A high-precision method for detecting the thickness of marine rock-filled layers based on multi-source physical fields

Abstract

This invention provides a high-precision method for detecting the thickness of marine boulder layers based on multi-source physical fields. The method includes: processing the frequency imaging results based on the shear wave velocity of the boulder layer in the survey profile using a frequency imaging method to obtain a geophysical measurement of the boulder layer thickness; drilling a geological borehole at the borehole location to obtain the true thickness of the boulder layer at that location, and calculating the ratio k between the true thickness and the measured thickness at the borehole location; and correcting the obtained geophysical measurements of the boulder layer thickness based on the ratio k to obtain continuous thickness values ​​of the boulder layer detected by the frequency imaging method. This high-precision method for detecting the thickness of marine boulder layers based on multi-source physical fields significantly improves the accuracy of stratigraphic division by utilizing the resonance principle of seismic wave signals propagating in the strata.

Description

Technical Field

[0001] This invention belongs to the field of geological exploration technology, and in particular relates to a high-precision method for detecting the thickness of marine rock layers based on multi-source physical fields. Background Technology

[0002] For the construction of offshore artificial islands, the rock-filling method has become a widely adopted approach due to its simplicity and speed. During the island-building process, rocks are directly dumped onto the original seabed surface. This causes the silt and silty soil layers at the top of the seabed to be impacted by the filling load in a short period, resulting in shear failure and the formation of large slip surfaces, creating silt mounds and causing silt arching. This is very common in rock-filling island construction, and some silt mounds even protrude above the surface. The mud-rock interface formed during the artificial island construction process often has undulating and drastically changing morphology, and the thickness distribution of the soft soil layer is extremely uneven. If not handled properly, it can easily cause uneven settlement of the superstructure. Therefore, it is essential to accurately determine the continuous distribution characteristics of the silt mound thickness beneath the rock-filled layer as data support for foundation treatment design. Currently, traditional drilling is commonly used to detect the distribution of silt mounds. However, this method is inefficient, highly random, and costly, and can no longer meet the project's requirement for continuous distribution characteristics of silt mounds. Summary of the Invention

[0003] In view of this, the present invention aims to propose a high-precision detection method for the thickness of marine rock-filled layers based on multi-source physical fields, in order to solve the problems of low efficiency, high randomness, and poor detection effect of existing silt bag detection methods.

[0004] To achieve the above objectives, the technical solution of the present invention is implemented as follows:

[0005] A high-precision method for detecting the thickness of marine rock-filled layers based on multi-source physical fields includes:

[0006] Obtain the data of the project to be tested, and design the layout of the survey lines and boreholes based on the data of the project to be tested, so that the survey lines and boreholes can cover the load-bearing parts of the proposed superstructure of the project to be tested.

[0007] Multiple frequency imaging detectors are arranged at preset intervals on the measuring line, and the x, y, z spatial positions of the frequency imaging detectors are measured using RTK. After a preset observation and acquisition time, the frequency imaging results are obtained.

[0008] Remove the frequency imaging detector and place a numbered multi-point active source surface wave detector in the same position.

[0009] A mechanical seismic source is vertically arranged on the survey line. The mechanical seismic source actively generates seismic wave signals, and the multi-point active source surface wave detector receives the echo signals. Data is collected according to the numbers from small to large to obtain the surface wave acquisition results. The mechanical seismic source and the multi-point active source surface wave detector are set up in a one-to-one correspondence and are set at a certain distance apart.

[0010] The surface wave acquisition results are processed using a cross-correlation superposition algorithm to obtain the shear wave velocity of the riprap layer in the survey profile.

[0011] Based on the shear wave velocity of the boulders layer in the survey profile, the frequency imaging results are processed using the frequency imaging method to obtain the measured value of the boulders layer thickness based on the geophysical method.

[0012] Geological drilling is performed at the drilling location to obtain the true value of the rockfill layer thickness at the drilling location, and the ratio k of the true value of the rockfill layer thickness at the drilling location to the measured value of the rockfill layer thickness is calculated.

[0013] Based on the ratio k, the obtained rock-fill layer thickness measurements based on geophysical exploration are corrected to obtain continuous rock-fill layer thickness values ​​detected by frequency imaging.

