CN110045417B - First arrival wave automatic picking method based on two-stage optimization - Google Patents
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Abstract
The invention discloses a first-arrival wave automatic pickup method based on two-stage optimization, which comprises the steps of carrying out normalization processing on the energy value of each seismic channel in a common shot point channel set; sliding on each seismic channel by adopting a vertical sliding window based on a template range band detection algorithm, and performing correlation calculation with the template to obtain a top sample point subscript of a first arrival interval of the seismic channel; acquiring a first-arrival range band composed of first-arrival intervals of all seismic channels on a common shot gather according to the subscript of a sample point at the top end of the first-arrival interval of each seismic channel and the size of a vertical sliding window; within the first-arrival range band, the first-arrival wave position of each seismic trace is calculated using an improved energy ratio first-arrival pick-up algorithm.
Description
Technical Field
The invention relates to the technical field of data processing in geophysical exploration, in particular to a first-motion wave automatic pickup method based on two-stage optimization.
Background
Currently, there are many well known seismic data processing systems, such as Promax, CGG, Focus, and Grisys. They all involve the critical step of automatic first arrival picking. The results of each software vary greatly, subject to data quality and parameter settings. Therefore, a more accurate, efficient and stable algorithm is needed to solve this problem.
Many researchers have studied the first arrival wave automatic pickup method. The Coppens method processes data using an energy ratio within two windows. Al-Ghamdi improves this method by using adaptive thresholds. The multi-window algorithm uses three moving windows. In addition, it uses the average of the absolute amplitudes in each window to distinguish the signal from noise.
Sabdione and Velis improve the coppers method (MCM is a pick-up method after improvement of the coppers method) and entropy and fractal dimension methods are used to select the first-arrival waves. Molyneux proposes a direct correlation method (DC) using the maximum cross-correlation value as a criterion, but does not work well in data sets with low signal-to-noise ratios. McCormack applies the back-propagation neural network method (DNN) to the automatic pick-up of first-arrival waves.
The coppers' sliding time window energy ratio first arrival picking method is a popular first arrival picking method. The effective seismic signal before the first arrival time on the seismic data should be zero, and only noise is present; and after it is a very strong seismic signal. Thus, there is a very large difference in seismic energy within the window before and after the first arrival. The difference in energy of the seismic first-arrival waves before and after the takeoff time is used to pick up the first-arrival, and this method is called energy ratio method, which was proposed by coppers in 1985.
And selecting proper lengths of the front sliding window and the rear sliding window according to actual conditions, solving the energy sum of sampling points of each window, dividing the energy sum of the rear window by the energy sum of the front window and the rear window, and squaring to obtain the energy ratio of the front window and the rear window. The specific physical significance is as follows: if the two windows are both above the first arrival wave, the energy of the front window and the rear window is basically the environmental noise of the instrument, the numerical value is small, and the ratio is not large; when the intersection point of the front window and the rear window is just pressed on the first-arrival wave, the ratio has the maximum value. When moving below the first arrival, no large energy ratio is produced because the relative variation of the microseismic energy is small.
The basic technical scheme of the method is as follows: firstly, selecting a proper window length, and performing sliding calculation on each piece of seismic data by using front and rear windows; and then, calculating the energy ratio of the front window and the rear window of each channel of seismic data, and calculating the maximum energy ratio of the front window and the rear window of each channel, wherein the position corresponding to the junction of the front window and the rear window when the energy ratio is maximum is the position of the first arrival wave. The energy ratio method is a single-channel method for directly picking up the first-arrival waves, is easily influenced by the quality of seismic data, and has low accuracy in first-arrival picking up of the seismic data with low signal-to-noise ratio.
Disclosure of Invention
Aiming at the defects in the prior art, the invention provides a first-motion wave automatic picking method which is high in calculation accuracy and based on two-stage optimization.
