Coastal city land-sea junction shallow geological structure detection comprehensive data acquisition method

Abstract

The invention belongs to the technical field of geophysical exploration, and particularly relates to a coastal city land-sea junction shallow geological structure detection comprehensive data acquisition method, which comprises the following steps of: 1, adopting a geological radar, a high-density resistivity method, a conical transient electromagnetic method and micro-motion exploration multi-method collaborative layered detection; the detection depths are respectively 5 meters, 30 meters, 50 meters and 80 meters; and 2, realizing integrated analysis of the shallow geological structure through RTK dynamic positioning and hierarchical data fusion technologies. According to the invention, through the hierarchical collaborative design of 5 meters of geological radar, 30 meters of high-density resistivity method, 50 meters of conical transient electromagnetic method and 80 meters of micro exploration, and in combination with the RTK high-precision positioning and anti-interference optimization technology, the efficient detection of the geological structure within the depth range of 5-80 meters is realized. The method is high in data fusion degree, high in anti-interference performance and suitable for engineering geological exploration in a coastal complex environment.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of geophysical exploration, and particularly relates to a comprehensive data acquisition method for shallow geological structure exploration at a land-sea junction zone of a coastal city. BACKGROUND

[0002] The geological environment at the land-sea junction zone of a coastal city is complex, with problems such as salinization, dynamic changes in underground water, and significant electromagnetic interference. Traditional single detection methods cannot meet the needs of fine exploration of shallow geological structures. In the prior art, although geological radar, resistivity method, transient electromagnetic method, and micro-motion exploration each have their own advantages, there is a lack of a systematic integration scheme for the coastal environment, resulting in low detection efficiency and discontinuous data coverage. In addition, the detection depth and accuracy of different methods are not effectively complementary, making it difficult to meet the needs of integrated analysis of 5-80 meter shallow geological structures.

[0003] To meet the needs of shallow geological structure exploration at the land-sea junction zone of a coastal city, the present application proposes a comprehensive data acquisition method based on multi-method cooperation. Through hierarchical detection design, geological radar is used for 5 meters, high-density resistivity method for 30 meters, cone transient electromagnetic method for 50 meters, and micro-motion exploration for 80 meters. Combined with high-precision point positioning and quality control technology, the problems of insufficient data coverage and significant interference in complex environments are solved, and efficient and accurate exploration of shallow geological structures is achieved. SUMMARY

[0004] The purpose of the present application is to provide a comprehensive data acquisition method for shallow geological structure exploration at the land-sea junction zone of a coastal city, which can solve the problems of insufficient data coverage and significant interference in complex environments, and achieve efficient and accurate exploration of shallow geological structures.

[0005] The technical solutions adopted by the present application are as follows:

[0006] A comprehensive data acquisition method for shallow geological structure exploration at the land-sea junction zone of a coastal city, comprising the following steps:

[0007] Step 1: Multi-method cooperative hierarchical detection using geological radar, high-density resistivity method, cone transient electromagnetic method, and micro-motion exploration; detection depths are 5 meters, 30 meters, 50 meters, and 80 meters, respectively;

[0008] Step 2: Realize integrated analysis of shallow geological structures through RTK dynamic positioning and hierarchical data fusion technology.

[0009] Preferably, in step 1:

[0010] Geological radar: detection depth 5 meters, using 100 MHz center frequency antenna, scanning speed 600 channels / s, time window 256 ns, point spacing 50 meters, antenna spacing 0.5 meters, signal-to-noise ratio ≥120 dB;

[0011] The high-density resistivity method: detection depth 30 meters, electrode distance 5 meters, power supply electrode distance is 6-10 times of the target depth, total mean square relative error ≤1.83%(I class standard);

[0012] The transient electromagnetic method: detection depth 50 meters, transmission current ≥9A, time window range 0.004-127.483ms, 112 acquisition time windows, data curve I class rate ≥85%;

[0013] The micro-oscillation exploration: detection depth 80 meters, detector array one-dimensional linear arrangement (30 detectors, measuring point distance 5 meters), sampling frequency 500Hz, acquisition time length 20 minutes, root mean square error ≤3.67%.