[0014] Furthermore, the process involves arranging multiple frequency imaging detectors at preset intervals along the measuring line, measuring the x, y, and z spatial positions of the frequency imaging detectors using RTK, and obtaining frequency imaging results after a preset observation and acquisition time, including:

[0015] Multiple frequency imaging detectors are arranged at 2m intervals along the measuring line, and each frequency imaging detector is kept vertically positioned.

[0016] The x, y, z spatial positions of a frequency imaging detector were measured using RTK.

[0017] After observing and collecting data for 20 minutes using the frequency imaging detector, the frequency imaging results were obtained.

[0018] Furthermore, the mechanical seismic source and the multi-point active source surface wave detector are spaced 20cm apart.

[0019] Furthermore, the step of processing the surface wave acquisition results using a cross-correlation superposition algorithm to obtain the shear wave velocity of the riprap layer in the survey profile includes:

[0020] Set a time interval window in the time-space domain that can display all waveforms to highlight the fundamental surface wave characteristics and obtain surface wave records;

[0021] The surface wave record is converted into a dispersion curve in the frequency-wavenumber domain, and the maximum value data of the surface wave dispersion in the dispersion curve is extracted and converted into a dispersion curve in the depth-velocity domain to obtain dispersion curve data of the overall velocity increasing type.

[0022] By using the dispersion curve data of the overall velocity increasing type to divide the stratigraphic boundary points, and obtaining the shear wave velocity of the strata above the boundary points, the shear wave velocity of the riprap layer in the survey profile is obtained through cross-correlation calculation.

[0023] Furthermore, the step of processing the frequency imaging results based on the shear wave velocity of the boulders layer in the survey profile using frequency imaging to obtain the measured thickness of the boulders layer based on geophysical methods includes:

[0024] Interference suppression is applied to the frequency imaging results to improve the signal-to-noise ratio, thus obtaining the original signal data;

[0025] The resonant frequency features of the original signal data are extracted, and the geological image of the boulders in the survey profile is inverted using the shear wave velocity of the boulders in the survey profile.

[0026] Based on the geological imaging of the riprap layer in the survey profile, the thickness measurement value of the riprap layer based on geophysical exploration is obtained.

[0027] Furthermore, the step of extracting resonant frequency features from the original signal data and using the shear wave velocity of the boulders layer in the survey profile to invert the geological image of the boulders layer in the survey profile includes:

[0028] The resonant frequency features of the original signal data are extracted and used as the objective function.

[0029] An improved genetic algorithm was used, along with the shear wave velocity of the boulders layer in the survey profile, to perform inversion in the depth domain to obtain a geological image of the geological body thickness.

[0030] Furthermore, the step of drilling a geological borehole at the borehole location to obtain the true value of the rockfill layer thickness at the borehole location, and calculating the ratio k between the true value of the rockfill layer thickness at the borehole location and the measured value of the rockfill layer thickness, includes:

[0031] Using a down-the-hole drill bit, a geological borehole was drilled at the borehole location. The rock was broken and the hole was drilled downwards until the silt surface elevation was reached. Then, the core tube was replaced and 2m of silt was taken out.

[0032] The true thickness of the riprap layer is obtained by measuring the length of the drill rod from the borehole opening to the mud-rock interface.

[0033] Obtain the measured value of the rockfill layer thickness at the borehole location, and calculate the ratio k between the actual value of the rockfill layer thickness at the borehole location and the measured value of the rockfill layer thickness.

[0034] Compared with existing technologies, the high-precision detection method for marine rock-fill layer thickness based on multi-source physical fields described in this invention has the following advantages:

[0035] This invention discloses a high-precision method for detecting the thickness of marine boulders based on multi-source physical fields. By utilizing the resonance principle of seismic wave signal propagation in strata, the method significantly improves the accuracy of stratigraphic division. Simultaneously, by using active-source surface waves for relevant calculations, a more realistic apparent velocity value of propagation in the strata is obtained. This value is then used for stratum depth calculation in frequency imaging methods, greatly improving the accuracy of layer thickness detection. Finally, borehole drilling is used to verify and correct the above results using the actual layer thickness values ​​revealed in the field, achieving high-precision detection of the thickness of marine boulders. Attached Figure Description

[0036] The accompanying drawings, which form part of this invention, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an undue limitation of the invention. In the drawings:

[0037] Figure 1 This is a flowchart illustrating a high-precision detection method for the thickness of marine rock-filled layers based on multi-source physical fields, as described in an embodiment of the present invention.

