CN112241024B - Method for improving signal-to-noise ratio of seismic data, computer storage medium and system - Google Patents
Method for improving signal-to-noise ratio of seismic data, computer storage medium and system Download PDFInfo
- Publication number
- CN112241024B CN112241024B CN201910648785.6A CN201910648785A CN112241024B CN 112241024 B CN112241024 B CN 112241024B CN 201910648785 A CN201910648785 A CN 201910648785A CN 112241024 B CN112241024 B CN 112241024B
- Authority
- CN
- China
- Prior art keywords
- data
- source data
- expression
- noise ratio
- signal
- 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.)
- Active
Links
- 238000000034 method Methods 0.000 title claims abstract description 63
- 230000006870 function Effects 0.000 claims abstract description 49
- 238000001914 filtration Methods 0.000 claims abstract description 20
- 238000004590 computer program Methods 0.000 claims abstract description 10
- 238000012545 processing Methods 0.000 claims description 11
- 238000005311 autocorrelation function Methods 0.000 claims description 8
- 230000006872 improvement Effects 0.000 claims description 7
- 238000005314 correlation function Methods 0.000 claims description 4
- 238000004364 calculation method Methods 0.000 abstract description 14
- 238000012163 sequencing technique Methods 0.000 abstract description 2
- 108091006146 Channels Proteins 0.000 description 21
- 238000001228 spectrum Methods 0.000 description 11
- 238000010586 diagram Methods 0.000 description 9
- 230000008569 process Effects 0.000 description 8
- 230000000694 effects Effects 0.000 description 4
- 230000005284 excitation Effects 0.000 description 4
- 230000008901 benefit Effects 0.000 description 3
- 238000001514 detection method Methods 0.000 description 3
- 230000008859 change Effects 0.000 description 2
- 238000012937 correction Methods 0.000 description 2
- 238000013461 design Methods 0.000 description 2
- 239000000523 sample Substances 0.000 description 2
- 230000009466 transformation Effects 0.000 description 2
- 238000010521 absorption reaction Methods 0.000 description 1
- 238000004458 analytical method Methods 0.000 description 1
- 238000010276 construction Methods 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000003384 imaging method Methods 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 238000003672 processing method Methods 0.000 description 1
- 230000002035 prolonged effect Effects 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 238000005070 sampling 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. analysis, for interpretation, for correction
- G01V1/36—Effecting static or dynamic corrections on records, e.g. correcting spread; Correlating seismic signals; Eliminating effects of unwanted energy
- G01V1/364—Seismic filtering
-
- 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
Abstract
The invention discloses a method for improving signal-to-noise ratio of seismic data, a computer storage medium and a system, wherein the method comprises the following steps: determining a filter objective function corresponding to a minimum value of a preset least square fitting expression according to a plurality of data points on the obtained corresponding channels of the source data and the target data; performing wavelet matching on the source data points one by one according to the filter objective function to obtain a plurality of objective data points which are matched with the source data points one by one in a wavelet mode; sequencing the obtained target data points after the plurality of wavelets are matched to obtain a target data channel; the computer storage medium has stored therein a computer program which when executed by a processor performs the method, the system comprising a processor and a memory, the processor performing the method when executing the computer program stored in the memory. The filtering factor obtained by single-channel calculation is more reliable, the difference caused by inconsistent factor waves among different data is solved, and the signal-to-noise ratio of the seismic data is further improved.
Description
Technical Field
The invention relates to the technical field of seismic exploration data processing, in particular to a seismic data signal-to-noise ratio improving method, a computer storage medium and a system.
Background
In seismic exploration, due to the fact that the earth surface is complex, a plurality of types of seismic source mixed construction is adopted in field acquisition, large differences exist among seismic source records in amplitude, phase and frequency caused by different excitation modes, and inconsistencies of seismic data are caused, when a plurality of data are used together for offset imaging, differences of energy and the like among channels exist in an obtained seismic section, and the inconsistencies of the seismic data are also caused, and seriously reduce the signal to noise ratio of the seismic records.
The seismic data processing needs to process data acquired from adjacent blocks or different years of the same block frequently, is now more and more complex and finer based on geophysical research, and sometimes the data are found to have amplitude, phase or frequency spectrum differences when being processed identically, so that different data need to be processed.