[0014] Preferably, in step 1, the multi-method collaborative process in the multi-method collaborative layered detection includes the following steps:

[0015] Step a: rapid scanning of the geological radar within a depth range of 5 meters, identifying shallow stratum interfaces and abnormal bodies;

[0016] Step b: high-density resistivity method for encryption detection within a depth range of 30 meters, combining the results of the geological radar to optimize electrode layout;

[0017] Step c: transient electromagnetic method for detecting within a depth range of 50 meters, covering the middle-deep layer electrical structure, verifying the resistivity method results;

[0018] Step d: micro-oscillation exploration within a depth range of 80 meters, obtaining deep stratum shear wave velocity, supplementing structural information;

[0019] Step e: data fusion and three-dimensional modeling, combining drilling data to verify accuracy.

[0020] Preferably, the geological radar works dynamically adjusts the antenna spacing and polarization direction to suppress random noise caused by sea wind; the transient electromagnetic method uses late channel data screening to reduce electromagnetic interference caused by tidal activity; the micro-oscillation exploration uses rolling measurement and repeated observation (≥5% measuring points).

[0021] Preferably, in step e, in the geological radar data processing process, first, the original record is obtained, then the head and tail waste sections are cut off, then the horizontal distance is balanced, then the measurement direction is adjusted, then zero point correction is performed, then horizontal filtering and vertical filtering are performed, then dielectric constant or electromagnetic wave velocity identification and high-conductivity body influence distribution are performed, target signals are identified, and finally the distribution characteristics of underground geological bodies are output.

[0022] Preferably, in step e, in the process of high-density data processing, first, data preprocessing is carried out, and outliers and data smoothing are removed; for the measuring points with tens of times difference compared with adjacent resistivity, the outliers are removed during data preprocessing editing, and then curve interpolation is carried out; then, inversion imaging is carried out, the collected data is converted into apparent resistivity, and the data is inverted to obtain the true resistivity of the underground electrical structure.

[0023] Preferably, in step e, in the process of transient electromagnetic data processing, first, data editing, outlier removal and denoising are carried out on the field collected data; then, near-field correction and other data preprocessing are carried out; finally, one-dimensional and two-dimensional inversion imaging processing is carried out.

[0024] Preferably, in step e, in the process of microseismic data processing, the microseismic data is processed by the most commonly used SPAC method, and the processing steps are as follows: first, different geophone distances in a station array are grouped, and each group is processed respectively; then, the data recorded for a long time is screened and segmented, and the data with obvious interference and invalidity is extracted; then, the screened data is preprocessed, and the preprocessing includes removing direct current, removing mean value and normalizing; then, Fourier transform is carried out to calculate the self-power spectrum of each station array data and the mutual power spectrum between two stations; then, after obtaining the power spectrum, the autocorrelation coefficient between each two stations is calculated; then, the autocorrelation coefficients of the same geophone distance, that is, the station radius combination mode, are averaged to obtain the averaged correlation coefficient; then, the autocorrelation coefficients of different distance combination modes are fitted with the first type of standard zero-order Bessel function to obtain the frequency dispersion curve; finally, the frequency dispersion curve is segmented and averaged to obtain the averaged frequency dispersion curve.

[0025] The technical effects obtained by the present application are as follows:

[0026] The present application solves the problems of insufficient data coverage and significant interference in complex environments by the layered collaborative design of the geological radar 5 meters, the high-density resistivity method 30 meters, the conical transient electromagnetic method 50 meters and the microseismic exploration 80 meters, combined with the RTK high-precision positioning and anti-interference optimization technology, and realizes efficient exploration of the geological structure in the depth range of 5-80 meters; the present method has high data fusion degree and strong anti-interference, and is suitable for engineering geological exploration in complex coastal environments. BRIEF DESCRIPTION OF DRAWINGS

[0027] Figure 1 is the geological radar data processing flowchart in the present application;

[0028] Figure 2 is the geological radar result map in the present application;

[0029] Figure 3 is the Res2DINV software inversion and interpretation example in the present application;

[0030] Figure 4 is a transient electromagnetic data processing flowchart in the present application;

