CN110780344A - Shallow earth surface structure imaging method and device - Google Patents
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Abstract
The invention provides a method and a device for imaging a shallow earth surface structure, wherein the method comprises the following steps: acquiring a vibration wave field of underground rail transit according to the underground rail transit vibration signal; carrying out complex field continuation on a vibration wave field of the underground rail transit to obtain a complex field vibration wave field; determining cross-correlation imaging conditions of a plurality of components of the seismic wavefield from the complex field seismic wavefield; and according to the cross-correlation imaging conditions of the multiple components of the vibration wave field, performing reverse time migration imaging of the multiple components of the vibration wave field to obtain shallow earth surface structure imaging. The invention can realize the imaging of the shallow earth surface structure based on the vibration signal generated by the underground rail transit, and has high accuracy.
Description
Technical Field
The invention relates to the technical field of seismic exploration, in particular to a shallow earth surface structure imaging method and device.
Background
Urban underground rail transit is a main urban traffic mode because of the characteristics of energy conservation, greenness, all weather, large passenger capacity and safety, and is particularly suitable for large and medium-sized cities. The 21 st century is a century for large-scale development and utilization of underground space by human beings, along with the acceleration of the urbanization process, the living and production subsidiary facilities of population are switched into the underground, the urban development space is expanded, a more convenient, safe and comfortable living environment is provided for people, the urban development space is an important measure and research direction for solving the urban development dilemma, and the urban development space is also against the original intention of building smart cities nowadays.
The running speed of the subway which is running is close to the constant speed, the determined length and the load enable the subway to become a repeatable artificial seismic source, and the distribution range and the signal-to-noise ratio of the artificial seismic source are widened by the underground criss-cross rail transit network system and the shorter running interval of the rail transit, so that the subway has great potential for detecting the underground structure and physical property information of the shallow layer of the city. The main information of the existing digital city is the distribution of buildings above the earth surface obtained by remote sensing observation on one hand, and the design information of underground pipe networks on the other hand. Underground information of a shallow ring layer of the earth serving as an urban carrier is still very rare, and the underground information of the shallow layer of the earth cannot be acquired in all directions, which is extremely disadvantageous to creation of smart city groups. Through the geophysical processing and application of vibration data generated in underground rail transit, underground information of a shallow part circle layer of the earth serving as an urban carrier is obtained, underground space is exploited, land resource utilization is extended to a deep part, the method is an important method way for constructing a smart city, the cost of development of new infrastructure can be reduced, risks caused by geological disasters can be evaluated, and natural resources can be continuously utilized. Therefore, shallow earth surface structure imaging of the underground rail transit coverage area is carried out based on the vibration signals generated by the urban underground rail transit, so that shallow earth surface structure information and physical property information are obtained, the infrastructure construction process is optimized, the construction cost is saved, and the method has great theoretical and practical significance. At present, an effective method for realizing shallow earth surface structure imaging based on vibration signals generated by underground rail transit is lacked.
Disclosure of Invention
The embodiment of the invention provides a shallow earth surface structure imaging method, which is used for realizing shallow earth surface structure imaging based on a vibration signal generated by underground rail transit and has high accuracy, and the method comprises the following steps:
acquiring a vibration wave field of underground rail transit according to the underground rail transit vibration signal;
carrying out complex field continuation on a vibration wave field of the underground rail transit to obtain a complex field vibration wave field;
determining cross-correlation imaging conditions of a plurality of components of the seismic wavefield from the complex field seismic wavefield;
and according to the cross-correlation imaging conditions of the multiple components of the vibration wave field, performing reverse time migration imaging of the multiple components of the vibration wave field to obtain shallow earth surface structure imaging.
The embodiment of the invention provides a shallow earth surface structure imaging device, which is used for realizing shallow earth surface structure imaging based on a vibration signal generated by underground rail transit and has high accuracy, and the device comprises:
the vibration wave field obtaining module is used for obtaining a vibration wave field of the underground rail transit according to the underground rail transit vibration signal;
the complex field vibration wave field obtaining module is used for carrying out complex field continuation on the vibration wave field of the underground rail transit to obtain a complex field vibration wave field;
the device comprises a cross-correlation imaging condition obtaining module, a complex field vibration wave field obtaining module and a vibration wave field generating module, wherein the cross-correlation imaging condition obtaining module is used for determining cross-correlation imaging conditions of a plurality of components of the vibration wave field according to the complex field vibration wave field;
and the shallow surface structure imaging module is used for performing reverse time migration imaging on the components of the vibration wave field according to the cross-correlation imaging conditions of the components of the vibration wave field to obtain shallow surface structure imaging.
The embodiment of the present invention further provides a computer device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor implements the above-mentioned shallow surface structure imaging method when executing the computer program.
The embodiment of the invention also provides a computer readable storage medium, which stores a computer program for executing the shallow surface structure imaging method.
