a cross-sectional view of a certain area in an embodiment of the present invention;

[0062] Figure 3 - is a velocity profile of a certain region according to an embodiment of the present invention;

[0063] Figure 4 - This is a comparison diagram of the pre-stack depth migration seismic profile and the pre-stack time migration profile for tunnel constraint velocity modeling in an embodiment of the present invention;

[0064] Figure 5 - This is a schematic diagram of the cross-analysis of various lithological threshold values ​​in an embodiment of the present invention;

[0065] Figure 6 - is a pre-stack depth migration depth domain seismic profile of an embodiment of the present invention;

[0066] Figure 7 - is a depth-domain wave impedance inversion profile of a tunnel according to an embodiment of the present invention;

[0067] Figure 8 - is a seismic geological profile diagram according to an embodiment of the present invention;

[0068] Figure 9 - This is a step diagram illustrating the method for rapid tunneling in coal mine rock tunnels guided by three-dimensional seismic data, according to an embodiment of the present invention. Detailed Implementation

[0069] The method for rapid tunneling in coal mine rock tunnels guided by three-dimensional seismic data provided in this invention, such as... Figure 9 As shown, it includes the following steps:

[0070] Step S1: Use tunnel data for constraints, establish a tunnel constraint velocity model, and perform pre-stack depth migration processing based on the tunnel constraint velocity model to obtain the depth domain data processed by pre-stack depth migration.

[0071] Step S2: Perform cross-plot analysis on the logging curves, calibrate each lithology, and determine the threshold values ​​for each calibrated lithology;

[0072] Step S3: Perform logging-constrained depth domain acoustic impedance inversion on the depth domain data processed by pre-stack depth migration to obtain the depth domain acoustic impedance inversion profile of the tunnel.

[0073] Step S4: Based on the depth domain impedance inversion profile of the tunnel, and with reference to each calibrated lithology and its corresponding threshold value, interpret the lithology of the tunnel.

[0074] Step S5: Convert the depth domain impedance inversion profile of the tunnel into a seismic geological profile based on the threshold values ​​of each calibrated lithology, and draw the tunnel geological profile based on the depth domain impedance profile of the tunnel.

[0075] Step S6: Combining roadway lithology interpretation, seismic geological profiles, and roadway geological profiles to guide the rapid excavation of coal mine rock roadways.

[0076] In step S1 above, when using tunnel data for constraints, the following is included:

[0077] The elevation information of the target layer seen in boreholes and tunnels is extracted from the well and tunnel data, and the (X,Y,Z) information of each borehole and tunnel observation point is extracted from the elevation information.

[0078] The (X,Y,Z) information of each borehole and each tunnel observation point is used for constrained velocity modeling.

[0079] Specifically, based on the (X,Y,Z) information of the actual observation points of each borehole and each roadway, a distribution map of the actual observation points of each borehole and each roadway can be obtained. The (X,Y,Z) information of the actual observation points of each borehole and each roadway is used for constrained velocity modeling to establish a constrained velocity model for a shaft roadway, thereby improving the accuracy of the velocity model and further improving the precision of the offset profile. Figure 2 This is a cross-sectional location map of a certain area, by Figure 2It can be seen that there is a shallow paleo-uplift in this area, causing the low-velocity zone to thin. By constraining the data from the shafts and tunnels, a velocity model that matches the actual situation can be established, resulting in a more accurate velocity profile. Figure 3 As shown. By using this velocity model for pre-stack depth migration, the occurrence morphology of the target coal seam can be made more accurate. Figure 4 This is a comparison image of pre-stack depth-migrating seismic profiles and pre-stack time-migrating profiles for tunnel constrained velocity modeling. Figure 4 It can be seen that the elevation of coal seam 13 in borehole A1 is -688.52m, and in borehole A2 it is -750.01m. Due to the influence of low-velocity zone changes, the reflected wave of coal seam 13 in the pre-stack time migration profile also shows a false uplift, which does not match the actual borehole findings. However, pre-stack depth migration, using a refined velocity model constrained by the tunnel, allows for more accurate migration and repositioning of the target coal seam, improving the imaging accuracy of the seismic profile, and ensuring that the undulation morphology of the target coal seam is consistent with the actual borehole findings.