[0031] Figure 5 is a microseismic profile ratio method section in the present application;

[0032] Figure 6 is a multi-method collaborative detection flowchart in the present application;

[0033] Figure 7 is a working area range schematic diagram in the experimental case of the present application;

[0034] Figure 8 is a radar survey line arrangement diagram in the experimental case of the present application;

[0035] Figure 9 is a microseismic survey line arrangement diagram in the experimental case of the present application;

[0036] Figure 10 is a conical transient electromagnetic survey line arrangement diagram in the experimental case of the present application;

[0037] Figure 11 is a high-density resistivity survey line arrangement diagram in the experimental case of the present application;

[0038] Figure 12 is a geophysical integrated result map of survey line L1 in the experimental case of the present application, in which: Figure 12(a) is a radar image map of survey line L1; Figure 12(b) is a transient electromagnetic method result map of survey line L1; Figure 12(c) is a microseismic result map of survey line L1; Figure 12(d) is a high-density resistivity method result map of survey line L1-1; and Figure 12(e) is a high-density resistivity method result map of survey line L1-2;

[0039] Figure 13 is a geophysical integrated result map of survey line L8 in the experimental case of the present application, in which: Figure 13(a) is a radar image map of survey line L8; Figure 13(b) is a transient electromagnetic method result map of survey line L8; Figure 13(c) is a microseismic result map of survey line L8; and Figure 13(d) is a high-density resistivity method result map of survey line L8;

[0040] Figure 14 is a three-dimensional resistivity model in the experimental case of the present application. DETAILED DESCRIPTION

[0041] In order to make the objects and advantages of the present application clearer, the present application will be specifically described below in combination with embodiments. It should be understood that the following text is only used to describe one or several specific embodiments of the present application, and does not strictly limit the specific protection scope of the present application.

[0042] As Figures 1-14As shown, a comprehensive data collection method for detecting shallow geological structure of land-sea interface zone of coastal city, comprising the following steps:

[0043] Step 1: Multi-method collaborative layered detection by using geological radar, high-density resistivity method, cone transient electromagnetic method and micro-motion exploration; the detection depths are 5 meters, 30 meters, 50 meters and 80 meters respectively;

[0044] Step 2: Realize integrated analysis of shallow geological structure by RTK dynamic positioning and layered data fusion technology.

[0045] Preferably, in step 1:

[0046] Geological radar: detection depth 5 meters, using 100MHz center frequency antenna, scanning speed 600 channels / s, time window 256ns, measurement point spacing 50 meters, antenna spacing 0.5 meters, signal-to-noise ratio ≥120dB;

[0047] High-density resistivity method: detection depth 30 meters, electrode spacing 5 meters, power supply electrode spacing is 6-10 times the depth of the exploration target, total mean square relative error ≤1.83%(I class standard);

[0048] Cone transient electromagnetic method: detection depth 50 meters, transmission current ≥9A, time window range 0.004-127.483ms, 112 acquisition time windows, data curve class A rate ≥85%;

[0049] Micro-motion exploration: detection depth 80 meters, one-dimensional linear array of detector array (30 detectors, measurement point spacing 5 meters), sampling frequency 500Hz, acquisition time 20 minutes, root mean square error ≤3.67%.

[0050] Preferably, as shown, Figure 6 Figure 6 is a multi-method collaborative detection flowchart, the multi-method collaborative process in multi-method collaborative layered detection comprises the following steps:

[0051] Step a: Geological radar rapid scanning within 5 meters depth range, identifying shallow stratum interface and abnormal body;

[0052] Step b: High-density resistivity method for encryption detection within 30 meters depth range, combining with the results of geological radar to optimize electrode layout;

[0053] Step c: Cone transient electromagnetic method for detecting within 50 meters depth range, covering the middle-deep layer electrical structure, verifying the results of resistivity method;

[0054] Step d: Micro-motion exploration within 80 meters depth range, obtaining deep stratum shear wave velocity, supplementing structure information;

[0055] ​Step e: data fusion and three-dimensional modeling, combined with drilling data to verify accuracy.