[0038] Figure 2 This is a schematic diagram of frequency imaging results in a high-precision detection method for the thickness of marine rock-filled layers based on multi-source physical fields, as described in an embodiment of the present invention. Detailed Implementation

[0039] The present invention will now be described in further detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and not intended to limit it. Furthermore, it should be noted that, for ease of description, the accompanying drawings show only the parts relevant to the present invention, and not all of the structures.

[0040] Figure 1 This is a flowchart illustrating a high-precision method for detecting the thickness of marine rock-filled layers based on multi-source physical fields, as described in an embodiment of the present invention. This method enables rapid, continuous, and high-precision detection of silt pockets within the rock-filled layer. See also... Figure 1 This method specifically includes the following steps:

[0041] Step 101: Obtain the data of the project to be tested, and design the layout of the survey lines and boreholes according to the data of the project to be tested, so that the survey lines and boreholes can cover the load-bearing parts of the proposed superstructure of the project to be tested.

[0042] In the preparation phase before exploration, data on the project to be measured can be collected, including the construction process of the riprap layer, surface information of the riprap layer, and the preliminary depth of the riprap layer. Then, the survey line layout and drilling can be designed accordingly. The layout principle is to select open, flat surfaces as much as possible, while covering the key load-bearing parts of the proposed superstructure. Furthermore, in practical applications, consistency testing of the frequency imaging detector and the multi-point active source surface wave detector is necessary to ensure the consistency of the detector parameters, which is beneficial for improving detection accuracy.

[0043] Step 102: Arrange multiple frequency imaging detectors at preset intervals on the measuring line, and use RTK to measure the x, y, z spatial positions of the frequency imaging detectors. After observing and collecting data for a preset time, obtain the frequency imaging results.

[0044] Specifically, step 102 includes the following steps:

[0045] Step 1021: Arrange multiple frequency imaging detectors at 2m intervals on the measuring line, and keep each frequency imaging detector vertically positioned.

[0046] Step 1022: Measure the x, y, z spatial positions of the frequency imaging detector using RTK. Here, RTK measurement is an engineering term. In GPS measurements, static, rapid static, and dynamic measurements all require post-processing to obtain centimeter-level accuracy. RTK (Real-time kinematic) real-time differential positioning is a measurement method that can obtain centimeter-level positioning accuracy in real time in the field, greatly improving the efficiency of field operations.

[0047] Step 1023: After observing and acquiring data with the frequency imaging detector for 20 minutes, the frequency imaging results are obtained.

[0048] Natural source seismic frequency imaging, similar to data application methods in the electromagnetic field, utilizes the inherent frequency characteristics of boulders for identification and detection. Fundamental physics has long established that every object possesses its own inherent frequency, which is related to various physical parameters (geophysical scale, shape, density, P-wave velocity, S-wave velocity, etc.). Therefore, the inherent frequency of underground geological bodies can indirectly reflect their depth and physical properties. Underground strata possess specific inherent frequencies. When vibrations of a particular frequency act on a geological body, it causes resonance, resulting in a significant increase in the amplitude of seismic waves at that frequency. Vibrations of other frequencies acting on the same geological body exhibit significant attenuation.

[0049] Figure 2 This is a schematic diagram of frequency imaging results in a high-precision detection method for the thickness of marine rock-filled layers based on multi-source physical fields, as described in an embodiment of the present invention. (See also...) Figure 2The upper part of the cross-section is a layer of artificially filled crushed stone, which is sourced from quarrying. The stone is irregular in shape, varies in particle size, and is randomly piled up with high porosity, which is reflected as a strong frequency domain amplitude on the frequency imaging cross-section. The lower part is a layer of original marine sediments such as silt and silty soil, which is relatively uniform in texture and is reflected as a weaker frequency domain amplitude.

[0050] Assuming each stratum is equivalent to a damped spring with mass, the thickness detection of the riprap layer can be simplified to a model of riprap on top and mud underneath. According to vibration theory, this model conforms to a two-degree-of-freedom vibration system. The motion state of a two-degree-of-freedom vibration system needs to be characterized by two independent coordinates x1 and x2 (the equilibrium position when the system is at rest is the zero point). A simple force analysis of the system yields the vibration equation:

[0051]

[0052] Where: m1 and m2 are the equivalent mass of the stratum, which can be represented by the product of unit volume and density. The unit volume can be simplified to the product of unit area and thickness H. k1 and k2 are the spring stiffness coefficients, c1 and c2 are the damping coefficients, x1 and x2 are the vibration displacements of the stratum, and F is the vibration force.

