Karst detection multi-parameter joint interpretation method based on environmental noise and application

Abstract

The invention relates to a karst detection multi-parameter joint interpretation method based on environmental noise and application. The method comprises the following steps of: 1, acquiring an environmental noise signal by adopting a three-component broadband digital seismograph and a two-dimensional array observation system; 2, a Capon F-K (Force-Wave Domain) analysis algorithm is adopted to carry out calculation, so that a frequency-surface wave phase velocity curve of each two-dimensional array can be obtained; 3, calculating and obtaining a frequency spectrum curve and an H / V spectrum ratio curve of two horizontal components and vertical components of each detection point of each two-dimensional array by adopting an independently researched and developed MATLAB (Matrix Laboratory) program; 4, respectively drawing a surface wave phase velocity (or surface wave horizon velocity) profile map, a frequency spectrum profile map and an H / V spectrum ratio profile map by adopting an independently researched and developed MATLAB (Matrix Laboratory) program; and 5, performing multi-parameter joint interpretation on karst detection by using parameters such as surface wave phase velocity (or surface wave apparent velocity), frequency spectrum and H / V spectrum ratio. The multi-parameter joint interpretation method is used for multi-parameter joint interpretation of karst detection, reliability and accuracy of interpretation results can be improved, potential risk sources are found in advance for engineering construction, and major construction accidents are avoided.

Description

Technical Field

[0001] The present invention relates to an interpretation method for geophysical exploration results, and in particular to a multi-parameter joint interpretation method based on environmental noise for adverse geological exploration results such as karst that have a great impact on engineering construction and its application. Background Art

[0002] The hazards caused by karst landforms to various types of engineering construction mainly include: foundation settlement, water and mud bursts in tunnels and foundation pits, water bursts and gas accumulation in mines, roadbed collapse, suspended and broken pipelines, reservoir leakage and dam foundation erosion, etc. The hazards caused may cause major safety accidents or economic losses.

[0003] For major risk sources such as karst construction, advance detection and advance treatment are generally required to ensure construction safety. Karst detection is generally carried out by drilling or geophysical detection. Karst development is relatively complex, and it is generally difficult to identify it using a single drilling method. In addition, it is costly, pollutes the environment, and disturbs residents with noise. Especially in complex urban environments, there are basically no conditions for drilling construction and the risks are huge. The most feasible solution is to use non-destructive geophysical methods for comprehensive scanning + a small number of drilling verifications for advance detection.

[0004] There are many types of geophysical exploration methods. Electromagnetic methods are seriously affected by the complex electromagnetic background of the city; conventional seismic methods and direct current methods are affected by urban vibration interference, small ground space, and lack of grounding conditions; in cities in the south with shallow groundwater levels, geological radar signals attenuate quickly, the detection depth is limited, and they are also affected by electromagnetic interference, so the detection effect is not ideal; various cross-hole CT methods have certain effects, but they require drilling, which is often difficult to construct in urban areas. Many geophysical exploration methods cannot achieve the expected detection effect in complex urban environments. The present invention uses natural environmental noise as the source of earthquakes, mainly using vibrations generated by human activities, including vehicle movement, mechanical vibrations, and other sources with a frequency greater than 1 Hz. These sources are very abundant in urban environments, so that non-destructive detection methods based on environmental noise can adapt to complex urban environments.

[0005] The development of karst is relatively complex. It is difficult and inaccurate to interpret it using a single geophysical exploration result. The present invention uses a three-component seismograph to collect environmental noise signals with a two-dimensional array observation system, and can simultaneously calculate and obtain multiple parameters such as surface wave phase velocity (or surface wave apparent velocity), spectrum and H / V spectrum ratio, and perform multi-parameter joint interpretation, which can improve the reliability and accuracy of karst interpretation. Summary of the invention

[0006] The purpose of the present invention is to provide a multi-parameter joint interpretation method for karst detection based on environmental noise and its application.