[0056] Preferably, the ground penetrating radar dynamically adjusts the antenna spacing and polarization direction during operation to suppress random noise caused by sea wind; the transient electromagnetic method uses late channel data screening to reduce electromagnetic interference caused by tidal activity; the micro-motion exploration uses rolling measurement and repeated observation (≥5% measurement points) to eliminate the influence of sea wave vibration.

[0057] In actual use, the measurement points are laid out: based on RTK dynamic lofting, the main survey line is laid out at an interval of 50 meters, and the measurement points of the ground penetrating radar, resistivity method and transient electromagnetic method are labeled synchronously on each survey line;

[0058] Data acquisition sequence: preferentially complete the ground penetrating radar scanning, adjust the electrode position of the resistivity method according to the shallow anomalies, and then carry out transient electromagnetic and micro-motion exploration;

[0059] Quality control:

[0060] The ground penetrating radar is evaluated by waveform consistency, and the repeated observation in the abnormal area is ≥3 times;

[0061] The resistivity method performs instrument calibration every day, and the grounding resistance is ≤100Ω;

[0062] The transient electromagnetic method monitors the signal-to-noise ratio in real time, and eliminates the third-class curve data;

[0063] When the root mean square error of the micro-motion exploration data exceeds the limit, the acquisition time is extended to 30 minutes;

[0064] Preferably, in step e, during the data processing of the ground penetrating radar, the original data is played back before processing, and the qualified data needs to be recorded completely, the signal is clear, and the mileage marker is accurate. The unqualified original record cannot be processed and interpreted, and the data processing flow is as shown in Figure 1 First, the original record is obtained, then the head and tail waste segments are cut off, then the horizontal distance is balanced, then the measurement direction is adjusted, then the zero point is corrected, then the horizontal filtering and vertical filtering are performed, then the dielectric constant or electromagnetic wave speed identification and high-conductivity body influence distribution are identified, and the target signal is identified. Finally, the distribution characteristics of the underground geological body are output; the radar result image interpretation should be based on the physical parameters in the study area, and should be carried out according to the principle of from known to unknown and qualitative guidance to quantitative. According to the field record, the relationship between the possible interference position and the anomaly in the radar record is analyzed, the two-way travel time data is accurately read, the effective anomaly and the interference anomaly are distinguished, and the radar result image is as shown in Figure 2 .

[0065] Preferably, in step e, during the data processing of the high-density data,

[0066] First, data preprocessing, field data collection process inevitably exist all kinds of interference, therefore need to optimize the data processing, the commonly used method is: eliminate mutation point and data smoothing; Compared with adjacent resistivity has several times difference of the measuring point, in data preprocessing editing when eliminating, then again curve interpolation; Data smoothing is to use the method of moving average processing data, the purpose is to eliminate random interference in the measurement process;

[0067] Then inversion imaging, the data collected for apparent resistivity conversion, the apparent resistivity results can not reflect the true electrical structure of the underground, need to be inverted to obtain the true resistivity of the underground electrical structure; Data inversion using Sweden Res2DINV software, the software uses the least square method of smoothing constraint inversion technology, can be fully automated inversion; As shown in Figure 3 .

[0068] Preferably, in step e, in the process of transient electromagnetic data processing, first, the data collected in the field is edited, wild value is eliminated, and noise is removed; Then near field correction and other data preprocessing; Finally, one-dimensional and two-dimensional inversion imaging processing is carried out; The data collected in the field is processed in the laboratory to remove interference factors, and the apparent resistivity section is formed by inversion calculation, and then the change of underground electrical property is described intuitively. The processing flow framework diagram is shown in Figure 4 .

