CN107918155A - Inverse migration analogue data TEC time error correction method and system - Google Patents
Inverse migration analogue data TEC time error correction method and system Download PDFInfo
- Publication number
- CN107918155A CN107918155A CN201610884405.5A CN201610884405A CN107918155A CN 107918155 A CN107918155 A CN 107918155A CN 201610884405 A CN201610884405 A CN 201610884405A CN 107918155 A CN107918155 A CN 107918155A
- Authority
- CN
- China
- Prior art keywords
- msub
- mrow
- seismic wavelet
- error
- trough
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 238000013508 migration Methods 0.000 title claims abstract description 68
- 230000005012 migration Effects 0.000 title claims abstract description 68
- 238000012937 correction Methods 0.000 title claims abstract description 41
- 238000000034 method Methods 0.000 title claims abstract description 34
- 238000006467 substitution reaction Methods 0.000 claims abstract description 10
- 238000013075 data extraction Methods 0.000 claims abstract description 7
- 238000004088 simulation Methods 0.000 claims description 3
- 230000008901 benefit Effects 0.000 description 3
- 230000008859 change Effects 0.000 description 3
- 238000001914 filtration Methods 0.000 description 3
- 238000007596 consolidation process Methods 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 238000003384 imaging method Methods 0.000 description 2
- 238000005259 measurement Methods 0.000 description 2
- 230000006978 adaptation Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000010606 normalization Methods 0.000 description 1
- 238000012545 processing Methods 0.000 description 1
- 238000011160 research Methods 0.000 description 1
Classifications
-
- 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. for interpretation or for event detection
- 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
Landscapes
- Engineering & Computer Science (AREA)
- Remote Sensing (AREA)
- Physics & Mathematics (AREA)
- Life Sciences & Earth Sciences (AREA)
- Acoustics & Sound (AREA)
- Environmental & Geological Engineering (AREA)
- Geology (AREA)
- General Life Sciences & Earth Sciences (AREA)
- General Physics & Mathematics (AREA)
- Geophysics (AREA)
- Geophysics And Detection Of Objects (AREA)
Abstract
Disclose a kind of inverse migration analogue data TEC time error correction method and system.This method includes：Based on observation data extraction seismic wavelet waveform feature data, seismic wavelet waveform characteristic function is built；Based on the seismic wavelet waveform characteristic function, the matching error between seismic wavelet is obtained；Based on the matching error between the seismic wavelet and editing distance measure, the accumulated error between seismic wavelet is obtained；Based on the accumulated error between the seismic wavelet, error back substitution is carried out, obtains time shift amount sequence；And correct corresponding inverse migration analogue data using the time shift amount sequence.The present invention realizes the TEC time error correction of inverse migration analogue data by seismic wavelet waveform characteristic function and time shift amount sequence.
Description
Technical field
The present invention relates to seismic prospecting data digital processing technology field, and number is simulated more particularly, to a kind of inverse migration
According to TEC time error correction method and system.
Background technology
It is used to when real data is handled carry out with inverse migration analogue data, it is necessary to observe data in least-squares migration technology
Matching.But due to that there are velocity error, the especially large offseting distance analogue data presence of inverse migration analogue data can be caused tighter
Weight the data time difference problem caused by velocity error so that seriously affect least-squares migration imaging method convergence and
Imaging precision.And in actual treatment, velocity error is inevitably present, in this context, it is necessary to which research is to inverse migration
The method that analogue data is corrected with the observation data time difference.The matched method of routine data includes the filter of time-domain single track wiener
The methods of ripple, the filtering of frequency domain least energy, prediction error filtering, pattern match filtering.These methods are chiefly used in multiple wave pressure
System etc., its principle are that the data to be matched of prediction such as multiple wave data and initial data are carried out the time difference, phase and energy
Matching completely, can be by the effect of Multiple attenuation so as to reach.
But only TEC time error correction is needed to match between inverse migration analogue data and observation data, it is also necessary to retain capacity volume variance use
It is imaged and updates in iteration, therefore above-mentioned data matching method does not apply to.Therefore, it is necessary to when developing a kind of inverse migration analogue data
Difference correcting 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 inverse migration analogue data TEC time error correction method and system, it can pass through seismic wavelet ripple
Shape characteristic function and time shift amount sequence, realize the TEC time error correction of inverse migration analogue data.
According to an aspect of the invention, it is proposed that a kind of inverse migration analogue data TEC time error correction method.The described method includes：
Step 1：Based on observation data extraction seismic wavelet waveform feature data, seismic wavelet waveform characteristic function is built；Step 2：Base
In the seismic wavelet waveform characteristic function, the matching error between seismic wavelet is obtained；Step 3：Based on the seismic wavelet
Between matching error and editing distance measure, obtain seismic wavelet between accumulated error；Step 4：Based on described
The accumulated error between wavelet is shaken, carries out error back substitution, obtains time shift amount sequence；And step 5：Utilize the time shift amount sequence
Correct corresponding inverse migration analogue data.