At present, the main methods for solving the problem of consistency of different data in actual production include a time shifting method, a deconvolution parameter adjusting method and a matched filtering method. The time shift method processes two or more groups of data to be spliced by adopting different processes respectively, then analyzes the time difference change of the overlapped part, and performs integral time shift correction on one group of data relative to the other group of data so as to splice the data. The method is simple to realize, but only partially improves the consistency of two groups of seismic data, and is difficult to consider the change of shallow, medium and deep time differences, and the application effect is poor. The deconvolution parameter adjustment method mainly improves the consistency of seismic data by reasonably selecting deconvolution parameters, can well eliminate the frequency difference between different data, improves the signal to noise ratio of the data, has a certain effect, but is difficult to accurately select deconvolution parameters in practical application. Several phase correction techniques in practice have limitations in application such that the corrected record cannot be restored to the optimal form. The matched filtering method is a better method for eliminating the problem of consistency of seismic data, the wavelet matching technology directly utilizes repeated seismic traces (which can be respectively called a source data trace set and a target data trace set) to design a matched filter, and then the source data trace set is matched filtered to enable the source data trace set to be closest to the target data trace set to the maximum extent. Currently, wavelet matching is usually implemented by designing a filtering operator to achieve consistency of amplitude, phase or spectrum between data.
However, when wavelet matching is performed in the prior art, a plurality of tracks with strong contrast are sometimes selected in a recording time window to obtain a matching factor of the target data track set and the source data track set, and the matching factor obtained based on the plurality of tracks has the problem of low reliability, so that the signal-to-noise ratio of the processed seismic data is low.
Disclosure of Invention
The invention aims to solve the technical problems that: in the prior art, the matching factors obtained based on the multi-channel set have the problem of low signal-to-noise ratio of the seismic data due to low reliability.
In order to solve the technical problems, the invention provides a method for improving the signal-to-noise ratio of seismic data, a computer storage medium and a system.
According to a first aspect of the present invention, there is provided a seismic data signal to noise ratio improvement method comprising the steps of:
obtaining multiple groups of corresponding channel data points of source data and target data;
determining a filter objective function corresponding to the minimum value of the least square fitting expression of the group of corresponding data points and the preset least square fitting expression aiming at each group of corresponding data points;
performing wavelet matching on the source data points of the group of corresponding channel data points according to the filter objective function to obtain source data points matched with the source data points by the wavelet;
and sequencing the source data points which are obtained by the plurality of sets of corresponding channel data points and are subjected to wavelet matching to obtain the source data which are subjected to wavelet matching, so that the difference caused by wavelet inconsistency is eliminated, and the signal-to-noise ratio of the seismic data is improved.
Preferably, the method for improving the signal-to-noise ratio of the seismic data further comprises the steps of constructing the least square fitting expression, which comprises the following steps:
filtering the source data to obtain filtered source data;
performing inverse filtering processing on the target data to obtain inverse-filtered target data;
taking the square of the difference between the target data and the filtered source data as a first expression;
taking the square of the difference between the source data and the inverse filtered target data as a second expression;
and constructing the sum of the first expression and the second expression as the least square fitting expression.
Preferably, the least squares fit expression satisfies:
E＝(F·X-Y) 2 +(X-F -1 ·Y) 2 ；
wherein F is a filter objective function in a frequency domain, X is source data, and Y is target data.
Preferably, the filter corresponding to the filter objective function is a constant phase filter.
Preferably, the filter objective function satisfies:
F＝A 0 ·exp(iP 0 )；
wherein P is 0 As a phase coefficient, A 0 For the amplitude coefficient, i is an imaginary unit.
Preferably, the phase coefficient is calculated by a first preset expression, where the first preset expression is:
P 0 ＝arctan(-hilbert(xcor(Y,X))/xcor(Y,X))；
xcor (Y, X) is a cross-correlation function of the time-shifted source data and the target data estimated at the zero delay time, while hilbert (xcor (Y, X)) is a hilbert transform function of the cross-correlation of the time-shifted source data and the target data estimated at the zero delay time.
