High-precision detection method for thickness of riprap layer in sea based on multi-source physical field

Abstract

The invention provides an in-sea riprap layer thickness high-precision detection method based on a multi-source physical field, and the method comprises the steps: carrying out the data processing of a frequency imaging result through a frequency imaging method according to the shear wave speed of a riprap layer of a measuring line section, and obtaining a riprap layer thickness measurement value based on a geophysical prospecting method; geological drilling is carried out at the drilling position to obtain a real value of the thickness of the riprap layer at the drilling position, and the ratio k of the real value of the thickness of the riprap layer at the drilling position to the measured value of the thickness of the riprap layer is obtained through calculation; and based on the ratio k, correcting each obtained riprap layer thickness measurement value based on the geophysical prospecting method to obtain a riprap layer continuous thickness value detected based on the frequency imaging method. According to the high-precision detection method for the thickness of the riprap layer in the sea based on the multi-source physical field, stratigraphic division is carried out by utilizing the resonance principle of propagation of seismic wave signals in the strata, and the accuracy of stratigraphic division is remarkably improved.

Description

Technical Field

[0001] The invention belongs to the technical field of geological exploration, and in particular relates to a high-precision detection method for the thickness of a riprap layer in the sea based on a multi-source physical field. Background Art

[0002] For the construction of offshore artificial islands in the sea, the riprap island method has become a widely used method due to its advantages such as simple process and fast speed. During the island construction process, stones are directly dumped on the original seabed surface, causing the silt and silty soft soil layer on the top of the seabed to be impacted by the backfill load in a short period of time, resulting in shear failure, thereby generating a large sliding surface to form silt bags, causing arch siltation, which is very common under the riprap island process. Some silt bags even emerge on the surface. The mud-rock interface formed during the filling process of the artificial island is often undulating and changes dramatically. The thickness distribution of the soft soil layer is extremely uneven. If it is not handled properly, it is easy to cause uneven settlement of the upper buildings. Therefore, it is necessary to accurately explore the continuous distribution characteristics of the thickness of the silt bag under the riprap layer as data support for foundation treatment design. The traditional drilling method is usually used to detect the distribution of silt bags. This method is inefficient, highly random, and costly, and can no longer meet the needs of the continuous distribution characteristics of silt bags that the project is concerned about. Summary of the invention

[0003] In view of this, the present invention aims to propose a high-precision detection method for the thickness of the marine riprap layer based on a multi-source physical field, so as to solve the problems of low efficiency and strong randomness of the existing silt bag detection method, which affects the detection effect.

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

[0005] A high-precision detection method for the thickness of a riprap layer in the sea based on a multi-source physical field, comprising:

[0006] Obtaining data of the project to be measured, and designing the survey line and drilling arrangement according to the data of the project to be measured, so that the survey line and drilling can cover the load-bearing part of the upper building structure to be built of the project to be measured;

[0007] Arrange multiple frequency imaging detectors on the survey line at preset intervals, measure the x, y, and z spatial positions of the frequency imaging detectors using RTK, and obtain frequency imaging results after observing and collecting for a preset time;

[0008] The frequency imaging method detector is removed, and a numbered multi-point active source surface wave detector is arranged at the same position;

[0009] The mechanical seismic source is arranged vertically on the survey line, the mechanical seismic source is used to actively excite seismic wave signals, and after the echo signals are received by the multi-point active source surface wave detector, data are collected according to the serial numbers from small to large to obtain surface wave collection results; wherein the mechanical seismic source and the multi-point active source surface wave detector are arranged in a one-to-one correspondence, and the mechanical seismic source and the multi-point active source surface wave detector are arranged at a certain interval;

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

[0011] According to the shear wave velocity of the riprap layer in the survey line profile, the frequency imaging result is processed by using the frequency imaging method to obtain the thickness measurement value of the riprap layer based on the geophysical prospecting method;

[0012] Perform geological drilling at the drilling location to obtain a true value of the riprap layer thickness at the drilling location, and calculate a ratio k of the true value of the riprap layer thickness at the drilling location to a measured value of the riprap layer thickness;

[0013] Based on the ratio k, the obtained riprap layer thickness measurement values ​​based on the geophysical prospecting method are corrected to obtain continuous thickness values ​​of the riprap layer detected based on the frequency imaging method.

