CN107870358A - 3-component earthquake signal polarization vector analysis method and system - Google Patents
3-component earthquake signal polarization vector analysis method and system Download PDFInfo
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- CN107870358A CN107870358A CN201610855677.2A CN201610855677A CN107870358A CN 107870358 A CN107870358 A CN 107870358A CN 201610855677 A CN201610855677 A CN 201610855677A CN 107870358 A CN107870358 A CN 107870358A
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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
- G01V1/30—Analysis
- G01V1/307—Analysis for determining seismic attributes, e.g. amplitude, instantaneous phase or frequency, reflection strength or polarity
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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
- G01V2210/60—Analysis
- G01V2210/63—Seismic attributes, e.g. amplitude, polarity, instant phase
Abstract
Disclose a kind of 3-component earthquake signal polarization vector analysis method and system.This method can include：Based on three-component coefficient, it is determined that the when window comprising target wave field, window data during acquisition；Based on when window data, obtain three dimensions in particle position of centre of gravity；Based on when window data and position of centre of gravity, obtain spatial linear equation coefficient；And based on spatial linear equation coefficient, polarization vector is obtained, wherein, three-component coefficient includes：X-component, Y-component, Z component.This method projects to the particle trajectory of three component seismic wave in three dimensions, by linear fit algorithm and least-squares estimation, realizes and directly quickly obtains polarization vector.
Description
Technical field
The present invention relates to field of seismic exploration, more particularly, to a kind of 3-component earthquake signal polarization vector analysis side
Method and system.
Background technology
In field of seismic exploration, the traditional method of seismic prospecting received using simple component wave detector can not be completely anti-
The essence of seismic wave field is reflected, and uses the multi-component seismic of three-component wave detector reception, the vector wave field of three-dimensional is have recorded, is
People provide comprehensive space seismic wave field information.The polarization vector specificity analysis of the wherein seismic wave of three-component record is three
Component exploration carries out vector wave field reduction, the basis of the work such as crack and anisotropic analysis.At present, in three-component polarization vector
The method commonly used in analysis is the methods of losing the transient bearing histogram for holding curve method, energy criteria analytic method, energy to weight
To determine the polarization principal direction of various ripples.The common feature of these methods is, if to obtain three points of wave field polarization vector
Amount, the polarization vector analysis on two-dimensional space twice will be carried out.In addition, these method some also need to man-machine interactively.
The method of this two steps polarization analysis is unfavorable for directly quickly obtaining three components of polarization vector.Therefore, it is necessary to develop one
Kind 3-component earthquake signal polarization vector analysis method and system.
The information for being disclosed in background of invention part is merely intended to deepen the reason of the general background technology to the present invention
Solution, and be not construed as recognizing or imply known to those skilled in the art existing of the information structure in any form
Technology.
The content of the invention
The present invention proposes a kind of 3-component earthquake signal polarization vector analysis method and system, and it can by three-component
The particle trajectory of seismic wave is projected in three dimensions, by linear fit algorithm and least-squares estimation, is realized directly quick
Obtain polarization vector.
According to an aspect of the invention, it is proposed that a kind of 3-component earthquake signal polarization vector analysis method.Methods described
It can include：Based on three-component coefficient, it is determined that the when window comprising target wave field, window data when obtaining described；Based on described
When window data, obtain three dimensions in particle position of centre of gravity；Based on it is described when window data and the position of centre of gravity, obtain space
Linear equation coefficient；And based on the spatial linear equation coefficient, polarization vector is obtained, wherein, the 3-component earthquake note
Record includes：X-component, Y-component, Z component.
According to another aspect of the invention, it is proposed that a kind of 3-component earthquake signal polarization vector analysis system, the system
System can include：For based on three-component coefficient, it is determined that the when window comprising target wave field, the list of window data when obtaining described
Member；For based on it is described when window data, obtain three dimensions in particle position of centre of gravity unit；For based on it is described when window number
According to the position of centre of gravity, obtain spatial linear equation coefficient unit；And for based on the spatial linear equation coefficient,
The unit of polarization vector is obtained, wherein, the three-component coefficient includes：X-component, Y-component, Z component.
