WO2021174434A1 - 一种震电波场联合提取瑞雷波频散特征的面波勘探方法 - Google Patents

一种震电波场联合提取瑞雷波频散特征的面波勘探方法 Download PDF

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WO2021174434A1
WO2021174434A1 PCT/CN2020/077697 CN2020077697W WO2021174434A1 WO 2021174434 A1 WO2021174434 A1 WO 2021174434A1 CN 2020077697 W CN2020077697 W CN 2020077697W WO 2021174434 A1 WO2021174434 A1 WO 2021174434A1
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wave
dispersion
component
jointly
electric field
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French (fr)
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任恒鑫
杨振涛
陈晓非
袁士川
郑旭桢
何展翔
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南方科技大学
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Priority to US17/420,928 priority patent/US11754744B2/en
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
    • G01V1/00—Seismology; Seismic or acoustic prospecting or detecting
    • G01V1/28—Processing seismic data, e.g. for interpretation or for event detection
    • G01V1/282—Application of seismic models, synthetic seismograms
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
    • G01V1/00—Seismology; Seismic or acoustic prospecting or detecting
    • G01V1/28—Processing seismic data, e.g. for interpretation or for event detection
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
    • G01V1/00—Seismology; Seismic or acoustic prospecting or detecting
    • G01V1/28—Processing seismic data, e.g. for interpretation or for event detection
    • G01V1/30—Analysis
    • G01V1/303—Analysis for determining velocity profiles or travel times
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
    • G01V1/00—Seismology; Seismic or acoustic prospecting or detecting
    • G01V1/28—Processing seismic data, e.g. for interpretation or for event detection
    • G01V1/30—Analysis
    • G01V1/307—Analysis for determining seismic attributes, e.g. amplitude, instantaneous phase or frequency, reflection strength or polarity
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
    • G01V11/00—Prospecting or detecting by methods combining techniques covered by two or more of main groups G01V1/00 - G01V9/00
    • G01V11/007—Prospecting or detecting by methods combining techniques covered by two or more of main groups G01V1/00 - G01V9/00 using the seismo-electric effect
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
    • G01V3/00—Electric or magnetic prospecting or detecting; Measuring magnetic field characteristics of the earth, e.g. declination, deviation
    • G01V3/08—Electric or magnetic prospecting or detecting; Measuring magnetic field characteristics of the earth, e.g. declination, deviation operating with magnetic or electric fields produced or modified by objects or geological structures or by detecting devices
    • G01V3/082—Electric or magnetic prospecting or detecting; Measuring magnetic field characteristics of the earth, e.g. declination, deviation operating with magnetic or electric fields produced or modified by objects or geological structures or by detecting devices operating with fields produced by spontaneous potentials, e.g. electrochemical or produced by telluric currents
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
    • G01V3/00—Electric or magnetic prospecting or detecting; Measuring magnetic field characteristics of the earth, e.g. declination, deviation
    • G01V3/12—Electric or magnetic prospecting or detecting; Measuring magnetic field characteristics of the earth, e.g. declination, deviation operating with electromagnetic waves
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
    • G01V2210/00—Details of seismic processing or analysis
    • G01V2210/60—Analysis
    • G01V2210/61—Analysis by combining or comparing a seismic data set with other data
    • G01V2210/614—Synthetically generated data

Definitions

  • the invention relates to the technical field of geological and geophysical prospecting, in particular to a surface wave prospecting method for extracting the Rayleigh wave dispersion characteristics jointly by a seismic wave field.
  • Rayleigh wave was first determined theoretically by British scientist Lord Rayleigh in 1887, hence the name. Since the 1950s, with the continuous in-depth research of scientists, it has been discovered that Rayleigh waves carry media information such as P-wave velocity, S-wave velocity, and density of each layer of media when they propagate in layered media. Obvious dispersion characteristics (that is, the velocity changes with frequency), and mainly depends on the S-wave velocity structure of the layered medium. Therefore, the characteristics of the energy and velocity changes of Rayleigh waves in the propagation process carry a lot of stratum information. Therefore, in the engineering field, the characteristics of Rayleigh wave dispersion are often used to solve engineering surveys, site and foundation treatment evaluation, obstacles and cavity detection, etc. Layer geological issues. At this stage, surface wave exploration has become one of the most widely used geophysical prospecting methods in the field of engineering geophysical prospecting.
  • the technical problem to be solved by the present invention is to provide a surface wave exploration method for extracting the dispersion characteristics of Rayleigh wave by the seismoelectric wave field in view of the above-mentioned shortcomings of the prior art, aiming to solve the high-order mode dispersion imaging accuracy in the prior art Low problem.
  • a surface wave exploration method for jointly extracting the Rayleigh wave dispersion characteristics from the seismic wave field which comprises the following steps:
  • the seismic wave data includes: seismic wave component;
  • the electric field data includes: electric field component;
  • the performing joint imaging processing on the jointly collected data to obtain the superimposed dispersion spectrum includes:
  • the dispersion spectrum of the seismic wave component and the dispersion spectrum of the electric field component are superimposed to obtain a superimposed dispersion spectrum.
  • the surface wave exploration method for extracting Rayleigh wave dispersion characteristics jointly by the seismic wave field, wherein the dispersion spectrum of the seismic wave component and the dispersion spectrum of the electric field component are obtained according to the seismic wave component and the electric field component, respectively, include:
  • frequency scanning is performed to obtain the dispersion spectrum of the seismic wave component and the dispersion spectrum of the electric field component.
  • the seismic wave component includes: the seismic wave radial component and/or the seismic wave vertical component;
  • the electric field component includes: the electric field radial component And/or the vertical component of the electric field.
  • the surface wave exploration method for extracting the Rayleigh wave dispersion characteristics jointly by the seismic wave field, wherein the superimposing the dispersion spectrum of the seismic wave component and the dispersion spectrum of the electric field component to obtain a superimposed dispersion spectrum include:
  • the dispersion spectrum of the vertical component of the seismic wave and the dispersion spectrum of the radial component of the electric field are superimposed to obtain a superimposed dispersion spectrum
  • the dispersion spectrum of the vertical component of the seismic wave, the dispersion spectrum of the radial component of the seismic wave and the dispersion spectrum of the radial component of the electric field are superimposed to obtain the superimposed dispersion spectrum.