[0053] Let F be the simple harmonic force, i.e., F = F0e ikwt Let ω be the vibration frequency. Substituting it into the equation, rearranging, deriving, and simplifying, we can obtain the relationship between the characteristic (natural) frequency and the thickness:

[0054] H = V / 2af (3)

[0055] The relationship between the amplitude of the characteristic frequency and the physical properties of the medium:

[0056]

[0057] Z 11 Z 12 Z 22 It is related to the vibration frequency, mass, elastic modulus, and damping coefficient. Since the damping coefficient is related to Q, we have:

[0058]

[0059] In the formula, the maximum amplitude is obtained when the external source frequency is the same as the natural frequency. It can be seen that the characteristic amplitude of the resonant characteristic frequency observed by resonance imaging is related to the mass, stiffness and damping of the formation. Through various parameter combinations, it is actually related to the velocity, density and damping coefficient.

[0060] Since the frequency characteristics of external vibrations are time-varying, while the natural frequencies of the strata are time-invariant, the records observed in the field using portable broadband three-component seismic stations are shown in Equation 9, where m represents micro-vibrations of the strata, S represents external vibrations, and G represents the time-domain records observed at the surface:

[0061] G(t)=M(h,v)*S(t) (8)

[0062] In the frequency domain, it is:

[0063] G(f) = M(f) * S(f) (9)

[0064] M is a frequency filter composed of the natural frequencies of the geological structure, which is time-invariant, while S is the frequency of the external seismic source, which is time-varying. Accurate time-frequency analysis results can be obtained through high-order compressed time-frequency analysis. Long-term statistical analysis can suppress S and thus obtain M.

[0065] The extracted M is essentially the natural frequency vibration information of strata with different equivalent thicknesses. By combining formulas (5), (6), and (7) and using the layer-stripping method to eliminate the overlying strata effect, the thickness and characteristic amplitude information of each individual stratum can be obtained. Therefore, the presence of seismic waves of multiple frequencies in the natural source vibration signal can cause different strata to resonate. When the broadband natural vibration propagates to the geological body, the characteristic natural frequency energy will be amplified. By observing the amplified characteristic frequency signal, the characteristic frequency signal can be imaged, thereby obtaining a fine imaging effect of the boulders layer.

[0066] In practical applications, the frequency imaging detector consists of three mutually orthogonal low-frequency, high-sensitivity acquisition node units with a frequency of 0.2Hz. When placing it, ensure that the base is stable, vertical, and well coupled with the boulders layer.

[0067] Step 103: Remove the frequency imaging detector and place a numbered multi-point active source surface wave detector in the same location.

[0068] In practical applications, multi-point active source surface wave detectors are numbered one by one along the length of the survey line, and the numbers are arranged from smallest to largest.

[0069] Step 104: The mechanical seismic source is vertically arranged on the survey line. The mechanical seismic source actively excites the seismic wave signal, and the multi-point active source surface wave detector receives the echo signal. Data is collected according to the number from small to large to obtain the surface wave acquisition result. The mechanical seismic source and the multi-point active source surface wave detector are set in a one-to-one correspondence and are set at a certain distance apart.

[0070] Specifically, the mechanical seismic source and the multi-point active source surface wave detectors are spaced 20cm apart. By using a mechanical seismic source perpendicular to the survey line, seismic wave signals are actively excited at a distance of 20cm from the multi-point active source surface wave detectors. Each multi-point active source surface wave detector receives the echo signals and collects data sequentially from smallest to largest.

[0071] Since geological bodies are heterogeneous, the broadband characteristics of natural source seismic waves can cover more of the inherent frequencies of the objects being probed, effectively identifying the interfaces between different geological bodies. However, the low frequency of natural seismic waves leads to errors in determining the wave velocity within the geological body, affecting the accurate calculation of the geological body's thickness. Therefore, multi-point active source surface wave technology is introduced.

[0072] Step 105: Process the surface wave acquisition results using the cross-correlation superposition algorithm to obtain the shear wave velocity of the riprap layer in the survey profile.

[0073] Multi-point active source surface wave technology generates high-frequency seismic waves through active excitation. Surface wave signals are excited next to each multi-point active source surface wave detector, and are received by multi-point active source surface wave detectors arranged at equal intervals on the measured line. Through cross-correlation calculations between different multi-point active source surface wave detectors, the shear wave velocity of the formation can be measured more accurately.