[0007] The object of the present invention is achieved by the following technical solutions: A multi-parameter joint interpretation method for karst detection based on environmental noise, which comprises the following steps:

[0008] Step 1: Use a three-component broadband digital seismograph to collect environmental noise signals with a two-dimensional array observation system, and the signal collection time is generally not less than 20 minutes;

[0009] Step 2: Use the Capon F-K (Frequency-Wavenumber Domain) analysis algorithm to calculate the frequency-phase velocity curve of surface waves for each two-dimensional array;

[0010] Step 3: Use a self-developed MATLAB program to calculate the spectral curves of the two horizontal components and the vertical component of each geophone point of each two-dimensional array, as well as the H / V spectral ratio curve;

[0011] Step 4: Use a self-developed MATLAB program to draw the cross-section of surface wave phase velocity or apparent layer velocity of surface waves, as well as the spectral cross-section and H / V spectral ratio cross-section respectively, where each cross-section contains multiple two-dimensional array measurement points;

[0012] Step 5: Use the parameters of surface wave phase velocity or apparent layer velocity of surface waves, as well as spectrum and H / V spectral ratio to perform multi-parameter joint interpretation for karst detection. The specific interpretation process is as follows:

[0013] Process (1). Using the connection lines of the first relatively large peak value and the last relatively large peak value of each array measurement point in the H / V spectral ratio cross-section, which respectively correspond to the initial bedrock surface in the shallow part of the stratum and the relatively complete bedrock surface in the deep part of the stratum, first divide the overall development range of karst in the stratum, that is, karst is mainly distributed between the initial bedrock surface in the shallow part of the stratum and the relatively complete bedrock surface in the deep part of the stratum;

[0014] Process (2). Translate the karst development range line to the corresponding positions of the cross-section of surface wave phase velocity or apparent layer velocity of surface waves and the spectral cross-section, and then analyze the velocity change situation within the karst development range according to the velocity cross-section. The range where the velocity shows an increasing trend inside the rock formation is inferred to be relatively complete surrounding rock, and the area where there is an obvious velocity inversion phenomenon is inferred to be a karst development area. The velocity inversion phenomenon is manifested as a low-high-low or high-low-high change; among them, the relatively low-velocity range is inferred to be filled or semi-filled karst, and the area with significantly higher velocity is inferred to be unfilled karst;

[0015] Then, analyze the energy change situation within the karst development range according to the spectral cross-section. Among them, the range with higher energy is inferred to be filled or semi-filled karst, and the range with significantly lower energy is inferred to be relatively complete surrounding rock;

[0016] Process (3). Comprehensively analyze the preliminary interpretation results of the above-mentioned surface wave phase velocity or surface wave apparent layer velocity, as well as the spectrum and H / V spectrum ratio, and then compare, review, and adjust the inferred overall development range of karst and the distribution ranges of filled, semi-filled, and unfilled karst, and finally form a geological interpretation map of the karst detection results. The multi-parameter joint interpretation method for karst detection based on ambient noise is used for the multi-parameter joint interpretation of karst detection, which can improve the reliability and accuracy of the interpretation results.

[0017] Compared with the prior art, the advantages of the present invention are as follows:

[0018] 1. Using ambient noise as the signal, it is not affected by electromagnetic interference, grounding conditions, etc., and has strong adaptability to complex urban environments;

[0019] 2. Using a three-component seismograph to collect ambient noise signals with a two-dimensional array observation system, multiple parameters such as surface wave phase velocity (or surface wave apparent layer velocity), spectrum, and H / V spectrum ratio can be calculated simultaneously;

[0020] 3. Using multiple parameters such as surface wave phase velocity (or surface wave apparent layer velocity), spectrum, and H / V spectrum ratio to jointly interpret karst. Through mutual corroboration of multiple parameters, the reliability and accuracy of karst interpretation can be improved. Description of the Drawings

[0021] Figure 1 It is a schematic diagram of a circular array observation system in Embodiment 1.

[0022] Figure 2 It is the frequency-surface wave phase velocity curve obtained in Step 2 of the present invention.

[0023] Figure 3 It is the spectrum curve obtained in Step 3 of the present invention.

[0024] Figure 4 It is the H / V spectrum ratio curve obtained in Step 3 of the present invention.

[0025] Figure 5 It is the H / V spectrum ratio cross-section diagram in Embodiment 1.

[0026] Figure 6 It is the surface wave apparent layer velocity cross-section diagram in Embodiment 1.

