CN105301654A - Linear noise removing method and device - Google Patents
Linear noise removing method and device Download PDFInfo
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- CN105301654A CN105301654A CN201510599228.1A CN201510599228A CN105301654A CN 105301654 A CN105301654 A CN 105301654A CN 201510599228 A CN201510599228 A CN 201510599228A CN 105301654 A CN105301654 A CN 105301654A
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Abstract
The invention discloses a linear noise removing method and device. The method comprises the steps that singular value decomposition is carried out on a common imaging point gather matrix to acquire a first singular value matrix and left and right feature matrixes; singular values of the first singular value matrix are sorted by descending order, and column vectors of left and right feature matrixes are correspondingly adjusted according to the order of the singular values; first m singular values of the sorted first singular value matrix are reserved; the singular values except m singular values are set to be zero to acquire a second singular value matrix, wherein m is the preset number of the singular values; according to the second singular value matrix and adjusted left and right feature matrixes, calculation is carried out to acquire a first common imaging point gather matrix after linear noise removing. According to the linear noise removing method and device, which are provided by the invention, a valid signal is reserved, and at the same time linear noise in a common imaging point gather is removed.
Description
Technical field
The present invention relates to a kind of seismic prospecting data treatment technology, particularly a kind of line noise minimizing technology and device.
Background technology
The main task of seismic prospecting realizes the architectonic imaging in underground, and obtain corresponding seismic prospecting data.Subsequently through the process to described seismic prospecting data, thus find out subsurface geological structure.In the processing procedure to described seismic prospecting data, usually need to use migration and imaging techniques to form common imaging gather; Then carry out the operations such as velocity analysis according to the residual error curvature on described mixed precipitate, to optimize the quality of migration imaging, reduce subsurface geological structure to greatest extent.
But, in practical application, all kinds of noise can be subject to when forming common imaging gather.Described noise comprises random noise and line noise.As shown in Figure 1, show a typical common imaging gather, upper right corner is divided into skewed striped and is line noise.Due to the lineups that the useful signal in common imaging gather is linear, so when there is linear noise, when utilizing residual error picking algorithm to carry out velocity analysis according to the residual error curvature on described common imaging gather, be easy to line noise also be thought it together picks up with useful signal by useful lineups signal, thus the precision of residual error pickup can be affected.
At present, in order to reduce line noise, following three kinds of methods are mainly taked to the interference caused the identification of residual error curvature.
(1) method is excised: directly excision is subject to the region of linear voice interference.Its shortcoming is, the useful signal in cut region is also rejected together, has influence on the precision of residual error pickup.
(2) horizontal filter method: do low-pass filtering in transverse direction and can suppress oblique noise, but also have influence on residual signals simultaneously, reduce the precision of residual error pickup.
(3) identification-method of difference: the direction first identifying linear voice, then carries out calculus of differences along noise direction to signal, to remove noise.But difference algorithm also can cause the phase place of useful signal to change, and finally causes difference algorithm major injury useful signal.
Therefore, be necessary to propose a kind of method that can retain useful signal and the line noise of common imaging gather can be removed again.
Summary of the invention
The object of this invention is to provide a kind of line noise minimizing technology and device, common imaging gather internal linear noise can be removed while reservation useful signal.
Above-mentioned purpose of the present invention can adopt following technical proposal to realize:
A kind of line noise minimizing technology, comprising:
Obtain pending common imaging gather matrix;
Svd is carried out to described common imaging gather matrix, obtains the first singular value matrix, left eigenmatrix, right eigenmatrix;
The singular value be positioned on diagonal line in described first singular value matrix is sorted according to descending order, and the column vector of described left eigenmatrix and right eigenmatrix is done corresponding adjustment according to described singular value size sequence; Column vector is done corresponding adjustment according to described singular value size sequence and is retained m singular value before on the first singular value matrix diagonal line after described sequence, singular value on described first singular value matrix diagonal line except a described m singular value is set to zero, obtain the second singular value matrix, described m is the singular value value number pre-set;
Calculate according to the left eigenmatrix after described second singular value matrix and described adjustment, right eigenmatrix, obtain the first common imaging gather matrix after line noise removal.
