CN106405648B - The imaging method and device of diffracted wave - Google Patents
The imaging method and device of diffracted wave Download PDFInfo
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- 238000013508 migration Methods 0.000 claims abstract description 37
- 230000005012 migration Effects 0.000 claims abstract description 37
- 238000003325 tomography Methods 0.000 claims abstract description 24
- 238000004364 calculation method Methods 0.000 claims abstract description 14
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- 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
- G01V1/34—Displaying seismic recordings or visualisation of seismic data or attributes
- G01V1/345—Visualisation of seismic data or attributes, e.g. in 3D cubes
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Abstract
The present invention provides a kind of imaging method of diffracted wave and devices, are related to the technical field of seismic imaging, including：Obtain initial shot gather data, wherein the geological information in target area is carried in initial shot gather data；Data prediction is carried out to the initial shot gather data got, obtains common offset diffracted wave data, wherein common offset diffracted wave data offset distance having the same；Migration velocity based on diffracted wave in common offset diffracted wave data and common offset diffracted wave data structure weight weighted imaging model；It is calculated using preset algorithm counterweight weighted imaging model, and using result of calculation as the target imaging result of diffracted wave, it solves in the prior art during determining tomography using diffracted wave imaging technique and subsideing columnar region, the poor technical problem for causing to determine inaccuracy of imaging effect.
Description
Technical field
The present invention relates to seismic imaging technical fields, more particularly, to the imaging method and device of a kind of diffracted wave.
Background technology
During exploitation, geological disaster in order to prevent occurs in coalfield, needs to detect small scale before exploitation and does not connect
The construction of continuous and heterogeneous geology, for example, tomography and karst collapse col umn etc., wherein tomography and karst collapse col umn are high for the coal mine of mechanization
Effect safety in production is most important.Tomography can cause coal rock layer to be connected with strong aquifer, in turn, induce water leak accident, or even hair
Well is flooded in life；If fault belt assembles a large amount of gas, it can cause gas burst accident, gas burst accident can be to the person
Cause expendable injury.Area is developed in karst collapse col umn, the coal seam and country rock in coal measure strata are often destroyed, to lead
It causes coal reserves to reduce, results even in the region and lose extraction value；Also, it is difficult arrangement longwell actual mining in the region
Face, this also just seriously hampers mechanical coal mining.
In order to reduce property loss, related scholar has carried out a large amount of research to the identification of tomography and karst collapse col umn in the industry.Mesh
Before, the method for tomography and karst collapse col umn is mainly theoretical according to earthquake reflected wave for identification in industrial quarters, is carried out on this basis
Acceleration Algorithm in Seismic Coherence Cube is analyzed；Spectral factorization algorithm etc. can also be used.But to be built upon subsurface reflective boundary smooth for theoretical reflection
Under infinitely great assumed condition, and due to limited resolution, theoretical reflection be difficult to meet small scale it is discontinuous and it is non-
Quality plastid detects.
Other than being based on theoretical reflection, tomography and karst collapse col umn can also be determined using earthquake diffracted wave, wherein in profit
In the identification process for carrying out tomography and karst collapse col umn with diffracted wave, diffracted wave separation and diffracted wave imaging are two big critical issues.Phase
It closes scholar and multiple trial has been carried out with regard to the separation of diffracted wave, for example, using united based on local dip filtering and prediction inverting
Diffracted wave separation method, the diffracted wave wave field separation method etc. that filter (PWD) is destroyed based on plane wave.
Currently, diffracted wave technological core content is focused on mostly in diffracted wave separation, there is no be directed to Diffraction Point and reflection
The physics inverse model difference at interface is studied.Although considering diffraction information in the prior art in spatial distribution with dilute
Discontinuity feature is dredged, but the prior art is mandatory to the constraint of solving model too strong, is difficult to reach optimization in refutation process
Imaging effect.
Invention content
The purpose of the present invention is to provide diffracted wave imaging method and device, with alleviate in the prior art using around
During ejected wave imaging technique determines tomography and subsides columnar region, imaging effect is poor to be caused to determine that the technology of inaccuracy is asked
Topic.
One side according to the ... of the embodiment of the present invention provides a kind of imaging method of diffracted wave, including：Obtain initial big gun
Collect data, wherein in the initial shot gather data carry target area in geological information, the geological information include with down toward
It is one of few：The geological information of the geological information of rock stratum horizon texture, the geological information of tomography form, Cave；To getting
The initial shot gather data carry out data prediction, obtain common offset diffracted wave data, wherein the common offset diffraction
Wave number is according to offset distance having the same；Migration velocity based on diffracted wave in the common offset diffracted wave data and described inclined altogether
It moves and builds weight weighted imaging model away from diffracted wave data；The heavy weighted imaging model is calculated using preset algorithm, and
Using result of calculation as the target imaging result of the diffracted wave.
Further, migration velocity and the common offset based on diffracted wave in the common offset diffracted wave data around
Ejected wave data build weight weighted imaging model：Target Green's function is calculated according to the migration velocity of the diffracted wave, wherein
The target Green's function indicate the diffracted wave by any one the imaging point position of shot position through subsurface imaging space to
The propagation time of geophone station position and the amplitude compensation factor；Based on the target Green's function and the common offset diffraction wave number
According to the structure heavy weighted imaging model.
Further, based on the target Green's function and common offset diffracted wave data structure is described heavy is weighted to
As model includes：Pass through formulaBuild the heavy weighted imaging model, wiAttach most importance to and adds
Weight coefficient, G are the matrix form of the target Green's function, riFor imaging point x in the subsurface imaging spaceiDiffracted wave at
As result r (xi) scalar form, dobsFor the common offset diffracted wave data, i take successively 1 to N, N indicate the underground at
The quantity of imaging point in image space.
Further, the preset algorithm includes adaptive Homotopy, using preset algorithm to the heavy weighted imaging
Model is calculated, and includes using result of calculation as the target imaging result of the diffracted wave：By using described adaptive
Homotopy carries out superposition operation to the heavy weighted imaging model, and using the result after superposition as the target imaging knot
Fruit.