  • the surface wave exploration method for extracting the Rayleigh wave dispersion characteristics jointly by the seismoelectric wave field wherein the extracting processing of the superimposed dispersion spectrum to obtain a dispersion curve includes:
  • the dispersion curve is obtained by extracting the superimposed dispersion spectrum by the maximum energy value; the dispersion curve is a multi-mode dispersion curve containing a fundamental-order mode and a higher-order mode.
  • the surface wave exploration method for extracting the Rayleigh wave dispersion characteristics jointly by the seismoelectric wave field, wherein the inversion processing of the dispersion curve to obtain a stratum structure section includes:
  • the inversion method includes one or more of genetic algorithm, group algorithm, and quasi-Newton algorithm kind.
  • a surface wave exploration device capable of jointly extracting Rayleigh wave dispersion characteristics with seismic electric wave field, which includes:
  • An acquisition device for acquiring jointly acquired data wherein the jointly acquired data includes seismic wave data and electric field data;
  • a joint imaging device configured to perform joint imaging processing on the jointly collected data to obtain a superimposed dispersion spectrum
  • the inversion device is used for extracting the superimposed dispersion spectrum to obtain a dispersion curve, and performing inversion processing on the dispersion curve to obtain a stratum structure section.
  • a terminal device including: a processor, and a memory connected to the processor,
  • the memory stores a surface wave exploration program for extracting Rayleigh wave dispersion characteristics jointly by a seismoelectric wave field, and the following steps are implemented when the surface wave exploration program for extracting Rayleigh wave dispersion characteristics jointly by a seismoelectric wave field is executed by the processor :
  • a storage medium wherein a surface wave exploration program for extracting Rayleigh wave dispersion characteristics jointly by a seismoelectric wave field is stored, and the surface wave exploration program for extracting Rayleigh wave dispersion characteristics jointly by a seismoelectric wave field is executed by a processor
  • Figure 1 is a shot collection record of seismic wave components u r and u z and electric field components E r and E z received by the linear observation system of the present invention.
  • Fig. 2 is the dispersion spectrum obtained by shot collection recording of seismic wave components u r , u z and electric field components E r , E z in the present invention.
  • Figure 3a is the superimposed dispersion spectrum D Seismic obtained from the dispersion spectrum of the seismic wave components u r and u z in the present invention.
  • Fig. 3b is the superimposed dispersion spectrum D Seismoelectirc obtained from the dispersion spectrum of the radial electric field Er and the dispersion spectrum of the seismic wave components u r and u z in the present invention.
  • FIG. 4b is according to the present invention, u z, u r, E r superposition superimposition of spectral dispersion.
  • Fig. 5 is a schematic diagram of the dispersion curve in the present invention.
  • Fig. 6 is the formation velocity structure obtained by inversion of the multi-mode dispersion curve in the present invention.
  • Fig. 7 is the interpolated drawing of the velocity structure of multiple surface waves in the survey line into the cross-section of the stratum shear wave velocity structure in the present invention.
  • Figure 8 is a schematic diagram of the combined seismic and electrical collection of the present invention.
  • Fig. 9 is a flow chart of the surface wave exploration method for extracting the Rayleigh wave dispersion characteristics jointly by the mid-seismic electric wave field of the present invention.
  • the present invention provides some embodiments of a surface wave exploration method for extracting Rayleigh wave dispersion characteristics jointly by a seismic wave field.
  • the electromagnetic wave amplitude generated by the seismoelectric conversion decays rapidly when it leaves the interface, which is called evanescent electromagnetic wave.
  • EM evanescent electromagnetic wave
  • the dispersion spectrum calculated by the evanescent electromagnetic wave contains rich and high-quality high-order mode information, and the dispersion spectrum of these high-order modes cannot be directly calculated by using seismic waves (Rayleigh waves).
  • seismic waves Rayleigh waves
  • the frequency ranges in which evanescent electromagnetic waves and seismic waves have significant energy in the dispersion spectrum are not the same, and the two are just complementary. Therefore, the evanescent electromagnetic wave (EM) generated by the seismoelectric conversion has great potential to improve the quality of Rayleigh wave dispersion imaging, which is of great significance for further improving the accuracy of Rayleigh surface wave exploration.
  • EM evanescent electromagnetic wave
  • the surface wave exploration method of the present invention for extracting the dispersion characteristics of Rayleigh wave by the seismoelectric wave field includes the following steps:
  • the jointly collected data may also include: magnetic field data.
  • the seismic wave data includes seismic wave components; the electric field data includes electric field components. More specifically, the seismic wave component includes: a seismic wave radial component u r and/or a seismic wave vertical component u z ; and the electric field component includes: an electric field radial component Er and/or an electric field vertical component E z .
  • the seismic sources used in transient Rayleigh wave exploration are generally hammers, drop hammers and other seismic sources, which can be approximated as a single point force source in the vertical direction, which can theoretically only generate longitudinal waves (P waves) and vertical component transverse waves. (SV wave) and transverse magnetic mode electromagnetic field.
  • the excited P wave and SV wave coherently generate Rayleigh waves and generate corresponding evanescent electromagnetic waves. Therefore, in actual exploration, we can observe the radial component u r and vertical component u z (cylindrical coordinate system) of Rayleigh waves, as well as the radial component Er and vertical component E z of the electric field, and the transverse component of the magnetic field.
  • the component B ⁇ since the magnetic field component is weak, only the seismic wave component and the electric field component are considered in this embodiment.
  • the acquisition device uses different noise reduction and front-end amplification systems.
  • the seismic source is excited by the hammer, the two different sensors of seismic and electric conduct high-frequency digital sampling at the same time.
  • S200 Perform joint imaging processing on the jointly collected data to obtain a superimposed dispersion spectrum.
  • step S200 includes the steps:
  • S210 Obtain the dispersion spectrum of the seismic wave component and the dispersion spectrum of the electric field component according to the seismic wave component and the electric field component, respectively.
  • S210 includes steps:
  • the response wave field of the pulse source time function such as G(r, ⁇ ,z, ⁇ )
  • G T,m , G S,m and G R,m are the expansion coefficients corresponding to the basis function, which are expressed as follows:
  • G(r, ⁇ ,z, ⁇ ) can also be expressed as:
  • G(r, ⁇ ,z, ⁇ ) G r (r, ⁇ ,z, ⁇ )e r +G ⁇ (r, ⁇ ,z, ⁇ )e ⁇ +G z (r, ⁇ ,z, ⁇ ) e z .