In a preferred embodiment, described method also comprises:
Retain front k singular value on the first singular value matrix diagonal line after described sequence, singular value on described first singular value matrix diagonal line except a described k singular value is set to zero, obtain the 3rd singular value matrix, described k is the singular value value number pre-set being different from described m;
Calculate according to the left eigenmatrix after described 3rd singular value matrix and described adjustment, right eigenmatrix, obtain the second common imaging gather matrix after line noise removal;
Respectively order is asked to described first common imaging gather matrix, the second common imaging gather matrix, chooses the minimum matrix of order as the target common imaging gather matrix after process.
In a preferred embodiment, the value of described k comprises two or more.
In a preferred embodiment, described geological data is floating number form.
In a preferred embodiment, described geological data comprises N track data, and per pass data comprise M sampled point, and the described common imaging gather matrix of formation is two-dimensional matrix A, utilizes following formula to carry out svd to described two-dimensional matrix:
A＝US
1V
T
In above formula, U is left eigenvector, V
trepresent the transposition of V, V is right proper vector, S
1for first singular value matrix of A, formula is as follows:
U=[u
1, u
2..., u
n], u in above formula
nfor N number of column vector in U, N is natural number;
V=[v
1, v
2..., v
n], v in above formula
nfor N number of column vector in V, N is natural number.
A kind of line noise removal device, it comprises:
Common imaging gather matrix acquisition module, for obtaining pending common imaging gather matrix;
Svd module, for carrying out svd to described common imaging gather matrix, obtains the first singular value matrix, left eigenmatrix, right eigenmatrix;
Order arranges module, for the singular value be positioned on diagonal line in described first singular value matrix being sorted according to descending order, and the column vector of described left eigenmatrix and right eigenmatrix is done corresponding adjustment according to described singular value size sequence;
Second singular value matrix acquisition module, m singular value before on the first singular value matrix diagonal line after retaining described sequence, singular value on described first singular value matrix diagonal line except a described m singular value is set to zero, obtain the second singular value matrix, described m is the singular value value number pre-set;
First common imaging gather matrix acquisition module, for calculating according to the left eigenmatrix after described second singular value matrix and described adjustment, right eigenmatrix, obtains the first common imaging gather matrix after line noise removal.
In a preferred embodiment, described device also comprises:
3rd singular value matrix acquisition module, k singular value before on the first singular value matrix diagonal line after retaining described sequence, singular value on described first singular value matrix diagonal line except a described k singular value is set to zero, obtain the 3rd singular value matrix, described k is the singular value value number pre-set being different from described m;
Second common imaging gather matrix acquisition module, for calculating according to the left eigenmatrix after described 3rd singular value matrix and described adjustment, right eigenmatrix, obtains the second common imaging gather matrix after line noise removal;
Target common imaging gather matrix acquisition module, for asking order respectively to described first common imaging gather matrix, the second common imaging gather matrix, chooses the minimum matrix of order as the target common imaging gather matrix after process.
In a preferred embodiment, the value of described k comprises two or more.
In a preferred embodiment, described geological data is floating number form.
In a preferred embodiment, described geological data comprises N track data, and per pass data comprise M sampled point, and the described common imaging gather matrix of formation is two-dimensional matrix A, utilizes following formula to carry out svd to described two-dimensional matrix:
A＝US
1V
T
In above formula, U is left eigenvector, V
trepresent the transposition of V, V is right proper vector, S
1for first singular value matrix of A, formula is as follows:
U=[u
1, u
2..., u
n], u in above formula
nfor N number of column vector in U, N is natural number;
V=[v
1, v
2..., v
n], v in above formula
nfor N number of column vector in V, N is natural number.
The features and advantages of the invention are: line noise minimizing technology of the present invention carries out svd by the common imaging gather matrix formed by geological data, and the singular value be positioned on diagonal line in described first singular value matrix is sorted according to descending order, and the column vector of described left eigenmatrix and right eigenmatrix is done corresponding adjustment according to described singular value size sequence; Retain described diagonal line to go forward the number of m singular value, and remaining singular value is set to zero, to obtain the first common imaging gather matrix and the first common imaging gather mode removes line noise.Described line noise minimizing technology utilizes svd line noise and useful signal to be made a distinction, generally can have influence on for the acquisition of useful signal while removing noise relative to the mode of existing removal noise, common imaging gather internal linear noise can be removed while reservation useful signal.