[0014] Furthermore, the multiple frequency imaging method geophones are arranged on the survey line at a preset interval, and the x, y, and z spatial positions of the frequency imaging method geophones are measured by RTK. After the observation and collection are performed for a preset time, the frequency imaging result is obtained, including:

[0015] Arrange a plurality of frequency imaging method geophones on the survey line at intervals of 2 m, and keep each of the frequency imaging method geophones vertically arranged;

[0016] Use RTK to measure the x, y, and z spatial positions of frequency imaging detectors;

[0017] After observing and collecting the frequency imaging method detector for 20 minutes, the frequency imaging result is obtained.

[0018] Furthermore, the mechanical seismic source and the multi-point active source surface wave detector are arranged at an interval of 20 cm.

[0019] Furthermore, the method of processing the surface wave acquisition results by using a cross-correlation superposition algorithm and obtaining the shear wave velocity of the riprap layer of the survey line profile includes:

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

[0021] Converting the surface wave record into a dispersion curve in the frequency-wave number domain, extracting the maximum value data of the surface wave dispersion in the dispersion curve and converting it into a dispersion curve in the depth-velocity domain to obtain dispersion curve data of the overall velocity increasing type;

[0022] The dispersion curve data of the overall velocity increasing type is used to divide the stratum boundary points, and after obtaining the stratum shear wave velocity above the boundary points, the shear wave velocity of the riprap layer of the survey line profile is obtained through cross-correlation calculation.

[0023] Furthermore, the frequency imaging method is used to process the frequency imaging result according to the shear wave velocity of the riprap layer in the survey line profile, and the thickness measurement value of the riprap layer based on the geophysical prospecting method is obtained, including:

[0024] Performing interference suppression on the frequency imaging result to improve the signal-to-noise ratio and obtain original signal data;

[0025] Extracting resonance frequency characteristics of the original signal data, and inverting the geological imaging of the riprap layer of the survey line section by using the shear wave velocity of the riprap layer of the survey line section;

[0026] According to the geological imaging of the riprap layer in the survey line profile, a thickness measurement value of the riprap layer based on the geophysical prospecting method is obtained.

[0027] Furthermore, the resonant frequency feature extraction of the original signal data and the inversion of the geological imaging of the riprap layer of the survey line profile using the shear wave velocity of the riprap layer of the survey line profile include:

[0028] Extracting resonance frequency features from the original signal data and using it as the target function;

[0029] By using an improved genetic algorithm and the shear wave velocity of the riprap layer in the survey line profile, an inversion is performed in the depth domain to obtain a geological imaging of the thickness of the geological body.

[0030] Further, the geological drilling is performed at the drilling position to obtain the true value of the riprap layer thickness at the drilling position, and the ratio k of the true value of the riprap layer thickness at the drilling position to the measured value of the riprap layer thickness is calculated, including:

[0031] Use a down-the-hole drill bit to perform geological drilling at the drilling location, break the rock and drill a hole downward until the mud surface elevation, then replace the core tube to take 2m of mud;

[0032] Measure the length of the drill rod from the borehole to the mud-rock interface to obtain the true value of the riprap layer thickness;

[0033] The measured value of the riprap layer thickness at the drilling position is obtained, and the ratio k between the true value of the riprap layer thickness at the drilling position and the measured value of the riprap layer thickness is calculated.

[0034] Compared with the prior art, the high-precision detection method for the thickness of the riprap layer in the sea based on a multi-source physical field described in the present invention has the following advantages:

[0035] The high-precision detection method for the thickness of the riprap layer in the sea based on the multi-source physical field described in the present invention divides the strata by using the resonance principle of the seismic wave signal propagating in the strata, which significantly improves the accuracy of the stratum division. At the same time, by using the active source surface wave and performing relevant calculations, a more realistic apparent velocity value propagating in the stratum is obtained, which is used for the calculation of the stratum depth in the frequency imaging method, and can greatly improve the detection accuracy of the layer thickness. Finally, drilling is used to check and correct the above results through the actual layer thickness value revealed on site, thereby realizing high-precision detection of the thickness of the riprap layer in the sea. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] The accompanying drawings constituting a part of the present invention are used to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the accompanying drawings:

[0037] Figure 1 A schematic diagram of a process of a high-precision detection method for the thickness of a riprap layer in the sea based on a multi-source physical field according to an embodiment of the present invention;

[0038] Figure 2 This is a schematic diagram of frequency imaging results in a method for high-precision detection of the thickness of a riprap layer in the sea based on a multi-source physical field according to an embodiment of the present invention. DETAILED DESCRIPTION

[0039] The present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It is to be understood that the specific embodiments described herein are only used to explain the present invention, rather than to limit the present invention. It should also be noted that, for ease of description, only parts related to the present invention, rather than all structures, are shown in the accompanying drawings.