  • the radial component u r and vertical component u z of the seismic wave (using a cylindrical coordinate system), as well as the radial component Er and vertical component E z of the electric field, can be expressed as:
  • u S (k, ⁇ ,z), u R (k, ⁇ ,z), E S (k, ⁇ ,z), E R (k, ⁇ ,z) are the kernel functions of fluctuation and electric field;
  • F( ⁇ ) represents the Fourier transform of the actual source time function;
  • u r (r, ⁇ ,z), u z (r, ⁇ ,z), E r (r, ⁇ ,z), E z (r, ⁇ , z) is the Fourier of time domain wavefield components u r (r,t,z), u z (r,t,z), Er (r,t,z), E z (r,t,z)
  • r and z respectively represent the radial distance between a receiver and the seismic source and the depth of the receiver in actual observations.
  • the acquisition system can be arbitrarily arranged according to the detection area, without linear or other regular shapes. , And no offset is required. Therefore, it can be arranged in any shape according to the detection site environment, which can more comprehensively reflect the underground velocity structure of the detection area. applicability.
  • the second layer of the model is set as a porous medium saturated with water, the other layers are set as a porous medium saturated with air, and the phreatic surface is located at a depth of 10 meters underground.
  • the seismic source is a vertical single-force point source (hammer hit, drop hammer source) excited on the surface, and the source time function uses a Ricker wavelet with a dominant frequency of 10 Hz and a delay time of 0.5 seconds; in order to facilitate data collection, as shown in the figure As shown in 8, the observation system adopts a linear arrangement with a channel spacing of 2 meters and a total of 91 channels.
  • the received seismic wave component shot set records and electric field component shot set records are shown in Figure 1. According to the seismic wave component shot set records and the electric field component shot set records The recorded dispersion spectrum is shown in Figure 2.
  • the dotted line in Figure 2 is the theoretical Rayleigh wave dispersion curve calculated from the formation parameters.
  • S220 includes steps:
  • S300 Perform extraction processing on the superimposed dispersion spectrum to obtain a dispersion curve, and perform inversion processing on the dispersion curve to obtain a stratum structure section.
  • S300 includes the steps:
  • the dispersion curve is a multi-mode dispersion curve containing a fundamental-order mode and a higher-order mode.
  • the multi-mode dispersion curve containing the fundamental and higher-order modes is extracted from the dispersion spectrum (see Figure 5) for later inversion.
  • the inversion method includes one or more of genetic algorithm, cluster algorithm, and quasi-Newton algorithm. Establish an initial inversion stratigraphic model based on basic data, and then use genetic algorithms, swarm algorithms (particle swarms, bee swarms, etc.), quasi-Newton and other inversion methods to simulate the multi-mode dispersion curve extracted in Figure 5 To invert the stratigraphic structure, as shown in Figure 6.
  • Moving the observation system can obtain the velocity structure of multiple stratum positions. Interpolate the velocity structure of different positions, and draw the stratum section according to the spatial position, as shown in Figure 7.
  • the present invention also provides a surface wave exploration device for extracting the Rayleigh wave dispersion characteristics by the seismoelectric wave field.
  • a surface wave exploration device for extracting the Rayleigh wave dispersion characteristics by the seismoelectric wave field.
  • the surface wave exploration device for jointly extracting the Rayleigh wave dispersion characteristics by the seismic wave field includes: an acquisition device for acquiring jointly acquired data; wherein the jointly acquired data includes: seismic wave data And electric field data;
  • a joint imaging device configured to perform joint imaging processing on the jointly collected data to obtain a superimposed dispersion spectrum
  • the inversion device is used for extracting the superimposed dispersion spectrum to obtain a dispersion curve, and performing inversion processing on the dispersion curve to obtain a stratum structure section.
  • the seismic wave data includes seismic wave components; the electric field data includes electric field components.
  • the joint imaging device is specifically configured to obtain the dispersion spectrum of the seismic wave component and the dispersion spectrum of the electric field component according to the seismic wave component and the electric field component, respectively; and combine the dispersion spectrum of the seismic wave component and the electric field component
  • the dispersion spectrum is superimposed to obtain the superimposed dispersion spectrum.
  • the joint imaging device is also used to extract the imaginary part of the seismic wave component and the imaginary part of the electric field component respectively, and then perform frequency scanning to obtain the dispersion spectrum of the seismic wave component and the dispersion spectrum of the electric field component.
  • the seismic wave component includes: a seismic wave radial component and/or a seismic wave vertical component;
  • the electric field component includes: an electric field radial component and/or an electric field vertical component.
  • the joint imaging device is also used to superimpose the dispersion spectrum of the vertical component of the seismic wave and the dispersion spectrum of the radial component of the electric field to obtain a superimposed dispersion spectrum;
  • the dispersion spectrum of the vertical component of the seismic wave, the dispersion spectrum of the radial component of the seismic wave and the dispersion spectrum of the radial component of the electric field are superimposed to obtain a superimposed dispersion spectrum.
  • the inversion device is specifically configured to extract the superimposed dispersion spectrum to obtain a dispersion curve by using a maximum energy value; the dispersion curve is a multi-mode dispersion curve containing a fundamental-order mode and a higher-order mode.
  • the inversion device is also used to establish an initial inversion stratum model, and use a variety of inversion methods to fit the dispersion curve to obtain a stratum structure profile; the inversion method includes: genetic algorithm, cluster algorithm, simulation One or more of Newton's algorithms.
  • the present invention also provides a preferred embodiment of a terminal device:
  • a terminal device includes: a processor, and a memory connected to the processor,
  • the memory stores a surface wave exploration program for extracting Rayleigh wave dispersion characteristics jointly by a seismoelectric wave field, and the following steps are implemented when the surface wave exploration program for extracting Rayleigh wave dispersion characteristics jointly by a seismoelectric wave field is executed by the processor :
  • the seismic wave data includes seismic wave components; the electric field data includes electric field components.
  • the dispersion spectrum of the seismic wave component and the dispersion spectrum of the electric field component are superimposed to obtain a superimposed dispersion spectrum.