In the embodiment of the invention, a vibration wave field of underground rail transit is obtained according to the underground rail transit vibration signal; carrying out complex field continuation on a vibration wave field of the underground rail transit to obtain a complex field vibration wave field; determining cross-correlation imaging conditions of a plurality of components of the seismic wavefield from the complex field seismic wavefield; and according to the cross-correlation imaging conditions of the multiple components of the vibration wave field, performing reverse time migration imaging of the multiple components of the vibration wave field to obtain shallow earth surface structure imaging. In the process, complex field continuation is carried out on the vibration wave field of the underground rail transit, the complex field vibration wave field is obtained, and low-frequency noise and imaging false noise in offset imaging can be suppressed when reverse time offset imaging is carried out under the condition of cross-correlation imaging of a plurality of components of the vibration wave field determined according to the complex field vibration wave field, so that the imaging accuracy of the obtained shallow earth surface structure is high.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts. In the drawings:
FIG. 1 is a flow chart of a method for imaging a shallow earth formation in an embodiment of the invention;
FIG. 2 is a detailed flowchart of a method for imaging a shallow surface structure according to an embodiment of the present invention;
fig. 3 is a schematic diagram of an imaging device for a shallow ground surface structure according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the embodiments of the present invention are further described in detail below with reference to the accompanying drawings. The exemplary embodiments and descriptions of the present invention are provided to explain the present invention, but not to limit the present invention.
In the description of the present specification, the terms "comprising," "including," "having," "containing," and the like are used in an open-ended fashion, i.e., to mean including, but not limited to. Reference to the description of the terms "one embodiment," "a particular embodiment," "some embodiments," "for example," etc., means that a particular feature, structure, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the application. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. The sequence of steps involved in the embodiments is for illustrative purposes to illustrate the implementation of the present application, and the sequence of steps is not limited and can be adjusted as needed.
Fig. 1 is a flowchart of a method for imaging a shallow surface structure according to an embodiment of the present invention, as shown in fig. 1, the method including:
102, carrying out complex field continuation on a vibration wave field of the underground rail transit to obtain a complex field vibration wave field;
103, determining cross-correlation imaging conditions of a plurality of components of the vibration wave field according to the complex field vibration wave field;
and 104, performing reverse time migration imaging on the multiple components of the vibration wave field according to the cross-correlation imaging conditions of the multiple components of the vibration wave field to obtain shallow earth surface structure imaging.
In the embodiment of the invention, the complex field continuation is carried out on the vibration wave field of the underground rail transit, the complex field vibration wave field is obtained, and the low-frequency noise and the imaging false noise in the offset imaging can be suppressed when the reverse time offset imaging is carried out under the condition of cross-correlation imaging of a plurality of components of the vibration wave field determined according to the complex field vibration wave field, so that the imaging accuracy of the obtained shallow earth surface structure is high.
In specific implementation, before step 101, an underground rail transit seismic signal needs to be obtained, seismic interference is performed because a seismic wave field of underground rail transit is obtained, and the seismic interference requires an assumption that detectors are surrounded by seismic sources and a medium is a lossless medium, so that the distribution of the seismic sources has a great influence on the interference result, specifically, an actual problem of the underground rail transit seismic sources is reflected on the arrangement mode of the detectors, in order to obtain a better interference result, seismic data with a longer period can be recorded/superposed or more detectors are arranged in front of, behind, on the left of and on the right of a target area along a rail, so that the target area is surrounded as much as possible, and the distribution of the seismic sources is approximately dispersed.
In the implementation, there are various methods for obtaining the seismic wavefield of the underground rail transit according to the underground rail transit seismic signal, and one example is given below.
In one embodiment, obtaining a seismic wavefield of underground rail transit from an underground rail transit seismic signal includes:
obtaining virtual body wave records of a plurality of seismic records according to the underground rail transit vibration signals, wherein the virtual body wave records comprise longitudinal wave records and transverse wave records;
and performing numerical simulation on the input seismic source wavelet and the virtual body wave record of the multi-channel seismic record to obtain a seismic wave field of underground rail transit.
In the above embodiment, the underground rail transit seismic signal includes a plurality of seismic records, which is equivalent to extracting virtual body wave records of the seismic records.
In one embodiment, before obtaining the virtual volume wave records of the multiple seismic records according to the underground rail transit seismic signals, the method further comprises the following steps:
carrying out time-frequency domain response analysis on the underground rail transit vibration signal to obtain the time-frequency domain response characteristics of the underground rail transit vibration signal;
preprocessing the underground rail transit vibration signals according to the time-frequency domain response characteristics;
according to underground rail transit vibrations signal, obtain the virtual body wave record of multichannel seismic record, include:
and obtaining a plurality of virtual body wave records of the seismic records according to the preprocessed underground rail transit vibration signals.