Further, superposition operation is carried out to the heavy weighted imaging model by using adaptive Homotopy, and will
Result after superposition includes as the target imaging result：Using the initial parameter value of pre-set target component as working as
Preceding parameter value executes following steps, until the parameter value of the target component meets preset condition, wherein the target component
Including：The heavy weighting coefficient, the imaging point x in the subsurface imaging spaceiDiffracted wave imaging results, iteration ends parameter；
First calculates step, according to formulaThe scalar value of the parameter value of current weight weighting coefficient is calculated, and calculates and works as
Preceding update direction vectorWherein, GΓFor by the target in the matrix G of the target Green's function
Column vector groups at matrix, in sequence number of the target column vector in the matrix of the Green's function and current collection Γ
Call number is corresponding, and the call number in the current collection Γ is by current inversion solution vector r (xi) in the corresponding sequence of non-zero values
Number composition, the current inversion solution vector r (xi) by riComposition, diagonal matrix W and diagonal matrixDiagonal entry respectively by wi
WithComposition；Second calculates step, according to formulaCalculate current update step delta ri,
Wherein, siFor i-th of element of the current update direction vector s；Third calculates step, according to formula ri:=ri+(Δri)si
And formulaCalculate current iteration result；First update step, for judging Δ ri<1 feelings
Under condition, the corresponding elements of i are deleted in the current collection Γ, alternatively, judging Δ riIn the case of >=1, work as described
Increase new call number in preceding set Γ；Second update step, according to formulaDescribed in update
The parameter value of current weight weighting coefficient；Judgment step judges the current heavy weighting coefficient after updating and current iteration end
Only whether parameter meets the preset condition, wherein the preset condition is max (wi)≤τ is set up, alternatively, described currently change
It is more than or equal to targets threshold, i=1,2 ..., N for terminal parameter；Wherein, if it is judged that meeting the preset condition, then
Export the current inversion solution vector r (xi), if it is judged that being unsatisfactory for the preset condition, then it is whole to control the current iteration
Only the parameter value of parameter increases default value, and the third is calculated the r in step after iterationiParameter value and described
The parameter value of the current heavy weighting coefficient after being updated in two update steps returns as the current parameter value and executes institute
State the first calculating step.
Further, data prediction is carried out to the initial shot gather data got, obtains common offset diffracted wave
Data include：The initial shot gather data is screened, obtains total offset shot gather data, wherein described to deviate big gun collection number altogether
According to offset distance having the same；The shot gather data of offset altogether is converted according to sparse Radon hyperbolic transformations method, is obtained
The domains Radon after transformation；Cut off part corresponding with the frequency spectrum of back wave in the domains Radon；To the institute after excision
It states the domains Radon and carries out anti-sparse Radon hyperbolic transformations, obtain the common offset diffracted wave data.
One side according to the ... of the embodiment of the present invention additionally provides a kind of imaging device of diffracted wave, including：It obtains single
Member, for obtaining initial shot gather data, wherein the geological information in target area is carried in the initial shot gather data, it is described
Geological information includes at least one of：The geological information of rock stratum horizon texture, the geological information of tomography form, Cave
Geological information；Processing unit, for carrying out data prediction to the initial shot gather data got, obtain common offset around
Ejected wave data, wherein the common offset diffracted wave data offset distance having the same；Construction unit, for based on described total
The migration velocity of diffracted wave and common offset diffracted wave data structure weight weighted imaging model in offset distance diffracted wave data；
Computing unit, for being calculated the heavy weighted imaging model using preset algorithm, and using result of calculation as it is described around
The target imaging result of ejected wave.
Further, the construction unit includes：First computation subunit, for the migration velocity according to the diffracted wave
Calculate target Green's function, wherein the target Green's function indicates the diffracted wave by shot position through subsurface imaging space
Propagation time and the amplitude compensation factor of any one imaging point position to geophone station position；Subelement is built, for being based on
The Green's function and the common offset diffracted wave data build the heavy weighted imaging model.
Further, the structure subelement includes：Module is built, for passing through formulaBuild the heavy weighted imaging model, wiAttach most importance to weighting coefficient, G is the target
The matrix form of Green's function, riFor the scalar form of the diffracted wave imaging results of imaging point xi in the subsurface imaging space,
dobsFor the common offset diffracted wave data, i takes 1 to N, N to indicate the quantity of imaging point in the subsurface imaging space successively.
Further, the preset algorithm includes adaptive Homotopy, and the computing unit includes：Second calculates son list
Member, for carrying out superposition operation to the heavy weighted imaging model by using adaptive Homotopy, after obtaining superposition
As a result it is used as the target imaging result.
In the imaging method of diffracted wave provided in an embodiment of the present invention, the initial big gun for carrying geological information is obtained first
Collect data, then, data prediction is carried out to the data got, common offset diffracted wave data are obtained, next, according to place
Common offset diffracted wave data and migration velocity structure weight weighted imaging model are obtained after reason, finally, using preset algorithm pair
Weight weighted imaging model is calculated, and the target imaging result of diffracted wave is obtained.In embodiments of the present invention, by being weighted to again
The mode that diffracted wave imaging results are determined as model has achieved the purpose that accurately detecting tomography and karst collapse col umn, alleviates existing
In technology during being determined tomography using diffracted wave imaging technique and being subside columnar region, imaging effect is poor to be caused to determine not
Accurate technical problem, to reach the technique effect for improving tomography and Techniques in Surveying of Collapse Pillars precision.
Description of the drawings
It, below will be to specific in order to illustrate more clearly of the specific embodiment of the invention or technical solution in the prior art
Embodiment or attached drawing needed to be used in the description of the prior art are briefly described, it should be apparent that, in being described below
Attached drawing is some embodiments of the present invention, for those of ordinary skill in the art, before not making the creative labor
It puts, other drawings may also be obtained based on these drawings.