  • frequency scanning is performed to obtain the dispersion spectrum of the seismic wave component and the dispersion spectrum of the electric field component.
  • the seismic wave component includes: a seismic wave radial component and/or a seismic wave vertical component;
  • the electric field component includes: an electric field radial component and/or an electric field vertical component.
  • the dispersion spectrum of the vertical component of the seismic wave and the dispersion spectrum of the radial component of the electric field are superimposed to obtain a superimposed dispersion spectrum
  • the dispersion spectrum of the radial component of the seismic wave, the dispersion spectrum of the vertical component of the seismic wave and the dispersion spectrum of the radial component of the electric field are superimposed to obtain a superimposed dispersion spectrum.
  • the superimposed dispersion spectrum is extracted by the maximum energy value to obtain a dispersion curve.
  • the dispersion curve is a multi-mode dispersion curve containing a basic-order mode and a high-order mode.
  • An initial inversion stratum model is established, and a variety of inversion methods are used to fit the dispersion curve to obtain a stratum structure section.
  • the inversion method includes one or more of genetic algorithm, group algorithm, and quasi-Newton algorithm.
  • the present invention also provides a preferred embodiment of a storage medium:
  • a storage medium stores a surface wave exploration program for extracting Rayleigh wave dispersion characteristics by a seismoelectric wave field, and a surface wave exploration program for extracting Rayleigh wave dispersion characteristics by a seismoelectric wave field When executed by the processor, the following steps are implemented:

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Abstract

一种震电波场联合提取瑞雷波频散特征的面波勘探方法，包括步骤：获取联合采集的数据；其中，联合采集的数据包括：地震波数据和电场数据；将联合采集的数据进行联合成像处理得到叠加的频散谱；对叠加的频散谱进行提取处理得到频散曲线，并对频散曲线进行反演处理得到地层结构剖面。由于采用地震波数据和电场数据进行联合成像处理得到叠加的频散谱，并提取得到多模式频散曲线，在进行反演时大大降低反演的多解性，从而大大提高面波勘探的精度和稳定性。

Description

一种震电波场联合提取瑞雷波频散特征的面波勘探方法 技术领域
本发明涉及地质、地球物理勘探技术领域，尤其涉及的是一种震电波场联合提取瑞雷波频散特征的面波勘探方法。
背景技术
瑞雷波(Rayleigh wave)由英国科学家Lord Rayleigh首先于1887年在理论上确定，故此命名。自二十世纪五十年代，随着科学家研究不断深入，发现瑞雷波(Rayleigh wave)在层状介质中传播时携带了各层介质的P波速度、S波速度、密度等介质信息，呈现明显的频散特性(即速度随频率变化而变化)，且主要取决于层状介质的S波速度结构。所以瑞雷波在传播过程中能量和速度的变化特征携带了大量地层信息，因此在工程领域常常通过研究Rayleigh波频散特征来解决工程勘察、场地和地基处理评价、障碍物和空洞探测等浅层地质问题。现阶段面波勘探已成为工程物探领域应用最广泛的物探方法之一。
在实际应用中，大量学者发现面波勘探如果仅采用基阶模式面波频散信息进行反演得到的地层模型具有很大的不确定性，但将基阶、高阶模式频散联合反演将会大大降低这种不确定性；而且在工程勘探中，经常遇到某一频率范围内的瑞雷波高阶模式比基阶模式具有更强的能量，这就意味着在某些频率范围内我们只能得到高阶模式频散曲线。现阶段面波勘探方法均是从面波的波动信息中提取频散信息，虽然基阶模式能较好的成像，但高阶尤其较高模式的高阶模式频散成像精度有限。
因此，现有技术还有待于改进和发展。