[0069] Preferably, in step e, in the process of microseismic data processing, the microseismic data is processed by the most commonly used SPAC method, and the processing steps are as follows: first, different receiver distances in a station array are grouped, and each group is processed respectively; Then, the data recorded for a long time is screened and segmented, and the data with obvious interference and invalidity is extracted; Then, the screened data is preprocessed, which includes removing direct current, removing mean value and normalizing; Then, the Fourier transform is carried out to calculate the self power spectrum of each station data and the mutual power spectrum between two stations; Then, the autocorrelation coefficient between each two stations is calculated after obtaining the power spectrum; Then, the autocorrelation coefficients of the same receiver distance, that is, the station radius combination mode, are averaged to obtain the average correlation coefficient; Then, the autocorrelation coefficients of different distance combination modes are fitted with the first type of standard zero order Bessel function to obtain the dispersion curve; Finally, the dispersion curve is segmented and averaged to obtain the average dispersion curve; The dispersion curve after processing can represent the shear wave velocity structure of the stratum, and the high and low of the velocity value directly reflects the hardness of the stratum. In addition, the H / V parameter represents the impedance interface of the stratum, and the peak value reflects the interface between the strata. The result map is shown in Figure 5 .

[0070] Experimental case, choose Qingdao land and sea junction with more abundant geological data of the region for measurement, measurement area for by ring bay road, Changmao road, Ruihu road, Ruisan road and Changjia road closed interval; Figure 7 The area surrounded by the blue line. Along the meridian and latitude roads in the region, 9 lines are laid out to form an approximately parallel survey network. The subway and construction in the survey area have caused some areas to be closed, and the large area of concrete pavement at the traffic intersection has made it impossible to lay out electrodes. Therefore, the design and measurement of the lines of different geophysical methods have been adjusted according to the actual situation;

[0071] GPR method has a total of 9 lines, with a total length of 5471m, the longest line (L7) is 1400m, and the shortest line (L2) is 250m, with a point marked every 50m. Figure 8 GPR line layout diagram, actual measurement lines are consistent with the designed lines.

[0072] Microseismic measurement has a total of 9 lines, with the same line positions as GPR and CPT lines. The point spacing is 5m, the total number of measurement points is 1108, the total length of the lines is 5540m, the longest line (L7) is 1350m, and the shortest line (L2E) is 200m. Figure 9 Microseismic exploration line layout diagram.

[0073] CPT measurement has a total of 10 lines, with L10 added compared to the radar lines. The point spacing is 5m, the total number of measurement points is 1176, the total length of the lines is 5880m, the longest line (L7) is 1440m, and the shortest line (L2W and L10) is 130m. Figure 10 CPT line layout diagram.

[0074] Due to the limitations of the working conditions on site, high-density resistivity measurement has a total of 5 lines, namely L1, L4, L6, L7 and L8. The point spacing is 5m, the total number of measurement points is 623, the total length of the lines is 3115m, the longest line (L7) is 1350m, and the shortest line (L1) is 250m. Figure 11 High-density resistivity line layout diagram. Due to the poor grounding conditions of some electrodes during actual measurement, high-density resistivity measurement is used as a reference for the interpretation of other methods.

[0075] Next, the measurement results and interpretation of two typical lines are given.

[0076] (1) Comprehensive interpretation of line L1

[0077] The measuring line L1 is laid along the Ruijiang branch, and FIG. 12 is a measurement result map of several geophysical methods of the measuring line, wherein FIG. 12(a) is a radar image map of the measuring line L1; FIG. 12(b) is a transient electromagnetic method result map of the measuring line L1; FIG. 12(c) is a microseismic result map of the measuring line L1;

[0078] FIG. 12(d) is a high-density resistivity method result map of the measuring line L1-1; and FIG. 12(e) is a high-density resistivity method result map of the measuring line L1-2. As can be seen from the radar image map, an obvious reflection interface (red line) appears in the upper part of the measuring line, and combined with the existing geological data of the survey area, it is speculated that it is quaternary miscellaneous fill. The surface layer is concrete or asphalt pavement, and the pavement below is loose layer with a thickness of about 0.8-1.0m, the thickness changes little, and the distribution is relatively uniform. The miscellaneous fill below is hydraulic fill (silty clay, fine sand, etc.), which is reflected as strong reflection wave energy on the radar waveform. The phase axis is obviously arched, the regular and symmetrical diffraction arc is a tubular object, and various pipelines may cause secondary diseases such as non-compaction, void, etc. (blue circle position on the map).