Further, line noise minimizing technology of the present invention retains the number of different singular value on diagonal line by presetting, the multiple common imaging gather matrix of corresponding acquisition, and by described multiple common imaging gather Matrix Calculating order.The target common imaging gather matrix asking the mode of order to determine by described and the target common imaging gather of correspondence, can maximally remove common imaging gather internal linear noise while reservation useful signal.
Accompanying drawing explanation
Fig. 1 is the schematic diagram of common imaging gather;
Fig. 2 is the process flow diagram of a kind of line noise minimizing technology in the embodiment of the present invention;
Fig. 3 is the first common imaging gather schematic diagram after the line noise obtained in the embodiment of the present invention is removed;
Fig. 4 is the noise schematic diagram removed in the embodiment of the present invention;
Fig. 5 is the process flow diagram of a kind of line noise minimizing technology in the embodiment of the present invention;
Fig. 6 is the common imaging gather schematic diagram of corresponding acquisition during previous singular value on singular value matrix reservation diagonal line in the embodiment of the present invention;
Fig. 7 is the common imaging gather schematic diagram of corresponding acquisition during the first two singular value on singular value matrix reservation diagonal line in the embodiment of the present invention;
Fig. 8 is the common imaging gather schematic diagram of corresponding acquisition during first three singular value on singular value matrix reservation diagonal line in the embodiment of the present invention;
Fig. 9 be in the embodiment of the present invention singular value matrix retain diagonal line go forward four singular values time the corresponding common imaging gather schematic diagram obtained;
Figure 10 is the common imaging gather schematic diagram of corresponding acquisition during the first five singular value on singular value matrix reservation diagonal line in the embodiment of the present invention;
Figure 11 is the common imaging gather schematic diagram of corresponding acquisition during the first six singular value on singular value matrix reservation diagonal line in the embodiment of the present invention;
Figure 12 is the module map of a kind of line noise removal device in the embodiment of the present invention;
Figure 13 is the module map of a kind of line noise removal device in the embodiment of the present invention.
Embodiment
Below in conjunction with the drawings and specific embodiments, technical scheme of the present invention is elaborated, these embodiments should be understood only be not used in for illustration of the present invention and limit the scope of the invention, after having read the present invention, the amendment of those skilled in the art to the various equivalent form of value of the present invention has all fallen in the application's claims limited range.
The invention provides a kind of line noise minimizing technology and device, common imaging gather internal linear noise can be removed while reservation useful signal.
The present invention adopts svd to remove line noise in common imaging gather.Arbitrary real matrix A can be decomposed into three matrix multiple A=USV by svd
t, wherein, U is called left eigenmatrix, and V is called right eigenmatrix, and the two is all orthogonal matrix, S=diag (s
1, s
2...) be diagonal matrix, be called singular value matrix, the value on its diagonal line is called the singular value of matrix A.Line noise minimizing technology of the present invention can effectively be removed line noise, recovers by the former useful signal of noise pollution and keep its curvature information.
Referring to Fig. 2, is a kind of in embodiment of the present invention process flow diagram of line noise minimizing technology.Described line noise minimizing technology can comprise the steps.
Step S10: obtain pending common imaging gather matrix.
Described common imaging gather matrix can be formed by the geological data read containing sampled point.Described geological data can comprise N track data, and every track data can comprise M sampled point.Described N track data, the described common imaging gather matrix that M sampled point of every track data can be formed.Described common imaging gather matrix specifically can be two-dimensional matrix A.In described geological data, each track data is independent signal, there is not correlativity between horizontal Dao Yu road.
Described reading geological data can read with the form of floating number, correspondingly, can floating number form store.Described geological data reads with floating number form and stores.In a concrete embodiment, computing machine reads with floating number form (i.e. float type) and stores described geological data, can divide significance bit and exponent bits.Such as 12.3, what store in computing machine is 1 power of 1.230000*10.Namely significance bit is 1.230000, and exponent bits is 1.6 position effective digitals are retained, fully to improve the precision of described geological data after described significance bit radix point.
Step S12: carry out svd to described common imaging gather matrix, obtains the first singular value matrix, left eigenmatrix, right eigenmatrix.