Preferably, the amplitude coefficient is calculated by a second preset expression, wherein the second preset expression is:
acor (X) is a source data autocorrelation function at zero delay time, and acor (Y) is a target data autocorrelation function at zero delay time.
Preferably, wavelet matching is achieved by convolving the filter objective function with the source data point.
According to a second aspect of the present invention there is provided a computer storage medium having a computer program stored therein, which when executed by one or more processors implements a seismic data signal to noise ratio improvement method as described above.
According to a third aspect of the present invention there is provided a computer system comprising a processor and a memory, the memory having stored therein a computer program which when executed by the processor implements a seismic data signal to noise ratio improvement method as described above.
One or more embodiments of the above-described solution may have the following advantages or benefits compared to the prior art:
by applying the method for improving the signal-to-noise ratio of the seismic data, the filtering factors obtained through single-channel calculation are more reliable, the difference caused by the inconsistency of the amplitude, the phase and the frequency spectrum among wavelets is solved, the signal-to-noise ratio of the seismic data is further improved, and the method can be applied to matched filtering of the seismic data under different conditions of excitation, reception and the like.
Drawings
The scope of the present disclosure may be better understood by reading the following detailed description of exemplary embodiments in conjunction with the accompanying drawings. The drawings included herein are:
FIG. 1 is a flow chart of an overall method according to an embodiment of the present invention;
FIG. 2 is a schematic representation of the results corresponding to FIG. 1;
FIG. 3 is a flow chart of a method for constructing a least squares fit expression in accordance with the present invention;
FIG. 4 is a diagram of source data for a northwest probe region;
FIG. 5 is a schematic diagram of the target data in FIG. 4;
FIG. 6 is a schematic view of source data after applying the seismic data signal-to-noise ratio enhancement method of the present invention;
FIG. 7 is a schematic cross-sectional view of the difference between the target data of FIG. 5 and the source data of FIG. 4;
FIG. 8 is a schematic diagram of a cross section of the difference between the target data in FIG. 5 and the source data of FIG. 6 after the seismic data signal-to-noise ratio improvement method of the present invention is applied.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the following detailed description of the implementation method of the present invention will be given with reference to the accompanying drawings and examples, by which the technical means are applied to solve the technical problems, and the implementation process for achieving the technical effects can be fully understood and implemented accordingly.
In the prior art, the matching factor obtained based on the multi-channel set has the problem of low signal-to-noise ratio of the seismic data due to low reliability.
Example 1
The embodiment provides a method for improving the signal-to-noise ratio of seismic data, which mainly comprises the following steps S101 to S105.
Fig. 1 shows an overall method flowchart of an embodiment of the present invention, fig. 2 shows a schematic diagram of the result corresponding to fig. 1, the source data and the target data shown in fig. 2 are obtained in step S101, the cross-correlation operator design shown corresponds to step S102 and step S103, the operator application shown to the source data corresponds to step S104, and the output result shown corresponds to step S105.
Specifically, as shown in fig. 1 and 2:
in step S101, multiple sets of corresponding trace data points of source data and target data are obtained, a first dimension of the three-dimensional data is a measuring line, a second dimension is each trace along the measuring line, a third dimension is different according to a domain where the third dimension is located, and the third dimension can be a time domain or a depth domain, where the third dimension is located, and the third dimension is a time domain.
Further, the seismic data signal-to-noise ratio improving method further includes step S102, and fig. 3 shows a flowchart of a method for constructing the least square fitting expression, and as shown in fig. 3, the least square fitting expression is constructed, which mainly includes the following steps S1021 to S1025.
In step S1021, the source data is subjected to filtering processing to obtain filtered source data.
In step S1022, the target data is subjected to inverse filtering processing to obtain inverse filtered target data, and the actual seismic record is affected by absorption, so that the high-frequency component is lost in the source pulse, the duration is prolonged, the time length of the seismic wave can be compressed by performing inverse filtering on the target data, and the resolution of the seismic data is improved.
In step S1023, the square of the difference between the target data and the filtered source data is taken as a first expression.
In step S1024, the square of the difference between the source data and the inverse-filtered target data is taken as a second expression.