[0080] Furthermore, when using the (X,Y,Z) information of each point for constrained velocity modeling, this includes:

[0081] The depth information of each point is obtained from the (X,Y,Z) information of each borehole and each tunnel.

[0082] Pre-stack time migration processing is performed on the tunnel data to obtain the pre-stack time migration profile, and the two-way travel time is read from the pre-stack time migration profile.

[0083] The depth information and two-way travel time at each point are used to constrain the velocity model, as shown in Formula 1:

[0084] S = 1 / 2 * C * V (1);

[0085] In the formula, S represents the depth information of each point, C represents the two-way travel time, and V represents the speed.

[0086] In step S1 above, the pre-stack depth migration process based on the tunnel constraint velocity model includes:

[0087] Kirchoff integration method is used for Kirchoff pre-stack depth migration, as shown in Equation 2:

[0088]

[0089] In the formula, ∑ represents the observation line, and C D C, C H σ represents the spatial location of the source point, imaging point, and receiver point. D σ H For the travel time from the source to the imaging point and from the imaging point to the receiver, B is the geometric diffusion factor, m is the outward normal direction of the observation surface, ν is the recorded wave field, and T is the reflection coefficient.

[0090] Furthermore, when performing pre-stack depth migration processing based on the tunnel constraint velocity model, the following steps are also included:

[0091] After dividing the seismic signal frequency in the tunnel data into multiple narrow frequency bands using the reflectance spectral imaging method, Kirchhoff pre-stack depth migration processing is performed on each narrow frequency band separately.

[0092] In step S2 above, determining the threshold values ​​for each calibrated lithology includes:

[0093] Determine the density threshold, acoustic threshold, and wave impedance threshold for each calibrated lithology.

[0094] Specifically, cross-plot analysis is performed on the well logging curves to determine the threshold values ​​for each lithology, such as... Figure 5 As shown in the figure. Cross-plot analysis reveals that the density of coal and rock in this area is generally between 1.2 and 1.8 g / cm³. 3 The velocity of sound waves is between 1600 and 2600 m / s; the density of mudstone is generally between 1.8 and 2.4 g / cm³. 3 The velocity of sound waves is between 2000 and 3800 m / s; the density of siltstone is generally between 2.4 and 2.52 g / cm³. 3 The velocity of sound waves is between 2500 and 4000 m / s; the density of sandstone is generally between 2.5 and 2.9 g / cm³. 3 The speed of sound waves is between 3200 and 6500 m / s.

[0095] In step S3 above, when performing well logging-constrained depth domain acoustic impedance inversion, the following steps are included:

[0096] Stratigraphic data is obtained by picking the depth domain data processed by pre-stack depth migration, and the determined target layer is verified, corrected, interpolated and smoothed to obtain more effective stratigraphic data.

[0097] Based on the tunnel data, the acoustic transit time curve and density curve in the depth domain were obtained;

[0098] Based on the depth domain data processed by pre-stack depth migration and more effective stratigraphic data, the acoustic and density curves in the depth domain are used to generate the wave impedance curves in the depth domain of the well, and seismic wavelets are extracted from the seismic traces near the well to form a synthetic seismic record in the depth domain.

[0099] An initial wave impedance model is generated based on more effective stratigraphic data and the wave impedance curves in the depth domain.

[0100] The depth domain data and seismic wavelet processed by pre-stack depth migration are normalized to obtain normalized pre-stack depth domain data and normalized seismic wavelet.

[0101] The reflection coefficient sequence is obtained by inversion based on the depth domain data processed by the normalized pre-stack depth migration, the normalized seismic wavelet, and the initial wave impedance model.