Carry out svd to described two-dimensional matrix, its computing formula is as follows:
A＝US
1V
T，
Wherein, U is left eigenvector, V
trepresent the transposition of V, V is right proper vector, S
1for first singular value matrix of A, its formula is as follows:
U=[u
1, u
2..., u
n], u in above formula
nfor N number of column vector in U, N is natural number;
V=[v
1, v
2..., v
n], v in above formula
nfor N number of column vector in V, N is natural number.
Step S14: the singular value be positioned on diagonal line in described first singular value matrix is sorted according to descending order, and the column vector of described left eigenmatrix and right eigenmatrix is done corresponding adjustment according to described singular value size sequence.Concrete, such as, s
1compare s
2little, so the order of the two is exchanged, now the secondary series u of left eigenmatrix U
2with first row u
1exchange; The secondary series v of right feature V
2with first row v
1exchange.
Step S16: retain front m singular value on the first singular value matrix diagonal line after described sequence, singular value on described first singular value matrix diagonal line except a described m singular value is set to zero, obtain the second singular value matrix S2, described m is the singular value value number pre-set.
Wherein S
2formula as follows.
Wherein, S
mfor described second singular value matrix S
2singular value on diagonal line, described m is natural number, and its concrete value can be 1,2,3 ... any one number in N.
Step S18: calculate according to the left eigenmatrix after described second singular value matrix and described adjustment, right eigenmatrix, obtains the first common imaging gather matrix after line noise removal.
In the present embodiment, can according to the left eigenmatrix U after described adjustment
1, the second singular value matrix S
2, right eigenmatrix V after sequence
1obtain the first common imaging gather matrix A after line noise removal
1, its computing formula is as follows.
A
1＝U
1S
2V
1
Because described first image gather matrix is corresponding with the first common imaging gather, obtain described first common imaging gather matrix and also namely obtain the first common imaging gather.Refer to Fig. 3, for the line noise that obtains in the embodiment of the present invention remove after the first common imaging gather schematic diagram.Be divided into skewed line noise by comparison diagram 3 and Fig. 1, Fig. 1 upper right corner, be greatly reduced in figure 3.Referring to Fig. 4 in addition, is the noise schematic diagram removed in the embodiment of the present invention.As can be seen from Figure 4, while the line noise removing top-right part, any large impact is not produced for horizontal useful signal.That is, line noise minimizing technology of the present invention, while the described skewed line noise of removal, can not have an impact to described horizontal useful signal.
Line noise minimizing technology of the present invention carries out svd by the common imaging gather matrix formed by geological data, and the singular value be positioned on diagonal line in described first singular value matrix is sorted according to descending order, and the column vector of described left eigenmatrix and right eigenmatrix is done corresponding adjustment according to described singular value size sequence; Retain described diagonal line to go forward the number of m singular value, and remaining singular value is set to zero, to obtain the first common imaging gather matrix and the first common imaging gather mode removes line noise.Described line noise minimizing technology utilizes svd line noise and useful signal to be made a distinction, generally can have influence on for the acquisition of useful signal while removing noise relative to the mode of existing removal noise, common imaging gather internal linear noise can be removed while reservation useful signal.
Refer to Fig. 5, described line noise minimizing technology can also comprise the steps.
Step S20: retain front k singular value on the first singular value matrix diagonal line after described sequence, singular value on described first singular value matrix diagonal line except a described k singular value is set to zero, obtain the 3rd singular value matrix, described k is the singular value value number pre-set being different from described m.
Step S22: calculate according to the left eigenmatrix after described 3rd singular value matrix and described adjustment, right eigenmatrix, obtains the second common imaging gather matrix after line noise removal.
Step S24: calculate according to the left eigenmatrix after described 3rd singular value matrix and described adjustment, right eigenmatrix, obtains the second common imaging gather matrix after line noise removal.
In the present embodiment, the value of described k comprises two or more.According to the different values of described k, retain the number of singular value on different described diagonal line respectively, and then obtain different singular value matrixs.
Please refer to Fig. 6 to Figure 11, in above-mentioned 6 figure, leftmost figure is the original common imaging gather with line noise, i.e. matrix A, and middle figure is front 1,2,3,4,5,6 row and the S retaining U, V respectively
1front 1,2,3,4,5,6 singular value to be multiplied the result obtained; Rightmost figure is the result that leftmost figure deducts middle figure and obtains, the noise namely removed.