In step S1035, the sum of the first expression and the second expression is constructed as a least squares fit expression.
The least squares fit expression satisfies:
E＝(F·X-Y) 2 +(X-F -1 ·Y) 2 。
wherein F is a filter objective function in a frequency domain, X is source data, and Y is target data.
Further, if the filter corresponding to the filter objective function is a constant phase filter, F is a constant phase filter, that is, an expression for the phase spectrum and the amplitude spectrum.
Further, the filter objective function satisfies:
F＝A 0 ·exp(iP 0 )。
wherein P is 0 As a phase coefficient, A 0 For the amplitude coefficient, i is an imaginary unit.
Specifically, the phase coefficient is calculated through a first preset expression, wherein the first preset expression is:
P 0 ＝arctan(-hilbert(xcor(Y,X))/xcor(Y,X))。
xcor (Y, X) is a cross-correlation function of the time-shifted source data and the target data estimated at the zero delay time, while hilbert (xcor (Y, X)) is a hilbert transform function of the cross-correlation of the time-shifted source data and the target data estimated at the zero delay time.
The relation between the amplitude frequency and the phase frequency, the real part and the imaginary part of the Fourier transformation can be established through the Hilbert transformation function; the corresponding resolved signal is constructed to contain only positive frequency components so that the sampling rate of the seismic signal can be reduced.
Calculating an amplitude coefficient through a second preset expression, wherein the second preset expression is:
acor (X) is a source data autocorrelation function at zero delay time, and acor (Y) is a target data autocorrelation function at zero delay time.
The phase coefficient P can be utilized 0 And amplitude coefficient A 0 Characterizing the filter objective function F, thereby bringing the phase coefficient P 0 And amplitude coefficient A 0 And substituting the zero delay time into a least square fitting expression for subsequent calculation, and selecting zero delay time by the functions, so that the calculation process can be further simplified.
In step S103, for each set of corresponding trace data points, a filter objective function corresponding to the minimum value of the preset least squares fitting expression is determined for the set of corresponding trace data points, so that wavelets can be processed by the filter objective function, and thus wavelet matching work can be performed.
In step S104, wavelet matching is performed on the source data points of the set of corresponding channel data points according to the filter objective function, so as to obtain source data points after wavelet matching with the source data points.
Specifically, wavelet matching is realized by convolving the filter objective function with the source data point, and the calculation mode is simple.
In step S105, the source data after wavelet matching is obtained by sorting the source data after multiple wavelet matching obtained by multiple sets of corresponding channel data points.
Thus, the method utilizes the amplitude coefficient A 0 And phase coefficient P 0 Characterizing the filter objective function F, and introducing the filter objective function F into a least square fitting expression E, so as to minimize the value of the least square fitting expression E, thereby obtaining the amplitude coefficient A corresponding to the set of corresponding data points 0 And phase coefficient P 0 The filter objective function F of the channel is calculated, the filter objective function F and the source data point are convolved to obtain the source data point after wavelet matching in the channel, then other channels are calculated successively, and finally the source data point obtained by calculating the one inline line is ordered according to the channel sequence, so that the source data after an operator is applied is obtained. The filtering factor obtained through single-channel calculation is more reliable, the difference caused by the inconsistency of amplitudes, phases and frequency spectrums among wavelets is solved, the signal to noise ratio of the seismic data is further improved, and the method can be applied to matched filtering of the seismic data under different conditions of excitation, reception and the like.
The embodiment calculates the actual data to verify the correctness of the operator of the method.
Fig. 4 shows a schematic diagram of source data of a northwest detection zone, fig. 5 shows a schematic diagram of target data in fig. 4, and the object of the present invention is to match the source data and the target data of the northwest detection zone in amplitude and phase.