[0074] Specifically, the surface wave detection method employs a cross-correlation superposition algorithm. In the time-space domain, i.e., the "XT domain," an appropriate time interval window is set to highlight the characteristics of the fundamental surface wave and eliminate the influence of other interfering waves. The surface wave record is converted into a dispersion curve in the frequency-wavenumber domain (FK domain). In the "FK domain," the maximum dispersion data of the surface wave is extracted and converted into a dispersion curve in the depth-velocity domain (ZV domain). In the "ZV domain," using the obtained dispersion curve data of the overall velocity increasing type, a human-computer interaction method (the existing processing software has built-in functions that automatically track the interface, and manual adjustment is required in places where there are obvious errors) is used to delineate the stratigraphic boundary points. Based on the geometric boundary conditions, the shear wave velocity of the riprap layer in the entire survey profile is calculated using cross-correlation.

[0075] In practical applications, the theoretical basis of surface wave signal processing is as follows:

[0076] Establish the objective function for the surface wave dispersion curve:

[0077]

[0078] C(ω)=ω / k(ω) (11)

[0079] The spectrum D(c,ω) of the surface wave signal can be obtained by applying Radon transform and FFT transform, where c is the phase velocity and ω is the angular frequency. From the spectrum, the dispersion curve of the fundamental wave is selected to obtain κ(ω) = ω / C(ω), where k(ω) is the wave number.

[0080] Then, by superimposing the above formula, the gradient function of the objective function with respect to the shear wave velocity is:

[0081]

[0082] The linear search iterative formula using the fastest descent direction is as follows:

[0083]

[0084] Equation (13) is superimposed using different exponents. When the calculated residual is lower than the required standard, the shear wave velocity model can be obtained using equation (13).

[0085] a. Use window suppression to remove direct body waves, backscattered data, and higher-order Rayleigh waves from the shot concentration, then apply a one-dimensional Fourier transform along x g The coordinates are used to obtain its spectrum. The same suppression method is applied to the predicted shot gather and observation data obtained by finite difference calculations using the elastic wave equation.

[0086] b. Apply the Linear Radon Transform (LRT) to the spectrum of the predicted and observed data to obtain the phase velocity image within the ω-C region, where C is the phase velocity of the surface wave. The fundamental dispersion curve is automatically extracted based on the maximum amplitude of the phase velocity spectrum.

[0087] c. Calculate the weighted values The forward propagation wavefield is also weighted when calculating the reverse propagation data.

[0088] d. Use a linear search method to estimate the inversion iteration step size α.

[0089] e. Superimpose the gradients of each offset gather to obtain the new S-wave velocity. Repeat step ad above to iteratively update the S-wave velocity model until the residual meets the minimum criterion.

[0090] For example, the multi-point active source surface wave detector uses an integrated short-period, high-sensitivity single-component seismic acquisition node with a frequency of 5Hz. During field data acquisition, a linear arrangement is used, with the same frequency imaging method detectors at the same channel spacing, ensuring verticality, stability, and coupling with the ground surface. Mechanical seismic source excitation is initiated perpendicular to the survey line, with the detector as the vertical foot, at a distance of 20cm. The mechanical seismic source hammer weighs 25kg and drops from a height of 30cm. This is performed sequentially near each detector until all detector-side seismic source acquisitions are completed.

[0091] Specifically, step 105 includes the following steps:

[0092] Step 1051: Set a time interval window in the time-space domain that can display all waveforms to highlight the fundamental surface wave characteristics and obtain surface wave records.

[0093] Step 1052: Convert the surface wave record into a dispersion curve in the frequency-wavenumber domain, and extract the maximum value data of the surface wave dispersion in the dispersion curve to convert it into a depth-velocity domain dispersion curve, thereby obtaining dispersion curve data of the overall velocity increasing type.

[0094] Step 1053: Using the dispersion curve data of the overall velocity increasing type, divide the stratigraphic boundary points, obtain the shear wave velocity of the strata above the boundary points, and then calculate the shear wave velocity of the riprap layer in the survey profile through cross-correlation.