发明内容
本发明要解决的技术问题在于，针对现有技术的上述缺陷，提供一种震电波场联合 提取瑞雷波频散特征的面波勘探方法，旨在解决现有技术中高阶模式频散成像精度低的问题。
本发明解决技术问题所采用的技术方案如下：
一种震电波场联合提取瑞雷波频散特征的面波勘探方法，其中，包括步骤：
获取联合采集的数据；其中，所述联合采集的数据包括：地震波数据和电场数据；
将所述联合采集的数据进行联合成像处理得到叠加的频散谱；
对所述叠加的频散谱进行提取处理得到频散曲线，并对所述频散曲线进行反演处理得到地层结构剖面。
所述的震电波场联合提取瑞雷波频散特征的面波勘探方法，其中，所述地震波数据包括：地震波分量；所述电场数据包括：电场分量；
所述将所述联合采集的数据进行联合成像处理得到叠加的频散谱，包括：
根据所述地震波分量、所述电场分量分别得到地震波分量的频散谱、电场分量的频散谱；
将所述地震波分量的频散谱和所述电场分量的频散谱叠加得到叠加的频散谱。
所述的震电波场联合提取瑞雷波频散特征的面波勘探方法，其中，所述根据所述地震波分量、所述电场分量分别得到地震波分量的频散谱、电场分量的频散谱，包括：
分别提取所述地震波分量的虚部、所述电场分量的虚部后进行频率扫描得到地震波分量的频散谱、电场分量的频散谱。
所述的震电波场联合提取瑞雷波频散特征的面波勘探方法，其中，所述地震波分量包括：地震波径向分量和/或地震波垂向分量；所述电场分量包括：电场径向分量和/或电场垂向分量。
所述的震电波场联合提取瑞雷波频散特征的面波勘探方法，其中，所述将所述地震波分量的频散谱和所述电场分量的频散谱叠加得到叠加的频散谱，包括：
将地震波垂向分量的频散谱和电场径向分量的频散谱叠加得到叠加的频散谱；或者
将地震波径向分量的频散谱和电场径向分量的频散谱叠加得到叠加的频散谱；或者
将地震波垂向分量的频散谱、地震波径向分量的频散谱和电场径向分量的频散谱叠 加得到叠加的频散谱。
所述的震电波场联合提取瑞雷波频散特征的面波勘探方法，其中，所述对所述叠加的频散谱进行提取处理得到频散曲线，包括：
通过能量极大值来提取所述叠加的频散谱得到频散曲线；所述频散曲线为含有基阶模式、高阶模式的多模式频散曲线。
所述的震电波场联合提取瑞雷波频散特征的面波勘探方法，其中，所述对所述频散曲线进行反演处理得到地层结构剖面，包括：
建立初始反演地层模型，利用多种反演方法对所述频散曲线进行拟合得到地层结构剖面；所述反演方法包括：遗传算法、群类算法、拟牛顿算法中的一种或多种。
一种震电波场联合提取瑞雷波频散特征的面波勘探装置，其中，包括：
采集装置，用于获取联合采集的数据；其中，所述联合采集的数据包括：地震波数据和电场数据；
联合成像装置，用于将所述联合采集的数据进行联合成像处理得到叠加的频散谱；
反演装置，用于对所述叠加的频散谱进行提取处理得到频散曲线，并对所述频散曲线进行反演处理得到地层结构剖面。
一种终端设备，其中，包括：处理器，以及与所述处理器连接的存储器，
所述存储器存储有震电波场联合提取瑞雷波频散特征的面波勘探程序，所述震电波场联合提取瑞雷波频散特征的面波勘探程序被所述处理器执行时实现以下步骤：
获取联合采集的数据；其中，所述联合采集的数据包括：地震波数据和电场数据；
将所述联合采集的数据进行联合成像处理得到叠加的频散谱；
对所述叠加的频散谱进行提取处理得到频散曲线，并对所述频散曲线进行反演处理得到地层结构剖面。
一种存储介质，其中，其上存储有震电波场联合提取瑞雷波频散特征的面波勘探程序，所述震电波场联合提取瑞雷波频散特征的面波勘探程序被处理器执行时实现以下步骤：
获取联合采集的数据；其中，所述联合采集的数据包括：地震波数据和电场数据；
将所述联合采集的数据进行联合成像处理得到叠加的频散谱；
对所述叠加的频散谱进行提取处理得到频散曲线，并对所述频散曲线进行反演处理得到地层结构剖面。
有益效果：由于采用地震波数据和电场数据进行联合成像处理得到叠加的频散谱，并提取得到多模式频散曲线，在进行反演时大大降低反演的多解性，从而大大提高面波勘探的精度和稳定性。
附图说明
图1是本发明中线性观测系统接收到地震波分量u r、u z以及电场分量E r、E z的炮集记录。
图2是本发明中地震波分量u r、u z以及电场分量E r、E z的炮集记录得到的频散谱。
图3a是本发明中由地震波分量u r、u z的频散谱得到的叠加的频散谱D Seismic。
图3b是本发明中由径向电场E r的频散谱与地震波分量u r、u z的频散谱得到的叠加的频散谱D Seismoelectirc。
图4a是本发明中u z、E r叠加得到的叠加的频散谱。
图4b是本发明中u z、u r、E r叠加得到的叠加的频散谱。
图5是本发明中频散曲线的示意图。
图6是本发明中多模式频散曲线进行反演得到的地层速度结构。
图7是本发明中将测线中多个面波反演的速度结构插值绘制成地层横波速度结构剖面。
图8是本发明中震、电联合采集示意图。
图9是本发明中震电波场联合提取瑞雷波频散特征的面波勘探方法的流程图。
具体实施方式
为使本发明的目的、技术方案及优点更加清楚、明确，以下参照附图并举实施例对本发明进一步详细说明。应当理解，此处所描述的具体实施例仅仅用以解释本发明，并 不用于限定本发明。
请同时参阅图1-图9，本发明提供了一种震电波场联合提取瑞雷波频散特征的面波勘探方法的一些实施例。
震电效应最早由前苏联科学家Ivanov在1939年发现，在不加电压的情况下，测量到了由地震波导致的电场，并指出这可能与双电层动电效应有关。此后，Frenkel建立了固相运动与孔隙流体运动相耦合的孔隙介质波动理论，并得到了Biot的进一步完善，形成了著名的Biot孔隙介质弹性波理论。上世纪90年代，随着电子科学技术的发展以及微弱信号提取和信号处理手段的提高，震电效应的研究得到了长足发展。1994年Pride在Frenkel和Biot的工作基础上提出了震电耦合的宏观控制方程组，该方程组中将Biot空隙弹性方程组与Maxwell电磁方程组通过动电耦合系数耦合在一起，描述了在多孔饱和介质中波动场与电磁场的耦合关系，现今已成为震电理论研究的基础。