In the above embodiment, the time-frequency domain response analysis is performed on the underground rail transit vibration signal, that is, the time-domain response analysis and the frequency-domain response analysis are performed on the underground rail transit vibration signal, and in addition, based on the time-frequency domain response characteristics of the underground rail transit vibration signal, the magnitude of the vibration response difference of different underground rail transit vehicles (for example, subway trains) passing through the same spatial position and the magnitude of the vibration response difference of the same vehicle passing through different spatial positions can be compared by using variance analysis to determine the repeatability characteristics of the underground rail transit vibration signal; and describing the distribution aggregation condition of the underground rail transit vibration signal characteristics at different space receiving points on the flow form by utilizing a cluster analysis algorithm so as to illustrate the aggregation of the underground rail transit vibration signal in a characteristic space and the consistency of the aggregation of a geographic space, and illustrating the consistency of the underground rail transit vibration signal characteristics with a geological structure environment on a finer scale according to the consistency degree. The analysis processes can determine the characteristics of the underground rail transit vibration signal such as repeatability, the consistency of the aggregation in the characteristic space and the aggregation in the geographic space and the consistency with the geological structure environment, and the three characteristics can further prove that the underground rail transit vibration signal can be used for obtaining shallow surface structure imaging.
In an embodiment, the pre-processing comprises a filtering process and/or an amplitude normalization process.
In the above embodiment, the filtering process may be a band-pass filtering process, and a part of external interference may be eliminated through the above preprocessing, so that a vibration signal with a single component is obtained, and the subsequent imaging accuracy is improved.
In specific implementation, there are various methods for obtaining virtual body wave records of a plurality of seismic records according to the preprocessed underground rail transit seismic signals, and one embodiment is given below.
In one embodiment, obtaining a virtual volume wave record of a plurality of seismic records according to the preprocessed underground rail transit seismic signals comprises:
and extracting a plurality of virtual body wave records of the seismic records from the preprocessed underground rail transit vibration signals by adopting a seismic interference method.
In the above embodiment, the seismic interference method is applied to the preprocessed underground rail transit seismic data, and normalization processing is performed to extract a plurality of virtual body wave records of the seismic records.
In one embodiment, extracting a plurality of virtual body wave records of seismic records from the preprocessed underground rail transit seismic signals by using a seismic interference method, includes:
and performing cross-correlation operation on each seismic record in the preprocessed underground rail transit vibration signals and other records to synthesize a virtual body wave record of the seismic record.
In the above embodiment, the virtual volume wave record includes a longitudinal wave record and a transverse wave record, the location of the shot point is the location of the selected demodulator probe, and the other demodulator probes are the receiving points, that is, two demodulator probes are respectively set as a virtual shot point and a demodulator probe combination, and the obtained response is equivalent to the convolution of the green function between the two demodulator probes and the seismic wavelet.
In specific implementation, there are various methods for obtaining the seismic wave field of underground rail transit by performing numerical simulation on the input seismic source wavelet and the virtual body wave record of the multi-channel seismic record, and one of the following embodiments is given.
In an embodiment, the seismic wavefields include a shot wavefield and a geophone wavefield;
carrying out numerical simulation on input seismic source wavelets and virtual body wave records of a plurality of seismic records to obtain a seismic wave field of underground rail transit, and the method comprises the following steps:
carrying out forward transmission numerical simulation on the input seismic source wavelet to obtain a shot point wave field;
and performing back propagation numerical simulation on the virtual body wave records of the multi-channel seismic records to obtain a wave field of a wave detection point.
In one embodiment, forward propagating numerical simulations of input source wavelets to obtain a shot wavefield include:
performing forward transmission numerical simulation on the input seismic source wavelet by adopting a finite difference operator optimized by an improved PSO-BFO algorithm to obtain a shot point wave field;
carrying out back propagation numerical simulation on the virtual body wave record of the multi-channel seismic record to obtain a wave field of a wave detection point, and the method comprises the following steps:
and performing back propagation numerical simulation on the virtual body wave record of the multi-channel seismic record by adopting a finite difference operator optimized by an improved PSO-BFO algorithm to obtain a wave field of a wave detection point.
In the two embodiments, forward numerical simulation and inverse numerical simulation are respectively performed on the input seismic source wavelet and the virtual volume wave record of the multi-channel seismic record by using a finite difference operator optimized by an improved PSO-BFO algorithm, so that the accuracy and efficiency of the numerical simulation can be improved, and the simulation process is as follows:
firstly, performing discrete processing on the elastic wave equation by using a finite difference operator to obtain the following elastic wave equation subjected to discrete processing:
wherein the content of the first and second substances,
and
is a discrete time domain wavefield.
Δ t is a time step, and Δ x and Δ z are space steps.
a
mAre finite difference coefficients in the time domain.