In order to achieve the purpose of the invention, the invention adopts the technical scheme that:
a first arrival wave automatic picking method based on two-stage optimization is provided, which comprises the following steps:
normalizing the energy value of each seismic channel in the common shot point channel set;
sliding on each seismic channel by adopting a vertical sliding window based on a template range band detection algorithm, and performing correlation calculation with the template to obtain a top sample point subscript of a first arrival interval of each seismic channel;
acquiring a first-arrival range band composed of first-arrival intervals of all seismic channels on a common shot gather according to the subscript of a sample point at the top end of the first-arrival interval of each seismic channel and the size of a vertical sliding window;
within the first-arrival range band, the first-arrival wave position of each seismic trace is calculated using an improved energy ratio first-arrival pick-up algorithm.
Further, the template-based range band detection algorithm slides on each seismic channel by using a vertical sliding window, and performs correlation calculation with the template to obtain the subscript of the top sample point of the first arrival interval of each seismic channel further comprises:
a1, acquiring a j-th seismic channel, and initializing a minimum value r ═ infinity of an objective function and a sample point index d at the top end of a vertical sliding window, wherein d is 1;
a2, judging whether the subscript d of the sample points at the top end of the vertical sliding window is larger than the difference value between the number m of the sample points in the seismic channel and the length l of the template, if so, entering the step A6, otherwise, entering the step A3;
a3, calculating the distance w between the sample energy value in the vertical sliding window and the templatedAnd according to the distance wdCalculating an objective function value r of a vertically sliding windowd;
A4, determination of rd<r*If yes, entering step a5, otherwise, updating the top sample point subscript d +1 of the vertical sliding window, and returning to step a 2;
a5, updating the minimum value r of the objective function value*=rdUpdating the subscript d of the top sample point of the first arrival interval of the seismic channeljD, updating the top sample point subscript d +1 of the vertical sliding window, and returning to the step A2;
a6: outputting the first arrival interval top sample point subscript d of the jth seismic channelj。
Further, the calculation formula for calculating the objective function value of the vertical sliding window is as follows:
wherein a, b and c are all weighting adjustment factors; d'jAnd the subscript of the average top sample point of the first arrival interval of the adjacent seismic channel of the jth seismic channel.
Further, the distance wdThe calculation formula of (2) is as follows:
wherein s isi,jThe ith sampling point in the jth seismic channel is taken as the sampling point; t isiIs the ith template value in the template array T.
Further, the calculating the first-arrival wave position of each seismic trace in the first-arrival range band by using the improved energy ratio first-arrival pick-up algorithm further comprises:
b1, initializing a seismic channel with the label j equal to 1, and circulating a variable i equal to ne, wherein ne is the size of an external window;
b2, judging whether the label j of the seismic channel is larger than the total number n of the seismic channel, if so, entering a step B9, otherwise, entering a step B3;
b3, judging whether the circulating variable i is larger than the height e of the first arrival range, if so, entering a step B7, otherwise, entering a step B4;
b4, calculating the ratio lambda of the external window and the embedded window with the window bottom end sample point index as the cyclic variable i in the jth seismic channeli(i):
Wherein E is1,j(i) And E2,j(i) The average value of the energy square sum of the sampling points in the embedded window and the external window is obtained; the length of the embedded window is smaller than that of the external window;
b5 according to the ratio lambdaj(i) Calculating optimization of window with cyclic variable i as window bottom end sample point index in jth seismic channelValue of objective function M lambdaj(i):
Mλj(i)=|si,j*λj(i)|α
Wherein s isi,jThe energy value of the ith sampling point in the first arrival interval corresponding to the jth seismic channel is α and β which are constant coefficients;
b6, updating the loop variable i ═ i +1, and returning to the step B3;
b7, according to the optimized objective function value M lambdaj(i) Calculating the first arrival wave position index F of the jth seismic channelj:
Fj=argmax(Mλj(i))+dj;
B8, updating the mark j of the seismic channel to be j +1, and entering the step B2;
and B9, outputting the first arrival position subscripts corresponding to all the picked seismic traces.
Further, the mean value E of the sum of squares of the energies of the samples in the embedded window1,j(i) The calculation formula of (2) is as follows:
wherein ns is the size of the embedded window, and i-ns +1 is the top sample point subscript of the embedded window; rk,jIs the kth sampling point energy value of the jth seismic channel in the first arrival range zone matrix.