Methods and apparatus of the present invention has other characteristics and advantage, and these characteristics and advantage are attached from what is be incorporated herein
It will be apparent in figure and subsequent embodiment, or by the accompanying drawing being incorporated herein and subsequent specific reality
Apply in mode and stated in detail, these the drawings and specific embodiments are provided commonly for explaining the certain principles of the present invention.
Brief description of the drawings
Exemplary embodiment of the invention is described in more detail in conjunction with the accompanying drawings, it is of the invention above-mentioned and its
Its purpose, feature and advantage will be apparent, wherein, in exemplary embodiment of the invention, identical reference number
Typically represent same parts.
Fig. 1 shows the flow chart of the step of 3-component earthquake signal polarization vector analysis method according to the present invention.
Fig. 2 shows the schematic diagram of the three-component coefficient according to an embodiment of the invention.
Fig. 3 shows the signal of the particle motion trace and particle position of centre of gravity according to an embodiment of the invention
Figure.
Fig. 4 shows the schematic diagram of the principal direction of the particle motion trace according to an embodiment of the invention.
Embodiment
The present invention is more fully described below with reference to accompanying drawings.Although the side of being preferable to carry out of the present invention is shown in accompanying drawing
Formula, however, it is to be appreciated that may be realized in various forms the present invention without should be limited by embodiments set forth herein.Phase
Instead, there is provided these embodiments be in order that the present invention is more thorough and complete, and can be by the scope of the present invention intactly
It is communicated to those skilled in the art.
Embodiment 1
Fig. 1 shows the flow chart of the step of 3-component earthquake signal polarization vector analysis method according to the present invention.
In this embodiment, can be included according to the 3-component earthquake signal polarization vector analysis method of the present invention：Step
Rapid 101, based on three-component coefficient, it is determined that the when window comprising target wave field, window data during acquisition；Step 102, based on when window
Data, obtain the position of centre of gravity of particle in three dimensions；Step 103, based on when window data and position of centre of gravity, obtain spatial linear
Equation coefficient；And step 104, based on spatial linear equation coefficient, polarization vector is obtained, wherein, three-component coefficient bag
Include：X-component, Y-component, Z component.
The embodiment projects to the particle trajectory of three component seismic wave in three dimensions, by linear fit algorithm with
Least-squares estimation, realize and directly quickly obtain polarization vector.
The following detailed description of the specific steps of the 3-component earthquake signal polarization vector analysis method according to the present invention.
In one example, based on three-component coefficient, it is determined that the when window comprising target wave field, window number when can obtain
According to, wherein, three-component coefficient can include：X-component, Y-component, Z component.
In one example, based on when window data, the position of centre of gravity of particle in three dimensions can be obtained.
In one example, the coordinate variable of position of centre of gravity can be：
Wherein, wnWindow sampling number during expression, xc、yc、zcRepresent the coordinate variable of position of centre of gravity, xsum、ysum、zsumRespectively
Represent X-component, Y-component, Z component when window particle energy and.
Specifically, based on three-component coefficient, it is determined that the when window comprising target wave field, window data when can obtain, its
In, three-component coefficient can include：X-component, Y-component, Z component.
Window data when can be based on, by formula (2) calculate respectively each component when window wnInterior particle energy and：
Wherein, xi、yi、ziThe sampling point record of X-component, Y-component, Z component is represented respectively.
Particle energy can be based on and pass through formula (1) computation window wnThe barycentric coodinates of interior particle.
In one example, based on when window data and position of centre of gravity, spatial linear equation coefficient can be obtained.
In one example, spatial linear equation can be：
Wherein, x, y, z represents the coordinate of sampling point in X-component, Y-component, Z component respectively, and a and b represents spatial linear equation
Coefficient.
In one example, spatial linear equation coefficient can be：
Wherein, xi、yi、ziThe sampling point record of X-component, Y-component, Z component is represented respectively.