[0027] Figure 7 It is the amplitude spectrum cross-section diagram in Embodiment 1.

[0028] Figure 8 It is the geological interpretation map of the karst detection results in Embodiment 1. Detailed Implementation Modes

[0029] The content of the present invention will be described in detail below in conjunction with the specification drawings and embodiments:

[0030] A multi-parameter joint interpretation method for karst detection based on environmental noise, which comprises the following steps:

[0031] Step 1: According to the general situation of the detection target body, a two-dimensional observation array (optional circular array, embedded triangular array, cross-shaped array, etc.) is arranged on the ground surface, and environmental noise signals are collected, and the acquisition recording time is not less than 20 min;

[0032] Step 2: Use the Capon F-K (Frequency-Wavenumber Domain) analysis algorithm to calculate the frequency-surface wave phase velocity curve of each two-dimensional array;

[0033] Step 3: Use the self-developed MATLAB program to calculate the spectral curves of the two horizontal components and the vertical component of each geophone point of each two-dimensional array and the H / V spectral ratio curve;

[0034] Step 4: Use the self-developed MATLAB program to draw the surface wave phase velocity (or surface wave apparent layer velocity) profile, the spectral profile and the H / V spectral ratio profile respectively;

[0035] Step 5: Use parameters such as surface wave phase velocity (or surface wave apparent layer velocity), spectrum and H / V spectral ratio to conduct multi-parameter joint interpretation for karst detection. The specific interpretation process is as follows:

[0036] Process (1). Using the rule that the connection line of the first relatively large peak value and the connection line of the last relatively large peak value of each array measurement point in the H / V spectral ratio profile respectively correspond to the shallow initial bedrock surface and the relatively complete deep bedrock surface of the formation, first divide the overall development range of karst in the formation, that is, karst is mainly distributed between the shallow initial bedrock surface and the relatively complete deep bedrock surface of the formation;

[0037] Process (2). Translate the karst development range line to the corresponding positions of the surface wave phase velocity (or surface wave apparent layer velocity) profile and the spectral profile, and then analyze the velocity change situation within the karst development range according to the velocity profile. The range where the velocity shows an increasing trend inside the rock formation is inferred as relatively complete surrounding rock, and the range where there is an obvious velocity inversion phenomenon (the velocity shows a low-high-low or high-low-high change) is inferred as the karst development area. Among them, the relatively low-velocity range is inferred as filled or semi-filled karst, and the range with significantly higher velocity is inferred as unfilled karst; then analyze the energy change situation within the karst development range according to the spectral profile. Among them, the range with higher energy is inferred as filled or semi-filled karst, and the range with significantly lower energy is inferred as relatively complete surrounding rock;

[0038] Process (3). Comprehensively analyze the preliminary interpretation results of the above-mentioned surface wave phase velocity (or surface wave apparent layer velocity), spectrum, and H / V spectrum ratio, and then compare, review, and adjust the inferred overall development range of karst and the distribution ranges of filled, semi-filled, and unfilled karst. Finally, form a geological interpretation map of the karst detection results.

[0039] When using the self-developed MATLAB program to draw the surface wave phase velocity profile in Step 4, the following formula is used for the frequency-depth conversion;

[0040]

[0041] In the formula, H is the detection depth; v is the surface wave phase velocity; f is the frequency corresponding to the surface wave phase velocity; c is the conversion coefficient, and the value of c ≤ 1 / 2. In actual operation, generally take 1 / 2, and the value of c can be appropriately adjusted after calibration with known boreholes.

[0042] When using the self-developed MATLAB program to draw the surface wave phase velocity profile in Step 4, choose to convert the surface wave phase velocity to the surface wave apparent layer velocity;

[0043]

[0044] In the formula, is the surface wave apparent layer velocity; is the surface wave phase velocity; is the frequency; i is the i-th point; c is a constant, and c takes 2, 3, or 4, usually taking 4.