Preferably, the seismic wavelet waveform characteristic function is：
Wherein, wavelet is the seismic wavelet waveform characteristic function, and j=1 ..., N, N are observation data and inverse migration
The length of analogue data sequence, pjRepresent the extreme value place of the seismic wavelet wave crest or trough at j, wjRepresent the seismic wavelet at j
The ripple of wave crest or trough is wide, ajRepresent the extreme value of the seismic wavelet wave crest or trough at j, vjRepresent j at seismic wavelet wave crest or
The waveform variation tendency of trough.
Preferably, the matching error between the seismic wavelet is：
Wherein, matching errors of the e (j, l) between the seismic wavelet, ω1、ω2、ω3、ω4Respectively corresponding power
Coefficient, l is the window ranges of longitudinal Dynamic Matching, i.e., as with reference to seismic wavelet, to be carried out describedly in window ranges l at j
The comparison and matching of wavelet waveforms feature are shaken, l ∈ [- win, win], win are that longitudinal time shift amount estimates parameter, pmaxTo be described
Shake the maximum extreme value place of wavelet wave crest or trough, wmaxTo show that the maximum ripple of the seismic wavelet wave crest or trough is wide, amaxFor
The maximum extreme value of the seismic wavelet wave crest or trough, vmaxBecome for the change of the maximum waveform of the seismic wavelet wave crest or trough
Gesture.
Preferably, the accumulated error between the seismic wavelet is：
D [j, l]=e [0, l] as j=0,
Wherein, accumulated errors of the d [j, l] between the seismic wavelet, ε are threshold parameter.
Preferably, the time shift amount sequence is：
U [j]=argmind [N-1, l] as j=N-1,
U [j]=argmind [j, l] is as j ∈ [N-2,0].
According to another aspect of the invention, it is proposed that a kind of inverse migration analogue data TEC time error correction system, the system bag
Include：Seismic wavelet waveform characteristic function unit is built, for based on observation data extraction seismic wavelet waveform feature data, structure
Seismic wavelet waveform characteristic function；Match error unit is obtained, for based on the seismic wavelet waveform characteristic function, obtaining ground
Shake the matching error between wavelet；Accumulated error unit is obtained, for based on the matching error and volume between the seismic wavelet
Distance metric method is collected, obtains the accumulated error between seismic wavelet；Time shift amount sequence units are obtained, for based on the earthquake
Accumulated error between wavelet, carries out error back substitution, obtains time shift amount sequence；And TEC time error correction unit, for described in utilization
Time shift amount sequence corrects corresponding inverse migration analogue data.
Preferably, the seismic wavelet waveform characteristic function is：
Wherein, wavelet is the seismic wavelet waveform characteristic function, and j=1 ..., N, N are observation data and inverse migration
The length of analogue data sequence, pjRepresent the extreme value place of the seismic wavelet wave crest or trough at j, wjRepresent the seismic wavelet at j
The ripple of wave crest or trough is wide, ajRepresent the extreme value of the seismic wavelet wave crest or trough at j, vjRepresent j at seismic wavelet wave crest or
The waveform variation tendency of trough.
Preferably, wherein, the matching error between the seismic wavelet is：
Wherein, matching errors of the e (j, l) between the seismic wavelet, ω1、ω2、ω3、ω4Respectively corresponding power
Coefficient, l is the window ranges of longitudinal Dynamic Matching, i.e., as with reference to seismic wavelet, to be carried out describedly in window ranges l at j
The comparison and matching of wavelet waveforms feature are shaken, l ∈ [- win, win], win are that longitudinal time shift amount estimates parameter, pmaxTo be described
Shake the maximum extreme value place of wavelet wave crest or trough, wmaxTo show that the maximum ripple of the seismic wavelet wave crest or trough is wide, amaxFor
The maximum extreme value of the seismic wavelet wave crest or trough, vmaxBecome for the change of the maximum waveform of the seismic wavelet wave crest or trough
Gesture.
Preferably, wherein, the accumulated error between the seismic wavelet is：
D [j, l]=e [0, l] as j=0,
Wherein, accumulated errors of the d [j, l] between the seismic wavelet, ε are threshold parameter.
Preferably, wherein, the time shift amount sequence is：
U [j]=argmind [N-1, l] as j=N-1,
U [j]=argmind [j, l] is as j ∈ [N-2,0].
The time shift amount sequence that the present invention is obtained based on seismic wavelet waveform characteristic function with dynamic time consolidation (DTW) method
The TEC time error correction for carrying out inverse migration analogue data with observing data is combined, according to the similitude of earthquake signal subspace ripple wave character
The time difference of two sets of data is analyzed, then carries out TEC time error correction, so as to fulfill the amendment to inverse migration analogue data.