在层状孔隙介质模型的波场模拟研究中发现，当震波超过临界角入射孔隙介质界面时，震电转换产生的电磁波振幅在离开界面时快速衰减，称其为隐失电磁波。研究发现垂向单力点源所激发的瑞雷面波产生的隐失电磁波(EM)具有与瑞雷波一致的频散特性。这样为通过接收面波产生的隐失电磁波信号来提取面波的频散信息提供了理论基础。研究表明，通过隐失电磁波计算得到的频散谱，包含有丰富的、高质量的高阶模式信息，并且这些高阶模式频散是直接利用地震波(瑞雷波)计算得到的频散谱无法提供的，另外对于基阶模式，隐失电磁波和地震波在频散谱中具有显著能量的频率范围不尽相同，两者正好形成互补。所以，震电转换产生的隐失电磁波(EM)具有提高瑞雷波频散成像质量的巨大潜力，这对于进一步提高瑞雷面波勘探精度具有重大意义。
如图9所示，本发明的一种震电波场联合提取瑞雷波频散特征的面波勘探方法，包括以下步骤：
S100、获取联合采集的数据；其中，所述联合采集的数据包括：地震波数据和电场数据。
具体地，所述联合采集的数据还可以包括：磁场数据。所述地震波数据包括：地震波分量；所述电场数据包括：电场分量。更具体地，所述地震波分量包括：地震波径向 分量u r和/或地震波垂向分量u z；所述电场分量包括：电场径向分量E r和/或电场垂向分量E z。
实际工程应用中瞬态瑞雷波勘探所采用的震源一般为锤击、落锤等震源，可近似为一垂直方向的单点力源，理论上仅能产生纵波(P波)和垂直分量横波(SV波)以及横磁模式电磁场。激发的P波和SV波相干产生瑞雷(Rayleigh)波并产生相应的隐失电磁波。所以在实际勘探中，我们能观测到瑞雷波的径向分量u r和垂向分量u z(柱坐标系)，以及电场的径向分量E r和垂向分量E z，以及磁场的横向分量B θ，由于磁场分量微弱，故本实施例中仅考虑地震波分量和电场分量。
由于电场分量信号较地震波信号微弱，故采集装置采用不同的降噪和前段放大系统。当锤击激发震源后，震、电两种不同的传感器同时进行高频数字采样。
S200、将所述联合采集的数据进行联合成像处理得到叠加的频散谱。
具体地，步骤S200包括步骤：
S210、根据所述地震波分量、所述电场分量分别得到地震波分量的频散谱、电场分量的频散谱。
S210包括步骤：
S211、分别提取所述地震波分量的虚部、所述电场分量的虚部后进行频率扫描得到地震波分量的频散谱、电场分量的频散谱。
在水平层状地层模型中，脉冲震源时间函数的响应波场，例如G(r,θ,z,ω)，能够表示为：
Figure PCTCN2020077697-appb-000001
其中，k′为所有可能的水平波数，
Figure PCTCN2020077697-appb-000002
为一组完备正交的矢量基函数，具体表示如下：
Figure PCTCN2020077697-appb-000003
其中，
Figure PCTCN2020077697-appb-000004
i为虚数单位，m＝0,±1,±2,...，k′∈(0,+∞)；J m(k′r)表示m阶第一类贝塞尔函数。式(1)中G T,m，G S,m和G R,m是与基函数相对应的展开系数，具体表示如下：
Figure PCTCN2020077697-appb-000005
其中，符号*表示复共轭。在柱坐标系中，G(r,θ,z,ω)也能表示为：
G(r,θ,z,ω)＝G r(r,θ,z,ω)e r+G θ(r,θ,z,ω)e θ+G z(r,θ,z,ω)e z.  (4)
结合(1)、(2)、(3)、(4)，并考虑0阶第一类贝塞尔函数的导数性质：J′ 0(k′r)＝-J 1(k′r)，我们可以得到：
Figure PCTCN2020077697-appb-000006
根据贝塞尔函数的正交性质：
Figure PCTCN2020077697-appb-000007
(其中k为观测的水平波数)，由式(5)可得：
Figure PCTCN2020077697-appb-000008
Figure PCTCN2020077697-appb-000009
Figure PCTCN2020077697-appb-000010
定义如下的核函数：
Figure PCTCN2020077697-appb-000011
将式(9)代入式(6)-(8)可得：
Figure PCTCN2020077697-appb-000012
因为脉冲震源时间函数的响应波场G(r,θ,z,ω)与实际震源时间函数F(ω)以及实际波场U(r,θ,z,ω)之间存在如下关系：
U(r,θ,z,ω)＝F(ω)G(r,θ,z,ω)，    (11)
所以，地震波的径向分量u r和垂向分量u z(采用柱坐标系)，以及电场的径向分量E r和垂向分量E z，根据式(10)、(11)可以表示为：
Figure PCTCN2020077697-appb-000013
其中u S(k,ω,z)，u R(k,ω,z)，E S(k,ω,z)，E R(k,ω,z)为波动和电场的核函数；F(ω)表示实际震源时间函数的傅里叶变换；u r(r,ω,z)，u z(r,ω,z)，E r(r,ω,z)，E z(r,ω,z)为时间域波场分量u r(r,t,z)，u z(r,t,z)，E r(r,t,z)，E z(r,t,z)的傅里叶变换；r和z在实际观测中分别表示一个接收器与震源的径向距离以及接收器的深度。
这样，在面波勘探中，可将(12)中的积分近似为求和，并取其虚部进行频率扫描从而得到频散谱，具体公式如下：
Figure PCTCN2020077697-appb-000014
其中，
Figure PCTCN2020077697-appb-000015
和
Figure PCTCN2020077697-appb-000016
表示近似得到的频散谱；Im[·]表示求取一个复变量的虚部；k为观测的水平波数，ω为角频率，N表示记录道的总数；r j表示第j个检波器到震源的径向距离，由于面波勘探基于水平层状地层，所有传感器与震源无需要多个传感器沿线性等间距排列或其他规则形状排列，也无需与震源保持一定的偏移距，故检波器可根据实际情况任意布设。也就是说，本实施例中，通过地震波、电场数据的联合采集和成像(现有面波勘探仅用地震波分量进行探测法)，采集系统可根据探测区域任意布设，无需线性或其他规则形状布设，且无需偏移距。所以可根据探测场地环境按任意形状排列，这样能更加综合地反映探测区域的地下速度结构，同时相较于传统的直线等间距排列且需要一定最小偏移距的面波观测系统具有更高的适用性。
S220、将所述地震波分量的频散谱和所述电场分量的频散谱叠加得到叠加的频散谱。
地球浅地表介质中时常存在地下水位面，在水位面以上介质，尤其是对于接近地表的介质，可以近似为空气填充的孔隙介质。因此，我们根据实际地层情况建立一个四层孔隙半空间模型，参数详见表1。
表1.一个四层含高速夹层半空间孔隙介质模型的参数
Figure PCTCN2020077697-appb-000017
Figure PCTCN2020077697-appb-000018
该模型第二层被设置为饱含水的孔隙介质，其他层都被设置为饱含空气的孔隙介质，潜水面位于地下10米深度的位置。震源为地表激发的垂向单力点源(锤击、落锤震源)，震源时间函数采用主频为10赫兹、延迟时间为0.5秒的雷克子波(Ricker wavelet)；为了便于数据采集，如图8所示，观测系统采用线性排列，道间距2米，共91道，接收到的地震波分量炮集记录和电场分量炮集记录见图1；根据地震波各分量炮集记录、电场各分量炮集记录得到的频散谱见图2。图2中点线为由地层参数计算得到的瑞雷波理论频散曲线。
S220包括步骤：
S221、将地震波垂向分量的频散谱和电场径向分量的频散谱叠加得到叠加的频散谱； 或者
S222、将地震波径向分量的频散谱和电场径向分量的频散谱叠加得到叠加的频散谱；或者
S223、将地震波垂向分量的频散谱、地震波径向分量的频散谱和电场径向分量的频散谱叠加得到叠加的频散谱。
从图1，我们可以看到炮集记录上瑞雷波占据主导地位，并且在面波区域电场分量E r、E z比地震波分量u r、u z高阶模式更加发育。图2频散谱中的黑色点线为理论频散曲线，可以看到频散谱中能量最大值与理论频散曲线位置相吻合，所以我们可通过能量极大值来提取瑞雷波频散曲线。从图2中我们可以看到在电场分量E r、E z的频散谱
Figure PCTCN2020077697-appb-000019
Figure PCTCN2020077697-appb-000020
中，瑞雷波高阶模式的成像质量明显高于地震分量u r、u z的频散谱
Figure PCTCN2020077697-appb-000021
u r、u z的频散谱中基阶模式的成像频段明显宽于E r、E z的频散谱。所以地震波分量和电场分量联合提取多模式频散曲线进行反演将大大降低反演的多解性，从而大大提高反演的精度和稳定性。
从图3a，我们可以看到仅用地震波u r、u z分量叠加得到的频散谱D Seismic中高阶模式成像依然没有电场分量得到的高阶模式多。考虑到电场垂直分量E z信号较弱并且在实际探测中数据采集较难，所以实际应用中我们将电场径向分量E r的频散谱与D Seismic叠加得到新的频散谱D Seismoelectirc(如图3b所示)，可以看到叠加后的频散谱中，基阶模式和高阶模式的成像质量均得到了提高。
地震波径向分量u r的采集需要水平两个分量进行转换，实际探测中需要三分量检波器进行采集，而地震波垂向分量u z的采集仅需要垂直检波器，不但经济而且高效，所以我们将u z、E r频散谱叠加与u z、u r、E r三个分量叠加频散谱进行比较。图4a为u z、E r叠加得到的频散谱，图4b为u z、u r、E r叠加得到的频散谱，我们可以看到两者没有显著差别，所以也可以只用u z、E r进行叠加，从而避免多个地震波、电场分量的采集和叠加。这样可以在保证频散谱成像质量的前提下，有效地降低采集成本。
S300、对所述叠加的频散谱进行提取处理得到频散曲线，并对所述频散曲线进行反演处理得到地层结构剖面。
具体地，S300包括步骤：
S310、通过能量极大值来提取所述叠加的频散谱得到频散曲线。
具体地，所述频散曲线为含有基阶模式、高阶模式的多模式频散曲线。通过设置区域，然后通过计算机程序自动搜索区域内的极值点的方法从频散谱上提取含有基阶、高阶模式的多模式频散曲线(见图5)，以便用于后期反演。
S320、建立初始反演地层模型，利用多种反演方法对所述频散曲线进行拟合得到地层结构剖面。
具体地，所述反演方法包括：遗传算法、群类算法、拟牛顿算法中的一种或多种。根据基础资料建立初始反演地层模型，然后可利用遗传算法、群类算法(粒子群、蜂群等)、拟牛顿等多种反演方法对图5中提取得到的多模式频散曲线进行拟合，从而反演地层结构，见图6。
将观测系统移动就可以得到多个地层位置的速度结构，将不同位置的速度结构进行插值，根据空间位置即可绘制地层剖面，如图7。
基于上述任意一实施例所述的震电波场联合提取瑞雷波频散特征的面波勘探方法，本发明还提供了一种震电波场联合提取瑞雷波频散特征的面波勘探装置的较佳实施例：
本发明实施例所述一种震电波场联合提取瑞雷波频散特征的面波勘探装置，包括：采集装置，用于获取联合采集的数据；其中，所述联合采集的数据包括：地震波数据和电场数据；
联合成像装置，用于将所述联合采集的数据进行联合成像处理得到叠加的频散谱；
反演装置，用于对所述叠加的频散谱进行提取处理得到频散曲线，并对所述频散曲线进行反演处理得到地层结构剖面。
所述地震波数据包括：地震波分量；所述电场数据包括：电场分量。
所述联合成像装置具体用于根据所述地震波分量、所述电场分量分别得到地震波分量的频散谱、电场分量的频散谱；并将所述地震波分量的频散谱和所述电场分量的频散谱叠加得到叠加的频散谱。
所述联合成像装置还用于分别提取所述地震波分量的虚部、所述电场分量的虚部后 进行频率扫描得到地震波分量的频散谱、电场分量的频散谱。
所述地震波分量包括：地震波径向分量和/或地震波垂向分量；所述电场分量包括：电场径向分量和/或电场垂向分量。
所述联合成像装置还用于将地震波垂向分量的频散谱和电场径向分量的频散谱叠加得到叠加的频散谱；或者
将地震波径向分量的频散谱和电场径向分量的频散谱叠加得到叠加的频散谱；或者
将地震波垂向分量的频散谱、地震波径向分量的频散谱和电场径向分量的频散谱叠加得到叠加的频散谱。
所述反演装置具体用于通过能量极大值来提取所述叠加的频散谱得到频散曲线；所述频散曲线为含有基阶模式、高阶模式的多模式频散曲线。
所述反演装置还用于建立初始反演地层模型，利用多种反演方法对所述频散曲线进行拟合得到地层结构剖面；所述反演方法包括：遗传算法、群类算法、拟牛顿算法中的一种或多种。
基于上述任意一实施例所述的震电波场联合提取瑞雷波频散特征的面波勘探方法，本发明还提供了一种终端设备的较佳实施例：
本发明实施例所述一种终端设备，包括：处理器，以及与所述处理器连接的存储器，
所述存储器存储有震电波场联合提取瑞雷波频散特征的面波勘探程序，所述震电波场联合提取瑞雷波频散特征的面波勘探程序被所述处理器执行时实现以下步骤：
获取联合采集的数据；其中，所述联合采集的数据包括：地震波数据和电场数据；
将所述联合采集的数据进行联合成像处理得到叠加的频散谱；
对所述叠加的频散谱进行提取处理得到频散曲线，并对所述频散曲线进行反演处理得到地层结构剖面。
所述地震波数据包括：地震波分量；所述电场数据包括：电场分量。
所述震电波场联合提取瑞雷波频散特征的面波勘探程序被所述处理器执行时，还实现以下步骤：
根据所述地震波分量、所述电场分量分别得到地震波分量的频散谱、电场分量的频 散谱；
将所述地震波分量的频散谱和所述电场分量的频散谱叠加得到叠加的频散谱。
所述震电波场联合提取瑞雷波频散特征的面波勘探程序被所述处理器执行时，还实现以下步骤：
分别提取所述地震波分量的虚部、所述电场分量的虚部后进行频率扫描得到地震波分量的频散谱、电场分量的频散谱。
所述地震波分量包括：地震波径向分量和/或地震波垂向分量；所述电场分量包括：电场径向分量和/或电场垂向分量。
所述震电波场联合提取瑞雷波频散特征的面波勘探程序被所述处理器执行时，还实现以下步骤：
将地震波垂向分量的频散谱和电场径向分量的频散谱叠加得到叠加的频散谱；或者
将地震波径向分量的频散谱和电场径向分量的频散谱叠加得到叠加的频散谱；或者
将地震波径向分量的频散谱、地震波垂向分量的频散谱和电场径向分量的频散谱叠加得到叠加的频散谱。
所述震电波场联合提取瑞雷波频散特征的面波勘探程序被所述处理器执行时，还实现以下步骤：
通过能量极大值来提取所述叠加的频散谱得到频散曲线。
所述频散曲线为含有基阶模式、高阶模式的多模式频散曲线。
所述震电波场联合提取瑞雷波频散特征的面波勘探程序被所述处理器执行时，还实现以下步骤：
建立初始反演地层模型，利用多种反演方法对所述频散曲线进行拟合得到地层结构剖面。
所述反演方法包括：遗传算法、群类算法、拟牛顿算法中的一种或多种。
基于上述任意一实施例所述的震电波场联合提取瑞雷波频散特征的面波勘探方法，本发明还提供了一种存储介质的较佳实施例：
本发明实施例所述一种存储介质，其上存储有震电波场联合提取瑞雷波频散特征的 面波勘探程序，所述震电波场联合提取瑞雷波频散特征的面波勘探程序被处理器执行时实现以下步骤：
获取联合采集的数据；其中，所述联合采集的数据包括：地震波数据和电场数据；
将所述联合采集的数据进行联合成像处理得到叠加的频散谱；
对所述叠加的频散谱进行提取处理得到频散曲线，并对所述频散曲线进行反演处理得到地层结构剖面。
应当理解的是，本发明的应用不限于上述的举例，对本领域普通技术人员来说，可以根据上述说明加以改进或变换，所有这些改进和变换都应属于本发明所附权利要求的保护范围。

Claims (10)

  1. 一种震电波场联合提取瑞雷波频散特征的面波勘探方法，其特征在于，包括步骤：
    获取联合采集的数据；其中，所述联合采集的数据包括：地震波数据和电场数据；
    将所述联合采集的数据进行联合成像处理得到叠加的频散谱；
    对所述叠加的频散谱进行提取处理得到频散曲线，并对所述频散曲线进行反演处理得到地层结构剖面。
  2. 根据权利要求1所述的震电波场联合提取瑞雷波频散特征的面波勘探方法，其特征在于，所述地震波数据包括：地震波分量；所述电场数据包括：电场分量；
    所述将所述联合采集的数据进行联合成像处理得到叠加的频散谱，包括：
    根据所述地震波分量、所述电场分量分别得到地震波分量的频散谱、电场分量的频散谱；
    将所述地震波分量的频散谱和所述电场分量的频散谱叠加得到叠加的频散谱。
  3. 根据权利要求2所述的震电波场联合提取瑞雷波频散特征的面波勘探方法，其特征在于，所述根据所述地震波分量、所述电场分量分别得到地震波分量的频散谱、电场分量的频散谱，包括：
    分别提取所述地震波分量的虚部、所述电场分量的虚部后进行频率扫描得到地震波分量的频散谱、电场分量的频散谱。
  4. 根据权利要求2-3任意一项所述的震电波场联合提取瑞雷波频散特征的面波勘探方法，其特征在于，所述地震波分量包括：地震波径向分量和/或地震波垂向分量；所述电场分量包括：电场径向分量和/或电场垂向分量。
  5. 根据权利要求4所述的震电波场联合提取瑞雷波频散特征的面波勘探方法，其特征在于，所述将所述地震波分量的频散谱和所述电场分量的频散谱叠加得到叠加的频散谱，包括：
    将地震波垂向分量的频散谱和电场径向分量的频散谱叠加得到叠加的频散谱；或者
    将地震波径向分量的频散谱和电场径向分量的频散谱叠加得到叠加的频散谱；或者
    将地震波垂向分量的频散谱、地震波径向分量的频散谱和电场径向分量的频散谱叠加得到叠加的频散谱。
  6. 根据权利要求1所述的震电波场联合提取瑞雷波频散特征的面波勘探方法，其特征在于，所述对所述叠加的频散谱进行提取处理得到频散曲线，包括：
    通过能量极大值来提取所述叠加的频散谱得到频散曲线；所述频散曲线为含有基阶模式、高阶模式的多模式频散曲线。
  7. 根据权利要求1所述的震电波场联合提取瑞雷波频散特征的面波勘探方法，其特征在于，所述对所述频散曲线进行反演处理得到地层结构剖面，包括：
    建立初始反演地层模型，利用多种反演方法对所述频散曲线进行拟合得到地层结构剖面；所述反演方法包括：遗传算法、群类算法、拟牛顿算法中的一种或多种。
  8. 一种震电波场联合提取瑞雷波频散特征的面波勘探装置，其特征在于，包括：
    采集装置，用于获取联合采集的数据；其中，所述联合采集的数据包括：地震波数据和电场数据；
    联合成像装置，用于将所述联合采集的数据进行联合成像处理得到叠加的频散谱；
    反演装置，用于对所述叠加的频散谱进行提取处理得到频散曲线，并对所述频散曲线进行反演处理得到地层结构剖面。
  9. 一种终端设备，其特征在于，包括：处理器，以及与所述处理器连接的存储器，
    所述存储器存储有震电波场联合提取瑞雷波频散特征的面波勘探程序，所述震电波场联合提取瑞雷波频散特征的面波勘探程序被所述处理器执行时实现以下权利要求1-7任意一项所述的震电波场联合提取瑞雷波频散特征的面波勘探方法的步骤。
  10. 一种存储介质，其特征在于，其上存储有震电波场联合提取瑞雷波频散特征的面波勘探程序，所述震电波场联合提取瑞雷波频散特征的面波勘探程序被处理器执行时实现权利要求1-7中任意一项所述的震电波场联合提取瑞雷波频散特征的面波勘探方法的步骤。
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