Further, the mean value E of the sum of the squares of the energies of the samples in the outer window2,j(i) The calculation formula of (2) is as follows:
wherein, i-ne +1 is the top sample point subscript of the external window; rk,jIs the kth sampling point energy value of the jth seismic channel in the first arrival range zone matrix.
Further, the template is divided into two parts, wherein the first half part is set to be a numerical value of 0-0.2, and the second half part is set to be a numerical value of 0.6-0.8.
The invention has the beneficial effects that: compared with the method (MCM, DC and BNN) for directly picking up the first-arrival waves in the prior art, the method has the advantages that the search range of the first-arrival waves is narrowed, and the data set is compressed, so that the time efficiency of the method is improved.
In the picking process, the position similarity of adjacent first-arrival waves is considered, the first-arrival picking results of adjacent seismic channels are guaranteed not to fluctuate greatly up and down to a certain extent, and the stability of the picking results and the accuracy of first-arrival wave picking are guaranteed.
Drawings
Fig. 1 is a flow chart of a first-arrival wave automatic picking method based on two-stage optimization.
FIG. 2 is a waveform of 10 seismic traces taken during a comparative experiment.
Fig. 3 shows the first arrival picking results of the present method and three algorithms (BNN, DC, MCM) in the prior art.
Detailed Description
The following description of the embodiments of the present invention is provided to facilitate the understanding of the present invention by those skilled in the art, but it should be understood that the present invention is not limited to the scope of the embodiments, and it will be apparent to those skilled in the art that various changes may be made without departing from the spirit and scope of the invention as defined and defined in the appended claims, and all matters produced by the invention using the inventive concept are protected.
Referring to fig. 1, fig. 1 shows a flow chart of a first-arrival wave automatic picking method based on two-stage optimization; as shown in fig. 1, the method 100 includes steps 101 to 104.
In step 101, normalizing the energy value of each seismic channel in the common shot point channel set to a range of [ -1, 1 ]; the normalization processing can eliminate the influence of seismic channel data caused by differences among different geophones.
Co-shot gather represents a matrix S ═ S [ S ] of size m × ni,j]Where n is the number of seismic traces, m is the number of samples per trace, si,jIs the ith of the jth seismic traceA sample energy value.
In step 102, a template-based range band detection algorithm slides on each seismic trace by using a vertical sliding window, and correlation calculation is performed on the template to obtain a top sample point subscript of a first arrival interval of each seismic trace.
In an embodiment of the present invention, the template-based range band detection algorithm further includes steps a1 through a6, wherein the sliding is performed on each seismic trace by using a vertical sliding window, and the correlation calculation is performed on the template to obtain the first arrival interval top sample point subscript of the seismic trace.
In step a1, acquiring a j-th seismic trace, and initializing a minimum value r ═ infinity of an objective function and a sample point index d ═ 1 at the top end of a vertical sliding window;
in the step A2, judging whether the subscript d of the sample points at the top end of the vertical sliding window is larger than the difference value between the number m of the sample points in the seismic channel and the length l of the template, if so, entering the step A6, otherwise, entering the step A3;
in step A3, the distance w between the energy value of the sampling point in the vertical sliding window and the template is calculateddAnd according to the distance wdCalculating an objective function value r of a vertically sliding windowd(ii) a Wherein the distance wdThe calculation formula of (2) is as follows:
wherein s isi,jThe ith sampling point in the jth seismic channel is taken as the sampling point; t isiIs the ith template value in the template array T.
The calculation formula for calculating the objective function value of the vertical sliding window is as follows:
wherein a, b and c are all weighting adjustment factors; d'jAnd the subscript of the average top sample point of the first arrival interval of the adjacent seismic channel of the jth seismic channel.