[0079] In the transient electromagnetic resistivity profile, according to the longitudinal difference of resistivity, it is reflected that there are three layers in depth, the first layer presents high resistance characteristics, the bottom interface of which changes violently in the depth range of 6-12m; the second layer bottom interface is the bedrock surface, the depth of which is between 25-32m, and the electrical property presents medium-low resistance characteristics; the third layer below the bedrock surface presents medium-high resistance characteristics. In the horizontal distance range of 20-60m at the left end of the measuring line, there is a downward extending low resistance zone, the center depth of which is about 20m, and there is a low resistance zone at the depth of 10m and the horizontal distance of 100-120m. In the microseismic transverse wave velocity profile, the microseismic profile also presents obvious layered characteristics, the first layer velocity is less than 220m / s, the layer thickness is about 5-10m; the second layer velocity is 220-450m / s, the layer thickness is 15-25m; the third layer velocity is >450m / s, and the local area (horizontal distance 100-155m) below the bedrock surface presents low velocity reaction. The high-density resistivity electrode grounding condition is poor, and the profile is only for reference.

[0080] According to the existing geological and drilling data in the study area, it is believed that the L1 line has a three-layer structure. The first layer has a bottom interface depth of about 10 m, with large lateral changes (red dotted line), mainly composed of miscellaneous fill, hydraulic fill and part of silty clay. This layer has high resistivity and low velocity characteristics. Because the phreatic aquifer is located in this layer, the water content of the rock at different positions in the line is different, resulting in large lateral changes in resistivity. The second layer has a bottom interface depth of about 27 m, with clear layer interfaces and large lateral changes (black dotted line), mainly composed of silty clay, medium-coarse sand and coarse gravel. This layer has medium-low resistivity and velocity characteristics, which is the boundary bedrock surface between the Quaternary stratum and the underlying gravel. The third layer is below the bedrock surface, mainly composed of strongly and moderately weathered gravel, with medium-high resistivity and high velocity characteristics.

[0081] The low-resistivity area at a horizontal distance of 100-120 m and a depth of 10 m in the transient electromagnetic profile is close to the Cangkou fault, which may be a fault fracture zone. Within a horizontal distance of 170-210 m in the transient electromagnetic and microseismic profiles, there is a downward extending contour segment area, which is speculated to be a gravel fracture zone. The microseismic profile shows low velocity response at a horizontal distance of 100-155 m, which is at the bottom boundary of the transient electromagnetic profile. It is speculated that the gravel is fractured and may be water-rich at this location (yellow dotted line range). The high-density resistivity line is divided into two sections due to the hardening road surface in the middle. The inversion results show that the surface hydraulic fill and miscellaneous fill have a depth of about 7-10 m. High-resistivity anomalies appear at the middle 80 m of line L1-1 and the middle 45 m of line L1-2, which are speculated to be boulder responses.

[0082] (2) Interpretation of line L8

[0083] Line L8 is located along the Ruisanda Road. Figure 13 shows the measurement results of several geophysical methods for this line. In Figure 13, Figure 13(a) is the radar image of line L8; Figure 13(b) is the transient electromagnetic method result of line L8; Figure 13(c) is the microseismic result of line L8; and Figure 13(d) is the high-density resistivity method result of line L8. From the radar image, it can be seen that there is a clear reflection interface above the red line, which is speculated to be the Quaternary miscellaneous fill. The surface is mainly concrete or asphalt pavement with a thickness of 0.8-1.0 m, and the overall thickness changes little and is evenly distributed. Below the miscellaneous fill is the hydraulic fill, mainly composed of silty clay and fine sand. The blue circle position in the figure is the response of the pipeline, which shows strong reflected wave energy on the radar waveform, with a clear arch on the phase axis and regular and symmetrical diffraction arcs, which can easily cause secondary diseases such as non-compaction and void. No obvious non-compaction or void area is found in this section of the line.