According to step S101, first X on a transverse line corresponding to one longitudinal line of source data is read 1 Reading the first Y on the transverse line corresponding to one longitudinal line of the target data 1 I.e. the current first source data point X for source data and target data 1 And a target data point Y 1 。
According to step S102, the source data point X 1 And a target data point Y 1 Is carried into a least square fitting expression E by using an amplitude coefficient A 0 And phase coefficient P 0 Characterizing a filter objective function F 1 Belt with a belt bodyFitting to the least squares fit expression E 1 In order E 1 The value of (a) is the smallest, and the amplitude coefficient A corresponding to the first channel is obtained 0 And phase coefficient P 0 The first pass filter objective function F is calculated 1 。
According to step S104, the filter objective function F 1 With source data point X 1 Performing convolution to obtain a source data point Z after wavelet matching 1 Then, the second path, the third path … and the nth path are successively calculated, and in the subsequent calculation, the corresponding target filter function F is required to be recalculated for each pair of the source data point X and the target data point Y, so that wavelet matching work can be performed, namely, the single path calculation is based, and the reliability of the filter factor obtained by calculation is higher.
According to step S105, the source data points Z after the wavelet matching obtained by the calculation of the inline line are sorted according to the channel sequence, so as to obtain the source data after the operator is applied, that is, the source data schematic diagram of the probe area after the seismic data signal-to-noise ratio improving method of the invention is applied, which is shown in fig. 6.
Subtracting the source data in fig. 4 from the target data in fig. 5 to obtain the difference between the source data and the target data, which is the schematic diagram of the difference section between the target data in fig. 5 and the source data in fig. 4 shown in fig. 7.
Then, subtracting the source data after the seismic data signal-to-noise ratio improving method of the invention in FIG. 6 from the target data in FIG. 5 to obtain the difference between the matched source data and the target data, namely, the difference section schematic diagram of the target data in FIG. 5 shown in FIG. 8 and the source data after the seismic data signal-to-noise ratio improving method of the invention in FIG. 6.
As can be seen from FIGS. 7 and 8, the difference between the source data and the target data after the seismic data signal-to-noise ratio improving method of the invention is reduced, so that the effectiveness and the correctness of the seismic data signal-to-noise ratio improving method of the invention in seismic data processing are illustrated by the actual data of the northwest detection zone.
As can be seen from the analysis of the effects before and after the actual data processing, the seismic data signal-to-noise ratio improving method can realize the consistency adjustment of wavelet amplitudes, phases or frequency spectrums among different data, and solve the cross section inter-channel difference obtained by the inconsistency of the wavelet amplitudes, phases and frequency spectrums.
Example two
The present embodiment provides a computer storage medium having a computer program stored therein, which when executed by one or more processors implements the seismic data signal-to-noise ratio improvement method as described in embodiment one.
Specifically, the process of the computer program being executed by the processor includes executing steps a101 to a105 as follows.
In performing step A101, multiple sets of corresponding trace data points of source data and target data are obtained to enable single trace computation of the seismic traces.
Further, the processing method further includes executing step a102 to construct a least squares fit expression, which mainly includes the following executing steps a1021 to a1025.
When step a1021 is executed, filtering processing is performed on the source data to obtain filtered source data.
When step a1022 is executed, inverse filtering processing is performed on the target data to obtain inverse filtered target data.
In performing step a1023, the square of the difference between the target data and the filtered source data is taken as a first expression.
In performing step a1024, the square of the difference between the source data and the inverse-filtered target data is taken as the second expression.
In performing step a1035, the sum of the first expression and the second expression is constructed as a least squares fit expression.
The least squares fit expression satisfies:
E＝(F·X-Y) 2 +(X-F -1 ·Y) 2 。
wherein F is a filter objective function in a frequency domain, X is source data, and Y is target data.
Further, if the filter corresponding to the filter objective function is a constant phase filter, F is a constant phase filter, that is, an expression for the phase spectrum and the amplitude spectrum.
Further, the filter objective function satisfies:
F＝A 0 ·exp(iP 0 )。
wherein P is 0 As a phase coefficient, A 0 For the amplitude coefficient, i is an imaginary unit.
Specifically, the phase coefficient is calculated through a first preset expression, wherein the first preset expression is:
P 0 ＝arctan(-hilbert(xcor(Y,X))/xcor(Y,X))。
xcor (Y, X) is a cross-correlation function of the time-shifted source data and the target data estimated at the zero delay time, while hilbert (xcor (Y, X)) is a hilbert transform function of the cross-correlation of the time-shifted source data and the target data estimated at the zero delay time.