[0045] When using the self-developed MATLAB program to draw the spectrum profile and H / V spectrum ratio profile in Step 4, the following fitting formula is used for the frequency-depth conversion;

[0046]

[0047] In the formula, H is the detection depth; f is the frequency corresponding to the first peak with a relatively large value in the H / V spectrum ratio curve of the array measurement point; c1, c2, c3 are fitting coefficients. The fitting coefficients c1, c2, c3 are obtained by fitting the depths H of the bedrock surfaces initially seen in several known boreholes within the measurement area and the corresponding frequencies f of the first peaks with relatively large values in the H / V spectrum ratio curves.

[0048] By converting the vertical coordinates of the surface wave phase velocity profile, spectrum profile, and H / V spectrum ratio profile from frequency to depth, the purpose of unifying the vertical coordinates of the surface wave phase velocity or surface wave apparent layer velocity profile, spectrum profile, and H / V spectrum ratio profile to depth is achieved, which is conducive to realizing the multi-parameter joint interpretation of the surface wave phase velocity, spectrum, and H / V spectrum ratio.

[0049] When using the self-developed MATLAB program to draw the spectral profile and H / V spectral ratio profile in Step 4, the following formulas are selected to normalize the spectral curve and the H / V spectral ratio curve respectively;

[0050]

[0051] In the formula, is the normalized spectral curve; is the spectrum; is the maximum value of the spectrum; f is the frequency;

[0052]

[0053] In the formula, is the H / V normalized spectral ratio curve; is the spectral ratio; is the maximum value of the spectral ratio; f is the frequency.

[0054] The method described in the present invention is mainly applied to the multi-parameter joint interpretation of karst exploration results based on ambient noise.

[0055] The present invention will be described below in conjunction with the implementation cases

[0056] Example 1: Multi-parameter joint interpretation of karst exploration results based on ambient noise for a certain karst development area

[0057] Project overview: The exploration data shows that the rock and soil layers from top to bottom within the survey area are mainly: miscellaneous fill (plain fill), silty clay, silty clay containing eggs (gravels), slightly weathered marble; the depth of slightly weathered marble ranges from more than ten to more than twenty meters; filled, semi-filled and unfilled karst caves are developed in the slightly weathered marble. During the construction at a certain place within the survey area, mud gushed out from the river channel more than 300 meters away from the survey area. When the construction stopped, the mud gushing in the river channel also stopped, and different degrees of ground settlement occurred on the surface within the survey area during the construction process. It is initially inferred that the underground karst in the survey area is relatively developed and has good connectivity. In order to further clarify the development of karst, karst geophysical exploration based on ambient noise was adopted.

[0058] Step 1: In this case, a three-component broadband digital seismograph was used to collect ambient noise signals with a circular array observation system with a radius of 2.5 m (see Figure 1 ), the signal collection time was 20 min, and the sampling time interval was 4 ms;

[0059] Step 2: The Capon F-K (Frequency-Wavenumber Domain) analysis algorithm was used to calculate the frequency-phase velocity curve of surface waves for each two-dimensional array (see Figure 2 );

[0060] Step 3: Use the self-developed MATLAB program to calculate the spectral curves of the two horizontal components and the vertical component of each geophone point of each two-dimensional array and the H / V spectral ratio curve (see Figure 3 , Figure 4 );

[0061] Step 4: Use the self-developed MATLAB program to draw the apparent layer velocity profile, spectral profile and H / V spectral ratio profile of surface waves respectively (see Figures 5 to 7 );

[0062] Step 5: Use parameters such as the apparent layer velocity, spectrum and H / V spectral ratio of surface waves to conduct multi-parameter joint interpretation of karst detection as follows:

[0063] Figure 5 This is the H / V spectral ratio profile. The abscissa in the figure is the horizontal distance (m); the ordinate is the elevation (m); different gray levels represent the magnitude of the H / V spectral ratio. The analysis is as follows: 1) The connection line of the first relatively large peak value of each array measurement point in the figure (the light black dotted line in the figure) corresponds to the interface of slightly weathered marble in the shallow part of the stratum, with a buried depth of 14.9 m - 21.6 m; 2) The connection line of the last relatively large peak value of each array measurement point (the dark black dotted line in the figure) corresponds to the interface of relatively intact slightly weathered marble in the deep part of the stratum, with a buried depth of 21.6 m - 40.6 m; 3) Karst is mainly distributed between the initial bedrock surface in the shallow part of the stratum and the relatively intact bedrock surface in the deep part of the stratum. The overall development range of karst is below the measurement points E1 - E28; 4) It is inferred that there is basically no karst development below the measurement points E29 - E32.