[0040] Figure 1 This is a flow chart of a method for high-precision detection of the thickness of a riprap layer in the sea based on a multi-source physical field according to an embodiment of the present invention. This method for high-precision detection of the thickness of a riprap layer in the sea based on a multi-source physical field can achieve rapid, continuous and high-precision detection of silt bags in the riprap layer. Figure 1 , this method specifically includes the following steps:

[0041] Step 101: Acquire data of the project to be measured, and design the survey line and drilling arrangement according to the data of the project to be measured, so that the survey line and drilling can cover the load-bearing part of the upper building structure to be built of the project to be measured.

[0042] In the preparation stage before detection, we can collect data on the project to be tested, master the construction process of the riprap layer, the surface information of the riprap layer, the initial depth of the riprap layer, and then carry out targeted survey line layout design and drilling. The layout principle is to select open and flat surfaces as much as possible, and cover the key load-bearing parts of the proposed upper building structure. In addition, in the actual application process, it is also necessary to perform consistency detection on the frequency imaging method detector and the multi-point active source surface wave detector to ensure the consistency of the parameters of each detector, which is conducive to improving the detection accuracy.

[0043] Step 102: Arrange multiple frequency imaging geophones at preset intervals on the survey line, measure the x, y, and z spatial positions of the frequency imaging geophones using RTK, and obtain frequency imaging results after observing and collecting for a preset time.

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

[0045] Step 1021: Arrange a plurality of frequency imaging geophones on the survey line at intervals of 2 m, and keep each of the frequency imaging geophones vertically arranged.

[0046] Step 1022, use RTK to measure the x, y, z spatial position of the frequency imaging detector. RTK measurement is an engineering technical term. In GPS measurement, static, fast static, and dynamic measurements all need to be solved afterwards to obtain centimeter-level accuracy, and 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, and its emergence has greatly improved the efficiency of field operations.

[0047] Step 1023: After observing and collecting the frequency imaging detector for 20 minutes, a frequency imaging result is obtained.

[0048] Since the natural source seismic frequency imaging method is similar to the data application method in the electromagnetic field, it uses the inherent frequency characteristics of the riprap layer for identification and detection. The basic theory of physics has long shown that any object has its own inherent frequency, and the inherent frequency is related to a variety of physical parameters (geophysical scale, shape, density, longitudinal wave velocity, transverse wave velocity, etc.). Therefore, the inherent frequency of each underground geological body can indirectly reflect its burial depth and physical properties. The underground strata have a certain inherent frequency. When a specific frequency vibration acts on the geological body, it will cause the geological body to resonate, causing the amplitude of the seismic wave of the frequency to increase significantly. Vibrations of other frequencies acting on the geological body will show obvious attenuation.

[0049] Figure 2 This is a schematic diagram of the frequency imaging results of a high-precision detection method for the thickness of a riprap layer in the sea based on a multi-source physical field according to an embodiment of the present invention. Figure 2The upper part of the profile is an artificially dumped gravel layer. The source of the stone is mountain quarrying stone. It has irregular shapes, different particle sizes, and is randomly piled up. It has a large porosity and is manifested as a strong frequency domain amplitude on the frequency imaging profile. The lower part is the original marine sedimentary layer such as silt and silty soil. The texture is relatively uniform, and it is manifested as a weaker frequency domain amplitude.

[0050] Assuming that each stratum is equivalent to a spring with mass and damping, the thickness detection of the riprap layer can be simplified to a rock-up and mud-down model. 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 expressed by two independent coordinates x 1 、x 2 To characterize (the equilibrium position of the system when it is stationary is the zero point position). By doing a simple force analysis on the system, we can get the vibration equation of the system:

[0051]

[0052] Where: m 1 、m 2 is the equivalent mass of the formation, which can be expressed by the product of unit volume and density. The unit volume can be simplified to the product of unit area and thickness H. 1 , k 2 is the spring stiffness coefficient, c 1 、c 2 is the damping coefficient, x 1 、x 2 is the vibration displacement of the formation, and F is the vibration force.