[0095] In practical applications, the specific operation method is as follows: screen the waveforms displayed in the "XT domain", set an appropriate time interval window to display all waveforms, select the fundamental surface wave and eliminate the influence of other interference waves, and convert the multi-channel transient surface wave records in the time-space domain into dispersion curves in the frequency-wavenumber domain (FK domain); in the "FK domain", extract the maximum value data of surface wave dispersion and convert it into a ZV domain dispersion curve; enter "ZV domain processing", use the obtained dispersion curve data of the overall velocity increasing type to divide the stratigraphic boundary point and obtain the shear wave velocity of the strata above the boundary point.

[0096] Step 106: Based on the shear wave velocity of the boulders layer in the survey profile, the frequency imaging results are processed using the frequency imaging method to obtain the measured value of the boulders layer thickness based on the geophysical method.

[0097] Since frequency imaging acquires natural ultra-low frequency seismic wave signals, it is necessary to perform methods such as outlier suppression, extra surface wave suppression, and single-frequency interference suppression to improve the signal-to-noise ratio and obtain high-quality signal data.

[0098] Specifically, the basic process of frequency imaging data processing is as follows: Based on the field measurement results and field plan design, the spatial location of the observation system is defined; the raw data undergoes fine preprocessing, mainly including: suppression of anomalous amplitude noise (outliers), suppression of surface wave noise, and suppression of single-frequency interference; based on the raw data with a high signal-to-noise ratio, the resonant frequency characteristics are extracted and used as the objective function. Using an improved genetic algorithm, the relatively accurate shear wave velocity obtained by the multi-point source surface wave method is inverted in the depth domain to obtain the thickness of the geological body. Based on the Z-coordinate value of the survey line surface and the actual thickness value of the riprap layer exposed by the borehole, elevation and depth calibration correction is performed to form the final interpretation data.

[0099] In practical applications, step 106 specifically includes the following steps:

[0100] Step 1061: Perform interference suppression on the frequency imaging results to improve the signal-to-noise ratio and obtain the original signal data.

[0101] Step 1062: Extract the resonance frequency features from the original signal data, and use the shear wave velocity of the boulders layer in the survey profile to invert the geological image of the boulders layer in the survey profile.

[0102] Specifically, the resonant frequency features of the original signal data can be extracted first and used as the objective function. Then, an improved genetic algorithm is used, along with the shear wave velocity of the boulders layer in the survey profile, to perform inversion in the depth domain to obtain a geological image of the geological body thickness.

[0103] Step 1063: Based on the geological imaging of the riprap layer in the survey profile, obtain the thickness measurement value of the riprap layer based on the geophysical method.

[0104] Step 107: Conduct geological drilling at the borehole location to obtain the true value of the riprap layer thickness at the borehole location, and calculate the ratio k between the true value of the riprap layer thickness at the borehole location and the measured value of the riprap layer thickness.

[0105] Since it involves the design of foundation treatment schemes and engineering measurement, the accuracy requirements for detecting the thickness of the riprap layer are extremely high. In order to calculate the thickness of the riprap layer more accurately, geological downhole drilling can be carried out in typical areas, and the thickness of the riprap layer can be corrected by the thickness of the riprap layer revealed by the drilling.

[0106] Specifically, step 107 includes the following steps:

[0107] Step 1071: Use a down-the-hole drill bit to drill a geological hole at the specified drilling location, breaking the rock and drilling downwards until the silt surface elevation is reached. Then replace the core tube and take 2m of silt.

[0108] Step 1072: Measure the length of the drill rod from the borehole opening to the mud-rock interface to obtain the true value of the rock-fill layer thickness.

[0109] Step 1073: Obtain the measured value of the rock-fill layer thickness at the borehole location, and calculate the ratio k between the actual value of the rock-fill layer thickness at the borehole location and the measured value of the rock-fill layer thickness.

[0110] In practical applications, geological drilling can utilize down-the-hole drill bits to directly break the rock and drill downwards to the silt surface elevation. A core sample of 2m is then taken, and the drill rod length from the borehole opening to the silt interface is measured to determine the thickness of the riprap layer. The thickness value H obtained from the borehole is then compared with the actual thickness value obtained from the drilling. 钻孔 The thickness value H given by the frequency imaging method 频 The proportionality constant is obtained as k, and the formula is H. 钻孔 = k*H frequency.

[0111] Step 108: Based on the ratio k, correct the obtained rock-fill layer thickness measurements based on geophysical exploration to obtain the continuous thickness values ​​of the rock-fill layer detected by frequency imaging.