Calculating an amplitude coefficient through a second preset expression, wherein the second preset expression is:
acor (X) is a source data autocorrelation function at zero delay time, and acor (Y) is a target data autocorrelation function at zero delay time.
The phase coefficient P can be utilized 0 And amplitude coefficient A 0 Characterizing the filter objective function F, thereby bringing the phase coefficient P 0 And amplitude coefficient A 0 And substituting the zero delay time into a least square fitting expression for subsequent calculation, and selecting zero delay time by the functions, so that the calculation process can be further simplified.
When executing step a103, for each set of corresponding trace data points, determining a filter objective function corresponding to the minimum value of the preset least square fitting expression of the set of corresponding trace data points, so as to be capable of processing wavelets through the filter objective function and further performing wavelet matching work.
When executing step A104, the wavelet matching is carried out on the source data points of the group of corresponding channel data points according to the filter objective function, and the source data points after the wavelet matching with the source data points are obtained.
Specifically, wavelet matching is realized by convolving the filter objective function with the source data point, and the calculation mode is simple.
And (3) when the step A105 is executed, sorting the source data points after the matching of the plurality of wavelets obtained by the plurality of groups of corresponding channel data points, and obtaining the source data after the matching of the wavelets.
Example III
The embodiment provides a computer system, which comprises a processor and a memory, wherein a computer program is stored in the memory, and the computer program realizes the method for improving the signal-to-noise ratio of the seismic data according to the first embodiment when being executed by the processor, and the specific process is referred to in the second embodiment.
The technical scheme of the invention is described in detail above, and considering that in the related art, when wavelet matching work is performed, a plurality of record channels with strong contrast are sometimes selected in a record time window to obtain a matching factor of a target data channel set and a source data channel set by solving a filtering factor, and the matching factor obtained based on the multi-channel set has the problem of low reliability, so that the signal-to-noise ratio of processed seismic data is low. The method, the storage medium and the system for improving the signal-to-noise ratio of the seismic data provided by the invention utilize the amplitude coefficient A 0 And phase coefficient P 0 Characterizing the filter objective function F, and introducing the filter objective function F into a least square fitting expression E, so as to minimize the value of the least square fitting expression E, thereby obtaining the amplitude coefficient A corresponding to the set of corresponding data points 0 And phase coefficient P 0 The filter objective function F of the channel is calculated, the filter objective function F and the source data point are convolved to obtain the source data point after wavelet matching in the channel, then other channels are calculated successively, and finally the source data point obtained by calculating the one inline line is ordered according to the channel sequence, so that the source data after an operator is applied is obtained. The filtering factor obtained by single-channel calculation is more reliable, and the amplitude and phase between wavelets are solvedAnd the difference caused by the inconsistency of frequency spectrum, thereby improving the signal to noise ratio of the seismic data, and being applicable to the matched filtering of the seismic data under different conditions of excitation, reception and the like.
In several embodiments provided herein, it should be appreciated that the seismic data signal-to-noise ratio enhancement method of the invention may be stored on a computer readable storage medium or computer system, implemented as a software functional unit and sold or used as a stand-alone product. Based on such understanding, the technical solution of the present invention is essentially or a part contributing to the prior art, or all or part of the technical solution may be embodied in the form of a software product stored in a storage medium or a computer system, comprising several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods of the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
Although the embodiments of the present invention are disclosed above, the embodiments are only used for the convenience of understanding the present invention, and are not intended to limit the present invention. Any person skilled in the art can make any modification and variation in form and detail without departing from the spirit and scope of the present disclosure, but the scope of the present disclosure is still subject to the scope of the present disclosure as defined by the appended claims.