Methods and apparatus of the present invention have the advantages that other characteristics 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 attached 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 inverse migration analogue data TEC time error correction method according to the present invention.
Fig. 2 a, Fig. 2 b, Fig. 2 c and Fig. 2 d respectively illustrate an application example according to the present invention there are speed mistake
The inverse migration analogue data figure that is generated in the case of difference, observation datagram, after carrying out reverse-biased shift correction using the method for the present invention
Inverse migration analogue data figure and corresponding time shift amount sequence data figure.
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 attached 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 are of the invention more thorough and complete in order to make, 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 inverse migration analogue data TEC time error correction method according to the present invention.
In this embodiment, inverse migration analogue data TEC time error correction method according to the present invention includes：Step 1：It is based on
Data extraction seismic wavelet waveform feature data is observed, builds seismic wavelet waveform characteristic function；Step 2：Based on the earthquake
Wavelet waveforms characteristic function, obtains the matching error between seismic wavelet；Step 3：Based on the matching between the seismic wavelet
Error and editing distance measure, obtain the accumulated error between seismic wavelet；Step 4：Based between the seismic wavelet
Accumulated error, carry out error back substitution, obtain time shift amount sequence；And step 5：Corrected using the time shift amount sequence corresponding
Inverse migration analogue data.
The embodiment by seismic wavelet waveform characteristic function and time shift amount sequence, realize inverse migration analogue data when
Difference correction.
Least-squares migration inverse migration analogue data is measured with observation data arrangement error with editing distance, its expression formula
For：
Wherein, adaptation function is m (xi,yj)=H (ε-f (xi,yj)), xiWith yiObservation data and inverse migration are represented respectively
Analogue data, and f (xi,yj)=(xi-yj)2, i=1 ..., N, f (xi,yi) it is local match error function, N is observation data
With the length of inverse migration analogue data sequence, H is unit-step function, and threshold parameter ε, ε ∈ [0, ∞), select appropriate threshold
Value parameter ε, controls matched similarity degree between the sample of two sequences.
The function expression of Euclidean distance is E [i, l]=(x [i]-y [i+l])2, wherein, x [i] is to observe data, y [i]
It is inverse migration analogue data, l=u [i] is time shift amount data sequence to be asked.It is different from the Euclidean distance measurement used in routine,
The matching of partial points has also been carried out during calculating accumulated error using editing distance, has made error function small by threshold parameter
First matched in the partial points of threshold value, equivalent to adding some control points in the sequence, the Dynamic Matching carried out on this basis
Efficiency can be lifted further, can accurately be matched between the point point that can also ensure to meet condition.
Seismic data is being arranged to form by a lot of seismic wavelet, and present invention introduces seismic wavelet wave character
Function, is combined with editing distance measurement to carry out the Dynamic Matching of seismic wavelet, so as to reach inverse migration analogue data and sight
Survey lineups matching and the purpose of TEC time error correction of data.
The following detailed description of the specific steps of inverse migration analogue data TEC time error correction method according to the present invention, including：
Step 1：Based on observation data extraction seismic wavelet waveform feature data, seismic wavelet waveform characteristic function is built；
In one example, the seismic wavelet waveform characteristic function can be：
Wherein, wavelet is the seismic wavelet waveform characteristic function, and j=1 ..., N, N are observation data and inverse migration
The length of analogue data sequence, pjRepresent the extreme value place of the seismic wavelet wave crest or trough at j, wjRepresent the seismic wavelet at j
The ripple of wave crest or trough is wide, ajRepresent the extreme value of the seismic wavelet wave crest or trough at j, vjRepresent j at seismic wavelet wave crest or
The waveform variation tendency of trough.
Step 2：Based on the seismic wavelet waveform characteristic function, the matching error between seismic wavelet is obtained；
In one example, the matching error between the seismic wavelet can be：
Wherein, matching errors of the e (j, l) between the seismic wavelet, ω1、ω2、ω3、ω4Respectively corresponding power
Coefficient, l is the window ranges of longitudinal Dynamic Matching, i.e., as with reference to seismic wavelet, to be carried out describedly in window ranges l at j
Shake the comparison and matching of wavelet waveforms feature.L ∈ [- win, win], win are that longitudinal time shift amount estimates parameter, it is according to different
Data characteristics makes choice, generally higher than the maximum spacing of same seismic channel adjacent wavelet, pmaxFor the seismic wavelet wave crest or
The maximum extreme value place of trough, wmaxTo show that the maximum ripple of the seismic wavelet wave crest or trough is wide, amaxFor the seismic wavelet
The maximum extreme value of wave crest or trough, vmaxFor the maximum waveform variation tendency of the seismic wavelet wave crest or trough.