In step A4, r is judgedd<r*If yes, entering step a5, otherwise, updating the top sample point subscript d +1 of the vertical sliding window, and returning to step a 2; in step a5, the minimum value r of the objective function value is updated*=rdUpdating the subscript d of the top sample point of the first arrival interval of the seismic channeljD, updating the top sample point subscript d +1 of the vertical sliding window, and returning to the step A2;
in step A6, outputting first arrival interval top sample point index d of j-th seismic tracej。
The template is divided into two parts, wherein the first half part is set to be a numerical value of 0-0.2, and the second half part is set to be a numerical value of 0.6-0.8.
In step 103, acquiring a first arrival range band composed of first arrival intervals of all seismic channels on the common shot gather according to the subscript of the sample point at the top end of the first arrival interval of each seismic channel and the size of the vertical sliding window; the starting point of the first arrival range is the subscript of the sample point at the top end of the first arrival interval, and the length of the subscript is the size of the vertical sliding window.
In step 104, within the first arrival range band, the first arrival wave position of each seismic trace is calculated using a modified energy ratio first arrival pick-up algorithm.
In one embodiment of the present invention, calculating the first-arrival wave position for each seismic trace using the modified energy ratio first-arrival pick-up algorithm within the first-arrival range band further comprises steps B1 through B9.
In step B1, initializing a seismic trace with a label j equal to 1 and a loop variable i equal to ne, wherein ne is the external window size;
in the step B2, judging whether the label j of the seismic channel is larger than the total number n of the seismic channel, if so, entering the step B9, otherwise, entering the step B3;
in the step B3, judging whether the circulation variable i is larger than the height e of the first arrival range, if so, entering the step B7, otherwise, entering the step B4;
in step B4, calculating the ratio lambda of the external window and the embedded window with the window bottom sample point index as the cyclic variable i in the jth seismic tracej(i):
Wherein E is1,j(i) And E2,j(i) The average value of the energy square sum of the sampling points in the embedded window and the external window is obtained; the length of the embedded window is smaller than that of the external window;
in implementation, the scheme preferably selects the average value E of the energy square sum of the sampling points in the embedded window1,j(i) The calculation formula of (2) is as follows:
wherein ns is the size of the embedded window, and i-ns +1 is the top sample point subscript of the embedded window; rk,jThe energy value of the ith sampling point of the jth seismic channel in the first arrival range zone matrix is obtained.
Mean value E of the sum of squares of the energies of the samples in the outer window2,j(i) The calculation formula of (2) is as follows:
wherein, i-ne +1 is the top sample point subscript of the external window; rk,jThe energy value of the ith sampling point of the jth seismic channel in the first arrival range zone matrix is obtained.
In step B5, according to the ratio lambdaj(i) Calculating the optimized objective function value M lambda of the window with the window bottom sample point subscript as the cyclic variable i in the jth seismic channelj(i):
Mλj(i)=|si,j*λj(i)|α
Wherein s isi,jThe energy value of the ith sampling point in the first arrival interval corresponding to the jth seismic channel is α and β which are constant coefficients;
in step B6, the loop variable i ═ i +1 is updated, and the process returns to step B3;
in step B7, the value M lambda is determined according to the optimization objective functionj(i) Calculating the first arrival wave position index F of the jth seismic channelj:
Fj=argmax(Mλj(i))+dj;
In step B8, the trace label j ═ j +1 is updated, and the process proceeds to step B2;
in step B9, the first arrival position indices corresponding to all the seismic traces picked are output.
The results of the present application are illustrated below by comparing the present method (FPTO) with three algorithms (BNN, DC, MCM) of the prior art:
10 seismic channel data are selected for testing as shown in fig. 2, the position of the first-arrival wave is shown in the box of fig. 2, the first-arrival picking is carried out by adopting the method and three algorithms (BNN, DC and MCM) in the prior art, the picking result is shown in fig. 3, the box of fig. 3 shows the first-arrival wave picked by the MCM algorithm, the triangle shows the first-arrival wave picked by the DC algorithm, the dot shows the first-arrival wave picked by the BNN algorithm, and the five-pointed star shows the first-arrival wave picked by the method (FPTO).