Claims (8)
1. A method for improving the signal-to-noise ratio of seismic data, comprising the steps of:
obtaining multiple groups of corresponding channel data points of source data and target data;
determining a filter objective function corresponding to the minimum value of the least square fitting expression of the group of corresponding data points and the preset least square fitting expression aiming at each group of corresponding data points;
performing wavelet matching on the source data points of the group of corresponding channel data points according to the filter objective function to obtain source data points matched with the source data points by the wavelet;
sorting the source data points which are obtained by the plurality of groups of corresponding channel data points and are subjected to wavelet matching to obtain source data which are subjected to wavelet matching, so as to eliminate the difference caused by wavelet inconsistency and improve the signal-to-noise ratio of the seismic data;
constructing the least squares fit expression, comprising:
filtering the source data to obtain filtered source data;
performing inverse filtering processing on the target data to obtain inverse-filtered target data;
taking the square of the difference between the target data and the filtered source data as a first expression;
taking the square of the difference between the source data and the inverse filtered target data as a second expression;
constructing a sum of the first expression and the second expression as the least squares fit expression;
the least squares fit expression satisfies:
E＝(F·X-Y) 2 +(X-F -1 ·Y) 2 ；
wherein F is a filter objective function in a frequency domain, X is source data, and Y is target data.
2. The method for improving the signal-to-noise ratio of seismic data according to claim 1, wherein: the filter corresponding to the filter objective function is a constant phase filter.
3. The method for improving the signal-to-noise ratio of seismic data according to claim 1, wherein: the filter objective function satisfies:
F＝A 0 ·exp(iP 0 )；
wherein P is 0 As a phase coefficient, A 0 Is the amplitude coefficient, i is the imaginary orderBits.
4. A method of improving signal-to-noise ratio of seismic data according to claim 3, wherein: calculating the phase coefficient through a first preset expression, wherein the first preset expression is:
P 0 ＝arctan(-hilbert(xcor(Y,X))/xcor(Y,X))；
xcor (Y, X) is a cross-correlation function of the time-shifted source data and the target data estimated at the zero delay time, while hilbert (xcor (Y, X)) is a hilbert transform function of the cross-correlation of the time-shifted source data and the target data estimated at the zero delay time.
5. A method of improving signal-to-noise ratio of seismic data according to claim 3, wherein: calculating the amplitude coefficient through a second preset expression, wherein the second preset expression is:
acor (X) is a source data autocorrelation function at zero delay time, and acor (Y) is a target data autocorrelation function at zero delay time.
6. The method for improving the signal-to-noise ratio of seismic data according to claim 1, wherein: wavelet matching is achieved by convolving the filter objective function with the source data points.
7. A computer storage medium, characterized by: the computer storage medium having stored therein a computer program which, when executed by one or more processors, implements the seismic data signal-to-noise ratio improvement method of any of claims 1-6.
8. A computer system, characterized in that: comprising a processor and a memory, said memory having stored therein a computer program which, when executed by said processor, implements the seismic data signal-to-noise ratio improvement method of any of claims 1-6.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910648785.6A CN112241024B (en) | 2019-07-18 | 2019-07-18 | Method for improving signal-to-noise ratio of seismic data, computer storage medium and system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910648785.6A CN112241024B (en) | 2019-07-18 | 2019-07-18 | Method for improving signal-to-noise ratio of seismic data, computer storage medium and system |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN112241024A CN112241024A (en) | 2021-01-19 |
| CN112241024B true CN112241024B (en) | 2024-04-09 |
Family
ID=74167501
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910648785.6A Active CN112241024B (en) | 2019-07-18 | 2019-07-18 | Method for improving signal-to-noise ratio of seismic data, computer storage medium and system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN112241024B (en) |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| GB1392014A (en) * | 1972-03-01 | 1975-04-23 | Texaco Development Corp | Method for enhancing seismic data |