Can find out that the singular value along with retaining is more, middle figure and leftmost former figure is more close, and the amount that skewed line noise is removed is fewer, and it is fewer that useful signal is lost; Correspondingly, along with the singular value retained is more, middle figure differs far away with leftmost figure, and the amount that skewed line noise is removed is more, and it is more that useful signal is lost.Therefore, in order to obtain a desirable target common imaging gather matrix, make to retain useful signal and remove common imaging gather internal linear noise to reach optimization, by the above-mentioned mode asking order, the minimum matrix of order can be chosen as target common imaging gather matrix.The target common imaging gather corresponding by the above-mentioned target common imaging gather matrix asking the mode of order to determine while reservation useful signal, can maximally remove common imaging gather internal linear noise.
In sum, line noise minimizing technology of the present invention retains the number of different singular value on diagonal line by presetting, the multiple common imaging gather matrix of corresponding acquisition, and by described multiple common imaging gather Matrix Calculating order.The target common imaging gather matrix asking the mode of order to determine by described and the target common imaging gather of correspondence, can maximally remove common imaging gather internal linear noise while reservation useful signal.
Referring to Figure 12, is a kind of in embodiment of the present invention module map of line noise removal device.Described line noise removal device 100 can comprise: common imaging gather matrix acquisition module 10, svd module 12, order arrangement module 14, second singular value matrix acquisition module 16, first common imaging gather matrix acquisition module 18.
Described common imaging gather matrix acquisition module 10, for obtaining pending common imaging gather matrix.
Described common imaging gather matrix can be formed by the geological data read containing sampled point.Described geological data can comprise N track data, and every track data can comprise M sampled point.Described N track data, the described common imaging gather matrix that M sampled point of every track data can be formed.Described common imaging gather matrix specifically can be two-dimensional matrix A.In described geological data, each track data is independent signal, there is not correlativity between horizontal Dao Yu road.
Described reading geological data can read with the form of floating number, correspondingly, can floating number form store.Described geological data reads with floating number form and stores.In a concrete embodiment, computing machine reads with floating number form (i.e. float type) and stores described geological data, can divide significance bit and exponent bits.Such as 12.3, what store in computing machine is 1 power of 1.230000*10.Namely significance bit is 1.230000, and exponent bits is 1.6 position effective digitals are retained, fully to improve the precision of described geological data after described significance bit radix point.
Described svd module 12, for svd module, for carrying out svd to described common imaging gather matrix, obtains the first singular value matrix, left eigenmatrix, right eigenmatrix.
Carry out svd to described two-dimensional matrix, its computing formula is as follows:
A＝US
1V
T，
Wherein, U is left eigenvector, V
trepresent the transposition of V, V is right proper vector, S
1for first singular value matrix of A, its formula is as follows:
U=[u
1, u
2..., u
n], u in above formula
nfor N number of column vector in U, N is natural number;
V=[v
1, v
2..., v
n], v in above formula
nfor N number of column vector in V, N is natural number.
Described order arrangement module 14, for the singular value be positioned on diagonal line in described first singular value matrix being sorted according to descending order, and the column vector of described left eigenmatrix and right eigenmatrix is done corresponding adjustment according to described singular value size sequence.Concrete, such as, s
1compare s
2little, so the order of the two is exchanged, now the secondary series u of left eigenmatrix U
2with first row u
1exchange; The secondary series v of right feature V
2with first row v
1exchange.
Described second singular value matrix acquisition module 16, m singular value before on the first singular value matrix diagonal line after retaining described sequence, singular value on described first singular value matrix diagonal line except a described m singular value is set to zero, obtains the second singular value matrix S
2, described m is the singular value value number pre-set.
Wherein S
2formula as follows.
Wherein, S
mfor described second singular value matrix S
2singular value on diagonal line, described m is natural number, and its concrete value can be 1,2,3 ... any one number in N.
Described first common imaging gather matrix acquisition module 18, for calculating according to the left eigenmatrix after described second singular value matrix and described adjustment, right eigenmatrix, obtains the first common imaging gather matrix after line noise removal.
In the present embodiment, can according to the left eigenmatrix U after described adjustment
1, the second singular value matrix S
2, right eigenmatrix V after sequence
1obtain the first common imaging gather matrix A after line noise removal
1, its computing formula is as follows.