It is without considering the matching error between the seismic wavelet of seismic wavelet normalization situation
Wherein, wherein, ω1、ω2、ω3、ω4Respectively corresponding weight coefficient, l are the window ranges of longitudinal Dynamic Matching,
I.e., as reference wavelet, the comparison and matching of seismic wavelet wave character are carried out in window ranges l at j.
But since the order of magnitude of each earthquake wavelet waveforms characteristic attribute is different, so it is normalized,
The matching error obtained between the seismic wavelet is：
Wherein, matching errors of the e (j, l) between the seismic wavelet, ω1、ω2、ω3、ω4Respectively corresponding power
Coefficient, l is the window ranges of longitudinal Dynamic Matching, i.e., as with reference to seismic wavelet, to be carried out describedly in window ranges l at j
Shake the comparison and matching of wavelet waveforms feature.L ∈ [- win, win], win are that longitudinal time shift amount estimates parameter, it is according to different
Data characteristics makes choice, generally higher than the maximum spacing of same seismic channel adjacent wavelet, pmaxFor the seismic wavelet wave crest or
The maximum extreme value place of trough, wmaxTo show that the maximum ripple of the seismic wavelet wave crest or trough is wide, amaxFor the seismic wavelet
The maximum extreme value of wave crest or trough, vmaxFor the maximum waveform variation tendency of the seismic wavelet wave crest or trough.
Step 3：Based on the matching error between the seismic wavelet and editing distance measure, obtain seismic wavelet it
Between accumulated error；
In one example, the accumulated error between the seismic wavelet is：
D [j, l]=e [0, l] as j=0,
Wherein, accumulated errors of the d [j, l] between the seismic wavelet, ε are threshold parameter.
When the error between two seismic wavelets is less than threshold epsilon, it is believed that two seismic wavelets are in same same phase
On axis, make its accumulated error minimum, it is possible to which the two seismic wavelets are first matched.Sequence can be accelerated by introducing editing distance
Matched speed is arranged, improves accuracy.The ε important roles of threshold value, when the seismic data signal-to-noise ratio of input is low, seismic wavelet is special
During sign change unobvious, it can suitably reduce ε values.For each reference position seismic wavelet, all there are a shortest path to look for
The seismic wavelet approached the most with its seismic wavelet wave character on to another road, therefore, here in certain dynamic range
Matching distance stores, in order to follow-up error back substitution.
Step 4：Based on the accumulated error between the seismic wavelet, error back substitution is carried out, obtains time shift amount sequence；
In one example, the time shift amount sequence is：
U [j]=argmind [N-1, l] as j=N-1,
U [j]=argmind [j, l] is as j ∈ [N-2,0].
The sequence of the time shift amount, may be such that two sequences match after error and reach minimum, find shortest path.
Step 5：Corresponding inverse migration analogue data is corrected using the time shift amount sequence.
The method of the present invention realizes that its principle is the seismic wavelet waveform according to inverse migration analogue data and observation data by road
Characteristic similarity is matched and TEC time error correction, meets inverse migration data and observation data time difference school during least-squares migration
It is positive to need.
For ease of understanding the scheme of embodiment of the present invention and its effect, a concrete application example is given below.Ability
Field technique personnel should be understood that the example only for the purposes of understanding the present invention, its any detail is not intended in any way
The limitation present invention.
Application example
The present invention provides a kind of inverse migration analogue data TEC time error correction method, including：Step 1：Carried based on observation data
Seismic wavelet waveform feature data is taken, builds seismic wavelet waveform characteristic function；Step 2：It is special based on the seismic wavelet waveform
Function is levied, obtains the matching error between seismic wavelet；Step 3：Based on the matching error between the seismic wavelet and editor
Distance metric method, obtains the accumulated error between seismic wavelet；Step 4：Based on the accumulated error between the seismic wavelet,
Error back substitution is carried out, obtains time shift amount sequence；And step 5：Corresponding inverse migration simulation is corrected using the time shift amount sequence
Data.
Fig. 2 a, Fig. 2 b, Fig. 2 c and Fig. 2 d respectively illustrate an application example according to the present invention there are speed mistake
The inverse migration analogue data figure that is generated in the case of difference, observation datagram, after carrying out reverse-biased shift correction using the method for the present invention
Inverse migration analogue data figure and corresponding time shift amount sequence data figure.
Inverse migration analogue data TEC time error correction method of the present invention is tested using a set of model data.Such as Fig. 2 a
Shown in Fig. 2 b, Fig. 2 c and Fig. 2 d, due to the presence of velocity error, cause to produce between inverse migration analogue data and observation data
The raw larger time difference；Because since the time difference that velocity error is brought has been substantially achieved correction, pass through time shift amount sequence calibration
The time difference between inverse migration analogue data and observation data afterwards is smaller.
The time shift amount sequence that the present invention is obtained based on seismic wavelet waveform characteristic function with dynamic time consolidation (DTW) method
The TEC time error correction for carrying out inverse migration analogue data with observing data is combined, according to the similitude of earthquake signal subspace ripple wave character
The time difference of two sets of data is analyzed, then carries out TEC time error correction, so as to fulfill the amendment to inverse migration analogue data.