[0084] In the transient electromagnetic resistivity and microseismic shear wave velocity profile, according to the longitudinal difference of resistivity and wave velocity, it reflects that it has three-layer structure in depth, the first layer presents medium-high resistance characteristics, the velocity is less than 220 m / s, the layer thickness is about 10 m, the bottom interface is in the depth of 10-15 m, and the lateral distribution is uniform; the second layer bottom interface is the bedrock surface, its depth is between 30-35 m, the lateral change is large, the layer thickness is about 20 m, and the electrical performance is low resistance characteristics, the velocity is 220-450 m / s; the third layer below the bedrock surface presents medium-high resistance characteristics, the velocity is > 450 m / s. The low resistance area extending downward appears in the horizontal distance of 260-300 m of the transient electromagnetic profile, which should be connected with the low velocity area in the horizontal distance of 300-380 m of the microseismic profile.

[0085] According to the existing geology and drilling data of the study area, comprehensive analysis shows that L8 measuring line has three-layer stratum structure. The first layer bottom interface depth is about 12 m, the lateral distribution is uniform (red dotted line), mainly for miscellaneous fill, fill and part of silty clay; the stratum has medium-high resistivity and low velocity characteristics in physical properties, because the phreatic aquifer is located in the layer, the water content of the rock at different positions in the measuring line is different, which makes the lateral change of resistivity large. The second layer bottom interface depth is about 35 m, the layer interface is clear, the lateral distribution is uniform (black dotted line), mainly for silty clay, medium-coarse sand and coarse gravel; the stratum has medium-low resistivity and medium velocity characteristics in physical properties, which is the division bedrock surface of quaternary stratum and lower gravel. The third layer is below the bedrock surface, mainly for strong and medium weathered gravel, which presents high resistivity and high velocity characteristics in physical properties. The low resistance and low velocity area near the horizontal distance of 300 m of the measuring line is speculated to be the bedrock fracture zone.

[0086] The high-density resistivity inversion result shows that the resistivity presents obvious stratified characteristics, the shallow area presents high resistance characteristics, combined with the site reconnaissance situation, it is speculated that it reflects the comprehensive situation of surface concrete, asphalt pavement, artificial fill and underground infrastructure, the layer thickness is about 0-10 m. It presents a relatively coherent medium-high resistance band downward, which is speculated to be the surface fill, miscellaneous fill; the deep low resistivity area is speculated to be the strong weathered bedrock area with local water enrichment.

[0087] According to the geophysical data processing results, the reflection depth of the geological radar is 5-7m or less, which is mainly used to reveal the integrity of the concrete pavement, the distribution range of underground pipelines and the possibility of geological disaster. The shallow interpretation is mainly based on the geological radar results, and the data results are used for shallow correction in geological modeling. Due to the characteristics of cable arrangement measurement of high-density resistivity method, the data acquisition in the study area is limited by poor electrode grounding and closed measurement area, and the obtained data and results are used as reference for geological interpretation of corresponding lines within 30m. The transient electromagnetic and micro-motion exploration data are relatively complete, and the revealed stratum depth is limited to 50m and 80m. On the basis of drilling and radar data constraints, the database of the two methods can be established to construct a three-dimensional geophysical model, which lays the foundation for three-dimensional geological modeling. Figure 14 The three-dimensional resistivity model is established according to the high-density resistivity method and the transient electromagnetic method.

[0088] The above is only the preferred embodiment of the present application, it should be noted that for those skilled in the art, without departing from the principles of the present application, can make a number of improvements and refinements, these improvements and refinements should also be considered as the protection scope of the present application. The structures, devices and operation methods not specifically described and explained in the present application, such as no special description and limitation, are implemented according to the conventional means in the art.

Claims

1. A comprehensive data acquisition method for shallow geological structure detection in the land-sea boundary zone of coastal cities, characterized in that: It comprises the following steps: Step 1: Multi-method collaborative layered detection by using geological radar, high-density resistivity method, cone transient electromagnetic method and micro-oscillation exploration; the detection depths are 5 meters, 30 meters, 50 meters and 80 meters respectively; Step 2: Realize integrated analysis of shallow geological structure by RTK dynamic positioning and layered data fusion technology.