[0064] Figure 6 This is the apparent layer velocity profile of surface waves. The abscissa in the figure is the horizontal distance (m); the ordinate is the elevation (m); different gray levels represent different apparent layer velocity values of surface waves (m / s). First, Figure 5 translate the interpretation result of the H / V spectral ratio profile, that is, the overall development range line of karst, to Figure 6 the apparent layer velocity profile of surface waves, and then analyze the change of the apparent layer velocity of surface waves within the karst development range: 1) The velocity within the rock formation below the measurement points E29 - E32 shows an increasing trend, and it is inferred that there is basically no karst development below it, which is basically consistent with the result inferred from the H / V profile; 2) There are varying degrees of velocity inversion phenomena in the apparent layer velocity of surface waves below the measurement points E1 - E28, and it is inferred that there are varying degrees of karst development, which is also basically consistent with the result inferred from the H / V profile; 3) The ranges with significantly low velocities, such as the elevation range of 10 m - 0 m below the measurement points E1 - E3, the elevation range of 15 m - 12 m below the measurement points E3 - E4, the elevation range of 14 m - 8 m below the measurement points E20 - E21, the elevation range of 5 m - 1 m below the measurement points E23 - E24, and the elevation range of 10 m - 6 m below the measurement points E26 - E27, are inferred to be filled karst; 4) The range with significantly high velocity in the elevation range of 14 m - 8 m below the measurement points E4 - E6 is inferred to be unfilled karst.

[0065] Figure 7 is a spectrum profile, where the horizontal axis is the horizontal distance (m); the vertical axis is the elevation (m); different grayscales represent the magnitude of the spectrum. Figure 5 The interpretation result of H / V spectrum ratio section is that the overall karst development range line is shifted to Figure 7 On the spectrum profile, the changes in spectrum energy are analyzed within the range of karst development: 1) The energy below the bedrock surface below measuring points E29~E32 is relatively small, and it is inferred that the bedrock below is relatively complete and karst is basically not developed, which is basically consistent with the results inferred by the H / V profile and the surface wave apparent velocity profile; 2) There are generally areas with larger energy below the bedrock surface below measuring points E1~E28, and it is inferred that there is karst development to varying degrees, which is also basically consistent with the results inferred by the H / V profile and the surface wave apparent velocity profile.

[0066] Figure 8 This is a geological interpretation map of karst exploration results, in which the horizontal axis is the horizontal distance (m); the vertical axis is the elevation (m). The preliminary interpretation results of the surface wave apparent velocity, spectrum and H / V spectrum ratio were comprehensively analyzed, and the inferred overall development range of karst and the distribution range of filled, semi-filled and unfilled karst were compared, verified and adjusted, and finally the geological interpretation map of karst exploration results was formed. The map marked the initial slightly weathered marble interface in the shallow stratum, the relatively complete slightly weathered marble interface in the deep stratum, the overall karst development area, and the development location of filled karst and unfilled karst.