[0102] The reflection coefficient sequence is converted into a wave impedance sequence to obtain the wave impedance inversion result. Based on the wave impedance inversion result, the depth domain wave impedance inversion profile of the tunnel is obtained.

[0103] Specifically, the depth-domain data processed by pre-stack depth migration includes pre-stack depth-domain seismic profiles, such as... Figure 6 As shown, well-logging-constrained depth-domain acoustic impedance inversion is performed on the pre-stack depth-migrated depth-domain seismic profile to obtain the depth-domain acoustic impedance inversion profile through the tunnel, as shown in the figure. Figure 7 As shown.

[0104] Furthermore, when performing the inversion to obtain the reflection coefficient sequence, the following steps are included:

[0105] The inversion is performed based on the relative wave impedance value at the sampling point, the wavelet convolution matrix, and the initial wave impedance model constraint factor, as shown in Equation 3:

[0106] d=(H T H+ωW mm +τV T V) -1 (H T f+τV T ψ m (3);

[0107] In the formula, f = [f1, f2, ..., f N ] T This is depth-domain seismic data processed by pre-stack depth migration; N is the total number of sampling points in the depth-domain seismic data; d = [d1, d2, ..., d N ] T is the reflection coefficient sequence; H is an N×N dimensional wavelet convolution matrix, with the superscript T representing the matrix transpose; ω is the sparsity constraint factor, used to control the sparsity of the reflection coefficients; τ is the initial wave impedance model constraint factor, used to control the dependence of the inversion results on the initial wave impedance model; V is the integral operator matrix; the diagonal elements of matrix W are: W mm Let ρ represent the value of the element in the m-th row and m-th column of matrix W, where m is the row and column index of matrix W. All elements of matrix W except for the diagonal elements are zero. r E represents the standard deviation of the noise. m It is the initial reflection coefficient at the location of the m-th sampling point, calculated from the initial wave impedance model; The relative wave impedance at the m-th sampling point

[0108] The impedance value, Z0, is the initial wave impedance value corresponding to the first sampling point within the inversion time window. m The wave impedance value at the m-th sampling point within the inversion window, d i Let ln be the reflection coefficient value at the i-th sampling point within the inversion window, and ln be the sign of the natural logarithm. This is a summation operation for m sampling points.

[0109] Furthermore, the process of converting the reflection coefficient sequence into a wave impedance sequence includes:

[0110] Based on the initial wave impedance value corresponding to the first sampling point within the inversion time window and the reflection coefficient value of the sampling point, the wave impedance value of the sampling point is obtained, as shown in formula (4):

[0111]

[0112] In the formula, Z m Zm is the wave impedance value at the m-th sampling point within the inversion window, Z0 is the initial wave impedance value corresponding to the first sampling point within the inversion window, and dm is the initial wave impedance value. i Let be the reflection coefficient value at the i-th sampling point within the inversion window, and let e represent the base of the natural logarithm. This is a summation operation for m sampling points.

[0113] Specifically, in step S4 above, the lithology of the tunnel is interpreted based on the depth domain impedance inversion profile of the tunnel and the threshold values ​​of lithology calibration and well logging cross-analysis.

[0114] Specifically, in step S5 above, the converted seismic geological profile is as follows: Figure 8 As shown, the geological profile of the tunnel also includes the undulating morphology, structural distribution and lithological distribution of the relevant target layer.

[0115] Specifically, in step S6 above, when guiding the rapid excavation of rock tunnels in coal mines, the data obtained by the method provided by this invention (including tunnel lithology interpretation, seismic geological profiles, and tunnel geological profiles) is an important basis for coal mines to design, formulate, and adjust rock tunnels.

[0116] The system for rapid tunneling in coal mine rock tunnels guided by three-dimensional seismic analysis provided by this invention includes: a migration processing module, a cross-analysis module, a wave impedance inversion module, a results acquisition unit, and an analysis unit.