As can be seen from fig. 3, the two-stage optimization-based first-arrival wave automatic picking algorithm provided by the present solution can pick up the first-arrival waves more accurately, and exhibits more consistent continuity as a whole.
The results of the four picking results with deviation less than 20ms from the manual picking results are regarded as correct picking, and the accuracy of the first-break wave automatic picking method based on two-stage optimization is compared with the accuracy of the other three methods in table 1.
TABLE 1 statistics of differences between results of four algorithm pickups and manual pickups within less than 20ms
The experimental result shows that compared with other three algorithms in the prior art, the method provided by the scheme can more accurately find the position of the first-arrival wave, and the effect of picking up the first-arrival wave is the best.
Claims (6)
1. The first arrival wave automatic picking method based on two-stage optimization is characterized by comprising the following steps of:
normalizing the energy value of each seismic channel in the common shot point channel set;
sliding on each seismic channel by adopting a vertical sliding window based on a template range band detection algorithm, and performing correlation calculation with the template to obtain a top sample point subscript of a first arrival interval of each seismic channel;
acquiring a first-arrival range band composed of first-arrival intervals of all seismic channels on a common shot gather according to the subscript of a sample point at the top end of the first-arrival interval of each seismic channel and the size of a vertical sliding window;
in the first-arrival range band, calculating the first-arrival wave position of each seismic channel by adopting an improved energy ratio first-arrival picking algorithm;
the template-based range band detection algorithm slides on each seismic channel by adopting a vertical sliding window, and performs correlation calculation with the template, and obtaining the first arrival interval top sample point subscript of each seismic channel further comprises:
a1, acquiring a j-th seismic channel, and initializing a minimum value r ═ infinity of an objective function and a sample point index d at the top end of a vertical sliding window, wherein d is 1;
a2, judging whether the subscript d of the sample points at the top end of the vertical sliding window is larger than the difference value between the number m of the sample points in the seismic channel and the length l of the template, if so, entering the step A6, otherwise, entering the step A3;
a3, calculating the distance w between the sample energy value in the vertical sliding window and the templatedAnd according to the distance wdCalculating an objective function value r of a vertically sliding windowd;
A4, determination of rdIf yes, entering a step A5, otherwise, updating the top sample point subscript d +1 of the vertical sliding window, and returning to the step A2;
a5, updating the minimum value r ═ r of the objective function valuedUpdating the subscript d of the top sample point of the first arrival interval of the seismic channeljD, updating the top sample point subscript d +1 of the vertical sliding window, and returning to the step A2;
a6: outputting the first arrival interval top sample point subscript d of the jth seismic channelj;
The calculation formula for calculating the objective function value of the vertical sliding window is as follows:
wherein a, b and c are all weighting adjustment factors; d'jAnd the subscript of the average top sample point of the first arrival interval of the adjacent seismic channel of the jth seismic channel.
2. The method for automatic first arrival picking based on two-stage optimization according to claim 1, wherein the distance wdThe calculation formula of (2) is as follows:
wherein s isi,jThe ith sampling point in the jth seismic channel is taken as the sampling point; t isiIs the ith template value in the template array T.
3. The method for automatic first-arrival wave picking based on two-stage optimization according to claim 1, wherein the calculating the first-arrival wave position of each seismic trace by using the improved energy ratio first-arrival picking algorithm in the first-arrival range band further comprises:
b1, initializing a seismic channel with the label j equal to 1, and circulating a variable i equal to ne, wherein ne is the size of an external window;
b2, judging whether the label j of the seismic channel is larger than the total number n of the seismic channel, if so, entering a step B9, otherwise, entering a step B3;
b3, judging whether the circulating variable i is larger than the height e of the first arrival range, if so, entering a step B7, otherwise, entering a step B4;
b4, calculating the ratio lambda of the external window and the embedded window with the window bottom end sample point index as the cyclic variable i in the jth seismic channelj(i):
Wherein E is1,j(i) And E2,j(i) The average value of the energy square sum of the sampling points in the embedded window and the external window is obtained; the length of the embedded window is smaller than that of the external window;
b5 according to the ratio lambdaj(i) Calculating the optimized objective function value M lambda of the window with the window bottom sample point subscript as the cyclic variable i in the jth seismic channelj(i):
Mλj(i)=|si,j*λj(i)|α
Wherein s isi,jThe energy value of the ith sampling point in the first arrival interval corresponding to the jth seismic channel is α and β which are constant coefficients;
b6, updating the loop variable i ═ i +1, and returning to the step B3;
b7, according to the optimized objective function value M lambdaj(i) Calculating the first arrival wave position index F of the jth seismic channelj:
Fj=argmax(Mλj(i))+dj;
B8, updating the mark j of the seismic channel to be j +1, and entering the step B2;
and B9, outputting the first arrival position subscripts corresponding to all the picked seismic traces.
