CN106547027A - A kind of data processing method and device for obtaining dynamic(al) correction parameter - Google Patents
A kind of data processing method and device for obtaining dynamic(al) correction parameter Download PDFInfo
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- CN106547027A CN106547027A CN201710015203.1A CN201710015203A CN106547027A CN 106547027 A CN106547027 A CN 106547027A CN 201710015203 A CN201710015203 A CN 201710015203A CN 106547027 A CN106547027 A CN 106547027A
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V1/00—Seismology; Seismic or acoustic prospecting or detecting
- G01V1/28—Processing seismic data, e.g. analysis, for interpretation, for correction
- G01V1/36—Effecting static or dynamic corrections on records, e.g. correcting spread; Correlating seismic signals; Eliminating effects of unwanted energy
- G01V1/362—Effecting static or dynamic corrections; Stacking
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V2210/00—Details of seismic processing or analysis
- G01V2210/50—Corrections or adjustments related to wave propagation
- G01V2210/52—Move-out correction
Abstract
The application provides a kind of data processing method and device for obtaining dynamic(al) correction parameter.Methods described includes：Using the corresponding geological data of middle near migration range common midpoint gather reset, differential similarity coefficient operator is calculated；Using differential similarity coefficient operator, the similarity coefficient normal-moveout spectrum is normalized；Root mean sequare velocity is picked up from the normalized similarity coefficient normal-moveout spectrum；Preliminary dynamic(al) correction process is carried out using described root mean sequare velocity；Using the corresponding geological data of common midpoint gather after the preliminary dynamic(al) correction reset, corresponding differential similitude operator is calculated；Using the differential similarity coefficient operator, similarity coefficient anisotropic parameters spectrum is normalized, obtains normalized similarity coefficient anisotropic parameters spectrum；Anisotropic parameters is picked up from the normalized similarity coefficient anisotropic parameters spectrum.Using each embodiment in the application, the lateral resolution of the Parameter Spectrum can be effectively improved, and then effectively improves the precision of the dynamic(al) correction parameter.
Description
Technical field
The application is related to seismic data processing technology field, more particularly to a kind of data processing side for obtaining dynamic(al) correction parameter
Method and device.
Background technology
Travel time curve, also known as time curve, is between the time required for representing the distance of seimic wave propagation and propagating
Relation curve.Travel time curve is the important foundation of Study of The Underground interface configuration.But, travel time curve is usually hyperbolic shape
, wherein the echo time for only receiving at shot point represents the normal reflection time at interface, therefore each must be seen
The time value of measuring point all becomes the normal reflection time of respective points, time curve or lineups form one just with subsurface interface
Cause.This is accomplished by carrying out dynamic(al) correction process, eliminates the NMO (normal moveout) that seismic wave reaches each geophone station.During dynamic(al) correction is processed, move
The precision of correction parameter, is the key factor for determining dynamic(al) correction treatment effect.
In prior art, at least there are the following problems：In prior art, dynamic(al) correction parameter is obtained, often joined from dynamic(al) correction
Pickup in number spectrum obtains the dynamic(al) correction parameter.But, often there is energy group hangover in dynamic(al) correction Parameter Spectrum of the prior art
Phenomenon, causes the lateral resolution of the dynamic(al) correction Parameter Spectrum relatively low, and then the precision of the dynamic(al) correction parameter that can cause to pick up
It is relatively low.
The content of the invention
The purpose of the embodiment of the present application is to provide a kind of data processing method and device for obtaining dynamic(al) correction parameter
The embodiment of the present application provides what a kind of data processing method and device for obtaining dynamic(al) correction parameter was realized in：
A kind of data processing method for obtaining dynamic(al) correction parameter, methods described include：
M rearrangement is carried out to the middle shortcut in the common midpoint gather of pending geological data, obtains near during M groups are reset
Road collection, controls there is the time difference, M >=1 between each pair neighboring track during rearrangement；
The corresponding geological data of middle near-trace gather reset using the M groups, is calculated M group differential similarity coefficient operators；
Using the M groups differential similarity coefficient operator, initial similarity coefficient-normal-moveout spectrum is normalized, is obtained
Normalized similarity coefficient-normal-moveout spectrum；
Root mean sequare velocity is picked up from the normalized similarity coefficient-normal-moveout spectrum；
Preliminary dynamic(al) correction process is carried out to the pending geological data using described root mean sequare velocity, is tentatively moved
Common midpoint gather after correction；
Whole roads in common midpoint gather after the preliminary dynamic(al) correction are carried out with R rearrangement, the road of R groups rearrangement is obtained
Collection, controls there is the time difference, R >=1 between each pair neighboring track during rearrangement；
The corresponding geological data of road collection reset using the R groups, is calculated R group differential similitude operators；
Using the R groups differential similarity coefficient operator, place is normalized to initial similarity coefficient-anisotropic parameters spectrum
Reason, obtains normalized similarity coefficient-anisotropic parameters spectrum；
Anisotropic parameters is picked up from the normalized similarity coefficient-anisotropic parameters spectrum；
Using the root mean sequare velocity and the anisotropic parameters as the dynamic(al) correction parameter.