A
1＝U
1S
2V
1
Because described first image gather matrix is corresponding with the first common imaging gather, obtain described first common imaging gather matrix and also namely obtain the first common imaging gather.Refer to Fig. 3, it is the first common imaging gather schematic diagram after the line noise obtained in the embodiment of the present invention is removed.Be divided into skewed line noise by comparison diagram 3 and Fig. 1, Fig. 1 upper right corner, be greatly reduced in figure 3.Referring to Fig. 4 in addition, is the noise schematic diagram removed in the embodiment of the present invention.As can be seen from Figure 4, while the line noise removing top-right part, any large impact is not produced for horizontal useful signal.That is, line noise minimizing technology of the present invention, while the described skewed line noise of removal, can not have an impact to described horizontal useful signal.
Line noise removal device 100 of the present invention carries out svd by the common imaging gather matrix formed by geological data, and the singular value be positioned on diagonal line in described first singular value matrix is sorted according to descending order, and the column vector of described left eigenmatrix and right eigenmatrix is done corresponding adjustment according to described singular value size sequence; Retain described diagonal line to go forward the number of m singular value, and remaining singular value is set to zero, to obtain the first common imaging gather matrix and the first common imaging gather mode removes line noise.Described line noise removal device 100 utilizes svd line noise and useful signal to be made a distinction, generally can have influence on for the acquisition of useful signal while removing noise relative to the mode of existing removal noise, common imaging gather internal linear noise can be removed while reservation useful signal.
Refer to Figure 13, it is the module map of a kind of line noise removal device in the embodiment of the present invention.Described line noise removal device 110 can also comprise: the 3rd singular value matrix acquisition module 20, second common imaging gather matrix acquisition module 22, target common imaging gather matrix acquisition module 24.
3rd singular value matrix acquisition module 20, k singular value before on the first singular value matrix diagonal line after retaining described sequence, singular value on described first singular value matrix diagonal line except a described k singular value is set to zero, obtain the 3rd singular value matrix, described k is the singular value value number pre-set being different from described m;
Second common imaging gather matrix acquisition module 22, for calculating according to the left eigenmatrix after described 3rd singular value matrix and described adjustment, right eigenmatrix, obtains the second common imaging gather matrix after line noise removal;
Target common imaging gather matrix acquisition module 24, for asking order respectively to described first common imaging gather matrix, the second common imaging gather matrix, chooses the minimum matrix of order as the target common imaging gather matrix after process.
In the present embodiment, the value of described k comprises two or more.According to the different values of described k, retain the number of singular value on different described diagonal line respectively, and then obtain different singular value matrixs.
Line noise removal device 110 of the present invention is by presetting the number retaining different singular value on diagonal line, and correspondence obtains multiple common imaging gather matrix, and by described multiple common imaging gather Matrix Calculating order.The target common imaging gather matrix asking the mode of order to determine by described and the target common imaging gather of correspondence, can maximally remove common imaging gather internal linear noise while reservation useful signal.
Each embodiment above-mentioned in this instructions all adopts the mode of going forward one by one to describe, and between each embodiment, identical similar portion is cross-referenced, and what each embodiment stressed is and other embodiment differences.Especially for device embodiment, because it is substantially similar to embodiment of the method, so description is fairly simple, relevant part illustrates see embodiment of the method part.
The foregoing is only several embodiments of the present invention, although the embodiment disclosed by the present invention as above, the embodiment that described content just adopts for the ease of understanding the present invention, is not intended to limit the present invention.Any those skilled in the art; under the prerequisite not departing from the spirit and scope disclosed by the present invention; any amendment and change can be done on the formal of embodiment and details; but scope of patent protection of the present invention, the scope that still must define with appended claims is as the criterion.
Claims (10)
1. a line noise minimizing technology, is characterized in that, comprising:
Obtain pending common imaging gather matrix;
Svd is carried out to described common imaging gather matrix, obtains the first singular value matrix, left eigenmatrix, right eigenmatrix;
The singular value be positioned on diagonal line in described first singular value matrix is sorted according to descending order, and the column vector of described left eigenmatrix and right eigenmatrix is done corresponding adjustment according to described singular value size sequence;
Retain front m singular value on the first singular value matrix diagonal line after described sequence, singular value on described first singular value matrix diagonal line except a described m singular value is set to zero, obtain the second singular value matrix, described m is the singular value value number pre-set;
Calculate according to the left eigenmatrix after described second singular value matrix and described adjustment, right eigenmatrix, obtain the first common imaging gather matrix after line noise removal.