4. The method for automatically picking up first arrival waves based on two-stage optimization according to claim 3, wherein the mean E of the square sum of the energies of the sampling points in the embedded window1,j(i) The calculation formula of (2) is as follows:
wherein ns is the size of the embedded window, and i-ns +1 is the top sample point subscript of the embedded window; rk,jIs the kth sampling point energy value of the jth seismic channel in the first arrival range zone matrix.
5. The method for automatic first arrival picking based on two-stage optimization as claimed in claim 3, wherein the sampling points in the external window can be selectedAverage value E of the sum of squares of quantities2,j(i) The calculation formula of (2) is as follows:
wherein, i-ne +1 is the top sample point subscript of the external window; rk,jIs the kth sampling point energy value of the jth seismic channel in the first arrival range zone matrix.
6. The automatic first arrival wave picking method based on the two-stage optimization as claimed in any one of claims 1 to 5, wherein the template is divided into two parts, the first half is set to a value of 0 to 0.2, and the second half is set to a value of 0.6 to 0.8.
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Citations (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN102073067A (en) * | 2009-11-25 | 2011-05-25 | 中国石油天然气集团公司 | Method for increasing automatic pickup efficiency of geological data first-motion waves |
CN102243320A (en) * | 2011-04-12 | 2011-11-16 | 中国石油天然气股份有限公司 | Seismic wave first arrival pickup method |
CN104266894A (en) * | 2014-09-05 | 2015-01-07 | 中国矿业大学 | Mine microearthquake signal preliminary wave moment extracting method based on correlation analysis |
CN108072896A (en) * | 2016-11-18 | 2018-05-25 | 中国石油化工股份有限公司 | A kind of fully automatically seismic wave first break pickup method and system |
CN108279436A (en) * | 2017-12-20 | 2018-07-13 | 中国石油天然气股份有限公司 | Method and device for picking up seismic wave first arrivals |
CN109143364A (en) * | 2017-06-27 | 2019-01-04 | 中国石油化工股份有限公司 | First arrival time pick-up method |
Family Cites Families (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US7423930B2 (en) * | 2003-12-10 | 2008-09-09 | Schlumberger Technology Corporation | Methods and systems for detecting arrivals of interest |
-
2019
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Patent Citations (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN102073067A (en) * | 2009-11-25 | 2011-05-25 | 中国石油天然气集团公司 | Method for increasing automatic pickup efficiency of geological data first-motion waves |
CN102243320A (en) * | 2011-04-12 | 2011-11-16 | 中国石油天然气股份有限公司 | Seismic wave first arrival pickup method |
CN104266894A (en) * | 2014-09-05 | 2015-01-07 | 中国矿业大学 | Mine microearthquake signal preliminary wave moment extracting method based on correlation analysis |
CN108072896A (en) * | 2016-11-18 | 2018-05-25 | 中国石油化工股份有限公司 | A kind of fully automatically seismic wave first break pickup method and system |
CN109143364A (en) * | 2017-06-27 | 2019-01-04 | 中国石油化工股份有限公司 | First arrival time pick-up method |
CN108279436A (en) * | 2017-12-20 | 2018-07-13 | 中国石油天然气股份有限公司 | Method and device for picking up seismic wave first arrivals |
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