Fig. 1 is a kind of flow chart of the imaging method of diffracted wave according to the ... of the embodiment of the present invention；
Fig. 2 is a kind of flow chart of the method for structure weight weighted imaging model according to the ... of the embodiment of the present invention；
Fig. 3 is the flow chart that a kind of adaptive Homotopy according to the ... of the embodiment of the present invention calculates weight weighted imaging model；
Fig. 4 is a kind of flow chart of the processing method of initial shot gather data according to the ... of the embodiment of the present invention；
Fig. 5 is a kind of schematic diagram of the imaging device of diffracted wave according to the ... of the embodiment of the present invention.
Specific implementation mode
Technical scheme of the present invention is clearly and completely described below in conjunction with attached drawing, it is clear that described implementation
Example is a part of the embodiment of the present invention, instead of all the embodiments.Based on the embodiments of the present invention, ordinary skill
The every other embodiment that personnel are obtained without making creative work, shall fall within the protection scope of the present invention.
In the description of the present invention, it should be noted that term "center", "upper", "lower", "left", "right", "vertical",
The orientation or positional relationship of the instructions such as "horizontal", "inner", "outside" be based on the orientation or positional relationship shown in the drawings, merely to
Convenient for the description present invention and simplify description, do not indicate or imply the indicated device or element must have a particular orientation,
With specific azimuth configuration and operation, therefore it is not considered as limiting the invention.In addition, term " first ", " second ",
" third " is used for description purposes only, and is not understood to indicate or imply relative importance.
In the description of the present invention, it should be noted that unless otherwise clearly defined and limited, term " installation ", " phase
Even ", " connection " shall be understood in a broad sense, for example, it may be being fixedly connected, may be a detachable connection, or be integrally connected；It can
Can also be electrical connection to be mechanical connection；It can be directly connected, can also indirectly connected through an intermediary, Ke Yishi
Connection inside two elements.For the ordinary skill in the art, above-mentioned term can be understood at this with concrete condition
Concrete meaning in invention.
Fig. 1 is a kind of flow chart of the imaging method of diffracted wave according to the ... of the embodiment of the present invention, as shown in Figure 1, this method
Include the following steps：
Step S102 obtains initial shot gather data, wherein the geology letter in target area is carried in initial shot gather data
Breath, geological information includes at least one of：The geological information of rock stratum horizon texture, the geological information of tomography form, karst cave
The geological information in cave.
In embodiments of the present invention, shot gather data can become seismic data again, be detected in geophone station for wave detector
Seismic data, wherein seismic data includes reflected waveform data and diffracted wave data, other than back wave and diffracted wave,
Further include other waveforms in seismic wave, still, in embodiments of the present invention, mainly to back wave and diffracted wave at
Reason obtains target imaging as a result, therefore, in embodiments of the present invention, to other other than back wave and diffracted wave in turn
Waveform is without being discussed in detail.
It is assumed that a shot point is arranged in related technical personnel in target area, when the shot point explosion time, earthquake will be generated
Wave.At this point it is possible to which multiple wave detectors are arranged in the ground in target area, that is, multiple geophone stations are arranged, then, by more
A wave detector detects the seismic wave of each geophone station.It should be noted that the data of foregoing description can become single-shot data again,
Multiple single-shot data form shot gather data.
Step S104 carries out data prediction to the initial shot gather data got, obtains common offset diffracted wave data,
Wherein, common offset diffracted wave data offset distance having the same.
In embodiments of the present invention, after getting shot gather data, it is necessary to data prediction is carried out to shot gather data,
Common offset diffracted wave data are obtained after processing.In embodiments of the present invention, common offset diffraction wave number is obtained after processing
According to for the identical data of offset distance, wherein offset distance is the horizontal distance of shot position and geophone station position.That is,
In common offset diffracted wave data, shot position and geophone station positional distance are equal.
It should be noted that initial shot gather data includes diffracted wave data and reflected waveform data, to initial big gun collection number
According to the process handled, it is included in the process that diffracted wave data are extracted in initial shot gather data, specifically, extraction process will be
It is described in detail in following embodiments.
Step S106, the migration velocity based on diffracted wave in common offset diffracted wave data and common offset diffracted wave data
Structure weight weighted imaging model.
In embodiments of the present invention, after common offset diffracted wave data are obtained in step S104, offset can be loaded
Speed file, to obtain the migration velocity of the diffracted wave stored in migration velocity file；In turn, according to migration velocity and total offset
Weight weighted imaging model is built away from diffracted wave data.It should be noted that in embodiments of the present invention, above-mentioned heavy weighted imaging mould
Type is preferably Kirchhoff high-resolution imaging models, again constraint of the weighting as Kirchhoff high-resolution imaging models
Value.
It should be noted that in embodiments of the present invention, migration velocity file is what related technical personnel got in advance
File includes spread speed of the seismic wave (for example, diffracted wave and back wave) in subsurface imaging space in this document.Specifically
Ground, related technical personnel can acquire the related data of migration velocity in the wild, then, pass through the inclined of observation system load acquisition
The related data of speed is moved, then, the processing procedures such as Denoising disposal and migration velocity analysis are carried out to the data, it finally, will
Obtained data after processing are as migration velocity file.
Step S108 is calculated using preset algorithm counterweight weighted imaging model, and using result of calculation as diffracted wave
Target imaging result.
In embodiments of the present invention, in step s 106 after structure weight weighted imaging model, so that it may with according to pre- imputation
Method calculates weight weighted imaging model, and will calculate the result obtained later as the imaging results of diffracted wave (that is, target imaging knot
Fruit).
In the imaging method of diffracted wave provided in an embodiment of the present invention, the initial big gun for carrying geological information is obtained first
Collect data, then, data prediction is carried out to the data got, common offset diffracted wave data are obtained, next, according to place
Common offset diffracted wave data and migration velocity structure weight weighted imaging model are obtained after reason, finally, using preset algorithm pair
Weight weighted imaging model is calculated, and the target imaging result of diffracted wave is obtained.In embodiments of the present invention, by being weighted to again
The mode that diffracted wave imaging results are determined as model has achieved the purpose that accurately detecting tomography and karst collapse col umn, alleviates existing
In technology during being determined tomography using diffracted wave imaging technique and being subside columnar region, imaging effect is poor to be caused to determine not
Accurate technical problem, to reach the technique effect for improving tomography and Techniques in Surveying of Collapse Pillars precision.