[0112] Specifically, the thickness values ​​of each profile measured by frequency imaging can be multiplied by a k-value and corrected to obtain the continuous thickness value of the riprap layer detected by frequency imaging. By comparing the actual thickness values ​​obtained from down-the-hole drilling with the elevation of the geophone position and correcting the calibrated geological profile, the thickness of the riprap layer at each borehole location can be made close to the true value.

[0113] This embodiment describes a high-precision method for detecting the thickness of marine boulders based on multi-source physical fields. The method involves acquiring data about the project under test and designing a survey line and borehole layout to cover the load-bearing parts of the proposed superstructure. Multiple frequency imaging detectors are arranged at preset intervals along the survey line. The x, y, and z spatial positions of the frequency imaging detectors are measured using RTK (Real-Time Kinematics) and observed for a preset time to obtain frequency imaging results. The frequency imaging detectors are then removed, and numbered multi-point active-source surface wave detectors are placed at the same locations. A mechanical seismic source is vertically positioned along the survey line to actively generate seismic wave signals. The echo signals are received by the multi-point active-source surface wave detectors, and data is collected from smallest to largest according to their numerical designation. The process involves obtaining surface wave acquisition results; wherein a mechanical seismic source and a multi-point active source surface wave detector are set up one-to-one, and the mechanical seismic source and the multi-point active source surface wave detector are set at a certain distance; the surface wave acquisition results are processed using a cross-correlation superposition algorithm to obtain the shear wave velocity of the riprap layer in the survey profile; based on the shear wave velocity of the riprap layer in the survey profile, the frequency imaging results are processed using a frequency imaging method to obtain the measured value of the riprap layer thickness based on the geophysical method; a geological borehole is drilled at the borehole location to obtain the true value of the riprap layer thickness at the borehole location, and the ratio k of the true value of the riprap layer thickness at the borehole location to the measured value of the riprap layer thickness is calculated; based on the ratio k, the obtained measured values ​​of the riprap layer thickness based on the geophysical method are corrected to obtain the continuous thickness value of the riprap layer detected by the frequency imaging method.

[0114] Compared to existing technologies, traditional seismic wave signals determine stratigraphic boundaries by tracking phase axes and amplitude signal strength. This embodiment utilizes the resonance principle of seismic wave signals propagating in strata for stratigraphic division, significantly improving the accuracy of stratigraphic division. Simultaneously, by using active source surface waves for relevant calculations, more realistic apparent velocity values ​​propagating in the strata are obtained. These values ​​are then used for stratigraphic depth calculation in frequency imaging methods, greatly improving the accuracy of layer thickness detection. Finally, borehole drilling is used to verify and correct the above results using the actual layer thickness values ​​revealed in the field, achieving high-precision detection of the thickness of marine riprap layers.

[0115] Note that the above description is merely a preferred embodiment of the present invention and the technical principles employed. Those skilled in the art will understand that the present invention is not limited to the specific embodiments described herein, and various obvious changes, readjustments, and substitutions can be made without departing from the scope of protection of the present invention. Therefore, although the present invention has been described in detail through the above embodiments, the present invention is not limited to the above embodiments, and may include many other equivalent embodiments without departing from the concept of the present invention, the scope of which is determined by the scope of the appended claims.

Claims

1. A high-precision method for detecting the thickness of marine rock-filled layers based on multi-source physical fields, characterized in that, include: Obtain the data of the project to be tested, and design the layout of the survey lines and boreholes based on the data of the project to be tested, so that the survey lines and boreholes can cover the load-bearing parts of the proposed superstructure of the project to be tested. Multiple frequency imaging detectors are arranged at preset intervals on the measuring line, and the x, y, z spatial positions of the frequency imaging detectors are measured using RTK. After a preset observation and acquisition time, the frequency imaging results are obtained. Remove the frequency imaging detector and place a numbered multi-point active source surface wave detector in the same position. A mechanical seismic source is vertically arranged on the survey line. The mechanical seismic source actively generates seismic wave signals, and the multi-point active source surface wave detector receives the echo signals. Data is collected according to the numbers from small to large to obtain the surface wave acquisition results. The mechanical seismic source and the multi-point active source surface wave detector are set up in a one-to-one correspondence and are set at a certain distance apart. The surface wave acquisition results are processed using a cross-correlation superposition algorithm to obtain the shear wave velocity of the riprap layer in the survey profile. Based on the shear wave velocity of the boulders layer in the survey profile, the frequency imaging results are processed using the frequency imaging method to obtain the measured value of the boulders layer thickness based on the geophysical method. Geological drilling is performed at the drilling location to obtain the true value of the rockfill layer thickness at the drilling location, and the ratio k of the true value of the rockfill layer thickness at the drilling location to the measured value of the rockfill layer thickness is calculated. Based on the ratio k, the obtained rock-fill layer thickness measurements based on geophysical exploration are corrected to obtain continuous rock-fill layer thickness values ​​detected by frequency imaging.