[0053] Assume F is a simple harmonic dynamics, that is, F = F 0 e ikwt , ω is the vibration frequency. Substituting it into, sorting, deducing and simplifying it, we can get the relationship between the characteristic (natural) frequency and 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] Where Z 11 , Z 12 , Z 22 It is related to the vibration frequency, mass, elastic coefficient, and damping coefficient, and the damping coefficient is related to Q, so:

[0058]

[0059] In the formula, the maximum amplitude is obtained when the external frequency is the same as the natural frequency. It can be seen that the characteristic amplitude of the resonance 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 the external vibration are time-varying, while the natural frequency of the formation is time-invariant, the records observed by the portable broadband three-component seismic station in the field are shown in Equation 9, where m is the formation microvibration, S is the external vibration, and G is the time domain record observed on 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 inherent frequency of the stratum structure, which is time-invariant, while S is the external source frequency, which is time-varying. Accurate time-frequency analysis results are obtained through high-order compressed time-frequency spectrum analysis technology. Long-term statistical analysis can suppress S and then obtain M.

[0065] The M extracted at this time 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 single stratum can be obtained. Therefore, the seismic waves with multiple frequencies in the natural source vibration signal are used to 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 is imaged, thereby obtaining a fine imaging effect of the riprap layer.

[0066] In actual application, the frequency imaging detector is composed of three mutually orthogonal low-frequency and high-sensitivity acquisition node units with a frequency of 0.2Hz. When placed, ensure that the base is stable, vertical, and well coupled with the riprap layer.

[0067] Step 103: remove the frequency imaging method detector and arrange a numbered multi-point active source surface wave detector at the same position.

[0068] In actual application, the 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 small to large.

[0069] Step 104, vertically arranging a mechanical seismic source on the survey line, using the mechanical seismic source to actively excite seismic wave signals, and using the multi-point active source surface wave geophone to receive echo signals, collecting data according to the serial numbers from small to large to obtain surface wave collection results; wherein the mechanical seismic source and the multi-point active source surface wave geophone are arranged in a one-to-one correspondence, and the mechanical seismic source and the multi-point active source surface wave geophone are arranged at a certain interval.

[0070] Specifically, the mechanical seismic source and the multi-point active source surface wave detector are set at an interval of 20 cm. By using the mechanical seismic source perpendicular to the survey line, the seismic wave signal is actively stimulated at a distance of 20 cm from the multi-point active source surface wave detector, and each multi-point active source surface wave detector receives the echo signal, and the data is collected in sequence from small to large.

[0071] Since geological bodies are inhomogeneous, the wide-band characteristics of natural source seismic waves can cover more inherent frequencies of the detection objects and effectively identify the interfaces of different geological bodies. However, the frequency of natural seismic waves is low, and there are errors in the determination of wave velocity in geological bodies, which affects the accurate calculation of the thickness of the geological bodies. Therefore, multi-point active source surface wave technology is introduced.

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

[0073] The multi-point active source surface wave technology uses active excitation to generate high-frequency seismic waves. 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 the cross-correlation calculation between different multi-point active source surface wave detectors, the formation shear wave velocity can be more accurately measured.

[0074] Specifically, the surface wave detection method adopts the cross-correlation superposition algorithm, sets an appropriate time window in the time-space domain, namely the "XT domain", highlights the fundamental surface wave characteristics and excludes the influence of other interference waves, and converts the surface wave record into a dispersion curve in the frequency-wavenumber domain (FK domain). In the "FK domain", the maximum value data of the surface wave dispersion is extracted and converted into a depth-velocity domain (ZV domain) dispersion curve. In the "ZV domain", the dispersion curve data of the overall velocity increment type is obtained, and a human-computer interaction method is adopted (the existing processing software has its own function to automatically track the interface, and manual adjustment is required in places where it is obviously wrong) to divide the stratigraphic boundary points. According to the geometric boundary conditions, the shear wave velocity of the riprap layer of the entire survey line profile is obtained by cross-correlation calculation.

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

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

[0077]

[0078] C(ω)=ω / k(ω) (11)

[0079] Applying Radon transform and FFT transform to the surface wave signal can obtain the spectrum D(c,ω), where c is the phase velocity and ω is the angular frequency. Selecting the fundamental wave dispersion curve from the spectrum gives κ(ω)=ω / C(ω), where k(ω) is the wave number.