Specifically, formula (3) representation space linear equation, can by when window data and position of centre of gravity bring into formula (3),
By least-squares estimation, spatial linear equation coefficient (4) and (5) are obtained, and then be fitted the principal direction of particle motion trace.
In one example, based on spatial linear equation coefficient, polarization vector can be obtained.
In one example, the coordinate variable of polarization vector can be：
Wherein, px、py、pzRepresent the coordinate variable of polarization vector.
Specifically, based on spatial linear equation coefficient, the seat of the principal direction polarization vector of particle motion trace can be obtained
Mark variable is formula (6), (px, py, pz) represent particle motion trace principal direction polarization vector.
Using example
For ease of understanding the scheme of embodiment of the present invention and its effect, a concrete application example given below.Ability
Field technique personnel should be understood that the example only for the purposes of understanding the present invention, and its any detail is not intended in any way
The limitation present invention.
Fig. 2 shows the schematic diagram of the three-component coefficient according to an embodiment of the invention.Time window length wn
=61, when window in from top to bottom be respectively tri- components of X, Y and Z, this when window in the real polarization vector of P ripples for (-
0.3805,0.0182,0.9225)。
Fig. 3 shows the signal of the particle motion trace and particle position of centre of gravity according to an embodiment of the invention
Figure, wherein, the black round dot in figure is attached most importance to the heart.Based on when window data, by formula (2) calculate respectively each component when window wn
Interior particle energy and：
Wherein, wnWindow sampling number during expression, xsum、ysum、zsumRepresent respectively X-component, Y-component, Z component when window
Particle energy and xi、yi、ziThe sampling point record of X-component, Y-component, Z component is represented respectively.By particle energy and bring formula into
(1), computation window wnThe coordinate variable of the barycentric coodinates of interior particle can be：
Wherein, xc、yc、zcRepresent the coordinate variable of position of centre of gravity, (xc,yc,zc) position of centre of gravity is represented, calculate to obtain center of gravity position
It is set to (18.6516, -1.8638, -37.4178).
Fig. 4 shows the schematic diagram of the principal direction of the particle motion trace according to an embodiment of the invention.Space
Linear equation is：
Wherein, x, y, z represents the coordinate of sampling point in X-component, Y-component, Z component respectively, and a and b represents spatial linear equation
Coefficient.
By when window data and position of centre of gravity bring into formula (3), pass through least-squares estimation, obtain spatial linear system of equations
Number is：
Calculate spatial linear equation coefficient is a=-0.4132, b=0.0184.Comparison diagram 3 and Fig. 4 is it can be found that sky
Between linear equation be fitted the movement locus of space particle well.
Based on spatial linear equation coefficient, the coordinate variable of the principal direction polarization vector of particle motion trace can be obtained
For：
Wherein, px、py、pzRepresent the coordinate variable of polarization vector, (px, py, pz) represent particle motion trace principal direction
Polarization vector, calculate polarization vector is (- 0.3819,0.0170,0.9241), with actual value (- 0.3805,0.0182,
0.9225) it is very close.
In summary, this method projects to the particle trajectory of three component seismic wave in three dimensions, passes through linear fit
Algorithm and least-squares estimation, realize and directly quickly obtain polarization vector.
It will be understood by those skilled in the art that the purpose of the description to embodiments of the present invention is only for exemplarily above
Illustrate the beneficial effect of embodiments of the present invention, be not intended to embodiments of the present invention being limited to given any show
Example.
Embodiment 2
According to the embodiment of the present invention, there is provided a kind of 3-component earthquake signal polarization vector analysis system, the system
System can include：For based on three-component coefficient, it is determined that the when window comprising target wave field, the unit of window data during acquisition；
For based on when window data, obtain three dimensions in particle position of centre of gravity unit；For based on when window data and center of gravity position
Put, obtain the unit of spatial linear equation coefficient；And for based on spatial linear equation coefficient, obtaining the list of polarization vector
Member, wherein, three-component coefficient includes：X-component, Y-component, Z component.
The embodiment projects to the particle trajectory of three component seismic wave in three dimensions, by linear fit algorithm with
Least-squares estimation, realize and directly quickly obtain polarization vector.
In one example, the coordinate variable of position of centre of gravity can be：
Wherein, wnWindow sampling number when representing described, xc、yc、zcRepresent the coordinate variable of the position of centre of gravity, xsum、
ysum、zsumRespectively represent X-component, Y-component, Z component when window particle energy and.
In one example, spatial linear equation can be：
Wherein, x, y, z represents the coordinate of sampling point in X-component, Y-component, Z component respectively, and a and b represents the spatial linear
Equation coefficient.
In one example, spatial linear equation coefficient can be：
Wherein, xi、yi、ziThe sampling point record of X-component, Y-component, Z component is represented respectively.
In one example, the coordinate variable of polarization vector can be：
Wherein, px、py、pzRepresent the coordinate variable of polarization vector.
It will be understood by those skilled in the art that the purpose of the description to embodiments of the present invention is only for exemplarily above
Illustrate the beneficial effect of embodiments of the present invention, be not intended to embodiments of the present invention being limited to given any show
Example.
It is described above the embodiments of the present invention, described above is exemplary, and non-exclusive, and
It is also not necessarily limited to disclosed each embodiment.It is right in the case of without departing from the scope and spirit of illustrated each embodiment
Many modifications and changes will be apparent from for those skilled in the art.The choosing of term used herein
Select, it is intended to best explain the principle, practical application or the improvement to the technology in market of each embodiment, or make this technology
Other those of ordinary skill in field are understood that each embodiment disclosed herein.
Claims (10)
1. a kind of 3-component earthquake signal polarization vector analysis method, including：
Based on three-component coefficient, it is determined that the when window comprising target wave field, window data when obtaining described；
Based on it is described when window data, obtain three dimensions in particle position of centre of gravity；
Based on it is described when window data and the position of centre of gravity, obtain spatial linear equation coefficient；And
Based on the spatial linear equation coefficient, polarization vector is obtained,
Wherein, the three-component coefficient includes：X-component, Y-component, Z component.
2. 3-component earthquake signal polarization vector analysis method according to claim 1, wherein, the seat of the position of centre of gravity
Marking variable is：
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Respectively represent X-component, Y-component, Z component when window particle energy and.
3. 3-component earthquake signal polarization vector analysis method according to claim 2, wherein, the spatial linear equation
For：
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Coefficient.
4. 3-component earthquake signal polarization vector analysis method according to claim 3, wherein, the spatial linear equation
Coefficient is：
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5. 3-component earthquake signal polarization vector analysis method according to claim 4, wherein, the seat of the polarization vector
Marking variable is：
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6. a kind of 3-component earthquake signal polarization vector analysis system, including：
For based on three-component coefficient, it is determined that the when window comprising target wave field, the unit of window data when obtaining described；
For based on it is described when window data, obtain three dimensions in particle position of centre of gravity unit；
For based on it is described when window data and the position of centre of gravity, obtain the unit of spatial linear equation coefficient；And
For based on the spatial linear equation coefficient, obtaining the unit of polarization vector,
Wherein, the three-component coefficient includes：X-component, Y-component, Z component.
7. 3-component earthquake signal polarization vector analysis system according to claim 6, wherein, the seat of the position of centre of gravity
Marking variable is：
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<mi>x</mi>
<mi>c</mi>
</msub>
<mo>=</mo>
<mfrac>
<msub>
<mi>x</mi>
<mrow>
<mi>s</mi>
<mi>u</mi>
<mi>m</mi>
</mrow>
</msub>
<msub>
<mi>w</mi>
<mi>n</mi>
</msub>
</mfrac>
</mrow>
</mtd>
</mtr>
<mtr>
<mtd>
<mrow>
<msub>
<mi>y</mi>
<mi>c</mi>
</msub>
<mo>=</mo>
<mfrac>
<msub>
<mi>y</mi>
<mrow>
<mi>s</mi>
<mi>u</mi>
<mi>m</mi>
</mrow>
</msub>
<msub>
<mi>w</mi>
<mi>n</mi>
</msub>
</mfrac>
</mrow>
</mtd>
</mtr>
<mtr>
<mtd>
<mrow>
<msub>
<mi>z</mi>
<mi>c</mi>
</msub>
<mo>=</mo>
<mfrac>
<msub>
<mi>z</mi>
<mrow>
<mi>s</mi>
<mi>u</mi>
<mi>m</mi>
</mrow>
</msub>
<msub>
<mi>w</mi>
<mi>n</mi>
</msub>
</mfrac>
</mrow>
</mtd>
</mtr>
</mtable>
</mfenced>
<mo>-</mo>
<mo>-</mo>
<mo>-</mo>
<mrow>
<mo>(</mo>
<mn>1</mn>
<mo>)</mo>
</mrow>
</mrow>
Wherein, wnWindow sampling number when representing described, xc、yc、zcRepresent the coordinate variable of the position of centre of gravity, xsum、ysum、zsum
Respectively represent X-component, Y-component, Z component when window particle energy and.
8. 3-component earthquake signal polarization vector analysis system according to claim 7, wherein, the spatial linear equation
For：
<mrow>
<mfenced open = "{" close = "">
<mtable>
<mtr>
<mtd>
<mrow>
<mi>x</mi>
<mo>=</mo>
<mi>a</mi>
<mrow>
<mo>(</mo>
<mi>z</mi>
<mo>-</mo>
<msub>
<mi>z</mi>
<mi>c</mi>
</msub>
<mo>)</mo>
</mrow>
<mo>+</mo>
<msub>
<mi>x</mi>
<mi>c</mi>
</msub>
</mrow>
</mtd>
</mtr>
<mtr>
<mtd>
<mrow>
<mi>y</mi>
<mo>=</mo>
<mi>b</mi>
<mrow>
<mo>(</mo>
<mi>z</mi>
<mo>-</mo>
<msub>
<mi>z</mi>
<mi>c</mi>
</msub>
<mo>)</mo>
</mrow>
<mo>+</mo>
<msub>
<mi>y</mi>
<mi>c</mi>
</msub>
</mrow>
</mtd>
</mtr>
</mtable>
</mfenced>
<mo>-</mo>
<mo>-</mo>
<mo>-</mo>
<mrow>
<mo>(</mo>
<mn>3</mn>
<mo>)</mo>
</mrow>
</mrow>
Wherein, x, y, z represents the coordinate of sampling point in X-component, Y-component, Z component respectively, and a and b represents the spatial linear equation
Coefficient.
9. 3-component earthquake signal polarization vector analysis system according to claim 8, wherein, the spatial linear equation
Coefficient is：
<mrow>
<mi>a</mi>
<mo>=</mo>
<mfrac>
<mrow>
<munderover>
<mo>&Sigma;</mo>
<mrow>
<mi>i</mi>
<mo>=</mo>
<mn>1</mn>
</mrow>
<msub>
<mi>w</mi>
<mi>n</mi>
</msub>
</munderover>
<msub>
<mi>x</mi>
<mi>i</mi>
</msub>
<mrow>
<mo>(</mo>
<msub>
<mi>z</mi>
<mi>i</mi>
</msub>
<mo>-</mo>
<msub>
<mi>z</mi>
<mi>c</mi>
</msub>
<mo>)</mo>
</mrow>
<mo>-</mo>
<munderover>
<mo>&Sigma;</mo>
<mrow>
<mi>i</mi>
<mo>=</mo>
<mn>1</mn>
</mrow>
<msub>
<mi>w</mi>
<mi>n</mi>
</msub>
</munderover>
<msub>
<mi>x</mi>
<mi>c</mi>
</msub>
<mrow>
<mo>(</mo>
<msub>
<mi>z</mi>
<mi>i</mi>
</msub>
<mo>-</mo>
<msub>
<mi>z</mi>
<mi>c</mi>
</msub>
<mo>)</mo>
</mrow>
</mrow>
<mrow>
<munderover>
<mo>&Sigma;</mo>
<mrow>
<mi>i</mi>
<mo>=</mo>
<mn>1</mn>
</mrow>
<msub>
<mi>w</mi>
<mi>n</mi>
</msub>
</munderover>
<mrow>
<mo>(</mo>
<msub>
<mi>z</mi>
<mi>i</mi>
</msub>
<mo>-</mo>
<msub>
<mi>z</mi>
<mi>c</mi>
</msub>
<mo>)</mo>
</mrow>
<mrow>
<mo>(</mo>
<msub>
<mi>z</mi>
<mi>i</mi>
</msub>
<mo>-</mo>
<msub>
<mi>z</mi>
<mi>c</mi>
</msub>
<mo>)</mo>
</mrow>
</mrow>
</mfrac>
<mo>-</mo>
<mo>-</mo>
<mo>-</mo>
<mrow>
<mo>(</mo>
<mn>4</mn>
<mo>)</mo>
</mrow>
</mrow>
<mrow>
<mi>b</mi>
<mo>=</mo>
<mfrac>
<mrow>
<munderover>
<mo>&Sigma;</mo>
<mrow>
<mi>i</mi>
<mo>=</mo>
<mn>1</mn>
</mrow>
<msub>
<mi>w</mi>
<mi>n</mi>
</msub>
</munderover>
<msub>
<mi>y</mi>
<mi>i</mi>
</msub>
<mrow>
<mo>(</mo>
<msub>
<mi>z</mi>
<mi>i</mi>
</msub>
<mo>-</mo>
<msub>
<mi>z</mi>
<mi>c</mi>
</msub>
<mo>)</mo>
</mrow>
<mo>-</mo>
<munderover>
<mo>&Sigma;</mo>
<mrow>
<mi>i</mi>
<mo>=</mo>
<mn>1</mn>
</mrow>
<msub>
<mi>w</mi>
<mi>n</mi>
</msub>
</munderover>
<msub>
<mi>y</mi>
<mi>c</mi>
</msub>
<mrow>
<mo>(</mo>
<msub>
<mi>z</mi>
<mi>i</mi>
</msub>
<mo>-</mo>
<msub>
<mi>z</mi>
<mi>c</mi>
</msub>
<mo>)</mo>
</mrow>
</mrow>
<mrow>
<munderover>
<mo>&Sigma;</mo>
<mrow>
<mi>i</mi>
<mo>=</mo>
<mn>1</mn>
</mrow>
<msub>
<mi>w</mi>
<mi>n</mi>
</msub>
</munderover>
<mrow>
<mo>(</mo>
<msub>
<mi>z</mi>
<mi>i</mi>
</msub>
<mo>-</mo>
<msub>
<mi>z</mi>
<mi>c</mi>
</msub>
<mo>)</mo>
</mrow>
<mrow>
<mo>(</mo>
<msub>
<mi>z</mi>
<mi>i</mi>
</msub>
<mo>-</mo>
<msub>
<mi>z</mi>
<mi>c</mi>
</msub>
<mo>)</mo>
</mrow>
</mrow>
</mfrac>
<mo>-</mo>
<mo>-</mo>
<mo>-</mo>
<mrow>
<mo>(</mo>
<mn>5</mn>
<mo>)</mo>
</mrow>
</mrow>
Wherein, xi、yi、ziThe sampling point record of X-component, Y-component, Z component is represented respectively.
10. 3-component earthquake signal polarization vector analysis system according to claim 9, wherein, the polarization vector
Coordinate variable is：
<mrow>
<mfenced open = "{" close = "">
<mtable>
<mtr>
<mtd>
<mrow>
<msub>
<mi>p</mi>
<mi>x</mi>
</msub>
<mo>=</mo>
<mfrac>
<mi>a</mi>
<msqrt>
<mrow>
<msup>
<mi>a</mi>
<mn>2</mn>
</msup>
<mo>+</mo>
<msup>
<mi>b</mi>
<mn>2</mn>
</msup>
<mo>+</mo>
<mn>1</mn>
</mrow>
</msqrt>
</mfrac>
</mrow>
</mtd>
</mtr>
<mtr>
<mtd>
<mrow>
<msub>
<mi>p</mi>
<mi>y</mi>
</msub>
<mo>=</mo>
<mfrac>
<mi>b</mi>
<msqrt>
<mrow>
<msup>
<mi>a</mi>
<mn>2</mn>
</msup>
<mo>+</mo>
<msup>
<mi>b</mi>
<mn>2</mn>
</msup>
<mo>+</mo>
<mn>1</mn>
</mrow>
</msqrt>
</mfrac>
</mrow>
</mtd>
</mtr>
<mtr>
<mtd>
<mrow>
<msub>
<mi>p</mi>
<mi>z</mi>
</msub>
<mo>=</mo>
<mfrac>
<mn>1</mn>
<msqrt>
<mrow>
<msup>
<mi>a</mi>
<mn>2</mn>
</msup>
<mo>+</mo>
<msup>
<mi>b</mi>
<mn>2</mn>
</msup>
<mo>+</mo>
<mn>1</mn>
</mrow>
</msqrt>
</mfrac>
</mrow>
</mtd>
</mtr>
</mtable>
</mfenced>
<mo>-</mo>
<mo>-</mo>
<mo>-</mo>
<mrow>
<mo>(</mo>
<mn>6</mn>
<mo>)</mo>
</mrow>
</mrow>
Wherein, px、py、pzRepresent the coordinate variable of the polarization vector.
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Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102156296A (en) * | 2011-04-19 | 2011-08-17 | 中国石油大学(华东) | Elastic reverse time migration imaging method by combining seismic multi-component |
| US8456950B2 (en) * | 2010-07-30 | 2013-06-04 | Pgs Geophysical As | Method for wave decomposition using multi-component motion sensors |
| CN104122585A (en) * | 2014-08-08 | 2014-10-29 | 中国石油大学(华东) | Seismic forward modeling method based on elastic wave field vector decomposition and low-rank decomposition |
| CN104216005A (en) * | 2013-06-03 | 2014-12-17 | 中国石油化工股份有限公司 | Downhole microseismic three-component rotating method |
| US20150309197A1 (en) * | 2012-12-20 | 2015-10-29 | Pavel Dimitrov | Method and System for Geophysical Modeling of Subsurface Volumes Based on Label Propagation |
| CN105137486A (en) * | 2015-09-01 | 2015-12-09 | 中国科学院地质与地球物理研究所 | Elastic wave reverse-time migration imaging method and apparatus in anisotropic media |
-
2016
- 2016-09-27 CN CN201610855677.2A patent/CN107870358B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US8456950B2 (en) * | 2010-07-30 | 2013-06-04 | Pgs Geophysical As | Method for wave decomposition using multi-component motion sensors |
| CN102156296A (en) * | 2011-04-19 | 2011-08-17 | 中国石油大学(华东) | Elastic reverse time migration imaging method by combining seismic multi-component |
| US20150309197A1 (en) * | 2012-12-20 | 2015-10-29 | Pavel Dimitrov | Method and System for Geophysical Modeling of Subsurface Volumes Based on Label Propagation |
| CN104216005A (en) * | 2013-06-03 | 2014-12-17 | 中国石油化工股份有限公司 | Downhole microseismic three-component rotating method |
| CN104122585A (en) * | 2014-08-08 | 2014-10-29 | 中国石油大学(华东) | Seismic forward modeling method based on elastic wave field vector decomposition and low-rank decomposition |
| CN105137486A (en) * | 2015-09-01 | 2015-12-09 | 中国科学院地质与地球物理研究所 | Elastic wave reverse-time migration imaging method and apparatus in anisotropic media |
Non-Patent Citations (2)
| Title |
|---|
| 何惺华: "基于三分量的微地震震源反演方法与效果", 《石油地球物理勘探》 * |
| 刘宪彬等: "利用qP波慢度和偏振矢量计算弱各向异性介质参数", 《地震学报》 * |
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