Fig. 2 is a kind of flow chart of the method for structure weight weighted imaging model according to the ... of the embodiment of the present invention, such as Fig. 2 institutes
Show, the migration velocity based on diffracted wave in common offset diffracted wave data and common offset diffracted wave data structure weight weighted imaging
Model includes the following steps：
Step S201, according to the migration velocity of diffracted wave calculate target Green's function, wherein target Green's function indicate around
Ejected wave is by any one imaging point position propagation time and amplitude to geophone station position of the shot position through subsurface imaging space
Compensation factor；
Step S202, based on target Green's function and common offset diffracted wave data structure weight weighted imaging model.
In embodiments of the present invention, after getting common offset diffracted wave data, so that it may with according to common offset around
Ejected wave data and the migration velocity file structure weight weighted imaging model got in advance.In structure weight weighted imaging model,
Under the premise of the migration velocity of known diffracted wave, diffracted wave can be calculated according to the migration velocity of diffracted wave by shot point,
By any one imaging point in subsurface imaging space, to each geophone station position when walking (that is, propagation time), in turn,
According to establishing target Green's function when being calculated away.
After target Green's function is calculated, so that it may with according to the target Green's function and common offset being calculated
Diffracted wave data structure weight weighted imaging model.Preferably, in embodiments of the present invention, kirchhoff may be used
(Kirchhoff) imaging algorithm structure weight weighted imaging model.Wherein, the weighting again obtained using Kirchhoff imaging algorithms
Imaging model is a kind of based on the Kirchhoff high-resolution imaging models for weighting sparse constraint again.
In the optional embodiment of the present invention, built based on target Green's function and common offset diffracted wave data
Weight weighted imaging model, specially：
Pass through formulaStructure weight weighted imaging model, wherein wiAttach most importance to and adds
Weight coefficient, G are the matrix form of target Green's function, riFor imaging point x in subsurface imaging spaceiDiffracted wave imaging results
Scalar form, dobsFor common offset diffracted wave data, i takes 1 to N successively, and N indicates the quantity of imaging point in subsurface imaging space.
In embodiments of the present invention, weight weighted imaging model, in above-mentioned formula, w can be built according to above-mentioned formulaiFor
Weight weighting coefficient, wherein wi>0；G is the matrix form of target Green's function；riFor imaging point x in subsurface imaging spaceiAround
Ejected wave imaging results, r (xi) it is riVector representation, wherein i=1,2 ..., N, N indicate discrete in subsurface imaging space
The quantity of sampling point number namely imaging point；Vectorial dobsAs above-mentioned common offset diffracted wave data.
Using formulaAfter structure weight weighted imaging model, need to this
Model is calculated, and in turn, obtains result of calculation, wherein the result of calculation is used to determine the target imaging result of diffracted wave.It needs
It is noted that in above-mentioned formulaIn,For's
Constraint portions.
Preferably, in embodiments of the present invention, preset algorithm can be chosen for adaptive Homotopy and (and be properly termed as same
The adaptive inversion algorithm of human relations).Specifically, superposition operation can be carried out by adaptive Homotopy counterweight weighted imaging model,
And using the result after superposition as target imaging result.Wherein, homotopy adaptive inversion algorithm can be complex to constructing
Ramp-like stratigraphic model carry out inverting, and can be restrained with fast speed.Below by the specific of adaptive Homotopy
Calculating process is described in detail.
Fig. 3 is the flow chart that a kind of adaptive Homotopy according to the ... of the embodiment of the present invention calculates weight weighted imaging model,
As shown in figure 3, carrying out superposition operation using adaptive Homotopy counterweight weighted imaging model, the result work after superposition is obtained
For target imaging as a result, including the following steps S301 to step S307：
Before executing computational methods described in following step S301 to step S307, first, to obtain and pre-set
Target component initial parameter value, and execute following steps S301 extremely using the initial parameter value got as current parameter value
Step S307, until the parameter value of target component meet it is described below in preset condition, wherein target component includes：Again plus
Weight coefficient wi, the imaging point x in subsurface imaging spaceiDiffracted wave imaging results ri, iteration ends parameter τ.
In embodiments of the present invention, the initial parameter value of above-mentioned target component can be chosen in the following manner：Wherein, greatest measure is sought in max expressions, and scalar τ is iteration ends
Parameter, τ determine by user, vectorial giFor the i-th row of above-mentioned target Green's function matrix G.
S301, first calculates step, according to formulaCalculate the mark of the parameter value of current weight weighting coefficient
Magnitude, and calculate current update direction vectorWherein, GΓFor by the matrix G of target Green's function
In target column vector composition matrix, in sequence number of the target column vector in the matrix of Green's function and current collection Γ
Call number is corresponding, and the call number in current collection Γ is by current inversion solution vector r (xi) in the corresponding serial number group of non-zero values
At current inversion solution vector r (xi) by riComposition, diagonal matrix W and diagonal matrixDiagonal entry respectively by wiWithComposition；
In embodiments of the present invention, system is after getting the current parameter value of target component, so that it may with according to formulaThe scalar value of current weight weighting coefficient is calculated, in turn, is according to the matrix of the scalar value and current weighting again
Several matrixes calculates current update direction vector S, wherein current update direction vector is for determining riAnd wiChange direction,
That is currently updating step delta r for determining in the second calculating stepiChange direction.
S302, second calculates step, according to formulaCalculate current update step delta
ri, wherein siCurrently to update i-th of element of direction vector s；
It is calculated in the first calculating step after current update direction vector, so that it may with according to formulaCalculate current update step delta ri。
S303, third calculates step, according to formula ri:=ri+(Δri)siAnd formulaMeter
Calculate current iteration result；
Current update step delta r is calculated in the second calculating stepiLater, so that it may with according to formula ri:=ri+(Δ
ri)siIt calculates by the result of calculation r after iterationi；And according to formulaIt calculates and passes through iteration
Result of calculation w lateri。
S304, the first update step, for judging Δ ri<In the case of 1, i correspondences are deleted in current collection Γ
Element, alternatively, judging Δ riIn the case of >=1, increase new call number in current collection Γ；
In embodiments of the present invention, the r after superposition is calculated during above-mentioned third calculates stepiAnd wiLater, it needs
Element in set Γ is updated, to carry out subsequent superposition.In the element in updating set Γ, Δ is first determined whether
ri<Whether 1 is true, wherein if it is judged that Δ ri<1 sets up, then the corresponding elements of i in set Γ is removed, if it is judged that Δ
ri<1 is invalid, then increases new element (wherein, new element, that is, above-mentioned new call number), increased element choosing in set Γ
The mode is taken to be：Wherein ΓcBy inversion solution vector r (xi) in the corresponding serial number group of zero value
At maximum value is sought in argmax expressions.
S305, the second update step, according to formulaThe current weight weighting coefficient of update
Parameter value；
After updating the element during step updates set Γ according to above-mentioned first, it is also necessary to currently weighing weighting coefficient
Parameter value is updated, and specific update can be according to formula
S306, judgment step judge whether the current weight weighting coefficient and current iteration terminal parameter after updating meet
Preset condition, wherein preset condition is max (wi)≤τ is set up, alternatively, current iteration terminal parameter is more than or equal to target
Threshold value, i=1,2 ..., N；Wherein, if it is judged that meeting preset condition, S307 is thened follow the steps, exports current inversion solution arrow
Measure r (xi), if it is judged that being unsatisfactory for preset condition, then the parameter value for controlling current iteration terminal parameter increases default value,
And third is calculated into the r in step after iterationiParameter value and the second update step in update after current weighting system again
Several parameter values returns as current parameter value and executes the first calculating step.
After the parameter value of the current weight weighting coefficient of above-mentioned second update step update, max (w are judgedi)≤τ whether at
It is vertical, alternatively, judging whether current iteration terminal parameter is more than or equal to targets threshold, wherein targets threshold indicates above-mentioned step
The maximum times of iteration required for rapid S301 to step S306.Wherein, if it is judged that max (wi)≤τ is set up, alternatively, judging
Go out current iteration terminal parameter and is more than or equal to targets threshold, then shut down, and output vector r (xi)；Otherwise, current iteration
Terminal parameter increases default value (for example, increasing by 1), then, third is calculated the r in step after iterationiParameter value and
For the parameter value of current weight weighting coefficient after being updated in second update step as current parameter value, return continues to execute first
Step is calculated, until result, which is calculated, meets preset condition.
Finally, it exports to obtain vectorial r (x in judgment stepi) after, the vector of output is substituting to above-mentioned formulaIn, and using the result of calculation of above-mentioned formula as target imaging result.
Fig. 4 is a kind of flow chart of the processing method of initial shot gather data according to the ... of the embodiment of the present invention, as shown in figure 4,
Data prediction is carried out to the initial shot gather data got, common offset diffracted wave data is obtained and includes the following steps：
Step S401 screens initial shot gather data, obtains total offset shot gather data, wherein deviate big gun collection number altogether
According to offset distance having the same；
Step S402 converts total offset shot gather data according to sparse Radon hyperbolic transformations method, obtains becoming alternatively
The domains Radon afterwards；
Part corresponding with the frequency spectrum of back wave in the domain step S403, excision Radon；
Step S404 carries out anti-sparse Radon hyperbolic transformations to the domains Radon after excision, obtains common offset diffraction
Wave number evidence.
In embodiments of the present invention, due to including a plurality of types of data in the initial shot gather data that gets, be
The diffracted wave seismic data employed in the embodiment of the present invention is got, needs to carry out phase to the initial shot gather data got
Answer the data prediction on ground.First, the initial shot gather data of the earthquake got is loaded in observation system；Then, to initial big gun
Collect data and carries out the processing such as denoising.After being handled in the manner described above, according to the initial big gun collection text of earthquake after processing
Keyword (for example, offset distance and Taoist monastic name) in part screens the initial shot gather data data of earthquake, with obtaining common offset
Data are shaken, i.e. screening obtains the identical shot gather data of offset distance, wherein offset distance is shot position and geophone station on acquisition ground
The horizontal distance of position, Taoist monastic name are number of the wave detector in earthquake shot gather data；Screening operation is i.e. according to identical offset distance
Extract corresponding seismic data.
After screening obtains common offset shot gather data, according to sparse Radon hyperbolic transformations method, common offset big gun collection
Data separating goes out the common offset seismic data for only including diffracted wave, and specifically separation method includes：Become by sparse Radon hyperbolics
Each common offset shot gather data of changing commanders transforms to the domains Radon, then, correspond in excision Radon domains the frequency spectrum of back wave at
Point, finally, the common offset diffraction that anti-sparse Radon hyperbolic transformations are isolated is carried out to the domains the Radon frequency spectrum after excision
Wave number evidence.
To sum up, the imaging method of diffracted wave provided in an embodiment of the present invention, including：It sub-elects first after pretreatment total
Offset distance seismic data；Then, according to stating the common offset seismic data sub-elected, according to sparse Radon hyperbolic transformations method,
Isolate the common offset seismic data for only including diffracted wave；Next, according to input migration velocity file and isolate
Common offset diffracted wave data, by Kirchhoff imaging methods build it is a kind of based on again weighting sparse constraint high-resolution at
As model；Finally, it is solved based on the high-resolution imaging model for weighting sparse constraint again by adaptive Homotopy, obtains diffraction
Wave imaging results.The present invention proposes that one kind is based on adding again on the basis of deep parsing routine diffraction physical model solves limitation
The diffracted wave adaptive sparse imaging method of model is weighed, for this method compared with conventional diffraction wave imaging method, which can be adaptive
Weighting coefficient should be adjusted, that is, increase the weight coefficient of the smaller position of model solution value and reduces the power of the larger position of model solution value
Weight coefficient achievees the purpose that diffracted wave Optimization inversion to ensure diffracted wave imaging iterative inversion process stability and convergence,
And then can accurately detecting fracture and small scale karst collapse col umn, reduce induced water inrush in coal mining and the safety such as gas leakage be hidden
Suffer from.
The embodiment of the present invention additionally provides a kind of imaging device of diffracted wave, and the imaging device of the diffracted wave is mainly used for holding
The imaging method for the diffracted wave that row the above of the embodiment of the present invention is provided, below to diffracted wave provided in an embodiment of the present invention
Imaging device do specific introduction.
Fig. 5 is a kind of schematic diagram of the imaging device of diffracted wave according to the ... of the embodiment of the present invention, as shown in figure 5, the diffraction
The imaging device of wave mainly include acquiring unit 51, processing unit 53, construction unit 55 and computing unit 57, wherein：
Acquiring unit 51, for obtaining initial shot gather data, wherein the ground in target area is carried in initial shot gather data
Matter information, geological information include at least one of：The geological information of rock stratum horizon texture, the geological information of tomography form, rock
The geological information in solution cavity cave；
In embodiments of the present invention, shot gather data can become seismic data again, be detected in geophone station for wave detector
Seismic data, wherein seismic data includes reflected waveform data and diffracted wave data, other than back wave and diffracted wave,
Further include other waveforms in seismic wave, still, in embodiments of the present invention, mainly to back wave and diffracted wave at
Reason obtains target imaging as a result, therefore, in embodiments of the present invention, to other other than back wave and diffracted wave in turn
Waveform is without being discussed in detail.
It is assumed that a shot point is arranged in related technical personnel in target area, when the shot point explosion time, earthquake will be generated
Wave.At this point it is possible to which multiple wave detectors are arranged in the ground in target area, that is, multiple geophone stations are arranged, then, by more
A wave detector detects the seismic wave of each geophone station.It should be noted that the data of foregoing description can become single-shot data again,
Multiple single-shot data form shot gather data.
Processing unit 53 obtains common offset diffraction for carrying out data prediction to the initial shot gather data got
Wave number evidence, wherein common offset diffracted wave data offset distance having the same；
In embodiments of the present invention, after getting shot gather data, it is necessary to data prediction is carried out to shot gather data,
Common offset diffracted wave data are obtained after processing.In embodiments of the present invention, common offset diffraction wave number is obtained after processing
According to for the identical data of offset distance, wherein offset distance is the horizontal distance of shot position and geophone station position.That is,
In common offset diffracted wave data, shot position and geophone station positional distance are equal.
It should be noted that initial shot gather data includes diffracted wave data and reflected waveform data, to initial big gun collection number
According to the process handled, it is included in the process that diffracted wave data are extracted in initial shot gather data, specifically, extraction process will be under
It states in embodiment and is described in detail.
Construction unit 55 is used for migration velocity and common offset diffraction based on diffracted wave in common offset diffracted wave data
Wave number is according to structure weight weighted imaging model；
In embodiments of the present invention, after common offset diffracted wave data are obtained in step S104, offset can be loaded
Speed file, to obtain the migration velocity of the diffracted wave stored in migration velocity file；In turn, according to migration velocity and total offset
Weight weighted imaging model is built away from diffracted wave data.It should be noted that in embodiments of the present invention, above-mentioned heavy weighted imaging mould
Type is preferably Kirchhoff high-resolution imaging models, again constraint of the weighting as Kirchhoff high-resolution imaging models
Value.
It should be noted that in embodiments of the present invention, migration velocity file is what related technical personnel got in advance
File includes spread speed of the seismic wave (for example, diffracted wave and back wave) in subsurface imaging space in this document.Specifically
Ground, related technical personnel can acquire the related data of migration velocity in the wild, then, pass through the inclined of observation system load acquisition
The related data of speed is moved, then, the processing procedures such as Denoising disposal and migration velocity analysis are carried out to the data, it finally, will
Obtained data after processing are as migration velocity file.
Computing unit 57, for being calculated using preset algorithm counterweight weighted imaging model, and using result of calculation as
The target imaging result of diffracted wave.
In embodiments of the present invention, in step s 106 after structure weight weighted imaging model, so that it may with according to pre- imputation
Method calculates weight weighted imaging model, and will calculate the result obtained later as the imaging results of diffracted wave (that is, target imaging knot
Fruit).
In the imaging method of diffracted wave provided in an embodiment of the present invention, the initial big gun for carrying geological information is obtained first
Collect data, then, data prediction is carried out to the data got, common offset diffracted wave data are obtained, next, according to place
Common offset diffracted wave data and migration velocity structure weight weighted imaging model are obtained after reason, finally, using preset algorithm pair
Weight weighted imaging model is calculated, and the target imaging result of diffracted wave is obtained.In embodiments of the present invention, by being weighted to again
The mode that diffracted wave imaging results are determined as model has achieved the purpose that accurately detecting tomography and karst collapse col umn, alleviates existing
In technology during being determined tomography using diffracted wave imaging technique and being subside columnar region, imaging effect is poor to be caused to determine not
Accurate technical problem, to reach the technique effect for improving tomography and Techniques in Surveying of Collapse Pillars precision.
Optionally, construction unit includes：First computation subunit, for calculating target lattice according to the migration velocity of diffracted wave
Woods function, wherein target Green's function indicates diffracted wave by any one the imaging point of shot position through subsurface imaging space
Set propagation time and the amplitude compensation factor of geophone station position；Subelement is built, for being based on Green's function and common offset
Diffracted wave data structure weight weighted imaging model.
Optionally, structure subelement includes：Module is built, for passing through formulaStructure weight weighted imaging model, wiAttach most importance to weighting coefficient, G is target Green's function
Matrix form, riFor the scalar form of the diffracted wave imaging results of imaging point xi in subsurface imaging space, dobsFor common offset
Diffracted wave data, i take 1 to N successively, and N indicates the quantity of imaging point in subsurface imaging space.
Optionally, preset algorithm includes adaptive Homotopy, and computing unit includes：Second computation subunit, for leading to
Cross and carry out superposition operation using adaptive Homotopy counterweight weighted imaging model, obtain result after superposition as target at
As result.
Optionally, the second computation subunit includes：Using the initial parameter value of pre-set target component as current ginseng
Numerical value executes following steps, until the parameter value of target component meets preset condition, wherein target component includes：Weighting system again
Number, the diffracted wave imaging results of the imaging point xi in subsurface imaging space, iteration ends parameter；First computing module, for according to
FormulaThe scalar value of the parameter value of current weight weighting coefficient is calculated, and calculates current update direction vectorWherein, GΓFor the matrix that the target column vector in the matrix G by target Green's function forms, mesh
It is corresponding with the call number in current collection Γ to mark sequence number of the column vector in the matrix of Green's function, in current collection Γ
Call number is by inversion solution vector r (xi) in non-zero values corresponding serial number composition, inversion solution vector r (xi) by riComposition, diagonal matrix
W and diagonal matrixDiagonal entry respectively by wiWithComposition；Second computing module, for according to formulaCalculate current update step delta ri, wherein siCurrently to update the i-th of direction vector s
A element；Third computing module, for according to formula ri:=ri+(Δri)siAnd formulaIt calculates
Current iteration result；First update module, for judging Δ ri<In the case that 1 sets up, i is deleted in current collection Γ
Corresponding element, or judging Δ riIn the case that >=1 sets up, increase new call number in current collection Γ；Second more
New module, for according to formulaThe parameter value of the current weight weighting coefficient of update；Judge mould
Block, for judging whether current weighting coefficient and current iteration terminal parameter again after update meet preset condition, wherein pre-
If condition is max (wi)≤τ is set up, alternatively, current iteration terminal parameter is more than or equal to targets threshold, i=1,2 ..., N；
Wherein, if it is judged that meeting preset condition, then current inversion solution vector r (x are exportedi), if it is judged that being unsatisfactory for default item
Part, then the parameter value for controlling current iteration terminal parameter increases default value, and third is calculated the r in step after iterationi
Parameter value and the second update step in update after current weight weighting coefficient parameter value as current parameter value, return is held
Row first calculates step.
Optionally, processing unit includes：Screening module obtains total offset big gun for being screened to initial shot gather data
Collect data, wherein deviate shot gather data offset distance having the same altogether；First conversion module, for according to sparse Radon hyperbolics
Converting means converts total offset shot gather data, the domains Radon after being converted；Module is cut off, for cutting off Radon
Part corresponding with the frequency spectrum of back wave in domain；Second conversion module is anti-sparse for being carried out to the domains Radon after excision
Radon hyperbolic transformations obtain common offset diffracted wave data.
Finally it should be noted that：The above embodiments are only used to illustrate the technical solution of the present invention., rather than its limitations；To the greatest extent
Present invention has been described in detail with reference to the aforementioned embodiments for pipe, it will be understood by those of ordinary skill in the art that：Its according to
So can with technical scheme described in the above embodiments is modified, either to which part or all technical features into
Row equivalent replacement；And these modifications or replacements, various embodiments of the present invention technology that it does not separate the essence of the corresponding technical solution
The range of scheme.
Claims (3)
1. a kind of imaging method of diffracted wave, which is characterized in that including：
Obtain initial shot gather data, wherein the geological information in target area, the geology are carried in the initial shot gather data
Information includes at least one of：The geology of the geological information of rock stratum horizon texture, the geological information of tomography form, Cave
Information；
Data prediction is carried out to the initial shot gather data got, obtains common offset diffracted wave data, wherein described
Common offset diffracted wave data offset distance having the same；
Migration velocity based on diffracted wave in the common offset diffracted wave data and common offset diffracted wave data structure
Weight weighted imaging model；
The heavy weighted imaging model is calculated using preset algorithm, and using result of calculation as the target of the diffracted wave
Imaging results；
Migration velocity based on diffracted wave in the common offset diffracted wave data and common offset diffracted wave data structure
Weighted imaging model includes again：
Calculate target Green's function according to the migration velocity of the diffracted wave, wherein the target Green's function indicate it is described around
Ejected wave is by any one imaging point position propagation time and amplitude to geophone station position of the shot position through subsurface imaging space
Compensation factor；
The heavy weighted imaging model is built based on the target Green's function and the common offset diffracted wave data；
Building the heavy weighted imaging model based on the target Green's function and the common offset diffracted wave data includes：
Pass through formulaBuild the heavy weighted imaging model, wherein wiAttach most importance to weighting
Coefficient, G are the matrix form of the target Green's function, riFor imaging point x in the subsurface imaging spaceiDiffracted wave imaging
As a result r (xi) scalar form, dobsFor the common offset diffracted wave data, i takes 1 to N successively, and N indicates the subsurface imaging
The quantity of imaging point in space；
The preset algorithm includes adaptive Homotopy, is calculated the heavy weighted imaging model using preset algorithm,
And include using result of calculation as the target imaging result of the diffracted wave：
Superposition operation is carried out to the heavy weighted imaging model by using the adaptive Homotopy, and will be after superposition
As a result it is used as the target imaging result；
Superposition operation is carried out to the heavy weighted imaging model by using adaptive Homotopy, and by the result after superposition
Include as the target imaging result：
Using the initial parameter value of pre-set target component as current parameter value, following steps are executed, until the target
The parameter value of parameter meets preset condition, wherein the target component includes：The heavy weighting coefficient, the subsurface imaging are empty
Between imaging point xiDiffracted wave imaging results, iteration ends parameter；
First calculates step, according to formulaThe scalar value of the parameter value of current weight weighting coefficient is calculated, and is counted
Calculate current update direction vectorWherein, GΓFor by the matrix G of the target Green's function
The matrix of target column vector composition, sequence number of the target column vector in the matrix of the Green's function and current collection Γ
In call number it is corresponding, the call number in the current collection Γ is by current inversion solution vector r (xi) in non-zero values correspond to
Serial number composition, the current inversion solution vector r (xi) by riComposition, diagonal matrix W and diagonal matrixDiagonal entry difference
By wiWithComposition；
Second calculates step, according to formulaCalculate current update step delta ri, wherein si
For i-th of element of the current update direction vector s；
Third calculates step, according to formula ri:=ri+(Δri)siAnd formulaCalculate current iteration
As a result；
First update step, for judging Δ riIn the case of < 1, the corresponding members of i are deleted in the current collection Γ
Element, alternatively, judging Δ riIn the case of >=1, increase new call number in the current collection Γ；
Second update step, according to formulai∈ΓcUpdate the ginseng of the current heavy weighting coefficient
Numerical value；
It is described pre- to judge whether the current heavy weighting coefficient and current iteration terminal parameter after updating meet for judgment step
If condition, wherein the preset condition is max (wi)≤τ i=1,2 ..., N is set up, alternatively, the current iteration terminal parameter
More than or equal to targets threshold；
Wherein, if it is judged that meeting the preset condition, then the current inversion solution vector r (x are exportedi), if it is judged that not
Meet the preset condition, then the parameter value for controlling the current iteration terminal parameter increases default value, and by the third
Calculate the r after iteration in stepiParameter value and the second update step in update after the current weighting system again
Several parameter values returns as the current parameter value and executes the first calculating step.
2. according to the method described in claim 1, it is characterized in that, pre- to the initial shot gather data progress data got
Processing, obtaining common offset diffracted wave data includes：
The initial shot gather data is screened, total offset shot gather data is obtained, wherein the shot gather data of offset altogether has
Identical offset distance；
The shot gather data of offset altogether is converted according to sparse Radon hyperbolic transformations method, the Radon after being converted
Domain；
Cut off part corresponding with the frequency spectrum of back wave in the domains Radon；
Anti- sparse Radon hyperbolic transformations are carried out to the domains Radon after excision, obtain the common offset diffraction wave number
According to.
3. a kind of imaging device of diffracted wave, which is characterized in that including：
Acquiring unit, for obtaining initial shot gather data, wherein the geology in target area is carried in the initial shot gather data
Information, the geological information include at least one of：The geological information of rock stratum horizon texture, the geological information of tomography form,
The geological information of Cave；
Processing unit obtains common offset diffracted wave for carrying out data prediction to the initial shot gather data got
Data, wherein the common offset diffracted wave data offset distance having the same；
Construction unit, for based on diffracted wave in the common offset diffracted wave data migration velocity and the common offset around
Ejected wave data structure weight weighted imaging model；
Computing unit, for being calculated the heavy weighted imaging model using preset algorithm, and using result of calculation as institute
State the target imaging result of diffracted wave；
First computation subunit, for calculating target Green's function according to the migration velocity of the diffracted wave, wherein the target
Green's function indicates the diffracted wave by any one the imaging point position of shot position through subsurface imaging space to detection point
The propagation time set and the amplitude compensation factor；
Subelement is built, for building the heavy weighting based on the target Green's function and the common offset diffracted wave data
Imaging model；
Module is built, for passing through formulaBuild the heavy weighted imaging model, wi
Attach most importance to weighting coefficient, G is the matrix form of the target Green's function, riFor imaging point x in the subsurface imaging spaceiAround
Ejected wave imaging results r (xi) scalar form, dobsFor the common offset diffracted wave data, i takes 1 to N successively, described in N is indicated
The quantity of imaging point in subsurface imaging space；
Second computation subunit is obtained for carrying out superposition operation by using adaptive Homotopy counterweight weighted imaging model
Result after to superposition is as the target imaging result；
Second computation subunit includes：Using the initial parameter value of pre-set target component as current parameter value, execute with
Lower step, until the parameter value of target component meets preset condition, wherein target component includes：Weight weighting coefficient, subsurface imaging
The diffracted wave imaging results of the imaging point xi in space, iteration ends parameter；First computing module, for according to formulaThe scalar value of the parameter value of current weight weighting coefficient is calculated, and calculates current update direction vectorWherein, GΓFor the matrix that the target column vector in the matrix G by target Green's function forms, mesh
It is corresponding with the call number in current collection Γ to mark sequence number of the column vector in the matrix of Green's function, in current collection Γ
Call number is by inversion solution vector r (xi) in non-zero values corresponding serial number composition, inversion solution vector r (xi) by riComposition, diagonal matrix
W and diagonal matrixDiagonal entry respectively by wiWithComposition；Second computing module, for according to formulaCalculate current update step delta ri, wherein siCurrently to update the i-th of direction vector s
A element；Third computing module, for according to formula ri:=ri+(Δri)siAnd formulaIt calculates
Current iteration result；First update module, for judging Δ riIn the case that < 1 is set up, i is deleted in current collection Γ
Corresponding element, or judging Δ riIn the case that >=1 sets up, increase new call number in current collection Γ；Second more
New module, for according to formulai∈ΓcThe parameter value of the current weight weighting coefficient of update；Judge mould
Block, for judging whether current weighting coefficient and current iteration terminal parameter again after update meet preset condition, wherein pre-
If condition is max (wi)≤τ is set up, alternatively, current iteration terminal parameter is more than or equal to targets threshold, i=1,2 ..., N；
Wherein, if it is judged that meeting preset condition, then current inversion solution vector r (x are exportedi), if it is judged that being unsatisfactory for default item
Part, then the parameter value for controlling current iteration terminal parameter increases default value, and third is calculated the r in step after iterationi
Parameter value and the second update step in update after current weight weighting coefficient parameter value as current parameter value, return is held
Row first calculates step.
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