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 inverse migration analogue data TEC time error correction system, the system can
With including：Seismic wavelet waveform characteristic function unit is built, for extracting seismic wavelet waveform feature data based on observation data,
Build seismic wavelet waveform characteristic function；Match error unit is obtained, for based on the seismic wavelet waveform characteristic function, obtaining
Take the matching error between seismic wavelet；Accumulated error unit is obtained, for based on the matching error between the seismic wavelet
With editing distance measure, the accumulated error between seismic wavelet is obtained；Time shift amount sequence units are obtained, for based on described
Accumulated error between seismic wavelet, carries out error back substitution, obtains time shift amount sequence；And TEC time error correction unit, for utilizing
The time shift amount sequence corrects corresponding inverse migration analogue data.
The embodiment by seismic wavelet waveform characteristic function and time shift amount sequence, realize inverse migration analogue data when
Difference correction.
The embodiments of the present invention are described above, 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 inverse migration analogue data TEC time error correction method, including：
Step 1：Based on observation data extraction seismic wavelet waveform feature data, seismic wavelet waveform characteristic function is built；
Step 2：Based on the seismic wavelet waveform characteristic function, the matching error between seismic wavelet is obtained；
Step 3：Based on the matching error between the seismic wavelet and editing distance measure, obtain between seismic wavelet
Accumulated error；
Step 4：Based on the accumulated error between the seismic wavelet, error back substitution is carried out, obtains time shift amount sequence；
Step 5：Corresponding inverse migration analogue data is corrected using the time shift amount sequence.
2. inverse migration analogue data TEC time error correction method according to claim 1, wherein, the seismic wavelet wave character
Function is：
<mrow>
<mi>w</mi>
<mi>a</mi>
<mi>v</mi>
<mi>e</mi>
<mi>l</mi>
<mi>e</mi>
<mi>t</mi>
<mrow>
<mo>(</mo>
<mi>j</mi>
<mo>)</mo>
</mrow>
<mo>=</mo>
<mfenced open = "{" close = "">
<mtable>
<mtr>
<mtd>
<msub>
<mi>p</mi>
<mi>j</mi>
</msub>
</mtd>
</mtr>
<mtr>
<mtd>
<msub>
<mi>w</mi>
<mi>j</mi>
</msub>
</mtd>
</mtr>
<mtr>
<mtd>
<msub>
<mi>a</mi>
<mi>j</mi>
</msub>
</mtd>
</mtr>
<mtr>
<mtd>
<msub>
<mi>v</mi>
<mi>j</mi>
</msub>
</mtd>
</mtr>
</mtable>
</mfenced>
<mo>,</mo>
<mi>j</mi>
<mo><</mo>
<mi>N</mi>
</mrow>
Wherein, wavelet is the seismic wavelet waveform characteristic function, and j=1 ..., N, N are observation data and inverse migration simulation
The length of data sequence, pjRepresent the extreme value place of the seismic wavelet wave crest or trough at j, wjRepresent the seismic wavelet wave crest at j
Or the ripple of trough is wide, ajRepresent the extreme value of the seismic wavelet wave crest or trough at j, vjRepresent the seismic wavelet wave crest or trough at j
Waveform variation tendency.
3. inverse migration analogue data TEC time error correction method according to claim 2, wherein, between the seismic wavelet
It is with error：
<mrow>
<mi>e</mi>
<mrow>
<mo>(</mo>
<mi>j</mi>
<mo>,</mo>
<mi>l</mi>
<mo>)</mo>
</mrow>
<mo>=</mo>
<msub>
<mi>&omega;</mi>
<mn>1</mn>
</msub>
<mfrac>
<mrow>
<mo>|</mo>
<msub>
<mi>p</mi>
<mi>j</mi>
</msub>
<mo>-</mo>
<msub>
<mi>p</mi>
<mrow>
<mi>j</mi>
<mo>+</mo>
<mi>l</mi>
</mrow>
</msub>
<mo>|</mo>
</mrow>
<msub>
<mi>p</mi>
<mrow>
<mi>m</mi>
<mi>a</mi>
<mi>x</mi>
</mrow>
</msub>
</mfrac>
<mo>+</mo>
<msub>
<mi>&omega;</mi>
<mn>2</mn>
</msub>
<mfrac>
<mrow>
<mo>|</mo>
<msub>
<mi>w</mi>
<mi>j</mi>
</msub>
<mo>-</mo>
<msub>
<mi>w</mi>
<mrow>
<mi>j</mi>
<mo>+</mo>
<mi>l</mi>
</mrow>
</msub>
<mo>|</mo>
</mrow>
<msub>
<mi>w</mi>
<mrow>
<mi>m</mi>
<mi>a</mi>
<mi>x</mi>