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

[0081]

[0082] The linear search iteration formula is as follows:

[0083]

[0084] Equation (13) is superimposed by different exponents. When the calculation 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, backscatter data, and higher-order Rayleigh waves from the shot gathers, and then apply a one-dimensional Fourier transform along the x g The same suppression method is applied to the predicted shot gathers and observed data obtained by finite difference calculation of the elastic wave equation.

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

[0087] c. Calculate the weighted amount Used to calculate the back propagation data, the forward propagation wave field also has a weighted term.

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

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

[0090] For example, the multi-point active source surface wave detector adopts an integrated short-period high-sensitivity single-component seismic acquisition node with a frequency of 5Hz. When collecting data on site, a linear arrangement is used, and the detectors with the same frequency imaging method are used, which are vertical, stable, and coupled to the surface. Mechanical source excitation is carried out at a distance of 20cm perpendicular to the survey line and with the detector as the vertical foot. The mechanical source hammer weighs 25kg and the drop height is 30cm. The detectors are triggered one by one in sequence until all the detectors are completed.

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

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

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

[0094] Step 1053: using the dispersion curve data of the overall velocity increasing type to divide the formation boundary points, after obtaining the formation shear wave velocity above the boundary points, the shear wave velocity of the riprap layer of the survey line profile is obtained by cross-correlation calculation.

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

[0096] Step 106: According to the shear wave velocity of the riprap layer in the survey line profile, the frequency imaging result is processed by using the frequency imaging method to obtain a measurement value of the thickness of the riprap layer based on the geophysical prospecting method.

[0097] Since the frequency imaging method collects 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: define the spatial position of the observation system according to the field measurement results and field scheme design; perform fine preprocessing on the original data, mainly including: suppression of abnormal amplitude noise (wild value), surface wave noise, single-frequency interference suppression, etc.; on the basis of obtaining the original data with a high signal-to-noise ratio, extract the resonance frequency characteristics, and use it as the objective function, using an improved genetic algorithm, and using the relatively accurate shear wave velocity obtained by the multi-point source surface wave method to invert in the depth domain to obtain the thickness of the geological body, and perform elevation depth calibration and correction based on the surface Z coordinate value of the survey line and the true thickness of the riprap layer revealed by the borehole to form the result data for final interpretation.

[0099] In actual application, step 106 specifically includes the following steps:

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

[0101] Step 1062: extract the resonance frequency characteristics of the original signal data, and use the shear wave velocity of the riprap layer of the survey line profile to invert the geological imaging of the riprap layer of the survey line profile.

[0102] Specifically, the resonant frequency feature of the original signal data may be extracted first and used as the target function, and then an improved genetic algorithm and the shear wave velocity of the riprap layer of the survey line profile may be used to perform inversion in the depth domain to obtain geological imaging of the thickness of the geological body.

[0103] Step 1063: Obtain a thickness measurement value of the riprap layer based on a geophysical prospecting method according to the geological imaging of the riprap layer in the survey line profile.

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

[0105] Since it involves the design of foundation treatment solutions and engineering measurement, the accuracy of the riprap layer thickness detection is required to be extremely high. In order to calculate the riprap layer thickness more accurately, geological down-the-hole drilling can be carried out in typical areas, and the riprap layer thickness can be corrected through 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 perform geological drilling at the drilling location, break the rock and form a hole downward until the mud surface elevation, then replace the core tube to take 2m of mud.

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

[0109] Step 1073, obtaining the measured value of the riprap thickness at the drilling position, and calculating the ratio k of the true value of the riprap thickness at the drilling position to the measured value of the riprap thickness.

[0110] In practical application, geological drilling can use a down-the-hole drill bit to directly break the rock and drill down to the mud surface elevation. Replace the core tube to take 2m of mud and measure the length of the drill rod from the hole mouth to the mud-rock interface to determine the thickness of the riprap layer. Compare the thickness value H obtained by drilling 钻孔 The thickness value H given by the frequency imaging method 频 , the proportionality coefficient is k, and the formula is H 钻孔 =k*H frequency.

[0111] Step 108: Based on the ratio k, correct the riprap layer thickness measurement values ​​obtained based on the geophysical prospecting method to obtain continuous thickness values ​​of the riprap layer detected based on the frequency imaging method.