Claims

1. A multi-parameter joint interpretation method for karst detection based on environmental noise, characterized in that: It includes the following steps: Step 1: Use a three-component broadband digital seismograph to collect ambient noise signals with a two-dimensional array observation system. The signal collection time is generally not less than 20 minutes; Step 2: Use the Capon F-K analysis algorithm to calculate the frequency-surface wave phase velocity curve for each two-dimensional array; Step 3: Use the self-developed MATLAB program to calculate the spectral curves of the two horizontal components and the vertical component at each geophone point of each two-dimensional array, as well as the H / V spectral ratio curve; Step 4: Use the self-developed MATLAB program to draw the cross-section of the surface wave phase velocity or the apparent layer velocity of the surface wave, as well as the spectral cross-section and the H / V spectral ratio cross-section. Each cross-section contains multiple measurement points of two-dimensional arrays; Step 5: Use the parameters of the surface wave phase velocity or the apparent layer velocity of the surface wave, as well as the spectrum and the H / V spectral ratio, to conduct multi-parameter joint interpretation for karst detection. The specific interpretation process is as follows: Process (1). Use the connection lines of the first relatively large peak value and the last relatively large peak value at each measurement point of each array in the H / V spectral ratio cross-section, which respectively correspond to the initial bedrock surface in the shallow part of the stratum and the relatively complete bedrock surface in the deep part of the stratum. First, divide the overall development range of karst in the stratum, that is, karst is mainly distributed between the initial bedrock surface in the shallow part of the stratum and the relatively complete bedrock surface in the deep part of the stratum; Process (2). Translate the karst development range line to the corresponding positions of the surface wave phase velocity or the apparent layer velocity cross-section and the spectral cross-section of the surface wave. Then, analyze the velocity change situation within the karst development range according to the velocity cross-section. The range where the velocity inside the rock formation shows an increasing trend is inferred as relatively complete surrounding rock, and the range where there is an obvious velocity inversion phenomenon is inferred as the karst development area. The velocity inversion phenomenon shows a low-high-low or high-low-high change; among them, the relatively low-velocity range is inferred as filled or semi-filled karst, and the range with significantly higher velocity is inferred as unfilled karst; Then, analyze the energy change situation within the karst development range according to the spectral cross-section. Among them, the range with higher energy is inferred as filled or semi-filled karst, and the range with significantly lower energy is inferred as relatively complete surrounding rock; Process (3). Comprehensively analyze the preliminary interpretation results of the above surface wave phase velocity or the apparent layer velocity of the surface wave, as well as the spectrum and the H / V spectral ratio. Then, compare, review, and adjust the inferred overall development range of karst and the distribution ranges of filled, semi-filled, and unfilled karst, and finally form a geological interpretation map of karst detection results.

2. The multi-parameter joint interpretation method for karst detection based on environmental noise according to claim 1, characterized in that: When using the self-developed MATLAB program in Step 4 to draw the surface wave phase velocity cross-section, the following formula is used for frequency-depth conversion; In the formula, H is the detection depth; v is the surface wave phase velocity; f is the frequency corresponding to the surface wave phase velocity; c is the conversion coefficient, and the value of c ≤ 1 / 2.

3. A multi-parameter joint interpretation method for karst detection based on environmental noise according to claim 2, characterized in that: When using the self-developed MATLAB program in Step 4 to draw the surface wave phase velocity cross-section, choose to convert the surface wave phase velocity into the apparent layer velocity of the surface wave; In the formula, is the apparent layer velocity of surface waves; is the phase velocity of surface waves; is the frequency; i is the i-th point; c is a constant, and c takes 2, 3, or 4.

4. A multi-parameter joint interpretation method for karst detection based on environmental noise according to claim 1, characterized in that: When using the self-developed MATLAB program in Step 4 to draw the spectral cross-section and the H / V spectral ratio cross-section, the following fitting formula is used for frequency-depth conversion; Wherein, H is the detection depth; f is the frequency corresponding to the first peak with a relatively large magnitude in the H / V spectral ratio curve of the array measurement point; c1, c2, and c3 are fitting coefficients.

5. The multi-parameter joint interpretation method for karst detection based on environmental noise according to claim 4, wherein: The fitting coefficients c1, c2, and c3 are obtained by fitting the buried depth H of the initial bedrock surface of several known boreholes within the survey area and the corresponding frequency f of the first peak with a relatively large magnitude in the H / V spectral ratio curve.

6. The multi-parameter joint interpretation method for karst detection based on environmental noise according to claim 1, wherein: When drawing the spectral profile and the H / V spectral ratio profile using the self-developed MATLAB program in Step 4, the following formulas are selected to normalize the spectral curve and the H / V spectral ratio curve respectively; wherein, is the normalized frequency spectrum curve; is the frequency spectrum; is the maximum value of the frequency spectrum; f is the frequency; In the formula, is the H / V normalized spectral ratio curve; is the spectral ratio; is the maximum value of the spectral ratio; f is the frequency.

7. Application of a multi-parameter joint interpretation method for karst detection based on environmental noise according to any one of claims 1-6, characterized in that: It is used for the joint interpretation of multiple parameters for karst detection to improve the reliability and accuracy of the interpretation results.

Images