And N is the order of the difference operator.
Because the difference operator is an approximation of the differential operator, it can be understood that a finite point weighted combination constitutes the differential operator, and therefore, an error, that is, a numerical dispersion error is inevitably introduced, which causes dispersion noise during imaging. Therefore, the embodiment of the invention provides that a finite difference operator is optimized by adopting an improved PSO-BFO algorithm, forward numerical simulation and backward numerical simulation are performed on input seismic source wavelets and virtual volume wave records of a plurality of seismic records by using the optimized finite difference operator, so as to further improve the precision and efficiency of the simulation, wherein the PSO is a particle swarm algorithm, the BFO is a bacterial foraging algorithm, and known first-order and second-order derivatives can be expressed as follows by using the difference operator:
wherein f is
n＝f(nΔx)，
Are finite difference coefficients.
Applying the fourier transform to equations (2) and (3) yields:
then, an error function of the first and second derivatives, i.e. an objective function, can be obtained according to the formula (4) and the formula (5), wherein the coefficients in the objective function are the coefficients to be optimized, and the objective functions expressed by the formula (6) and the formula (7) are as follows:
the advantages of an improved Particle Swarm Optimization (PSO) algorithm and a Bacterial Foraging Optimization (BFO) algorithm are applied to form the improved PSO-BFO algorithm, parallel search can be realized, the parameter optimization speed in multi-parameter optimization is improved, the calculation complexity is reduced, and the interference of local extreme values on final results is avoided. The improved PSO-BFO algorithm is applied to carry out optimization solution on an objective function containing a finite difference coefficient to obtain an optimized finite difference operator, and then the finite difference operator is utilized to carry out seismic wave field numerical simulation, so that the precision and the efficiency of the wave field numerical simulation can be improved. The specific process of improving the PSO-BFO algorithm is to apply the improved PSO algorithm in the BFO algorithm, update the trend direction of bacteria, reduce the search space range, improve the convergence speed and enable the improved algorithm to converge to the position of the optimal solution more quickly. The detailed steps of the improved PSO-BFO algorithm are as follows:
the first step is as follows: initializing parameters N, S, N
c,N
s,N
re,N
ed,P
edN is the search space dimension, S is the total number of bacteria in the population, N
cNumber of steps to approach step, N
sLength of swimming for bacteria, N
reFor the number of copying steps, N
edNumber of migration events, P
edIs the probability of a migration event. Bacteria are counted as i, migration events as j, replication events as k and trending events as l.
In the course of the trend, the direction of movement of each bacterium can be expressed as:
P(j,k,l)＝θ
i(j,k,l),i＝1,2,...S,
wherein, C (i) refers to the step size of the designated random direction in the overturning process of the bacteria i. Δ represents one unit vector in the random direction.
The fitness function J (i, J, k, l) of the bacteria is defined as:
J(i,j,k,l)＝J(i,j,k,l)+J
cc(θ
i(j,k,l),P(j,k,l))
wherein, J
ccAggregation behavior was simulated for intercellular repulsion.
The second step is that: calculating the fitness function J (i, J, k, l) of bacterium i, and making J
lastJ (i, J, k, l), stored as the optimal adaptation value for bacterium i.
The third step: updating the moving direction of bacteria i:
the second step is repeated and the fitness function J (i, J +1, k, l) of bacterium i is calculated.
Let m be the step length of the swim, when m is less than N
sIf J (i, J +1, k, l) < J
lastThe motion direction and fitness function continue to be updated. If J (i, J +1, k, l) > J
lastThen retain the current value to J
last。
Returning to the second step, the next bacterium i +1 is processed.
The fourth step: and selecting M bacteria positions with local better solutions, then calculating the average position of the M bacteria positions with local better solutions, and carrying out linear combination with the optimal position in the M bacteria positions with local optimal solutions to be used as the current optimal position E.
The fifth step: setting a range of an optimal solution which can be converged, traversing bacteria i, i-1, 2.. S, counting when the fitness of the bacteria i, i-1, 2.. S is within a threshold range of the optimal solution which can be converged, marking as P, randomly selecting a bacteria position as a learning object in the group P, and marking the randomly selected bacteria number as gamma
z＝rand()％P。
And a sixth step: applying the modified PSO algorithm, calculate the new direction for each bacterium i:
the seventh step: the next tropism operation is performed.
Eighth step: for a given k, l and each i ═ 1, 2.. S, the bacterial energy J is measured
healthArranged in the order from small to largeAnd (3) eliminating S/2 bacteria with smaller energy values, selecting the rest bacteria for replication, and dividing each bacteria into two identical bacteria. If k is less than N
reAnd returning to the sixth step.
The ninth step: after several generations of replication of the bacteria, each bacterium replicates with a probability P
edAre redistributed into the optimization space until the loop ends.