2. The method according to claim 1, wherein the method is characterized by: In the step 1: Geological radar: the detection depth is 5 meters, 100MHz center frequency antenna is used, the scanning speed is 600 channels / s, the time window is 256ns, the measuring point interval is 50 meters, the antenna interval is 0.5 meters, and the signal-to-noise ratio is greater than or equal to 120dB; The high-density resistivity method: the detection depth is 30 meters, the electrode distance is 5 meters, the power supply electrode distance is 6-10 times the depth of the exploration target, and the total mean square relative error is less than or equal to 1.83%(I class standard); The cone transient electromagnetic method: the detection depth is 50 meters, the transmitting current is greater than or equal to 9A, the time window range is 0.004-127.483ms, the acquisition time window is 112, and the data curve class rate is greater than or equal to 85%; The micro-oscillation exploration: the detection depth is 80 meters, the detector array is one-dimensional linear arrangement(30 detectors, measuring point distance 5 meters), the sampling frequency is 500Hz, the acquisition time is 20 minutes, and the root mean square error is less than or equal to 3.67%.

3. The method according to claim 1, characterized in that: In the step 1, the multi-method collaborative process in the multi-method collaborative layered detection comprises the following steps: Step a: The geological radar rapidly scans the depth range within 5 meters to identify the shallow stratum interface and abnormal body; Step b: The high-density resistivity method densely detects the depth range within 30 meters, and optimizes the electrode layout in combination with the geological radar results; Step c: The cone transient electromagnetic method detects the depth range within 50 meters to cover the middle-deep layer electrical structure and verify the resistivity method results; Step d: The micro-oscillation exploration detects the depth range within 80 meters to obtain the deep stratum shear wave velocity and supplement the structure information; Step e: Data fusion and three-dimensional modeling, combined with drilling data to verify the accuracy.

4. The method according to claim 1, characterized in that: In the working process of the geological radar, the antenna interval and polarization direction are dynamically adjusted to suppress the random noise caused by sea wind; in the transient electromagnetic method, late data screening is adopted to reduce the electromagnetic interference caused by tidal activity; in the micro-oscillation exploration, rolling measurement and repeated observation(≥5% measuring points) are adopted.

5. The method according to claim 1, wherein the method is characterized by: In the step e, in the data processing process of the geological radar, first, the original record is obtained, then the head and tail waste sections are cut off, then the horizontal distance is balanced, then the measurement direction is adjusted, then zero point correction is performed, then horizontal filtering and vertical filtering are performed, then dielectric constant or electromagnetic wave velocity identification and high-conductivity body influence distribution point identification are performed to identify the target signal, and finally the underground geological body distribution characteristics are output.

6. The method according to claim 1, wherein the method is characterized by: In the data processing process of the high-density data, first, data preprocessing is performed to remove mutation points and smooth data; the measuring points with tens of times difference compared with the adjacent resistivity are removed in the data preprocessing editing, and then curve interpolation is performed; then inversion imaging is performed, the collected data is converted into apparent resistivity, and the data is inverted to obtain the true resistivity of the underground electrical structure.

7. The method according to claim 1, characterized in that: In step e, in the process of processing transient electromagnetic data, first, the field collected data is edited, outliers are removed, and noise is removed; then, near-field correction and other data preprocessing are performed; finally, one-dimensional and two-dimensional inversion imaging processing is performed.

8. The method according to claim 1, characterized in that: In step e, in the process of processing microseismic data, the microseismic data is automatically processed by using the most commonly used SPAC method, and the processing steps are as follows: first, different geophone distances in a station array are grouped, and each group is processed; then, the data recorded for a long time is screened and segmented, and the data with obvious interference and invalidity are extracted; Then, the screened data is preprocessed, and the preprocessing includes removing direct current, removing mean value, and normalizing; Then, the Fourier transform is performed to calculate the self-power spectrum of each station array data and the mutual power spectrum between each two stations; then, after obtaining the power spectrum, the autocorrelation coefficient between each two stations is calculated; Then, the autocorrelation coefficients of the same geophone distance, that is, the station radius combination mode, are averaged to obtain the average correlation coefficient; then, the autocorrelation coefficients of different distance combination modes are fitted with the first type of standard zero-order Bessel function to obtain the frequency dispersion curve; finally, the frequency dispersion curve is segmented and averaged to obtain the average frequency dispersion curve.

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