[0112] Specifically, the thickness values ​​of each profile measured by the frequency imaging method can be multiplied by the k value, and the continuous thickness value of the riprap layer detected by the frequency imaging method can be obtained after correction. By comparing the actual thickness value obtained by the down-the-hole drill and the elevation of the detector position, and correcting the calibration geological profile, the thickness of the riprap layer at each drilling position can be made close to the true value.

[0113] The method for high-precision detection of the thickness of the riprap layer in the sea based on a multi-source physical field described in this embodiment obtains data of the project to be measured, and designs the survey line and borehole layout according to the data of the project to be measured, so that the survey line and borehole can cover the load-bearing part of the upper building structure to be built in the project to be measured; a plurality of frequency imaging method geophones are arranged on the survey line at a preset interval, and the x, y, and z spatial positions of the frequency imaging method geophones are measured by RTK, and the frequency imaging results are obtained after the preset collection time; the frequency imaging method geophones are removed, and multi-point active source surface wave geophones with numbers are arranged at the same position; a mechanical seismic source is arranged vertically on the survey line, and the mechanical seismic source is used to actively excite seismic wave signals, and after the echo signals are received by the multi-point active source surface wave geophones, data are collected from small to large according to the numbers, and the result is obtained. to the surface wave acquisition result; wherein, the mechanical seismic source and the multi-point active source surface wave geophone are arranged in one-to-one correspondence, and the mechanical seismic source and the multi-point active source surface wave geophone are arranged at a certain interval; the surface wave acquisition result is processed by using the cross-correlation superposition algorithm to obtain the shear wave velocity of the riprap layer of the survey line profile; according to the shear wave velocity of the riprap layer of the survey line profile, the frequency imaging result is processed by using the frequency imaging method to obtain the riprap layer thickness measurement value based on the geophysical method; geological drilling is performed at the drilling position to obtain the true value of the riprap layer thickness at the drilling position, and the ratio k of the true value of the riprap layer thickness at the drilling position to the measured value of the riprap layer thickness is calculated; based on the ratio k, the obtained riprap layer thickness measurement values ​​based on the geophysical method are corrected to obtain the continuous thickness value of the riprap layer detected based on the frequency imaging method.

[0114] Compared with the prior art, the traditional seismic wave signal determines the boundary of the layer by tracking the event axis and the strength of the amplitude signal. This embodiment uses the resonance principle of the seismic wave signal propagating in the stratum to divide the stratum, which significantly improves the accuracy of the stratum division. At the same time, by using the active source surface wave and performing relevant calculations, a more realistic apparent velocity value propagating in the stratum is obtained, which is used for the calculation of the stratum depth in the frequency imaging method, and can greatly improve the detection accuracy of the layer thickness. Finally, drilling is used to check and correct the above results through the actual layer thickness value revealed on site, so as to achieve high-precision detection of the thickness of the riprap layer in the sea.

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

Claims

1. A high-precision detection method for the thickness of riprap layer in the sea based on multi-source physical field, characterized in that: include: Obtaining data of the project to be measured, and designing the survey line and drilling arrangement according to the data of the project to be measured, so that the survey line and drilling can cover the load-bearing part of the upper building structure to be built of the project to be measured; Arrange multiple frequency imaging detectors on the survey line at preset intervals, measure the x, y, and z spatial positions of the frequency imaging detectors using RTK, and obtain frequency imaging results after observing and collecting for a preset time; The frequency imaging method detector is removed, and a numbered multi-point active source surface wave detector is arranged at the same position; The mechanical seismic source is arranged vertically on the survey line, the mechanical seismic source is used to actively excite seismic wave signals, and after the echo signals are received by the multi-point active source surface wave detector, data are collected according to the serial numbers from small to large to obtain surface wave collection results; wherein the mechanical seismic source and the multi-point active source surface wave detector are arranged in a one-to-one correspondence, and the mechanical seismic source and the multi-point active source surface wave detector are arranged at a certain interval; The surface wave acquisition results are processed by using a cross-correlation superposition algorithm to obtain the shear wave velocity of the riprap layer of the survey line profile; According to the shear wave velocity of the riprap layer in the survey line profile, the frequency imaging result is processed by using the frequency imaging method to obtain the thickness measurement value of the riprap layer based on the geophysical prospecting method; Perform geological drilling at the drilling location to obtain a true value of the riprap layer thickness at the drilling location, and calculate a ratio k of the true value of the riprap layer thickness at the drilling location to a measured value of the riprap layer thickness; Based on the ratio k, the obtained riprap layer thickness measurement values ​​based on the geophysical prospecting method are corrected to obtain continuous thickness values ​​of the riprap layer detected based on the frequency imaging method.