The improved PSO-BFO algorithm is applied to the solution of the optimized finite difference coefficient, namely an objective function formula (6) and a formula (7) are solved to obtain the optimized finite difference coefficient, so that a finite difference operator is constructed, and finally forward numerical simulation and backward numerical simulation are carried out on virtual body wave records of the input seismic source wavelet and the multi-channel seismic records by adopting the finite difference operator optimized by the improved PSO-BFO algorithm, so that the precision of the obtained shot point wave field and the wave detection point wave field is very high.
In specific implementation, there are various methods for obtaining a complex field seismic wave field by performing complex field continuation on a seismic wave field of underground rail transit, and one embodiment is given below.
In one embodiment, the complex domain continuation of the seismic wavefield of underground rail transit to obtain a complex domain seismic wavefield includes:
and (3) performing complex field continuation on the vibration wave field of the underground rail transit by adopting Hilbert transform to obtain a complex field vibration wave field.
In the above embodiment, Hilbert transform is adopted to perform complex domain continuation on the vibration wave field of underground rail transit, and there is no need to store elastic vector wave fields at all times and perform fourier transform, so that the storage capacity and the calculation amount can be significantly reduced, and a specific algorithm is shown in the following formula:
the above formula is applied to carry out complex field expansion on the vibration wave field s (t, x, z), wherein E
tIs a time complex field expansion operator, E
x,E
zIs a spatial complex field expansion operator.
In elastic wave reverse time migration imaging noiseThe low frequency noise and imaging artifact noise mainly originate from directional wave cross-correlation imaging in a specific direction, such as I
ldld,I
lulu,I
rdrd,I
ruru... the combination of these same subscripts is the main source of low frequency noise for imaging; and I
luld,I
lurd,I
ruld,I
rurd.. traveling up and down in the shot and geophone fields, when there is a strong velocity change, will result in primary artifacts due to the presence of backscatter, but this combination is accurate in imaging the bottom structure of the salt dome. In addition, if the inclination angle of the underground reflecting layer is large, a good result can be obtained by adopting the combination of the shot point left traveling wave and the demodulator probe right traveling wave. Therefore, in order to suppress low frequency noise and imaging artifact noise, the wavefield before imaging needs to be decomposed by directional waves.
In an embodiment, prior to determining the cross-correlation imaging condition for the plurality of components of the seismic wavefield from the complex-field seismic wavefield, further comprising:
and carrying out directional wave decomposition on the complex field vibration wave field to obtain a plurality of components of the vibration wave field.
In the above embodiment, the directional wave decomposition is performed for longitudinal and transverse waves, and is decomposed into four directional waves, i.e., up, down, left, and right, depending on the propagation direction of the longitudinal and transverse waves.
In one embodiment, the plurality of components of the seismic wavefield include a lower left directional wave, an upper left directional wave, a lower right directional wave, an upper right directional wave of the compressional wavefield, and a lower left directional wave, an upper left directional wave, a lower right directional wave, an upper right directional wave of the shear wavefield.
The following describes an omnidirectional directional wave decomposition strategy taking longitudinal waves as an example.
First, each seismic wavefield is recorded as
The superscript p represents the longitudinal wave. Subscripts l, r represent left and right, u, d represent up and down. The longitudinal wave field of the shot point wave field and the geophone point wave field can be expressed after being decomposed according to four directions of up, down, left and right:
wherein S is
pAnd R
pLongitudinal wave fields which are respectively a shot point wave field and a wave detection point wave field;
the wave fields are respectively the lower left directional wave, the lower right directional wave, the upper left directional wave and the upper right directional wave of the longitudinal wave field of the shot point wave field;
According to the formula (9), complex domain expansion can be performed on the seismic wavefield s (t, x, z) to obtain a complex domain seismic wavefield, and therefore, directional wave decomposition is performed on the complex domain seismic wavefield, and a plurality of components of the obtained seismic wavefield are as follows (taking the longitudinal wave wavefield of the shot wavefield as an example):
wherein H
x,H
z,H
tRepresenting the Hilbert transform in the time-space domain.
By using the complex domain expansion of Hilbert transform, the calculation efficiency can be greatly improved, the storage capacity can be reduced, elastic vector wave fields at all times do not need to be stored, and Fourier transform of a time-space domain does not need to be performed.
In step 103, according to the complex field seismic wave field, the cross-correlation imaging conditions of multiple components of the seismic wave field need to be determined, and based on the above advantages of complex field expansion of Hilbert transform, the embodiment of the present invention proposes the cross-correlation imaging conditions based on Hilbert transform.
Taking the left lower directional wave of the longitudinal wave field of the shot point wave field and the right upper directional wave of the longitudinal wave field of the demodulator probe wave field as examples, the cross-correlation imaging conditions corresponding to the directional waves are as follows:
operator E is expanded due to time complex field
tThe active shot or geophone wavefields are both 0 when the time is negative, so E
tOnly one time of action is needed for the shot point wave field or the wave detection point wave field. The embodiment of the invention selects an operator E only applied to the wave field of the wave detection point
t(ii) a Hilbert transformation of the wave field data of the demodulator probe based on time is firstly adopted, and then wave field continuation is carried out during reverse time migration imaging; therefore, wave fields at all moments can be prevented from being stored, and the cost for reverse time migration imaging is greatly reduced.
And (3) developing the formula (12), and obtaining the cross-correlation imaging condition that the lower left directional wave of the longitudinal wave field of the shot point wave field and the upper right directional wave of the longitudinal wave field of the demodulator probe wave field are based on Hilbert transform:
applying the cross-correlation imaging condition of equation (13) to perform reverse time migration imaging of multiple components of the seismic wavefield, it is possible to suppress low-frequency noise and imaging artifact noise in the reverse time migration imaging, so that the accuracy of the obtained shallow earth surface structure imaging is very high.
In an embodiment, the method further comprises:
and analyzing the structural information and physical property information of the shallow earth surface according to the shallow earth surface structural imaging.
Because the obtained shallow surface structure imaging accuracy is very high, the method provided by the embodiment of the invention can accurately analyze the structure information and physical property information of the shallow surface so as to optimize the construction process of underground space infrastructures such as tunnels and the like, save the construction cost and provide reference for the construction of smart cities.
Based on the above embodiments, the present invention provides the following embodiment to explain a detailed flow of the shallow surface structure imaging method, fig. 2 is a detailed flow chart of the shallow surface structure imaging method provided by the embodiment of the present invention, as shown in fig. 2, in an embodiment, the detailed flow of the shallow surface structure imaging method includes:
and step 210, analyzing the structural information and physical property information of the shallow earth surface according to the shallow earth surface structural imaging.
Of course, it is understood that there may be other variations to the detailed flow of the above-mentioned shallow surface structure imaging method, and all the related variations should fall into the scope of the present invention.
In summary, in the method provided by the embodiment of the invention, a vibration wave field of underground rail transit is obtained according to the underground rail transit vibration signal; carrying out complex field continuation on a vibration wave field of the underground rail transit to obtain a complex field vibration wave field; determining cross-correlation imaging conditions of a plurality of components of the seismic wavefield from the complex field seismic wavefield; and according to the cross-correlation imaging conditions of the multiple components of the vibration wave field, performing reverse time migration imaging of the multiple components of the vibration wave field to obtain shallow earth surface structure imaging. In the process, complex field continuation is carried out on the vibration wave field of the underground rail transit, the complex field vibration wave field is obtained, and low-frequency noise and imaging false noise in offset imaging can be suppressed when reverse time offset imaging is carried out under the condition of cross-correlation imaging of a plurality of components of the vibration wave field determined according to the complex field vibration wave field, so that the imaging accuracy of the obtained shallow earth surface structure is high.
Based on the same inventive concept, the embodiment of the invention also provides a shallow surface structure imaging device, as described in the following embodiments. Since the principles of these solutions are similar to the method for imaging a shallow surface structure, the implementation of the apparatus can be referred to the implementation of the method, and the repetition is not repeated.
Fig. 3 is a schematic view of an imaging apparatus for shallow ground surface structures according to an embodiment of the present invention, as shown in fig. 3, the apparatus including:
the vibration wave field obtaining module 301 is used for obtaining a vibration wave field of underground rail transit according to the underground rail transit vibration signal;
a complex field seismic wave field obtaining module 302, configured to perform complex field continuation on a seismic wave field of the underground rail transit to obtain a complex field seismic wave field;
a cross-correlation imaging condition obtaining module 303, configured to determine, according to the complex field seismic wave field, cross-correlation imaging conditions of multiple components of the seismic wave field;
and a shallow surface structure imaging module 304, configured to perform reverse time migration imaging of the multiple components of the seismic wave field according to the cross-correlation imaging conditions of the multiple components of the seismic wave field, so as to obtain a shallow surface structure image.
In one embodiment, the seismic wavefield acquisition module 301 is specifically configured to:
obtaining virtual body wave records of a plurality of seismic records according to the underground rail transit vibration signals, wherein the virtual body wave records comprise longitudinal wave records and transverse wave records;
and performing numerical simulation on the input seismic source wavelet and the virtual body wave record of the multi-channel seismic record to obtain a seismic wave field of underground rail transit.
In one embodiment, the apparatus further comprises a preprocessing module 305 for:
carrying out time-frequency domain response analysis on the underground rail transit vibration signal to obtain the time-frequency domain response characteristics of the underground rail transit vibration signal;
preprocessing the underground rail transit vibration signals according to the time-frequency domain response characteristics;
the seismic wavefield acquisition module 301 is specifically configured to:
and obtaining a plurality of virtual body wave records of the seismic records according to the preprocessed underground rail transit vibration signals.
In an embodiment, the pre-processing comprises a filtering process and/or an amplitude normalization process.
In one embodiment, the seismic wavefield acquisition module 301 is specifically configured to:
and extracting a plurality of virtual body wave records of the seismic records from the preprocessed underground rail transit vibration signals by adopting a seismic interference method.
In one embodiment, the seismic wavefield acquisition module 301 is specifically configured to:
and performing cross-correlation operation on each seismic record in the preprocessed underground rail transit vibration signals and other records to synthesize a virtual body wave record of the seismic record.
In an embodiment, the seismic wavefields include a shot wavefield and a geophone wavefield;
the seismic wavefield acquisition module 301 is specifically configured to:
carrying out forward transmission numerical simulation on the input seismic source wavelet to obtain a shot point wave field;
and performing back propagation numerical simulation on the virtual body wave records of the multi-channel seismic records to obtain a wave field of a wave detection point.
In one embodiment, the seismic wavefield acquisition module 301 is specifically configured to:
performing forward transmission numerical simulation on the input seismic source wavelet by adopting a finite difference operator optimized by an improved PSO-BFO algorithm to obtain a shot point wave field;
in one embodiment, the seismic wavefield acquisition module 301 is specifically configured to:
and performing back propagation numerical simulation on the virtual body wave record of the multi-channel seismic record by adopting a finite difference operator optimized by an improved PSO-BFO algorithm to obtain a wave field of a wave detection point.
In an embodiment, the complex-field seismic wavefield acquisition module 302 is specifically configured to:
and (3) performing complex field continuation on the vibration wave field of the underground rail transit by adopting Hilbert transform to obtain a complex field vibration wave field.
In one embodiment, the apparatus further comprises a decomposition module 306 configured to:
and carrying out directional wave decomposition on the complex field vibration wave field to obtain a plurality of components of the vibration wave field.
In one embodiment, the plurality of components of the seismic wavefield include a lower left directional wave, an upper left directional wave, a lower right directional wave, an upper right directional wave of the compressional wavefield, and a lower left directional wave, an upper left directional wave, a lower right directional wave, an upper right directional wave of the shear wavefield.
In an embodiment, the apparatus further comprises an analysis module 306 for:
and analyzing the structural information and physical property information of the shallow earth surface according to the shallow earth surface structural imaging.
In summary, in the apparatus provided in the embodiment of the present invention, a vibration wave field of the underground rail transit is obtained according to the underground rail transit vibration signal; carrying out complex field continuation on a vibration wave field of the underground rail transit to obtain a complex field vibration wave field; determining cross-correlation imaging conditions of a plurality of components of the seismic wavefield from the complex field seismic wavefield; and according to the cross-correlation imaging conditions of the multiple components of the vibration wave field, performing reverse time migration imaging of the multiple components of the vibration wave field to obtain shallow earth surface structure imaging. In the process, complex field continuation is carried out on the vibration wave field of the underground rail transit, the complex field vibration wave field is obtained, and low-frequency noise and imaging false noise in offset imaging can be suppressed when reverse time offset imaging is carried out under the condition of cross-correlation imaging of a plurality of components of the vibration wave field determined according to the complex field vibration wave field, so that the imaging accuracy of the obtained shallow earth surface structure is high.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The above-mentioned embodiments are intended to illustrate the objects, technical solutions and advantages of the present invention in further detail, and it should be understood that the above-mentioned embodiments are only exemplary embodiments of the present invention, and are not intended to limit the scope of the present invention, and any modifications, equivalent substitutions, improvements and the like made within the spirit and principle of the present invention should be included in the scope of the present invention.
Claims (15)
1. A method of imaging a shallow earth formation, comprising:
acquiring a vibration wave field of underground rail transit according to the underground rail transit vibration signal;
carrying out complex field continuation on a vibration wave field of the underground rail transit to obtain a complex field vibration wave field;
determining cross-correlation imaging conditions of a plurality of components of the seismic wavefield from the complex field seismic wavefield;
and according to the cross-correlation imaging conditions of the multiple components of the vibration wave field, performing reverse time migration imaging of the multiple components of the vibration wave field to obtain shallow earth surface structure imaging.
2. The method of imaging a shallow surface structure as claimed in claim 1, wherein obtaining a seismic wavefield of underground rail traffic from the underground rail traffic seismic signal comprises:
obtaining virtual body wave records of a plurality of seismic records according to the underground rail transit vibration signals, wherein the virtual body wave records comprise longitudinal wave records and transverse wave records;
and performing numerical simulation on the input seismic source wavelet and the virtual body wave record of the multi-channel seismic record to obtain a seismic wave field of underground rail transit.
3. The method of imaging a shallow surface structure as claimed in claim 2, further comprising, prior to obtaining the virtual volume wave recordings of the plurality of seismic recordings from the subsurface track traffic seismic signals:
carrying out time-frequency domain response analysis on the underground rail transit vibration signal to obtain the time-frequency domain response characteristics of the underground rail transit vibration signal;
preprocessing the underground rail transit vibration signals according to the time-frequency domain response characteristics;
according to underground rail transit vibrations signal, obtain the virtual body wave record of multichannel seismic record, include:
and obtaining a plurality of virtual body wave records of the seismic records according to the preprocessed underground rail transit vibration signals.
4. A method of imaging a shallow surface structure as claimed in claim 3 wherein the pre-processing includes filtering and/or amplitude normalisation.
5. The method of imaging a shallow surface structure as claimed in claim 3, wherein obtaining a plurality of virtual volume wave records of the seismic record from the preprocessed subsurface track traffic seismic signals comprises:
and extracting a plurality of virtual body wave records of the seismic records from the preprocessed underground rail transit vibration signals by adopting a seismic interference method.
6. The method for imaging a shallow surface structure as claimed in claim 1, wherein the step of extracting a plurality of virtual body wave records of the seismic record from the preprocessed underground rail transit seismic signals by using a seismic interference method comprises:
and performing cross-correlation operation on each seismic record in the preprocessed underground rail transit vibration signals and other records to synthesize a virtual body wave record of the seismic record.
7. The shallow surface formation imaging method of claim 2, wherein the seismic wavefield includes a shot wavefield and a geophone wavefield;
carrying out numerical simulation on input seismic source wavelets and virtual body wave records of a plurality of seismic records to obtain a seismic wave field of underground rail transit, and the method comprises the following steps:
carrying out forward transmission numerical simulation on the input seismic source wavelet to obtain a shot point wave field;
and performing back propagation numerical simulation on the virtual body wave records of the multi-channel seismic records to obtain a wave field of a wave detection point.
8. The method of imaging a shallow surface structure as claimed in claim 7, wherein performing a forward numerical simulation of the input source wavelet to obtain a shot wavefield comprises:
performing forward transmission numerical simulation on the input seismic source wavelet by adopting a finite difference operator optimized by an improved PSO-BFO algorithm to obtain a shot point wave field;
carrying out back propagation numerical simulation on the virtual body wave record of the multi-channel seismic record to obtain a wave field of a wave detection point, and the method comprises the following steps:
and performing back propagation numerical simulation on the virtual body wave record of the multi-channel seismic record by adopting a finite difference operator optimized by an improved PSO-BFO algorithm to obtain a wave field of a wave detection point.
9. The method for imaging a shallow surface structure as claimed in claim 1, wherein the complex domain continuation is performed on the seismic wavefield of the underground rail transit to obtain a complex domain seismic wavefield, comprising:
and (3) performing complex field continuation on the vibration wave field of the underground rail transit by adopting Hilbert transform to obtain a complex field vibration wave field.
10. The method of imaging a shallow surface structure as defined in claim 1, further comprising, prior to determining the cross-correlation imaging condition for the plurality of components of the seismic wavefield from the complex-field seismic wavefield:
and carrying out directional wave decomposition on the complex field vibration wave field to obtain a plurality of components of the vibration wave field.
11. The method of shallow formation imaging of claim 1, wherein the plurality of components of the seismic wavefield include a lower left directional wave, an upper left directional wave, a lower right directional wave, an upper right directional wave of the compressional wavefield, and a lower left directional wave, an upper left directional wave, a lower right directional wave, an upper right directional wave of the shear wavefield.
12. The method of imaging a shallow surface formation of claim 1, further comprising:
and analyzing the structural information and physical property information of the shallow earth surface according to the shallow earth surface structural imaging.
13. A shallow surface texture imaging apparatus comprising:
the vibration wave field obtaining module is used for obtaining a vibration wave field of the underground rail transit according to the underground rail transit vibration signal;
the complex field vibration wave field obtaining module is used for carrying out complex field continuation on the vibration wave field of the underground rail transit to obtain a complex field vibration wave field;
the device comprises a cross-correlation imaging condition obtaining module, a complex field vibration wave field obtaining module and a vibration wave field generating module, wherein the cross-correlation imaging condition obtaining module is used for determining cross-correlation imaging conditions of a plurality of components of the vibration wave field according to the complex field vibration wave field;
and the shallow surface structure imaging module is used for performing reverse time migration imaging on the components of the vibration wave field according to the cross-correlation imaging conditions of the components of the vibration wave field to obtain shallow surface structure imaging.
14. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the method of any of claims 1 to 12 when executing the computer program.
15. A computer-readable storage medium, characterized in that the computer-readable storage medium stores a computer program for executing the method of any one of claims 1 to 12.
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