[0117] The migration processing module is used to constrain tunnel data, establish a tunnel constraint velocity model, and perform pre-stack depth migration processing based on the tunnel constraint velocity model to obtain pre-stack depth migration processed depth domain data.

[0118] The cross-plot analysis module is used to perform cross-plot analysis on well logging curves, calibrate various lithologies, and determine the threshold values ​​for each calibrated lithology.

[0119] The wave impedance inversion module is used to perform well-logging-constrained depth-domain wave impedance inversion on depth-domain data processed by pre-stack depth migration, and obtain depth-domain wave impedance inversion profiles of tunnels.

[0120] The results acquisition unit is used to interpret the lithology of the tunnel based on the depth domain impedance inversion profile of the tunnel, with reference to each calibrated lithology and its corresponding threshold value; to convert the depth domain impedance inversion profile of the tunnel into a seismic geological profile based on the threshold value of each calibrated lithology; and to draw the geological profile of the tunnel based on the depth domain impedance inversion profile of the tunnel.

[0121] The analysis unit is used to combine roadway lithology interpretation, seismic geological profiles, and roadway geological profiles to guide the rapid excavation of rock roadways in coal mines.

[0122] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0123] (1) The method provided by this invention provides a basis for the formulation of precise design and excavation schemes for coal mine roadways, as well as for the adjustment of the schemes during the excavation process;

[0124] (2) The method provided by the present invention reduces the number of drilling operations during tunneling, improves the tunneling efficiency, reduces the frequency of construction plan adjustments, saves labor costs, reduces the risk of blade damage, and avoids the risk of abandoned tunnels.

[0125] The above embodiments are merely preferred embodiments of the present invention and should not be construed as limiting the scope of protection of the present invention. Any non-substantial changes and substitutions made by those skilled in the art based on the present invention shall fall within the scope of protection claimed by the present invention.

Claims

1. A method for rapid excavation of coal mine rock tunnels guided by three-dimensional seismic data, characterized in that, Includes the following steps: Using tunnel data as constraints, a tunnel constraint velocity model is established. Based on the tunnel constraint velocity model, pre-stack depth migration processing is performed to obtain pre-stack depth migration processed depth domain data. Cross-plot analysis was performed on the logging curves to calibrate each lithology and determine the threshold values ​​for each calibrated lithology. Well-logging-constrained depth domain acoustic impedance inversion is performed on the depth domain data of the pre-stack depth migration processing to obtain the depth domain acoustic impedance inversion profile of the tunnel. Based on the depth domain impedance inversion profile of the tunnel, and with reference to each calibrated lithology and its corresponding threshold value, the lithology of the tunnel is interpreted. Based on the threshold values ​​of each calibrated lithology, the depth domain impedance inversion profile of the tunnel is converted into a seismic geological profile, and the tunnel geological profile is drawn based on the depth domain impedance inversion profile of the tunnel. Combining the lithological interpretation of the roadway, the aforementioned seismic geological profile, and the aforementioned roadway geological profile, we can guide the rapid excavation of rock roadways in coal mines. Among them, when conducting well logging-constrained depth-domain acoustic impedance inversion, the following are included: The depth domain data from the pre-stack depth migration processing is used to obtain stratigraphic data, and the determined target stratigraphic layers are verified, corrected, interpolated, and smoothed to obtain more effective stratigraphic data; the acoustic curves and density curves in the depth domain are obtained based on the tunnel data. Based on the depth domain data from the pre-stack depth migration processing and the more effective stratigraphic data, the acoustic and density curves of the depth domain are used to generate the wave impedance curves of the depth domain in the well, and seismic wavelets are extracted from the seismic traces near the well to form a synthetic seismic record of the depth domain. An initial wave impedance model is generated based on the more effective stratigraphic data and the wave impedance curve in the depth domain. The depth domain data and the seismic wavelet processed by the pre-stack depth migration process are normalized to obtain the normalized depth domain data and the normalized seismic wavelet processed by the pre-stack depth migration process. The reflection coefficient sequence is obtained by inversion based on the normalized pre-stack depth migration data, the normalized seismic wavelet, and the initial wave impedance model. The reflection coefficient sequence is converted into a wave impedance sequence to obtain the wave impedance inversion result. Based on the wave impedance inversion result, the depth domain wave impedance inversion profile of the tunnel is obtained.

2. The method for rapid tunneling in coal mine rock tunnels guided by three-dimensional seismic analysis according to claim 1, characterized in that, When using tunnel data for constraints, the following are included: The elevation information of the target layer observed in boreholes and tunnels is extracted from the aforementioned mine and tunnel data, and the observation points of each borehole and tunnel are extracted from the elevation information. X,Y,Z information; The actual observation points of each borehole and each tunnel X,Y,Z The information is used for constrained velocity modeling.

3. The method for rapid tunneling in coal mine rock tunnels guided by three-dimensional seismic analysis according to claim 2, characterized in that, The actual observation points of each borehole and each tunnel were then recorded. X,Y,Z When information is used for constrained velocity modeling, it includes: The actual observation points of each borehole and each tunnel X,Y,Z The depth information of each borehole and each tunnel observation point is obtained from the information; Based on the tunnel data, pre-stack time migration processing is performed to obtain a pre-stack time migration profile, and the two-way travel time is read from the pre-stack time migration profile; The depth information of each borehole and each tunnel observation point, along with the two-way travel time, are used for constrained velocity modeling, as shown in Formula 1: (1)； In the formula, S represents the depth information of each borehole and each tunnel observation point, C represents the two-way travel time, and V represents the speed.

4. The method for rapid tunneling in coal mine rock tunnels guided by three-dimensional seismic analysis according to claim 1, characterized in that, When performing pre-stack depth migration processing based on the aforementioned tunnel constraint velocity model, the process includes: Kirchhoff integration is used for pre-stack depth migration, as shown in Equation 2: (2)； In the formula, For observation line, C D C, C H σ represents the spatial location of the source point, imaging point, and receiver point. D σ H For the travel time from the source to the imaging point and from the imaging point to the receiver, B is the geometric diffusion factor, m is the outward normal direction of the observation surface, v is the recorded wave field, and T is the reflection coefficient.

5. The method for rapid tunneling in coal mine rock tunnels guided by three-dimensional seismic analysis according to claim 4, characterized in that, When performing pre-stack depth migration processing based on the aforementioned tunnel constraint velocity model, the process also includes: After dividing the seismic signal frequency in the tunnel data into multiple narrow frequency bands using the reflectance spectral imaging method, Kirchhoff pre-stack depth migration processing is performed on each narrow frequency band.

6. The method for rapid tunneling in coal mine rock tunnels guided by three-dimensional seismic analysis according to claim 1, characterized in that, When determining the threshold values ​​for each calibrated lithology, the following are included: Determine the density threshold, acoustic threshold, and wave impedance threshold for each of the calibrated lithologies.

7. The method for rapid tunneling in coal mine rock tunnels guided by three-dimensional seismic analysis according to claim 1, characterized in that, When performing inversion to obtain the reflection coefficient sequence, the following is included: The inversion is performed based on the relative wave impedance value at the sampling point, the wavelet convolution matrix, and the initial wave impedance model constraint factor, as shown in Equation 3: (3)； In the formula, This is depth-domain seismic data processed by pre-stack depth migration; N is the total number of sampling points for the depth-domain seismic data; H is the reflection coefficient sequence; H is an N×N dimensional wavelet convolution matrix, and the superscript T represents the transpose of the matrix. It is a sparsity constraint factor used to control the sparsity of the reflection coefficient; V is the initial wave impedance model constraint factor, used to control the dependence of the inversion results on the initial wave impedance model; V is the integral operator matrix; the diagonal elements of matrix W are: W mm Let represent the value of the element in the m-th row and m-th column of matrix W, where m is the row and column index of matrix W. All elements of matrix W except for the diagonal elements are zero. E represents the standard deviation of the noise. m It is the initial reflection coefficient at the location of the m-th sampling point, calculated from the initial wave impedance model; Z is the relative wave impedance value at the m-th sampling point, Z0 is the initial wave impedance value corresponding to the first sampling point within the inversion time window, and Z m Let t be the wave impedance value at the m-th sampling point within the inversion window. i Let ln be the reflection coefficient value at the i-th sampling point within the inversion window, and ln be the sign of the natural logarithm. This is a summation operation for m sampling points.

8. The method for rapid tunneling in coal mine rock tunnels guided by three-dimensional seismic analysis according to claim 1, characterized in that, Converting the reflection coefficient sequence into a wave impedance sequence includes: Based on the initial wave impedance value corresponding to the first sampling point within the inversion time window and the reflection coefficient value of the sampling point, the wave impedance value of the sampling point is obtained, as shown in formula (4): (4)； In the formula, Z m Zm is the wave impedance value at the m-th sampling point within the inversion window, Z0 is the initial wave impedance value corresponding to the first sampling point within the inversion window, and dm is the initial wave impedance value. i Let be the reflection coefficient value at the i-th sampling point within the inversion window, and let e represent the base of the natural logarithm. This is a summation operation for m sampling points.

9. A system for rapid tunneling in coal mine rock tunnels guided by three-dimensional seismic data, characterized in that, include: Migration processing module: Used to constrain tunnel data, establish tunnel constraint velocity model, and perform pre-stack depth migration processing based on the tunnel constraint velocity model to obtain pre-stack depth migration processed depth domain data; Cross-plot analysis module: used to perform cross-plot analysis on well logging curves, calibrate various lithologies, and determine the threshold values ​​for each calibrated lithology; Wave impedance inversion module: used to perform well logging-constrained depth domain wave impedance inversion on the depth domain data of the pre-stack depth migration processing to obtain the depth domain wave impedance inversion profile of the tunnel. Results Acquisition Module: Used to interpret the lithology of the tunnel based on the depth domain impedance inversion profile of the tunnel, with reference to each calibrated lithology and its corresponding threshold value; convert the depth domain impedance inversion profile of the tunnel into a seismic geological profile based on the threshold value of each calibrated lithology; and draw the tunnel geological profile based on the depth domain impedance inversion profile of the tunnel. Analysis module: used to combine roadway lithology interpretation, the seismic geological profile, and the roadway geological profile to guide the rapid excavation of coal mine rock roadways; The wave impedance inversion module, when performing wave impedance inversion in the logging-constrained depth domain, is also used for: The depth domain data from the pre-stack depth migration processing is used to obtain stratigraphic data, and the determined target stratigraphic layers are verified, corrected, interpolated, and smoothed to obtain more effective stratigraphic data; the acoustic curves and density curves in the depth domain are obtained based on the tunnel data. Based on the depth domain data from the pre-stack depth migration processing and the more effective stratigraphic data, the acoustic and density curves of the depth domain are used to generate the wave impedance curves of the depth domain in the well, and seismic wavelets are extracted from the seismic traces near the well to form a synthetic seismic record of the depth domain. An initial wave impedance model is generated based on the more effective stratigraphic data and the wave impedance curve in the depth domain. The depth domain data and the seismic wavelet processed by the pre-stack depth migration process are normalized to obtain the normalized depth domain data and the normalized seismic wavelet processed by the pre-stack depth migration process. The reflection coefficient sequence is obtained by inversion based on the normalized pre-stack depth migration data, the normalized seismic wavelet, and the initial wave impedance model. The reflection coefficient sequence is converted into a wave impedance sequence to obtain the wave impedance inversion result. Based on the wave impedance inversion result, the depth domain wave impedance inversion profile of the tunnel is obtained.

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