</mrow>
</msub>
</mfrac>
<mo>+</mo>
<msub>
<mi>&omega;</mi>
<mn>3</mn>
</msub>
<mfrac>
<mrow>
<mo>|</mo>
<msub>
<mi>a</mi>
<mi>j</mi>
</msub>
<mo>-</mo>
<msub>
<mi>a</mi>
<mrow>
<mi>j</mi>
<mo>+</mo>
<mi>l</mi>
</mrow>
</msub>
<mo>|</mo>
</mrow>
<msub>
<mi>a</mi>
<mi>max</mi>
</msub>
</mfrac>
<mo>+</mo>
<msub>
<mi>&omega;</mi>
<mn>4</mn>
</msub>
<mfrac>
<mrow>
<mo>|</mo>
<msub>
<mi>v</mi>
<mi>j</mi>
</msub>
<mo>-</mo>
<msub>
<mi>v</mi>
<mrow>
<mi>j</mi>
<mo>+</mo>
<mi>l</mi>
</mrow>
</msub>
<mo>|</mo>
</mrow>
<msub>
<mi>v</mi>
<mrow>
<mi>m</mi>
<mi>a</mi>
<mi>x</mi>
</mrow>
</msub>
</mfrac>
</mrow>
Wherein, matching errors of the e (j, l) between the seismic wavelet, ω1、ω2、ω3、ω4Respectively corresponding weight coefficient, l
For the window ranges of longitudinal Dynamic Matching, i.e., as with reference to seismic wavelet, the seismic wavelet is carried out in window ranges l at j
The comparison of wave character and matching, l ∈ [- win, win], win are that longitudinal time shift amount estimates parameter, pmaxFor the seismic wavelet
The maximum extreme value place of wave crest or trough, wmaxTo show that the maximum ripple of the seismic wavelet wave crest or trough is wide, amaxTo be described
Shake the maximum extreme value of wavelet wave crest or trough, vmaxFor the maximum waveform variation tendency of the seismic wavelet wave crest or trough.
4. inverse migration analogue data TEC time error correction method according to claim 3, wherein, it is tired between the seismic wavelet
Accumulating error is：
D [j, l]=e [0, l] as j=0,
Wherein, accumulated errors of the d [j, l] between the seismic wavelet, ε are threshold parameter.
5. inverse migration analogue data TEC time error correction method according to claim 4, wherein, the time shift amount sequence is：
U [j]=argmind [N-1, l] as j=N-1,
U [j]=argmind [j, l] is as j ∈ [N-2,0].
6. a kind of inverse migration analogue data TEC time error correction system, including：
Seismic wavelet waveform characteristic function unit is built, for based on observation data extraction seismic wavelet waveform feature data, structure
Build seismic wavelet waveform characteristic function；
Match error unit is obtained, for based on the seismic wavelet waveform characteristic function, obtaining the matching between seismic wavelet
Error；
Accumulated error unit is obtained, for based on the matching error between the seismic wavelet and editing distance measure, obtaining
Take the accumulated error between seismic wavelet；
Time shift amount sequence units are obtained, for based on the accumulated error between the seismic wavelet, carrying out error back substitution, during acquisition
Shifting amount sequence；
TEC time error correction unit, for correcting corresponding inverse migration analogue data using the time shift amount sequence.
7. inverse migration analogue data TEC time error correction system according to claim 6, wherein, the seismic wavelet wave character
Function is：
<mrow>
<mi>w</mi>
<mi>a</mi>
<mi>v</mi>
<mi>e</mi>
<mi>l</mi>
<mi>e</mi>
<mi>t</mi>
<mrow>
<mo>(</mo>
<mi>j</mi>
<mo>)</mo>
</mrow>
<mo>=</mo>
<mfenced open = "{" close = "">
<mtable>
<mtr>
<mtd>
<msub>
<mi>p</mi>
<mi>j</mi>
</msub>
</mtd>
</mtr>
<mtr>
<mtd>
<msub>
<mi>w</mi>
<mi>j</mi>
</msub>
</mtd>
</mtr>
<mtr>
<mtd>
<msub>
<mi>a</mi>
<mi>j</mi>
</msub>
</mtd>
</mtr>
<mtr>
<mtd>
<msub>
<mi>v</mi>
<mi>j</mi>
</msub>
</mtd>
</mtr>
</mtable>
</mfenced>
<mo>,</mo>
<mi>j</mi>
<mo><</mo>
<mi>N</mi>
</mrow>
Wherein, wavelet is the seismic wavelet waveform characteristic function, and j=1 ..., N, N are observation data and inverse migration simulation
The length of data sequence, pjRepresent the extreme value place of the seismic wavelet wave crest or trough at j, wjRepresent the seismic wavelet wave crest at j
Or the ripple of trough is wide, ajRepresent the extreme value of the seismic wavelet wave crest or trough at j, vjRepresent the seismic wavelet wave crest or trough at j
Waveform variation tendency.