In preferred embodiment, the mode for controlling to there is the time difference between each pair neighboring track during rearrangement, bag
Include：
According to the skew in the middle near migration range road collection Huo and the common midpoint gather Zhong Ge roads after the preliminary dynamic(al) correction
Away from size, the road collection is reset, realize there is the time difference between the control each pair neighboring track.
It is in preferred embodiment, described using the M groups differential similarity coefficient operator, the similarity coefficient-normal-moveout spectrum is entered
The mode of row normalized, including being normalized to the similarity coefficient-normal-moveout spectrum using following formula, is returned
One similarity coefficient-the normal-moveout spectrum changed：
In formula,Represent M group differential similarity coefficient operators；
V represents root mean sequare velocity；
ND TR DvSimilarity coefficient when table S shows that root mean sequare velocity is v.
It is in preferred embodiment, described using the R groups differential similarity coefficient operator, to the similarity coefficient-anisotropy
The mode that Parameter Spectrum is normalized, is carried out including being composed to the similarity coefficient-anisotropic parameters using following formula
Normalized, obtains normalized similarity coefficient-anisotropic parameters spectrum：
In formula,Represent R group differential similarity coefficient operators；
η represents anisotropic parameters；
NDTRDSηSimilarity coefficient when representing that anisotropic parameters is η.
In preferred embodiment, the acquisition modes of the initial similarity coefficient-normal-moveout spectrum, including：
It is using the geological data and non-double curve travel time curve of the middle near migration range road collection, bent when being walked according to the non-double curve
The low order portion of line and the similarity coefficient computing formula, are calculated similarity coefficient-normal-moveout spectrum.
In preferred embodiment, the expression formula of the low order portion of the non-double curve travel time curve includes：
In formula, X represents offset distance；
T (X) represents the offset distance X corresponding propagation times；
V represents root mean sequare velocity；
t0Represent that offset distance is the corresponding propagation time at 0.
In preferred embodiment, the similarity coefficient, including being calculated using following formula：
In formula, S represents similarity coefficient；
N represents the corresponding total road number of geological data；
xiRepresent the offset distance in the i-th road；
Window width when λ is represented；
d(t,xi) represent t time points, offset distance xiThe amplitude at place.
In preferred embodiment, the mode of the initial similarity coefficient-anisotropic parameters spectrum, including：
Walked using the corresponding geological data in whole roads in the common midpoint gather after the preliminary dynamic(al) correction, and non-double curve
When curve；
According to the non-double curve travel time curve and the similarity coefficient computing formula for having substituted into the root mean sequare velocity, calculate
To similarity coefficient-anisotropic parameters spectrum
In preferred embodiment, the expression formula of the non-double curve travel time curve includes：
In formula：X represents offset distance；
T (X) represents the offset distance X corresponding propagation times；
V represents root mean sequare velocity；
t0Represent that offset distance is the corresponding propagation time at 0；
η represents anisotropic parameters.
In preferred embodiment, the differential similarity coefficient operator, including being calculated using following formula：
In formula,Represent the differential similarity coefficient operator；
N represents the corresponding total road number of geological data；
xiRepresent the offset distance in the i-th road；
Window width when λ is represented；
t0Represent that offset distance is the corresponding propagation time at 0；
d(t,xi) represent t time points, offset distance xiThe amplitude at place.
A kind of data processing equipment for obtaining dynamic(al) correction parameter, described device include：
Middle near-trace gather reordering module, for the common midpoint gather to pending geological data in middle shortcut carry out M time
Reset, obtain the middle near-trace gather of M groups rearrangement, control there is the time difference, M >=1 between each pair neighboring track during rearrangement；
Preliminary dynamic(al) correction module, for utilizing described root mean sequare velocity tentatively to move the pending geological data
Correction process, obtains the common midpoint gather after preliminary dynamic(al) correction；
Common midpoint gather reordering module, for entering to the whole roads in the common midpoint gather after the preliminary dynamic(al) correction
R rearrangement of row, obtains the road collection of R groups rearrangement, controls there is the time difference, R >=1 between each pair neighboring track during rearrangement；
Parameter Spectrum acquisition module, for the geological data according to the middle shortcut, is calculated similarity coefficient-normal-moveout spectrum,
It is additionally operable to according to the corresponding earthquake in whole roads in the common midpoint gather after the root mean sequare velocity and the preliminary dynamic(al) correction
Data, are calculated similarity coefficient-anisotropic parameters spectrum；
Normalized module, for using the M groups differential similarity coefficient operator, to initial similarity coefficient-normal-moveout spectrum
It is normalized, obtains normalized similarity coefficient-normal-moveout spectrum, is additionally operable to using the R groups differential similarity coefficient operator,
Initial similarity coefficient-anisotropic parameters spectrum is normalized, normalized similarity coefficient-anisotropic parameters is obtained
Spectrum；
Parameter pickup model, for picking up root mean sequare velocity from the normalized similarity coefficient-normal-moveout spectrum, is additionally operable to
Anisotropic parameters is picked up from the normalized similarity coefficient-anisotropic parameters spectrum；
Data generation module, for the root mean sequare velocity and the anisotropic parameters are joined as the dynamic(al) correction
Number.
A kind of data processing method of the acquisition dynamic(al) correction parameter provided using the embodiment of the present application, can be by road collection
Enter the mode of rearrangement, make there is the time difference between each pair neighboring track in the road collection of rearrangement, due to differential similarity coefficient operator over the ground
Between shake road, the sensitivity of the time difference is higher, makes there is the time difference between each pair neighboring track, it is possible to so that differential similarity coefficient operator is most
Bigization.And then using the differential similarity coefficient operator to initial similarity coefficient-normal-moveout spectrum and initial similarity coefficient-anisotropy
Parameter Spectrum carries out one or many normalized, can effectively improve the lateral resolution of described two Parameter Spectrums.Using horizontal stroke
Similarity coefficient-the normal-moveout spectrum improved to resolution and similarity coefficient-anisotropic parameters spectrum, the dynamic(al) correction parameter that pickup is obtained
Precision is higher, effectively increases the precision of the root mean sequare velocity and two kinds of dynamic(al) correction parameters of anisotropic parameter.Utilize
A kind of data processing equipment of acquisition dynamic(al) correction parameter that the embodiment of the present application is provided, can perform said method, automatically automatically
Obtain the dynamic(al) correction parameter that simultaneously output accuracy is improved, it is not necessary to implement the excessive participation of personnel, it is convenient to operation, effectively improve
Consumer's Experience.
Description of the drawings
In order to be illustrated more clearly that the embodiment of the present application or technical scheme of the prior art, below will be to embodiment or existing
Accompanying drawing to be used needed for having technology description is briefly described, it should be apparent that, drawings in the following description are only this
Some embodiments described in application, for those of ordinary skill in the art, in the premise for not paying creative labor
Under, can be with according to these other accompanying drawings of accompanying drawings acquisition.
Fig. 1 is a kind of method flow of the data processing method of acquisition dynamic(al) correction parameter that the application one embodiment is provided
Schematic diagram；
Fig. 2 is a kind of modular structure of the data processing equipment of acquisition dynamic(al) correction parameter that the application one embodiment is provided
Schematic diagram；
Fig. 3 is the seismic channel set in the application one embodiment not through the seismic channel set reset and through resetting；
Fig. 4 be the seismic channel set of the pending geological data in the application one embodiment and get similarity coefficient-
Normal-moveout spectrum；
Fig. 5 is the seismic channel set of the pending geological data in the application another embodiment and the similar system for getting
Number-anisotropic parameters is composed.
Specific embodiment
The embodiment of the present application provides a kind of data processing method and device for obtaining dynamic(al) correction parameter.
In order that those skilled in the art more fully understand the technical scheme in the application, below in conjunction with the application reality
The accompanying drawing in example is applied, the technical scheme in the embodiment of the present application is clearly and completely described, it is clear that described enforcement
Example is only some embodiments of the present application, rather than the embodiment of whole.Based on the embodiment in the application, this area is common
The every other embodiment obtained under the premise of creative work is not made by technical staff, should all belong to the application protection
Scope.
Fig. 1 is that a kind of a kind of herein described method flow of embodiment of data processing method for obtaining dynamic(al) correction parameter shows
It is intended to.Although this application provides such as following embodiments or method operating procedure shown in the drawings or apparatus structure, based on normal
Rule can include more or less operating procedures or module in methods described or device without the need for performing creative labour
Unit.In the step of there is no necessary cause effect relation in logicality or structure, the mould of the execution sequence or device of these steps
Block structure is not limited to the embodiment of the present application or execution sequence shown in the drawings or modular structure.Described method or modular structure
When device in practice or end product application, can carry out according to embodiment or method shown in the drawings or modular structure
Order is performed or executed in parallel (environment of such as parallel processor or multiple threads, even including distributed treatment
Implementation environment).
Specifically as described in Figure 1, a kind of one kind of the data processing method of acquisition dynamic(al) correction parameter that the application is provided is real
Applying example can include：
S1：M rearrangement is carried out to the middle shortcut in the common midpoint gather of pending geological data, the rearrangement of M groups is obtained
Middle near-trace gather, controls there is the time difference, M >=1 between each pair neighboring track during rearrangement.
Common midpoint gather after the preliminary dynamic(al) correction can be obtained by pending geological data is taken out road collection.
The middle shortcut includes seismic channel of the offset distance with the ratio of depth less than or equal to 1.5.
In the application one embodiment, the mode of the rearrangement is reset for definitiveness, and each pair phase is controlled during rearrangement
There is the mode of the time difference between neighboring trace, can include：
According to the middle near-trace gather Huo and the offset distance size in the common midpoint gather Zhong Ge roads, to the middle shortcut
Enter rearrangement, realize there is the time difference between the control each pair neighboring track.
It is by according to offset distance size, resetting to middle the being determined property of near-trace gather Zhong Ge roads, specifically, such as, false
Road collection x of the Ding Yitiao roads number for N=2m, the output road collection after definitiveness road is resetFor [x1, xm+1, x2, xm+2..., xk,
xm+k..., xm, xN], neighboring track is lined up by offset distance is differed larger road, it is possible to achieve deposit between control each pair neighboring track
In the effect of the obvious time difference.
(a) figure in Fig. 3 is in the application one embodiment not through the seismic channel set reset, (b) in Fig. 3
Figure is to enter the rearrangement that rearrangement after obtain to the corresponding seismic channel set of (a) figure in Fig. 3 using the rearranged form described in this method
Seismic channel set afterwards.In (a) figure and (b) figure in Fig. 3, abscissa all represents offset distance (offset, offset distance), vertical coordinate all tables
Show the time, it can be seen that after definitiveness is reset, in the road collection after rearrangement, between neighboring track, be clearly present the time difference.
S2：The corresponding geological data of middle near-trace gather reset using the M groups, is calculated the calculation of M group differential similarity coefficient
Son.
The M be more than or equal to 1, it is preferable that rearrangement more than twice can be carried out in the embodiment of the present application, obtain two groups with
On differential similarity coefficient operator.
The differential similarity coefficient operator, can include being calculated using following formula：
In formula,Represent the differential similarity coefficient operator；
N represents the corresponding total road number of geological data；
xiRepresent the offset distance in the i-th road；
Window width when λ is represented；
t0Represent that offset distance is the corresponding propagation time at 0；
d(t,xi) represent t time points, offset distance xiThe amplitude at place.
S3：Using the M groups differential similarity coefficient operator, initial similarity coefficient-normal-moveout spectrum is normalized, is obtained
To normalized similarity coefficient-normal-moveout spectrum.
The M is more than or equal to 1, it is preferable that in the embodiment of the present application, using two groups and differential similarity coefficient more than two
Operator, is normalized to initial similarity coefficient-normal-moveout spectrum, can preferably improve spectral resolution, the differential phase of employing
More like the group number of coefficient operator, resolution is higher.
In the application one embodiment, using the M groups differential similarity coefficient operator, to the similarity coefficient-normal-moveout spectrum
The mode being normalized, can include being normalized the similarity coefficient-normal-moveout spectrum using following formula,
Obtain normalized similarity coefficient-normal-moveout spectrum：
In formula,Represent M group differential similarity coefficient operators；
V represents root mean sequare velocity；
ND TR DvSimilarity coefficient when table S shows that root mean sequare velocity is v.
In the application another embodiment, the acquisition modes of the initial similarity coefficient-normal-moveout spectrum can include：
Using the geological data and non-double curve travel time curve of the middle near migration range road collection,
According to the low order portion and the similarity coefficient computing formula of the non-double curve travel time curve, similar system is calculated
Number-normal-moveout spectrum.
The expression formula of the low order portion of the non-double curve travel time curve can include：
In formula, X represents offset distance；
T (X) represents the offset distance X corresponding propagation times；
V represents root mean sequare velocity；
t0Represent that offset distance is the corresponding propagation time at 0.
The similarity coefficient formula is calculated can be included：
In formula, S represents similarity coefficient；
N represents the corresponding total road number of geological data；
xiRepresent the offset distance in the i-th road；
Window width when λ is represented；
d(t,xi) represent t time points, offset distance xiThe amplitude at place.
(a) figure in Fig. 4 is CMP (CMP) road collection of the pending geological data in the application one embodiment,
Wherein, vertical coordinate express time, abscissa represent offset distance.(b) figure in Fig. 4 is according to figure using existing Similar operator
Similarity coefficient-normal-moveout spectrum that (a) figure in 4 gets.(c) figure, (d) figure, (e) figure in Fig. 4 be respectively carry out 1 time, 2 times, 3
After secondary rearrangement, through similarity coefficient-normal-moveout spectrum that normalized is obtained, in Fig. 4, v represents speed, and unit is metre per second (m/s).Can
To find out, after rearrangement, spectral resolution is improved significantly, and the number of times reset is more, obtains after normalized
The resolution of spectrum is higher.
S4：Root mean sequare velocity is picked up from the normalized similarity coefficient-normal-moveout spectrum.
The root mean sequare velocity can be used as the parameter of dynamic(al) correction.
The mode of the pickup root mean sequare velocity, can voluntarily be selected by enforcement personnel, and the application is not limited.
S5：Preliminary dynamic(al) correction process is carried out to the pending geological data using described root mean sequare velocity, is obtained just
Common midpoint gather after step dynamic(al) correction.
The processing mode that the preliminary dynamic(al) correction is processed, enforcement personnel voluntarily can be selected, and concrete limit is not done in the application
It is fixed.
S6：Whole roads in common midpoint gather after the preliminary dynamic(al) correction are carried out with R rearrangement, the rearrangement of R groups is obtained
Road collection, during rearrangement control each pair neighboring track between there is the time difference, R >=1.
In the application one embodiment, the mode of the rearrangement is reset for definitiveness, and each pair phase is controlled during rearrangement
There is the mode of the time difference between neighboring trace, can include：
According to the middle near-trace gather Huo and the offset distance size in the common midpoint gather Zhong Ge roads, to the middle shortcut
Enter rearrangement, realize there is the time difference between the control each pair neighboring track.
By according to offset distance size, resetting to being determined property of the concentrically road collection Zhong Ge road.
S7：The corresponding geological data of road collection reset using the R groups, is calculated R group differential similitude operators.
The calculation of the differential similitude operator is with step S2.
S8：Using the R groups differential similarity coefficient operator, normalizing is carried out to initial similarity coefficient-anisotropic parameters spectrum
Change is processed, and obtains normalized similarity coefficient-anisotropic parameters spectrum.
In the application one embodiment, using the R groups differential similarity coefficient operator, to the similarity coefficient-each to different
The mode that property Parameter Spectrum is normalized, can be included using following formula to the similarity coefficient-anisotropic parameters
Spectrum is normalized, and obtains normalized similarity coefficient-anisotropic parameters spectrum：
In formula,Represent R group differential similarity coefficient operators；
η represents anisotropic parameters；
NDTRDSηSimilarity coefficient when representing that anisotropic parameters is η.
In the application one embodiment, the acquisition modes of the initial similarity coefficient-anisotropic parameters spectrum can be wrapped
Include：
Walked using the corresponding geological data in whole roads and non-double curve in the common midpoint gather after the preliminary dynamic(al) correction
When curve, according to the non-double curve travel time curve and the similarity coefficient computing formula for having substituted into the root mean sequare velocity, calculate
To similarity coefficient-anisotropic parameters spectrum.
In the application another embodiment, the expression formula of the non-double curve travel time curve can include：
In formula：X represents offset distance；
T (X) represents the offset distance X corresponding propagation times；
V represents root mean sequare velocity；
t0Represent that offset distance is the corresponding propagation time at 0；
η represents anisotropic parameters.
(a) figure in Fig. 5 is CMP (CMP) road collection of the geological data containing residual normal moveout, wherein, vertical coordinate
Express time, abscissa represent offset distance.(b) figure in Fig. 5 be got using existing conventional Similar operator frequency-
Anisotropic parameters compose, (c) figure, (d) figure, (e) figure in Fig. 5 be respectively carried out 1 time, 3 times, 6 times reset after, carry out normalizing
Change processes the frequency-anisotropic parameters frequency dispersion spectrum for obtaining, and in Fig. 5, η represents anisotropic parameters.It can be seen that sharp
The frequency got with conventional Similar operator-anisotropic parameters spectrum, the poor difference of mid-deep strata energy group focusing, affecting parameters
Pickup precision.After entering rearrangement, when it is 1 to reset number of times, in the spectrum for getting, energy group focusing makes moderate progress, and resolution is obtained
To effectively improving.Rearrangement number of times is higher, and energy group focusing can more be improved, and resolution is higher.Illustrate to utilize the application
Methods described can effectively improve the lateral resolution of frequency-anisotropic parameters spectrum, higher such that it is able to pick up precision
Anisotropic parameters.
S9：Anisotropic parameters is picked up from the normalized similarity coefficient-anisotropic parameters spectrum.
The anisotropic parameters can be used as the parameter of dynamic(al) correction.
Herein described anisotropic parameters is equivalent anisotropic parameters, and its expression formula includes：
In formula, ε represents compressional wave anisotropic parameters；
δ represents the parameter for affecting compressional wave velocity magnitude in nearly vertical direction.
The mode of the pickup anisotropic parameters, can voluntarily be selected by enforcement personnel, and the application is not limited.
S10：Using the root mean sequare velocity and the anisotropic parameters as the dynamic(al) correction parameter.
Preliminary dynamic(al) correction can be carried out to travel time curve using the root mean sequare velocity.
Further high-order NMO can be carried out to travel time curve using the anisotropic parameters.
A kind of data processing method of the acquisition dynamic(al) correction parameter provided using the various embodiments described above, can be by road collection
Enter the mode of rearrangement, make there is the time difference between each pair neighboring track in the road collection of rearrangement, due to differential similarity coefficient operator over the ground
Between shake road, the sensitivity of the time difference is higher, makes there is the time difference between each pair neighboring track, it is possible to so that differential similarity coefficient operator is most
Bigization.And then using the differential similarity coefficient operator to initial similarity coefficient-normal-moveout spectrum and initial similarity coefficient-anisotropy
Parameter Spectrum carries out one or many normalized, can effectively improve the lateral resolution of described two Parameter Spectrums.Using horizontal stroke
Similarity coefficient-the normal-moveout spectrum improved to resolution and similarity coefficient-anisotropic parameters spectrum, the dynamic(al) correction parameter that pickup is obtained
Precision is higher, effectively increases the precision of the root mean sequare velocity and two kinds of dynamic(al) correction parameters of anisotropic parameter.
Based on the data processing method for obtaining dynamic(al) correction parameter described herein, the application provides a kind of acquisition dynamic(al) correction
The data processing equipment of parameter, described device can be integrated in dynamic(al) correction component, carry out dynamic(al) correction process.Fig. 2 is the application
The modular structure schematic diagram of the data processing equipment of the acquisition dynamic(al) correction parameter provided in one embodiment.Specifically, such as Fig. 2 institutes
Show, described device can include：
Middle near-trace gather reordering module 101, the middle shortcut that can be used in the common midpoint gather to pending geological data
M rearrangement is carried out, the middle near-trace gather of M groups rearrangement is obtained, controls there is the time difference between each pair neighboring track during rearrangement,
M≥1。
Preliminary dynamic(al) correction module 102, can be used for entering the pending geological data using described root mean sequare velocity
The preliminary dynamic(al) correction of row is processed, and obtains the common midpoint gather after preliminary dynamic(al) correction.
Common midpoint gather reordering module 103, can be used in the common midpoint gather after the preliminary dynamic(al) correction
Whole roads carry out R rearrangement, obtain the road collection of R groups rearrangement, control during rearrangement it is equal between each pair neighboring track in the presence of
Difference, R >=1.
Parameter Spectrum acquisition module 104, can be used for the geological data according to the middle shortcut, be calculated similarity coefficient-
Normal-moveout spectrum, is additionally operable to corresponding according to the whole roads in the common midpoint gather after the root mean sequare velocity and the preliminary dynamic(al) correction
Geological data, be calculated similarity coefficient-anisotropic parameters spectrum；
Normalized module 105, can be used for using the M groups differential similarity coefficient operator, to initial similarity coefficient-
Normal-moveout spectrum is normalized, and obtains normalized similarity coefficient-normal-moveout spectrum, can be also used for using the R groups differential phase
Like coefficient operator, initial similarity coefficient-anisotropic parameters spectrum is normalized, obtain normalized similarity coefficient-
Anisotropic parameters is composed.
Parameter pickup model 106, can be used for root-mean-square speed is picked up from the normalized similarity coefficient-normal-moveout spectrum
Degree, can be also used for picking up anisotropic parameters from the normalized similarity coefficient-anisotropic parameters spectrum.
Data generation module 107, can be used for the root mean sequare velocity and the anisotropic parameters are moved as described
Correction parameter.
A kind of data processing equipment of the acquisition dynamic(al) correction parameter provided using above-described embodiment, can perform this Shen automatically
Please methods described, automatically derive and output accuracy improve dynamic(al) correction parameter, it is not necessary to implement the excessive participation of personnel, operation side
Just it is quick, effectively increase Consumer's Experience.
It is in the data processing equipment for obtaining dynamic(al) correction parameter, described to enter rearrangement to road collection, be calculated differential phase
It is normalized like coefficient operator, to initial similarity coefficient-normal-moveout spectrum, initial similarity coefficient-anisotropic parameters is composed
Be normalized, from the normalized similarity coefficient-normal-moveout spectrum pick up root mean sequare velocity, from the normalized phase
Like anisotropic parameters is picked up in coefficient-anisotropic parameters spectrum to the root mean sequare velocity and the anisotropic parameters are made
Extension for the embodiment of the dynamic(al) correction parameter is referred to the associated description of preceding method.
Although the data processing methods of different acquisition dynamic(al) correction parameters are mentioned in teachings herein, from weight is carried out to road collection
Row, be calculated differential similarity coefficient operator, initial similarity coefficient-normal-moveout spectrum be normalized, to initial similar system
Number-anisotropic parameters spectrum is normalized, root-mean-square speed is picked up from the normalized similarity coefficient-normal-moveout spectrum
Degree, anisotropic parameters is picked up from the normalized similarity coefficient-anisotropic parameters spectrum to by the root mean sequare velocity
With the anisotropic parameters as the various sequential manners of the dynamic(al) correction parameter, data acquisition/process/way of output etc.
Description, but, the application is not limited to be industry standard or the situation described by embodiment etc., some industry standards or
Person can also realize above-mentioned reality using embodiment amended slightly on the practice processes of self-defined mode or embodiment description
Apply example it is identical, equivalent or it is close, or deformation after foreseeable implementation result.Using these modification or deform after data acquisition,
The embodiment of process, output, judgment mode etc., within the scope of still may belong to the optional embodiment of the application.
Although this application provides the method operating procedure as described in embodiment or flow chart, is based on routine or noinvasive
The means of the property made can include more or less operating procedures.The step of enumerating in embodiment order is only numerous steps
A kind of mode in execution sequence, does not represent unique execution sequence.When device or client production in practice is performed, can
To perform or executed in parallel (such as at parallel processor or multithreading according to embodiment or method shown in the drawings order
The environment of reason, even distributed data processing environment).Term " including ", "comprising" or its any other variant are intended to contain
Lid nonexcludability is included, so that a series of process, method, product or equipment including key elements not only will including those
Element, but also including other key elements being not expressly set out, or also include for this process, method, product or equipment
Intrinsic key element.In the absence of more restrictions, it is not excluded that including the process of the key element, method, product or
Also there are other identical or equivalent elements in person's equipment.
Device that above-described embodiment is illustrated or module etc., specifically can be realized by computer chip or entity, or by having
There is the product of certain function to realize.For convenience of description, it is divided into various modules with function when describing apparatus above to retouch respectively
State.Certainly, the function of each module can be realized in same or multiple softwares and/or hardware when the application is implemented,
The module for realizing same function can be realized by the combination of multiple submodule etc..Device embodiment described above is only
Schematically, for example, the division of the module, only a kind of division of logic function can have other drawing when actually realizing
Point mode, such as multiple module or components can with reference to or be desirably integrated into another system, or some features can be ignored,
Or do not perform.
It is also known in the art that in addition to realizing controller in pure computer readable program code mode, it is complete
Entirely can by by method and step carry out programming in logic cause controller with gate, switch, special IC, may be programmed
The form of logic controller and embedded microcontroller etc. is realizing identical function.Therefore this controller is considered one kind
Hardware component, and the device for realizing various functions included to its inside can also be considered as the structure in hardware component.Or
Person even, can be used for realizing that the device of various functions be considered as not only being the software module of implementation method but also being hardware
Structure in part.
The application can be described in the general context of computer executable instructions, such as program
Module.Usually, program module includes execution particular task or realizes the routine of particular abstract data type, program, object, group
Part, data structure, class etc..The application is put into practice in a distributed computing environment can also, in these distributed computing environment,
Task is performed by the remote processing devices connected by communication network.In a distributed computing environment, program module can
With positioned at including in the local and remote computer-readable storage medium including storage device.
As seen through the above description of the embodiments, those skilled in the art can be understood that the application can
By software plus required general hardware platform mode realizing.Based on such understanding, the technical scheme essence of the application
On part that in other words prior art is contributed can be embodied in the form of software product, the computer software product
Can be stored in storage medium, such as ROM/RAM, magnetic disc, CD etc., use so that a computer equipment including some instructions
(can be personal computer, mobile terminal, server, or network equipment etc.) performs each embodiment of the application or enforcement
Method described in some parts of example.
Each embodiment in this specification is described by the way of progressive, same or analogous portion between each embodiment
Divide mutually referring to what each embodiment was stressed is the difference with other embodiment.The application can be used for crowd
In more general or special purpose computing system environments or configuration.For example：Personal computer, server computer, handheld device or
Portable set, laptop device, multicomputer system, set based on the system of microprocessor, set top box, programmable electronics
Standby, network PC, minicomputer, mainframe computer, including the distributed computing environment etc. of any of the above system or equipment.
Although depicting the application by embodiment, it will be appreciated by the skilled addressee that the application have it is many deformation and
Change is without deviating from spirit herein, it is desirable to which appended claim includes these deformations and changes without deviating from the application's
Spirit.
Claims (11)
1. it is a kind of obtain dynamic(al) correction parameter data processing method, it is characterised in that methods described includes：
M rearrangement is carried out to the middle shortcut in the common midpoint gather of pending geological data, the middle shortcut of M groups rearrangement is obtained
Collection, controls there is the time difference, M >=1 between each pair neighboring track during rearrangement；
The corresponding geological data of middle near-trace gather reset using the M groups, is calculated M group differential similarity coefficient operators；
Using the M groups differential similarity coefficient operator, initial similarity coefficient-normal-moveout spectrum is normalized, normalizing is obtained
Similarity coefficient-the normal-moveout spectrum of change；
Root mean sequare velocity is picked up from the normalized similarity coefficient-normal-moveout spectrum；
Preliminary dynamic(al) correction process is carried out to the pending geological data using described root mean sequare velocity, preliminary dynamic(al) correction is obtained
Common midpoint gather afterwards；
Whole roads in common midpoint gather after the preliminary dynamic(al) correction are carried out with R rearrangement, the road collection of R groups rearrangement is obtained,
Control there is the time difference, R >=1 between each pair neighboring track during rearrangement；
The corresponding geological data of road collection reset using the R groups, is calculated R group differential similitude operators；
Using the R groups differential similarity coefficient operator, initial similarity coefficient-anisotropic parameters spectrum is normalized,
Obtain normalized similarity coefficient-anisotropic parameters spectrum；
Anisotropic parameters is picked up from the normalized similarity coefficient-anisotropic parameters spectrum；
Using the root mean sequare velocity and the anisotropic parameters as the dynamic(al) correction parameter.
2. a kind of data processing method for obtaining dynamic(al) correction parameter as claimed in claim 1, it is characterised in that described to reset
During control between each pair neighboring track, the presence of the mode of the time difference, including：
It is big according to the offset distance of the middle near migration range road collection Huo and the common midpoint gather Zhong Ge roads after the preliminary dynamic(al) correction
It is little, the road collection is reset, realizes there is the time difference between the control each pair neighboring track.
3. a kind of data processing method for obtaining dynamic(al) correction parameter as claimed in claim 1, it is characterised in that the utilization institute
State M group differential similarity coefficient operators, the mode being normalized to the similarity coefficient-normal-moveout spectrum, including using following
Formula is normalized to the similarity coefficient-normal-moveout spectrum, obtains normalized similarity coefficient-normal-moveout spectrum：
In formula,Represent M group differential similarity coefficient operators；
V represents root mean sequare velocity；
ND TRDvSimilarity coefficient when table S shows that root mean sequare velocity is v.
4. a kind of data processing method for obtaining dynamic(al) correction parameter as claimed in claim 1, it is characterised in that the utilization institute
R group differential similarity coefficient operators are stated, the mode is normalized by the similarity coefficient-anisotropic parameters spectrum, including
The similarity coefficient-anisotropic parameters spectrum is normalized using following formula, obtain normalized similarity coefficient-
Anisotropic parameters is composed：
In formula,Represent R group differential similarity coefficient operators；
η represents anisotropic parameters；
NDTRDSηSimilarity coefficient when representing that anisotropic parameters is η.
5. a kind of data processing method for obtaining dynamic(al) correction parameter as claimed in claim 1, it is characterised in that the initial phase
Like the acquisition modes of coefficient-normal-moveout spectrum, including：
Using the geological data and non-double curve travel time curve of the middle near migration range, according to the low order of the non-double curve travel time curve
Part and the similarity coefficient computing formula, are calculated similarity coefficient-normal-moveout spectrum.
6. a kind of data processing method for obtaining dynamic(al) correction parameter as claimed in claim 5, it is characterised in that the non-double curve
The expression formula of the low order portion of travel time curve includes：
In formula, X represents offset distance；
T (X) represents the offset distance X corresponding propagation times；
V represents root mean sequare velocity；
t0Represent that offset distance is the corresponding propagation time at 0.
7. a kind of data processing method for obtaining dynamic(al) correction parameter as claimed in claim 5, it is characterised in that the similar system
Number formula is calculated and is included：
In formula, S represents similarity coefficient；
N represents the corresponding total road number of geological data；
xiRepresent the offset distance in the i-th road；
Window width when λ is represented；
d(t,xi) represent t time points, offset distance xiThe amplitude at place.
8. a kind of data processing method for obtaining dynamic(al) correction parameter as claimed in claim 1, it is characterised in that the initial phase
Like the acquisition modes of coefficient-anisotropic parameters spectrum, including：
According to the corresponding geological data in whole roads in the common midpoint gather after the preliminary dynamic(al) correction, when acquisition non-double curve is walked
Curve；
According to the non-double curve travel time curve and the similarity coefficient computing formula for having substituted into the root mean sequare velocity, phase is calculated
Like coefficient-anisotropic parameters spectrum.
9. a kind of data processing method for obtaining dynamic(al) correction parameter as claimed in claim 8, it is characterised in that the non-double curve
The expression formula of travel time curve includes：
In formula：X represents offset distance；
T (X) represents the offset distance X corresponding propagation times；
V represents root mean sequare velocity；
t0Represent that offset distance is the corresponding propagation time at 0；
η represents anisotropic parameters.
10. a kind of data processing method for obtaining dynamic(al) correction parameter as claimed in claim 1, it is characterised in that the differential
Similarity coefficient operator, including being calculated using following formula：
In formula,Represent the differential similarity coefficient operator；
N represents the corresponding total road number of geological data；
xiRepresent the offset distance in the i-th road；
Window width when λ is represented；
t0Represent that offset distance is the corresponding propagation time at 0；
d(t,xi) represent t time points, offset distance xiThe amplitude at place.
11. a kind of data processing equipments for obtaining dynamic(al) correction parameter, it is characterised in that described device includes：
Middle near-trace gather reordering module, for the common midpoint gather to pending geological data in middle shortcut carry out M time rearrangement,
The middle near-trace gather of M groups rearrangement is obtained, controls there is the time difference, M >=1 between each pair neighboring track during rearrangement；
Preliminary dynamic(al) correction module, for utilizing described root mean sequare velocity to carry out preliminary dynamic(al) correction to the pending geological data
Process, obtain the common midpoint gather after preliminary dynamic(al) correction；
Common midpoint gather reordering module, for carrying out R to the whole roads in the common midpoint gather after the preliminary dynamic(al) correction
Secondary rearrangement, obtains the road collection of R groups rearrangement, controls there is the time difference, R >=1 between each pair neighboring track during rearrangement；
Parameter Spectrum acquisition module, for the geological data according to the middle shortcut, is calculated similarity coefficient-normal-moveout spectrum, also uses
The corresponding geological data in whole roads in common midpoint gather after according to the root mean sequare velocity and the preliminary dynamic(al) correction,
It is calculated similarity coefficient-anisotropic parameters spectrum；
Normalized module, for using the M groups differential similarity coefficient operator, carrying out to initial similarity coefficient-normal-moveout spectrum
Normalized, obtains normalized similarity coefficient-normal-moveout spectrum, is additionally operable to using the R groups differential similarity coefficient operator, to first
Beginning similarity coefficient-anisotropic parameters spectrum is normalized, and obtains normalized similarity coefficient-anisotropic parameters spectrum；
Parameter pickup model, for picking up root mean sequare velocity from the normalized similarity coefficient-normal-moveout spectrum, is additionally operable to from institute
Anisotropic parameters is picked up in stating normalized similarity coefficient-anisotropic parameters spectrum；
Data generation module, for using the root mean sequare velocity and the anisotropic parameters as the dynamic(al) correction parameter.
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