2. The method for high-precision detection of marine riprap layer thickness based on multi-source physical fields according to claim 1, characterized in that, The method involves arranging multiple frequency imaging detectors at preset intervals along the measuring line, measuring the x, y, and z spatial positions of the frequency imaging detectors using RTK, and obtaining frequency imaging results after a preset acquisition time, including: Multiple frequency imaging detectors are arranged at 2m intervals along the measuring line, and each frequency imaging detector is kept vertically positioned. The x, y, z spatial positions of a frequency imaging detector were measured using RTK. After observing and collecting data for 20 minutes using the frequency imaging detector, the frequency imaging results were obtained.

3. The high-precision detection method for the thickness of marine rock-filled layers based on multi-source physical fields according to claim 1, characterized in that: The mechanical seismic source and the multi-point active source surface wave detector are spaced 20cm apart.

4. The method for high-precision detection of marine rock-fill layer thickness based on multi-source physical fields according to claim 1, characterized in that, The process of using a cross-correlation superposition algorithm to process the surface wave acquisition results and obtain the shear wave velocity of the riprap layer in the survey profile includes: Set a time interval window in the time-space domain that can display all waveforms to highlight the fundamental surface wave characteristics and obtain surface wave records; The surface wave record is converted into a dispersion curve in the frequency-wavenumber domain, and the maximum value data of the surface wave dispersion in the dispersion curve is extracted and converted into a dispersion curve in the depth-velocity domain to obtain dispersion curve data of the overall velocity increasing type. By using the dispersion curve data of the overall velocity increasing type to divide the stratigraphic boundary points, and obtaining the shear wave velocity of the strata above the boundary points, the shear wave velocity of the riprap layer in the survey profile is obtained through cross-correlation calculation.

5. The method for high-precision detection of marine boulder layer thickness based on multi-source physical fields according to claim 1, characterized in that, The step of processing the frequency imaging results based on the shear wave velocity of the boulders layer in the survey profile, and obtaining the measured thickness of the boulders layer based on geophysical exploration, includes: Interference suppression is applied to the frequency imaging results to improve the signal-to-noise ratio, thus obtaining the original signal data; The resonant frequency features of the original signal data are extracted, and the geological image of the boulders in the survey profile is inverted using the shear wave velocity of the boulders in the survey profile. Based on the geological imaging of the riprap layer in the survey profile, the thickness measurement value of the riprap layer based on geophysical exploration is obtained.

6. The method for high-precision detection of marine boulder layer thickness based on multi-source physical fields according to claim 5, characterized in that, The step of extracting resonance frequency features from the original signal data and using the shear wave velocity of the boulders layer in the survey profile to invert the geological imaging of the boulders layer in the survey profile includes: The resonant frequency features of the original signal data are extracted and used as the objective function. An improved genetic algorithm was used, along with the shear wave velocity of the boulders layer in the survey profile, to perform inversion in the depth domain to obtain a geological image of the geological body thickness.

7. The method for high-precision detection of marine boulder layer thickness based on multi-source physical fields according to claim 1, characterized in that, The process of drilling a geological borehole at the borehole location to obtain the true value of the rockfill layer thickness at the borehole location, and calculating the ratio k between the true value of the rockfill layer thickness at the borehole location and the measured value of the rockfill layer thickness, includes: Using a down-the-hole drill bit, a geological borehole was drilled at the borehole location. The rock was broken and the hole was drilled downwards until the silt surface elevation was reached. Then, the core tube was replaced and 2m of silt was taken out. The true thickness of the riprap layer is obtained by measuring the length of the drill rod from the borehole opening to the mud-rock interface. Obtain the measured value of the rockfill layer thickness at the borehole location, and calculate the ratio k between the actual value of the rockfill layer thickness at the borehole location and the measured value of the rockfill layer thickness.

Images