| US4535417A (en) * | 1982-12-23 | 1985-08-13 | Standard Oil Company | Method and apparatus for digital time-variant filtering |
| CN103913770A (en) * | 2014-03-27 | 2014-07-09 | 中国石油集团川庆钻探工程有限公司地球物理勘探公司 | Method for processing seismic data based on VSP data |
| CN104635264A (en) * | 2014-08-28 | 2015-05-20 | 中国石油天然气股份有限公司 | Processing method and apparatus of pre-stack seismic data |
| CN106569262A (en) * | 2015-10-12 | 2017-04-19 | 中国石油化工股份有限公司 | Background speed model reconstructing method in absence of low frequency earthquake data |
| CN107967240A (en) * | 2017-11-23 | 2018-04-27 | 大连理工大学 | Shatter-proof time-histories acceleration optimization algorithm based on artificial ground shaking generating process |
Family Cites Families (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US6950371B2 (en) * | 2003-05-20 | 2005-09-27 | Chevron U.S.A. Inc. | Method for signal-to-noise ratio enhancement of seismic data using frequency dependent true relative amplitude noise attenuation |
| US9250340B2 (en) * | 2012-02-28 | 2016-02-02 | Pgs Geophysical As | Methods and apparatus for automated noise removal from seismic data |
-
2019
- 2019-07-18 CN CN201910648785.6A patent/CN112241024B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| GB1392014A (en) * | 1972-03-01 | 1975-04-23 | Texaco Development Corp | Method for enhancing seismic data |
| US4535417A (en) * | 1982-12-23 | 1985-08-13 | Standard Oil Company | Method and apparatus for digital time-variant filtering |
| CN103913770A (en) * | 2014-03-27 | 2014-07-09 | 中国石油集团川庆钻探工程有限公司地球物理勘探公司 | Method for processing seismic data based on VSP data |
| CN104635264A (en) * | 2014-08-28 | 2015-05-20 | 中国石油天然气股份有限公司 | Processing method and apparatus of pre-stack seismic data |
| CN106569262A (en) * | 2015-10-12 | 2017-04-19 | 中国石油化工股份有限公司 | Background speed model reconstructing method in absence of low frequency earthquake data |
| CN107967240A (en) * | 2017-11-23 | 2018-04-27 | 大连理工大学 | Shatter-proof time-histories acceleration optimization algorithm based on artificial ground shaking generating process |
Non-Patent Citations (1)
| Title |
|---|
| 《子波一致性校正方法在地震资料处理中的应用》;陈志卿等;石油物探;第45卷(第2期);第169-170页 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN112241024A (en) | 2021-01-19 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN106597532B (en) | Pre-stack seismic data frequency band expanding method combining well data and horizon data | |
| CN108845357B (en) | Method for estimating formation equivalent quality factor based on synchronous extrusion wavelet transform | |
| WO2005017564A1 (en) | Dip value in seismic images | |
| AU2014345427A1 (en) | Method and device for processing seismic signals | |
| WO2012134496A4 (en) | Improved time-based processing of broadband borehole acoustic data | |
| Wang et al. | A simple approach to nonstationary source waveform estimation in seismic records | |
| CN104635264B (en) | The processing method of earthquake data before superposition and equipment | |
| CN103675904A (en) | Method and device for processing well seismic matching interpretive target | |
| CN112817040B (en) | Broadband quasi-zero phase deconvolution processing method, device, electronic equipment and medium | |
| CN105277984A (en) | Time-shifting seismic mutual constraint frequency consistency processing method | |
| CN112241024B (en) | Method for improving signal-to-noise ratio of seismic data, computer storage medium and system | |
| CN112782763B (en) | Seismic quality factor estimation method, device, equipment and storage medium | |
| CN112578438A (en) | Seismic wavelet extraction method and system | |
| CN113219539A (en) | Method and device for removing borehole wave interference in optical fiber acoustic sensing seismic data | |
| CN112764108B (en) | Novel seismic data noise suppression algorithm based on improved empirical wavelet transformation | |
| CN111929726B (en) | Seismic coherent data volume processing method and device | |
| CN111665536B (en) | Well depth design method based on quantitative constraint of micro logging wavelets | |
| CN108957550B (en) | TSP strong industrial electric interference suppression method based on SVD-ICA | |
| CN113138419B (en) | Method and device for extracting downlink wavelet and attenuation parameters | |
| Zhang et al. | Noise suppression of GPR data using Variational Mode Decomposition | |
| CN113391353A (en) | Seismic data processing method and device | |
| CN112526611A (en) | Method and device for extracting surface seismic wave quality factor | |
| CN113126163B (en) | Five-dimensional seismic data noise attenuation method and device | |
| CN114428282B (en) | Seismic signal time-frequency conversion method based on downscaling S conversion | |
| CN113359187B (en) | Wavelet sidelobe elimination method for seismic data |
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 |