2. According to the method of high-precision detection of the thickness of the riprap layer in the sea based on multi-source physical field in claim 1, it is characterized in that: The method of arranging a plurality of frequency imaging detectors on the survey line at a preset interval, and using RTK to measure the x, y, and z spatial positions of the frequency imaging detectors, and obtaining frequency imaging results after observing and collecting for a preset time, includes: Arrange a plurality of frequency imaging method geophones on the survey line at intervals of 2 m, and keep each of the frequency imaging method geophones vertically arranged; Use RTK to measure the x, y, and z spatial positions of frequency imaging detectors; After observing and collecting the frequency imaging method detector for 20 minutes, the frequency imaging result is obtained.

3. The high-precision detection method for the thickness of the riprap layer in the sea based on multi-source physical fields according to claim 1 is characterized by: The mechanical seismic source and the multi-point active source surface wave detector are arranged at an interval of 20 cm.

4. The high-precision detection method for the thickness of the riprap layer in the sea based on multi-source physical fields according to claim 1 is characterized in that: The method of processing the surface wave acquisition results by using a cross-correlation superposition algorithm and obtaining the shear wave velocity of the riprap layer of the survey line profile includes: In the time-space domain, a time interval window that can display all waveforms is set to highlight the fundamental surface wave characteristics and obtain surface wave records; Converting the surface wave record into a dispersion curve in the frequency-wave number domain, extracting the maximum value data of the surface wave dispersion in the dispersion curve and converting it into a dispersion curve in the depth-velocity domain to obtain dispersion curve data of the overall velocity increasing type; The dispersion curve data of the overall velocity increasing type is used to divide the stratum boundary points, and after obtaining the stratum shear wave velocity above the boundary points, the shear wave velocity of the riprap layer of the survey line profile is obtained through cross-correlation calculation.

5. The high-precision detection method for the thickness of the riprap layer in the sea based on multi-source physical fields according to claim 1 is characterized in that: The method of processing the frequency imaging result according to the shear wave velocity of the riprap layer in the survey line profile by using the frequency imaging method and obtaining the thickness measurement value of the riprap layer based on the geophysical prospecting method includes: Performing interference suppression on the frequency imaging result to improve the signal-to-noise ratio and obtain original signal data; Extracting resonance frequency characteristics of the original signal data, and inverting the geological imaging of the riprap layer of the survey line section by using the shear wave velocity of the riprap layer of the survey line section; According to the geological imaging of the riprap layer in the survey line profile, a thickness measurement value of the riprap layer based on the geophysical prospecting method is obtained.

6. A high-precision detection method for the thickness of riprap layer in the sea based on multi-source physical field according to claim 5, characterized in that: The resonant frequency feature extraction of the original signal data and the inversion of the geological imaging of the riprap layer of the survey line section using the shear wave velocity of the riprap layer of the survey line section include: Extracting resonance frequency features from the original signal data and using it as the target function; By using an improved genetic algorithm and the shear wave velocity of the riprap layer in the survey line profile, an inversion is performed in the depth domain to obtain a geological imaging of the thickness of the geological body.

7. The high-precision detection method for the thickness of the riprap layer in the sea based on multi-source physical fields according to claim 1 is characterized in that: The method of performing geological drilling at the drilling location to obtain the true value of the riprap layer thickness at the drilling location, and calculating the ratio k of the true value of the riprap layer thickness at the drilling location to the measured value of the riprap layer thickness, includes: Use a down-the-hole drill bit to perform geological drilling at the drilling location, break the rock and drill a hole downward until the mud surface elevation, then replace the core tube to take 2m of mud; Measure the length of the drill rod from the borehole to the mud-rock interface to obtain the true value of the riprap layer thickness; The measured value of the riprap layer thickness at the drilling position is obtained, and the ratio k between the true value of the riprap layer thickness at the drilling position and the measured value of the riprap layer thickness is calculated.

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