8. inverse migration analogue data TEC time error correction system according to claim 7, wherein, between the seismic wavelet
It is with error：
<mrow>
<mi>e</mi>
<mrow>
<mo>(</mo>
<mi>j</mi>
<mo>,</mo>
<mi>l</mi>
<mo>)</mo>
</mrow>
<mo>=</mo>
<msub>
<mi>&omega;</mi>
<mn>1</mn>
</msub>
<mfrac>
<mrow>
<mo>|</mo>
<msub>
<mi>p</mi>
<mi>j</mi>
</msub>
<mo>-</mo>
<msub>
<mi>p</mi>
<mrow>
<mi>j</mi>
<mo>+</mo>
<mi>l</mi>
</mrow>
</msub>
<mo>|</mo>
</mrow>
<msub>
<mi>p</mi>
<mrow>
<mi>m</mi>
<mi>a</mi>
<mi>x</mi>
</mrow>
</msub>
</mfrac>
<mo>+</mo>
<msub>
<mi>&omega;</mi>
<mn>2</mn>
</msub>
<mfrac>
<mrow>
<mo>|</mo>
<msub>
<mi>w</mi>
<mi>j</mi>
</msub>
<mo>-</mo>
<msub>
<mi>w</mi>
<mrow>
<mi>j</mi>
<mo>+</mo>
<mi>l</mi>
</mrow>
</msub>
<mo>|</mo>
</mrow>
<msub>
<mi>w</mi>
<mrow>
<mi>m</mi>
<mi>a</mi>
<mi>x</mi>
</mrow>
</msub>
</mfrac>
<mo>+</mo>
<msub>
<mi>&omega;</mi>
<mn>3</mn>
</msub>
<mfrac>
<mrow>
<mo>|</mo>
<msub>
<mi>a</mi>
<mi>j</mi>
</msub>
<mo>-</mo>
<msub>
<mi>a</mi>
<mrow>
<mi>j</mi>
<mo>+</mo>
<mi>l</mi>
</mrow>
</msub>
<mo>|</mo>
</mrow>
<msub>
<mi>a</mi>
<mi>max</mi>
</msub>
</mfrac>
<mo>+</mo>
<msub>
<mi>&omega;</mi>
<mn>4</mn>
</msub>
<mfrac>
<mrow>
<mo>|</mo>
<msub>
<mi>v</mi>
<mi>j</mi>
</msub>
<mo>-</mo>
<msub>
<mi>v</mi>
<mrow>
<mi>j</mi>
<mo>+</mo>
<mi>l</mi>
</mrow>
</msub>
<mo>|</mo>
</mrow>
<msub>
<mi>v</mi>
<mrow>
<mi>m</mi>
<mi>a</mi>
<mi>x</mi>
</mrow>
</msub>
</mfrac>
</mrow>
Wherein, matching errors of the e (j, l) between the seismic wavelet, ω1、ω2、ω3、ω4Respectively corresponding weight coefficient, l
For the window ranges of longitudinal Dynamic Matching, i.e., as with reference to seismic wavelet, the seismic wavelet is carried out in window ranges l at j
The comparison of wave character and matching, l ∈ [- win, win], win are that longitudinal time shift amount estimates parameter, pmaxFor the seismic wavelet
The maximum extreme value place of wave crest or trough, wmaxTo show that the maximum ripple of the seismic wavelet wave crest or trough is wide, amaxTo be described
Shake the maximum extreme value of wavelet wave crest or trough, vmaxFor the maximum waveform variation tendency of the seismic wavelet wave crest or trough.
9. inverse migration analogue data TEC time error correction system according to claim 8, wherein, it is tired between the seismic wavelet
Accumulating error is：
D [j, l]=e [0, l] as j=0,
Wherein, accumulated errors of the d [j, l] between the seismic wavelet, ε are threshold parameter.
10. inverse migration analogue data TEC time error correction system according to claim 9, wherein, the time shift amount sequence is：
U [j]=argmind [N-1, l] as j=N-1,
U [j]=argmind [j, l] is as j ∈ [N-2,0].