2. the method for claim 1, is characterized in that, also comprises:
Retain front k singular value on the first singular value matrix diagonal line after described sequence, singular value on described first singular value matrix diagonal line except a described k singular value is set to zero, obtain the 3rd singular value matrix, described k is the singular value value number pre-set being different from described m;
Calculate according to the left eigenmatrix after described 3rd singular value matrix and described adjustment, right eigenmatrix, obtain the second common imaging gather matrix after line noise removal;
Respectively order is asked to described first common imaging gather matrix, the second common imaging gather matrix, chooses the minimum matrix of order as the target common imaging gather matrix after process.
3. method as claimed in claim 2, is characterized in that: the value of described k comprises two or more.
4. the method for claim 1, is characterized in that: described geological data is floating number form.
5. the method for claim 1, it is characterized in that: described geological data comprises N track data, per pass data comprise M sampled point, and the described common imaging gather matrix of formation is two-dimensional matrix A, utilizes following formula to carry out svd to described two-dimensional matrix:
A＝US
1V
T
In above formula, U is left eigenvector, V
trepresent the transposition of V, V is right proper vector, S
1for first singular value matrix of A, formula is as follows:
U=[u
1, u
2..., u
n], u in above formula
nfor N number of column vector in U, N is natural number;
V=[v
1, v
2..., v
n], v in above formula
nfor N number of column vector in V, N is natural number.
6. a line noise removal device, is characterized in that, it comprises:
Common imaging gather matrix acquisition module, for obtaining pending common imaging gather matrix;
Svd module, for carrying out svd to described common imaging gather matrix, obtains the first singular value matrix, left eigenmatrix, right eigenmatrix;
Order arranges module, for the singular value be positioned on diagonal line in described first singular value matrix being sorted according to descending order, and the column vector of described left eigenmatrix and right eigenmatrix is done corresponding adjustment according to described singular value size sequence;
Second singular value matrix acquisition module, m singular value before on the first singular value matrix diagonal line after retaining described sequence, singular value on described first singular value matrix diagonal line except a described m singular value is set to zero, obtain the second singular value matrix, described m is the singular value value number pre-set;
First common imaging gather matrix acquisition module, for calculating according to the left eigenmatrix after described second singular value matrix and described adjustment, right eigenmatrix, obtains the first common imaging gather matrix after line noise removal.
7. device as claimed in claim 6, it is characterized in that, it also comprises:
3rd singular value matrix acquisition module, k singular value before on the first singular value matrix diagonal line after retaining described sequence, singular value on described first singular value matrix diagonal line except a described k singular value is set to zero, obtain the 3rd singular value matrix, described k is the singular value value number pre-set being different from described m;
Second common imaging gather matrix acquisition module, for calculating according to the left eigenmatrix after described 3rd singular value matrix and described adjustment, right eigenmatrix, obtains the second common imaging gather matrix after line noise removal;
Target common imaging gather matrix acquisition module, for asking order respectively to described first common imaging gather matrix, the second common imaging gather matrix, chooses the minimum matrix of order as the target common imaging gather matrix after process.
8. device as claimed in claim 7, is characterized in that: the value of described k comprises two or more.
9. device as claimed in claim 6, is characterized in that: described geological data is floating number form.
10. device as claimed in claim 6, it is characterized in that: described geological data comprises N track data, per pass data comprise M sampled point, and the described common imaging gather matrix of formation is two-dimensional matrix A, utilizes following formula to carry out svd to described two-dimensional matrix:
A＝US
1V
T
In above formula, U is left eigenvector, V
trepresent the transposition of V, V is right proper vector, S
1for first singular value matrix of A, formula is as follows:
U=[u
1, u
2..., u
n], u in above formula
nfor N number of column vector in U, N is natural number;
V=[v
1, v
2..., v
n], v in above formula
nfor N number of column vector in V, N is natural number.
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| CN201510599228.1A CN105301654A (en) | 2015-09-18 | 2015-09-18 | Linear noise removing method and device |
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