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610884405.5A CN107918155B (en) | 2016-10-10 | 2016-10-10 | Inverse migration analogue data TEC time error correction method and system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610884405.5A CN107918155B (en) | 2016-10-10 | 2016-10-10 | Inverse migration analogue data TEC time error correction method and system |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN107918155A true CN107918155A (en) | 2018-04-17 |
| CN107918155B CN107918155B (en) | 2019-11-12 |
Family
ID=61891856
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201610884405.5A Active CN107918155B (en) | 2016-10-10 | 2016-10-10 | Inverse migration analogue data TEC time error correction method and system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN107918155B (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112946744A (en) * | 2019-12-11 | 2021-06-11 | 中国石油天然气集团有限公司 | Least square offset imaging method and system based on dynamic time difference warping |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101021567A (en) * | 2007-02-07 | 2007-08-22 | 徐兆涛 | Seismic data processing shot gather wave equation prestack depth deviation parallel calculating method |
| US20130242693A1 (en) * | 2012-03-13 | 2013-09-19 | Seoul National University R&Db Foundation | Seismic imaging system using a reverse time migration algorithm |
| CN103576192A (en) * | 2012-08-02 | 2014-02-12 | 中国石油天然气集团公司 | Method for determining seismic wavelets |
| CN104391323A (en) * | 2014-11-21 | 2015-03-04 | 中国石油大学(华东) | Method for inverting low- and medium-wave number components in velocity field through reflection wave information |
| CN105182420A (en) * | 2015-10-13 | 2015-12-23 | 中国石油天然气集团公司 | Dynamic-matching dynamic-correction method |
| CN105334532A (en) * | 2015-10-21 | 2016-02-17 | 中国石油化工股份有限公司 | Seismic wavelet estimation method |
-
2016
- 2016-10-10 CN CN201610884405.5A patent/CN107918155B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101021567A (en) * | 2007-02-07 | 2007-08-22 | 徐兆涛 | Seismic data processing shot gather wave equation prestack depth deviation parallel calculating method |
| US20130242693A1 (en) * | 2012-03-13 | 2013-09-19 | Seoul National University R&Db Foundation | Seismic imaging system using a reverse time migration algorithm |
| CN103576192A (en) * | 2012-08-02 | 2014-02-12 | 中国石油天然气集团公司 | Method for determining seismic wavelets |
| CN104391323A (en) * | 2014-11-21 | 2015-03-04 | 中国石油大学(华东) | Method for inverting low- and medium-wave number components in velocity field through reflection wave information |
| CN105182420A (en) * | 2015-10-13 | 2015-12-23 | 中国石油天然气集团公司 | Dynamic-matching dynamic-correction method |
| CN105334532A (en) * | 2015-10-21 | 2016-02-17 | 中国石油化工股份有限公司 | Seismic wavelet estimation method |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112946744A (en) * | 2019-12-11 | 2021-06-11 | 中国石油天然气集团有限公司 | Least square offset imaging method and system based on dynamic time difference warping |
Also Published As
| Publication number | Publication date |
|---|---|
| CN107918155B (en) | 2019-11-12 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| EP3324216B1 (en) | Method and device for processing seismic data | |
| CN111487046B (en) | Fault diagnosis method for circuit breaker voiceprint and vibration entropy feature fusion | |
| CN107505654B (en) | Full waveform inversion method based on earthquake record integral | |
| CN107272066A (en) | A kind of noisy seismic signal first-arrival traveltime pick-up method and device | |
| CN103499345B (en) | A kind of Fiber Optic Gyroscope Temperature Drift compensation method based on wavelet analysis and BP neural network | |
| CN109212597A (en) | Microquake sources automatic positioning method based on deepness belief network and scanning superposition | |
| CN109598027B (en) | Method for correcting structural model parameters based on frequency response function | |
| CN104793253A (en) | Airborne electromagnetic data denoising method based on mathematical morphology | |
| CN103941254A (en) | Soil physical property classification recognition method and device based on geological radar | |
| CN107179552B (en) | A kind of wavelet stretching correction processing method based on waveform Dynamic Matching | |
| CN105572572A (en) | WKNN-LSSVM-based analog circuit fault diagnosis method | |
| CN110071706A (en) | Core pulse signal rising edge restoration methods, device and digitlization nuclear instrument | |
| CN109409442A (en) | Convolutional neural networks model selection method in transfer learning | |
| CN111562597A (en) | Beidou satellite navigation interference source identification method based on BP neural network | |
| CN115169422B (en) | Magnetotelluric signal denoising method and system based on stack self-encoder | |
| CN112487604A (en) | Long-time nonlinear drift compensation method for output data of marine gravimeter | |
| CN102928713B (en) | A kind of background noise measuring method of magnetic field antenna | |
| CN107918155B (en) | Inverse migration analogue data TEC time error correction method and system | |
| CN110057918A (en) | Damage of composite materials quantitative identification method and system under strong noise background | |
| CN106291293A (en) | A kind of Partial discharge signal self-adaptive solution method based on spectrum kurtosis with S-transformation | |
| CN109993727A (en) | A kind of method for detecting change of remote sensing image based on deep learning | |
| CN104765069B (en) | A kind of method for suppressing the adjacent big gun interference of simultaneous shot collection | |
| CN102868403B (en) | A kind of test macro testing analog to digital converter salient features index | |
| CN104977602A (en) | Control method and apparatus for earthquake data acquisition construction | |
| CN109856672B (en) | Transient wave packet extracting method, storage medium and terminal based on depth wave-number spectrum |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |