CN113495297A - Abnormal first arrival wave correction method and device - Google Patents
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Abstract
The invention provides an abnormal first-motion wave correction method and device, wherein the method comprises the following steps: classifying the seismic data according to positive and negative waveforms; determining first arrival time of the classified seismic data according to an energy ratio; determining abnormal first-arrival waves and reliable first-arrival waves according to the number of sampling points of positive and negative waveforms of the first-arrival time; constructing an evaluation function based on an ant colony algorithm according to the reliable first-arrival wave parameters; according to the evaluation function, calculating the pheromone concentration value left by the ant in each path to form an pheromone concentration path; and correcting the abnormal first-motion wave according to the pheromone concentration path by taking the reliable first-motion wave as a reference. The method effectively corrects the abnormal first-motion waves of the seismic data with large data volume and low signal-to-noise ratio.
Description
Technical Field
The invention relates to the technical field of processing of geophysical exploration data of petroleum, in particular to a method and a device for correcting abnormal first-motion waves.
Background
With the application of high-density and high-efficiency acquisition technology becoming more and more extensive, the target area of exploration gradually turns to areas with complex surface conditions, and the first arrival wave picking work of low signal-to-noise ratio mass data faces huge challenges. The traditional method needs a great deal of manpower and time to correct the abnormal first arrival waves, and a great deal of interaction influences the picking precision and efficiency. Therefore, the method for correcting abnormal first-arrival waves in the automatic first-arrival wave picking process is very necessary for the data with low signal-to-noise ratio and large data volume.
At present, a plurality of methods for automatically picking up first-arrival waves exist, Peraldi and element propose an inflection point correction method, which considers that seismic traces and reference traces are cross-correlated, time shift set first-arrival time corresponding to a normalized cross-correlation function maximum value is close to the picking-up precision of wavelets; gelchinskyan and Shtivevelman proposes a correlation method, and assumes that the pulse shape of each channel does not change, but the actual situation does not conform to the assumption; stevebson provides a short-time window energy average value and long-time window average value energy ratio method to determine a first-arrival wave (STA/LTA), the energy ratio method is widely applied due to simplicity and practicality, but under the condition of complex near-surface, the accuracy of the automatic first-arrival wave pickup method can not meet the requirement due to large changes of first-arrival wave energy characteristics, waveform characteristics and phase characteristics and frequent noise interference; the picking precision of the energy ratio method proposed by Coppens depends on the signal-to-noise ratio of seismic data; the fractal dimension method proposed by Fabio Boschetti has a large relation between the picking precision and the selection of the operation speed and parameters, and the calculation amount is large; the neural network algorithm proposed by Murat is slow in learning speed and complex to realize; the complex statistical method proposed by Hatherly is influenced by factors such as similarity between seismic traces; the automatic quality control technology of the first-arrival wave proposed by Khan is suitable for a exploration area with little topographic relief change, and the method cannot effectively pick up the first-arrival wave for the undulating surface of a mountain land and a loess highland; the spline interpolation technology proposed by pankrin et al is a reliable first-arrival linear interpolation for abnormal first-arrival utilization, and the technology is only suitable for areas with relatively stable thickness and speed space of the near surface, and the area with low signal-to-noise ratio of the first-arrival due to the complex near surface structure fails.
In summary, the prior art cannot realize high-precision abnormal first-arrival correction for the first-arrival waves of seismic data, especially for the first-arrival waves of seismic data with large data volume and low signal-to-noise ratio.
Disclosure of Invention
The embodiment of the invention provides an abnormal first-arrival wave correction method, which is used for realizing high-precision abnormal first-arrival wave correction and comprises the following steps:
classifying the seismic data according to positive and negative waveforms;
determining first arrival time of the classified seismic data according to an energy ratio;
determining abnormal first-arrival waves and reliable first-arrival waves according to the number of sampling points of positive and negative waveforms of the first-arrival time;
constructing an evaluation function based on an ant colony algorithm according to the reliable first-arrival wave parameters;
calculating the concentration value of pheromones left by the ants in each channel according to the evaluation function;
and correcting the abnormal first-motion wave according to the pheromone concentration path by taking the reliable first-motion wave as a reference.
The embodiment of the present invention further provides an abnormal first-arrival wave correction device, configured to implement high-precision abnormal first-arrival wave correction, including:
the data classification module is used for classifying the seismic data according to positive and negative waveforms;
the first-arrival time determining module is used for determining the first-arrival time of the classified seismic data according to the energy ratio;
the first-arrival wave determining module is used for determining abnormal first-arrival waves and reliable first-arrival waves according to the number of sampling points of the positive and negative waveforms of the first-arrival time;
the evaluation function construction module is used for constructing an evaluation function based on an ant colony algorithm according to the reliable first-arrival wave parameters;
the pheromone concentration path determining module is used for calculating the pheromone concentration value left by the ants in each path according to the evaluation function to form an pheromone concentration path;
and the correction module is used for correcting the abnormal first-motion wave according to the pheromone concentration path by taking the reliable first-motion wave as a reference.
The embodiment of the invention also provides computer equipment which comprises a memory, a processor and a computer program which is stored on the memory and can run on the processor, wherein the processor realizes the abnormal first arrival wave correction method when executing the computer program.
An embodiment of the present invention further provides a computer-readable storage medium, where a computer program for executing the above abnormal first-arrival wave correction method is stored in the computer-readable storage medium.
The embodiment of the invention classifies the seismic data according to positive and negative waveforms; determining the first-arrival time of the classified seismic data according to the energy ratio, and improving the accuracy of single-channel first-arrival wave pickup; according to the sampling points of the positive and negative waveforms of the first arrival time, the abnormal first arrival waves and the reliable first arrival waves can be accurately determined; according to the reliable first-arrival wave parameters, an evaluation function is constructed based on an ant colony algorithm, and the method is more efficient and accurate in calculating seismic data with large data volume and low signal-to-noise ratio; according to the evaluation function, calculating the pheromone concentration value left by the ant in each path to form an pheromone concentration path; and the abnormal first-arrival wave is corrected according to the pheromone concentration path by taking the reliable first-arrival wave as a reference, so that the high-precision abnormal first-arrival wave correction is realized, and the automatic picking precision of the first-arrival wave is improved.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without creative efforts. In the drawings:
fig. 1 is a flowchart of an abnormal first-arrival correction method according to an embodiment of the present invention;
fig. 2 is a schematic structural diagram of an abnormal first-motion wave correction apparatus according to an embodiment of the present invention.
FIG. 3 is a schematic illustration of seismic single shot data in an embodiment of the invention;
FIG. 4 is a schematic illustration of seismic data sorted by positive and negative waveforms in an embodiment of the invention;
FIG. 5 is a diagram illustrating a single original record according to an embodiment of the present invention;
FIG. 6 is a schematic illustration of a single trace classified seismic record in accordance with an embodiment of the present invention;
FIG. 7 is a graph illustrating a single pass energy ratio curve according to an embodiment of the present invention;
FIG. 8 is a diagram illustrating the result of picking up the first arrival time using the energy ratio formula according to an embodiment of the present invention;
FIG. 9 is a diagram illustrating a result of eliminating abnormal first-arrival time by using sampling points of positive and negative waveforms of the first-arrival time according to an embodiment of the present invention;
FIG. 10 is a schematic diagram of a time window for determining the first arrival time of ant colony tracking according to an embodiment of the present invention;
FIG. 11 is a diagram illustrating a result of a first arrival time of a final pick in an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The embodiment of the invention provides an abnormal first-arrival wave correction method, which can realize high-precision abnormal first-arrival wave correction, improve the automatic first-arrival wave pickup precision and particularly can be used for correcting abnormal first-arrival waves of seismic data with large data volume and low signal-to-noise ratio. Fig. 1 is a flowchart of an abnormal first arrival correction method according to an embodiment of the present invention. As shown in fig. 1, the method for correcting an abnormal first-arrival wave in the embodiment of the present invention may include:
step 101: classifying the seismic data according to positive and negative waveforms;
step 102: determining first arrival time of the classified seismic data according to an energy ratio;
step 103: determining abnormal first-arrival waves and reliable first-arrival waves according to the number of sampling points of positive and negative waveforms of the first-arrival time;
step 104: constructing an evaluation function based on an ant colony algorithm according to the reliable first-arrival wave parameters;
step 105: calculating the concentration value of pheromones left by the ants in each channel according to the evaluation function;
step 106: and correcting the abnormal first-motion wave according to the pheromone concentration path by taking the reliable first-motion wave as a reference.
As can be known from the process shown in FIG. 1, the embodiment of the invention classifies the seismic data according to the positive and negative waveforms; determining the first-arrival time of the classified seismic data according to the energy ratio, and improving the accuracy of single-channel first-arrival wave pickup; according to the sampling points of the positive and negative waveforms of the first arrival time, the abnormal first arrival waves and the reliable first arrival waves can be accurately determined; according to the reliable first-arrival wave parameters, an evaluation function is constructed based on an ant colony algorithm, and the method is more efficient and accurate in calculating seismic data with large data volume and low signal-to-noise ratio; according to the evaluation function, calculating the pheromone concentration value left by the ant in each path to form an pheromone concentration path; and the abnormal first-arrival wave is corrected according to the pheromone concentration path by taking the reliable first-arrival wave as a reference, so that the high-precision abnormal first-arrival wave correction is realized, and the automatic picking precision of the first-arrival wave is improved.
In specific implementation, the seismic data is classified according to positive and negative waveforms. In the embodiment, single-shot seismic data can be excited and collected and recorded, the number of tracks is m, and the number of sampling points of each track is n. The seismic data is then sorted by positive waveform, and the negative waveform is padded to zeros. In another embodiment, the seismic data may also be sorted by negative waveform, with positive waveforms padded to zeros. The following examples are described in terms of positive waveform classification.
In specific implementation, after seismic data are classified, the first arrival time of the classified seismic data is determined according to the energy ratio, and the accuracy of single-channel first arrival wave pickup can be improved. In an embodiment, the energy ratio of each sampling point may be calculated on each classified track to obtain an energy ratio curve of each track; and determining the sampling point number corresponding to the maximum value of each energy ratio curve as the peak point position of the first arrival wave, wherein the time corresponding to the peak point position of the first arrival wave is the first arrival time.
The method for calculating the energy ratio of the ith sampling point in the classified seismic data may be performed according to the following formula:
wherein w is the number of calculation points of the sliding time window, i is the seismic channel number, i is more than or equal to 1 and less than or equal to m, r is the sampling point number of the corresponding ith channel, r is more than or equal to 1 and less than or equal to n, n is the sampling point number of one channel, alpha is a stability factor, the default value is 0.1, beta is a number greater than 0, and the default value is 1.0.
In specific implementation, after the first arrival time is determined, the abnormal first arrival wave and the reliable first arrival wave are determined according to the number of sampling points of the positive and negative waveforms of the first arrival time. In an embodiment, determining the abnormal first-arrival wave and the reliable first-arrival wave according to the number of sampling points of the positive and negative waveforms of the first-arrival time may include: calculating the sampling point number of positive and negative waveforms of the first arrival time and the ratio of the sampling point number of the positive and negative waveforms; respectively carrying out linear fitting on the ratio of the sampling point number of the positive and negative waveforms and the sampling point number of the positive waveform by using a sliding time window; and determining the abnormal first-motion wave and the reliable first-motion wave according to the fitting result. For example, the length of a sliding time window is set to be L, the sliding step length is set to be 1, and the sliding time window is used for respectively carrying out linear fitting on the ratio of the number of sampling points of the positive and negative waveforms and the number of sampling points of the positive waveforms; the abnormal first-arrival wave and the reliable first-arrival wave can be accurately determined according to the fitting result.
In an embodiment, determining the abnormal first-arrival wave and the reliable first-arrival wave according to the fitting result may include: calculating the ratio of the sampling points of the positive and negative waveforms of each first arrival time in the sliding time window and the difference value between the sampling points of the positive waveforms and the fitting straight line; determining the seismic traces with the difference values larger than the threshold value as abnormal first-motion waves corresponding to the first-motion waves; and determining the seismic traces with the difference value not greater than the threshold value as reliable first-arrival waves corresponding to the first-arrival waves.
In specific implementation, after the reliable first-arrival waves are determined, an evaluation function is constructed based on the ant colony algorithm according to the reliable first-arrival wave parameters. The ant colony algorithm can accurately and efficiently calculate seismic data with large data volume and low signal-to-noise ratio. The reliable first arrival parameters in the embodiment may include: the waveform, energy and steepness parameters of the first-arrival wave are reliable. Constructing an evaluation function based on the ant colony algorithm according to the reliable first arrival wave parameters may include: and constructing an evaluation function based on an ant colony algorithm according to the waveform, energy and gradient parameters of the reliable first-motion wave.
In an embodiment, constructing the evaluation function based on the ant colony algorithm according to the waveform, energy and steepness parameters of the reliable first arrival wave may include: calculating the average value of the positive waveform sampling points of the initial waves with the reliable preset channel number and the average value of the peak point energy; calculating the gradient of the corresponding first-arrival time of the reliable first-arrival waves adjacent to the preset channel number; and (3) presetting the steepness of the corresponding first-arrival time of the reliable first-arrival waves adjacent to the channel number according to the average value of the positive waveform sampling points and the average value of the peak point energy of the reliable first-arrival waves of the preset channel number, and constructing an evaluation function based on an ant colony algorithm.
The following describes a process of constructing an evaluation function by way of specific implementation, and the specific calculation method in this example is as follows:
starting to search for abnormal first-motion wave by using the first-path first-motion wave as a starting point, if the kth1The track is the initial position of the abnormal first arrival wave, and the track is searched backwards by sliding one track by one track until the kth2Trace is an abnormal first arrival wave, but kth2+1 channel as reliable first arrival wave, will be the k-th channel1Way to k2The first-arrival waves between the traces are labeled as anomalous first-arrival bands, and the anomalous first-arrival waves in each shot are similarly labeled. Determine the k-th1The nearest reliable first arrival wave of the channel anomaly first arrival wave is the kth wave1-1 passes, respectively calculating the k-th1Lane-1 and k1-number of samples of positive waveform of wavelet where reliable first arrival exists between channels, arbitrary k1-the number of sampling points of the positive waveform of the wavelet in which the d-channel reliable first arrival is located is
Then it is equal to k1The average value of the number of positive waveform sampling points of the wavelets where 1 adjacent channel is the reliable first arrival is as follows:
in the formula, d is a positive integer which is greater than or equal to 1 and less than or equal to l, and the default value of l is 5.
Calculation and k1-the mean of the peak point energies corresponding to 1 adjacent reliable first arrival wave is:
in the formula
Is the k-th1D is the peak point energy corresponding to the reliable first arrival wave, and d is a positive integer greater than or equal to 1 and less than or equal to l, and the default value of l is 5.
At the k-th1Taking the-1 channel as a starting point, and sequentially calculating the corresponding first-arrival time of adjacent reliable first-arrival waves
The difference of (a) is:
the gradient of the first arrival time can be corresponded to the adjacent reliable first arrival waves by the following formula:
in the formula
Is the k-th1D is the first arrival time corresponding to the reliable first arrival wave, and d is a positive integer greater than or equal to 1 and less than or equal to l, and the default value of l is 5.
According to the average value of positive waveform sampling points and the average value of peak point energy of the reliable first-arrival waves of the preset channel number, the steepness of the corresponding first-arrival time of the reliable first-arrival waves adjacent to the preset channel number is constructed according to the following formula based on an ant colony algorithm:
in the formula
Represents the mean value of the energies of the wavelet peak points of the tracked reliable first-motion waves near the position of the ant,
represents the average value of the sampling points included in the positive waveform of the tracked reliable first-arrival wavelet near the position of the ant,
indicating the next adjacent lane where ants are at a given steepness
And the energy of the wave peak point of the first arrival wave in the range of the time window w,
indicating the next adjacent lane where ants are at a given steepness
And the number of samples included in the positive waveform of the reliable first-arrival wavelet over the time window w,
is shown in
The surrounding already tracks the steepness of the reliable first arrival wave.
In specific implementation, after an evaluation function is constructed, the pheromone concentration value left by the ant in each channel is calculated according to the evaluation function, and an pheromone concentration path is formed. In an embodiment, calculating a pheromone concentration value left by an ant in each channel according to the evaluation function to form a pheromone concentration path may include:
randomly placing ants at the position of the reliable first arrival wave peak point in the selected first arrival time window;
randomly placing ants at the positions of the peak points of the wavelets of the reliable first-motion waves or the abnormal first-motion waves for the abnormal first-motion waves in the selected first-motion time window;
and searching each ant on the seismic data classified according to the positive and negative waveforms one by one according to an evaluation function, searching a first-arrival wave peak point in a selected first-arrival time window according to the gradient of a given first-arrival wave in the next adjacent channel, and forming an pheromone concentration path by taking the first-arrival wave peak point as an identifier.
In specific implementation, the abnormal first-motion wave is corrected by taking the reliable first-motion wave as a reference according to the obtained pheromone concentration path.
Based on the same inventive concept, the embodiment of the present invention further provides an abnormal first-arrival wave correction apparatus, as described in the following embodiments. Because the principle of the device for solving the problems is similar to that of the abnormal first-arrival wave correction method, the implementation of the device can refer to the implementation of the abnormal first-arrival wave correction method, and repeated details are not repeated.
Fig. 2 is a schematic structural diagram of an abnormal first-motion wave correction device according to an embodiment of the present invention. As shown in fig. 2, the abnormal first-arrival correction apparatus according to the embodiment of the present invention may include:
a data classification module 201, configured to classify the seismic data according to positive and negative waveforms;
a first arrival time determining module 202, configured to determine a first arrival time according to an energy ratio for the classified seismic data;
a first-arrival wave determining module 203, configured to determine an abnormal first-arrival wave and a reliable first-arrival wave according to the number of sampling points of the positive and negative waveforms of the first-arrival time;
an evaluation function constructing module 204, configured to construct an evaluation function based on an ant colony algorithm according to the reliable first-arrival wave parameters;
the pheromone concentration path determining module 205 is configured to calculate a pheromone concentration value left by each ant according to the evaluation function to form a pheromone concentration path;
and a correction module 206, configured to correct the abnormal first-motion wave according to the pheromone concentration path by using the reliable first-motion wave as a reference.
In one embodiment, the data classification module 201 may be specifically configured to:
classifying the seismic data according to positive waveforms, and filling negative waveforms into zeros;
alternatively, the seismic data is sorted by negative waveform, and the positive waveform is padded to zero.
In an embodiment, the first arrival time determining module 202 may be specifically configured to:
calculating the energy ratio of each sampling point on each classified track to obtain an energy ratio curve of each track;
and determining the sampling point number corresponding to the maximum value of each energy ratio curve as the peak point position of the first arrival wave, wherein the time corresponding to the peak point position of the first arrival wave is the first arrival time.
In an embodiment, the first arrival wave determining module 203 may specifically be configured to:
calculating the sampling point number of positive and negative waveforms of the first arrival time and the ratio of the sampling point number of the positive and negative waveforms;
respectively carrying out linear fitting on the ratio of the sampling point number of the positive and negative waveforms and the sampling point number of the positive waveform by using a sliding time window;
and determining the abnormal first-motion wave and the reliable first-motion wave according to the fitting result.
In an embodiment, the first arrival wave determining module 203 may specifically be configured to:
calculating the ratio of the sampling points of the positive and negative waveforms of each first arrival time in the sliding time window and the difference value between the sampling points of the positive waveforms and the fitting straight line;
determining the seismic traces with the difference values larger than the threshold value as abnormal first-motion waves corresponding to the first-motion waves;
and determining the seismic traces with the difference value not greater than the threshold value as reliable first-arrival waves corresponding to the first-arrival waves.
In one embodiment, the evaluation function constructing module 204 may be specifically configured to:
and constructing an evaluation function based on an ant colony algorithm according to the waveform, energy and gradient parameters of the reliable first-motion wave.
In one embodiment, the evaluation function constructing module 204 may be specifically configured to:
calculating the average value of the positive waveform sampling points of the initial waves with the reliable preset channel number and the average value of the peak point energy;
calculating the gradient of the corresponding first-arrival time of the reliable first-arrival waves adjacent to the preset channel number;
and (3) presetting the steepness of the corresponding first-arrival time of the reliable first-arrival waves adjacent to the channel number according to the average value of the positive waveform sampling points and the average value of the peak point energy of the reliable first-arrival waves of the preset channel number, and constructing an evaluation function based on an ant colony algorithm.
In one embodiment, the evaluation function constructing module 204 may be specifically configured to construct the evaluation function according to the following formula:
in the formula
Represents the mean value of the energies of the wavelet peak points of the tracked reliable first-motion waves near the position of the ant,
represents the average value of the sampling points included in the positive waveform of the tracked reliable first-arrival wavelet near the position of the ant,
indicating the next adjacent lane where ants are at a given steepness
And the energy of the wave peak point of the first arrival wave in the range of the time window w,
indicating the next adjacent lane where ants are at a given steepness
And the number of samples included in the positive waveform of the reliable first-arrival wavelet over the time window w,
is shown in
The surrounding already tracks the steepness of the reliable first arrival wave.
In one embodiment, the pheromone concentration path determining module 205 may be specifically configured to:
randomly placing ants at the position of the reliable first arrival wave peak point in the selected first arrival time window;
randomly placing ants at the positions of the peak points of the wavelets of the reliable first-motion waves or the abnormal first-motion waves for the abnormal first-motion waves in the selected first-motion time window;
and searching each ant on the seismic data classified according to the positive and negative waveforms one by one according to an evaluation function, searching a first-arrival wave peak point in a selected first-arrival time window according to the gradient of a given first-arrival wave in the next adjacent channel, and forming an pheromone concentration path by taking the first-arrival wave peak point as an identifier.
The following describes an abnormal first arrival wave correction method according to an embodiment of the present invention, which includes the following steps:
1. exciting and collecting and recording single-shot seismic data, wherein the single shot has 30 arrays, the number of tracks is 8400, the sampling interval is 4 milliseconds, the number of sampling points of each track is 500, as shown in fig. 3, fig. 3 is a schematic diagram of the 2 nd array of the collected seismic single-shot data, in fig. 3, FFID is a file number, and CHAN is the number of tracks;
classifying the seismic data according to positive waveforms, and filling negative waveforms into zeros, as shown in fig. 4, where fig. 4 is a schematic diagram of the seismic data classified according to the positive and negative waveforms;
taking a segment of original recording between 88ms and 572ms of the 460 th track, as shown in fig. 5, fig. 5 is a schematic diagram of a single-track original recording, in which the position of the peak point of the first-arrival wave is at the position of 312 ms.
The original recording between 88ms and 572ms of the 460 th trace is classified according to the positive waveform, as shown in fig. 6, and fig. 6 is a schematic diagram of the seismic recording after single trace classification.
2. The single-channel energy ratio curve of the data between 88ms and 572ms of the 460 th channel is calculated by using the formula (1), and the result is shown in fig. 7, fig. 7 shows a single-channel energy ratio graph, wherein the maximum point of the energy ratio curve is at the position of 312ms, which corresponds to the position of the peak point of the original recorded first-arrival wave of fig. 5, and the first-arrival time is 312 ms.
The first arrival time results of single shot data picked up by using energy ratio are shown in fig. 8, wherein the 342 th to 352 th lanes, 367 th to 376 th lanes, 389 th to 394 th lanes, 511 th to 516 th lanes and 536 th to 560 th lanes are abnormal first arrival waves, the signal to noise ratio of the first arrival waves is low, particularly, the 545 th to 560 th lanes are noise lanes, and no effective first arrival wave exists.
3. And (3) according to the data obtained in the step (2), determining abnormal first-arrival waves and reliable first-arrival waves by calculating the number of sampling points of the positive and negative waveforms of the first-arrival time. As shown in fig. 9, fig. 9 is a schematic diagram illustrating the result of eliminating abnormal first-arrival time by using the sampling points of the positive and negative waveforms of the first-arrival time. In the figure, abnormal first-arrival waves of lanes 342 to 352, 367 to 376, 389 to 394, 511 to 516 and 536 to 560 can be effectively identified.
4. From the above data results, an evaluation function is constructed using equation (6). Setting the data in the negative waveform in the data classified according to the positive and negative waveforms in the step 2 as 0, keeping the data of the positive waveform unchanged, determining the time window range of the first-arrival wave by using spatial interpolation, wherein the time window for determining the ant colony tracking first-arrival time is shown in fig. 10, and two black lines are the time window range of the first-arrival wave.
5. According to the evaluation function, calculating the pheromone concentration value left by the ant on each path to form an pheromone concentration path
6. And connecting the abnormal first arrivals according to the pheromone concentration path by taking the first arrivals with high reliability as a reference, and determining the positions of the wave peak points of the first arrivals in a local range. The final picked first arrival time results are shown in fig. 11, and the black line segment is the corresponding first arrival time of each track.
It can be seen that, in this example, the abnormal first arrival waves of the lanes 342 to 352, the lanes 367 to 376, the lanes 389 to 394 and the lanes 511 to 516 are all corrected to the correct positions. The abnormal first-arrival waves of the 536 th to 544 th tracks are also corrected to the position of the correct first-arrival time, the 545 th to 560 th tracks are noise tracks, no effective first-arrival time exists, and the first-arrival time is 0.
The embodiment of the invention also provides computer equipment which comprises a memory, a processor and a computer program which is stored on the memory and can run on the processor, wherein the processor realizes the abnormal first arrival wave correction method when executing the computer program.
An embodiment of the present invention further provides a computer-readable storage medium, where a computer program for executing the above abnormal first-arrival wave correction method is stored in the computer-readable storage medium.
In summary, the embodiment of the invention classifies the seismic data according to the positive and negative waveforms; determining the first-arrival time of the classified seismic data according to the energy ratio, and improving the accuracy of single-channel first-arrival wave pickup; according to the sampling points of the positive and negative waveforms of the first arrival time, the abnormal first arrival waves and the reliable first arrival waves can be accurately determined; according to the reliable first-arrival wave parameters, an evaluation function is constructed based on an ant colony algorithm, and the method is more efficient and accurate in calculating seismic data with large data volume and low signal-to-noise ratio; according to the evaluation function, calculating the pheromone concentration value left by the ant in each path to form an pheromone concentration path; and the abnormal first-arrival wave is corrected according to the pheromone concentration path by taking the reliable first-arrival wave as a reference, so that the high-precision abnormal first-arrival wave correction is realized, and the automatic picking precision of the first-arrival wave is improved.
It should be apparent to those skilled in the art that embodiments of the present invention may be provided as a method, or computer program product. Accordingly, the present invention may take the form of an entirely software embodiment. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The above description is only a preferred embodiment of the present invention, and is not intended to limit the present invention, and various modifications and changes may be made to the embodiment of the present invention by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (18)
1. An abnormal first arrival correction method, comprising:
classifying the seismic data according to positive and negative waveforms;
determining first arrival time of the classified seismic data according to an energy ratio;
determining abnormal first-arrival waves and reliable first-arrival waves according to the number of sampling points of positive and negative waveforms of the first-arrival time;
constructing an evaluation function based on an ant colony algorithm according to the reliable first-arrival wave parameters;
according to the evaluation function, calculating the pheromone concentration value left by the ant in each path to form an pheromone concentration path;
and correcting the abnormal first-motion wave according to the pheromone concentration path by taking the reliable first-motion wave as a reference.
2. The method of claim 1, wherein classifying the seismic data into positive and negative waveforms comprises:
classifying the seismic data according to positive waveforms, and filling negative waveforms into zeros;
alternatively, the seismic data is sorted by negative waveform, and the positive waveform is padded to zero.
3. The method of claim 1, wherein determining the first arrival time from the sorted seismic data by energy ratio comprises:
calculating the energy ratio of each sampling point on each classified track to obtain an energy ratio curve of each track;
and determining the sampling point number corresponding to the maximum value of each energy ratio curve as the peak point position of the first arrival wave, wherein the time corresponding to the peak point position of the first arrival wave is the first arrival time.
4. The method of claim 1, wherein determining abnormal first-arrival waves and reliable first-arrival waves based on the number of sampling points of the positive and negative waveforms of the first-arrival times comprises:
calculating the sampling point number of positive and negative waveforms of the first arrival time and the ratio of the sampling point number of the positive and negative waveforms;
respectively carrying out linear fitting on the ratio of the sampling point number of the positive and negative waveforms and the sampling point number of the positive waveform by using a sliding time window;
and determining the abnormal first-motion wave and the reliable first-motion wave according to the fitting result.
5. The method of claim 4, wherein determining anomalous first-arrival waves and reliable first-arrival waves from the fitting results comprises:
calculating the ratio of the sampling points of the positive and negative waveforms of each first arrival time in the sliding time window and the difference value between the sampling points of the positive waveforms and the fitting straight line;
determining the seismic traces with the difference values larger than the threshold value as abnormal first-motion waves corresponding to the first-motion waves;
and determining the seismic traces with the difference value not greater than the threshold value as reliable first-arrival waves corresponding to the first-arrival waves.
6. The method of claim 1, wherein constructing an evaluation function based on an ant colony algorithm based on reliable first-arrival parameters comprises:
and constructing an evaluation function based on an ant colony algorithm according to the waveform, energy and gradient parameters of the reliable first-motion wave.
7. The method of claim 6, wherein constructing the merit function based on an ant colony algorithm from the waveform, energy, and steepness parameters of the reliable first arrival wave comprises:
calculating the average value of the positive waveform sampling points of the initial waves with the reliable preset channel number and the average value of the peak point energy;
calculating the gradient of the corresponding first-arrival time of the reliable first-arrival waves adjacent to the preset channel number;
and (3) presetting the steepness of the corresponding first-arrival time of the reliable first-arrival waves adjacent to the channel number according to the average value of the positive waveform sampling points and the average value of the peak point energy of the reliable first-arrival waves of the preset channel number, and constructing an evaluation function based on an ant colony algorithm.
8. The method of claim 7, wherein the merit function is constructed as follows:
in the formula
Represents the mean value of the energies of the wavelet peak points of the tracked reliable first-motion waves near the position of the ant,
represents the average value of the sampling points included in the positive waveform of the tracked reliable first-arrival wavelet near the position of the ant,
indicating the next adjacent lane where ants are at a given steepness
And the energy of the wave peak point of the first arrival wave in the range of the time window w,
indicating the next adjacent lane where ants are at a given steepness
And the number of samples included in the positive waveform of the reliable first-arrival wavelet over the time window w,
is shown in
The surrounding already tracks the steepness of the reliable first arrival wave.
9. The method as claimed in claim 1, wherein calculating the pheromone concentration value left by the ant in each passage according to the evaluation function to form a pheromone concentration path comprises:
randomly placing ants at the position of the reliable first arrival wave peak point in the selected first arrival time window;
randomly placing ants at the positions of the peak points of the wavelets of the reliable first-motion waves or the abnormal first-motion waves for the abnormal first-motion waves in the selected first-motion time window;
and searching each ant on the seismic data classified according to the positive and negative waveforms one by one according to an evaluation function, searching a first-arrival wave peak point in a selected first-arrival time window range according to the gradient of a given first-arrival wave in the next adjacent channel, and forming an pheromone concentration path by taking the first-arrival wave peak point as an identifier.
10. An abnormal first arrival correction apparatus, comprising:
the data classification module is used for classifying the seismic data according to positive and negative waveforms;
the first-arrival time determining module is used for determining the first-arrival time of the classified seismic data according to the energy ratio;
the first-arrival wave determining module is used for determining abnormal first-arrival waves and reliable first-arrival waves according to the number of sampling points of the positive and negative waveforms of the first-arrival time;
the evaluation function construction module is used for constructing an evaluation function based on an ant colony algorithm according to the reliable first-arrival wave parameters;
the pheromone concentration path determining module is used for calculating the pheromone concentration value left by the ants in each path according to the evaluation function to form an pheromone concentration path;
and the correction module is used for correcting the abnormal first-motion wave according to the pheromone concentration path by taking the reliable first-motion wave as a reference.
11. The apparatus of claim 10, wherein the first arrival determination module is specifically configured to:
calculating the sampling point number of positive and negative waveforms of the first arrival time and the ratio of the sampling point number of the positive and negative waveforms;
respectively carrying out linear fitting on the ratio of the sampling point number of the positive and negative waveforms and the sampling point number of the positive waveform by using a sliding time window;
and determining the abnormal first-motion wave and the reliable first-motion wave according to the fitting result.
12. The apparatus of claim 11, wherein the first arrival determination module is specifically configured to:
calculating the ratio of the sampling points of the positive and negative waveforms of each first arrival time in the sliding time window and the difference value between the sampling points of the positive waveforms and the fitting straight line;
determining the seismic traces with the difference values larger than the threshold value as abnormal first-motion waves corresponding to the first-motion waves;
and determining the seismic traces with the difference value not greater than the threshold value as reliable first-arrival waves corresponding to the first-arrival waves.
13. The apparatus of claim 10, wherein the merit function construction module is specifically configured to:
and constructing an evaluation function based on an ant colony algorithm according to the waveform, energy and gradient parameters of the reliable first-motion wave.
14. The apparatus of claim 13, wherein the merit function construction module is specifically configured to:
calculating the average value of the positive waveform sampling points of the initial waves with the reliable preset channel number and the average value of the peak point energy;
calculating the gradient of the corresponding first-arrival time of the reliable first-arrival waves adjacent to the preset channel number;
and (3) presetting the steepness of the corresponding first-arrival time of the reliable first-arrival waves adjacent to the channel number according to the average value of the positive waveform sampling points and the average value of the peak point energy of the reliable first-arrival waves of the preset channel number, and constructing an evaluation function based on an ant colony algorithm.
15. The apparatus of claim 14, wherein the merit function constructing module is specifically configured to construct the merit function according to the following formula:
in the formula
Represents the mean value of the energies of the wavelet peak points of the tracked reliable first-motion waves near the position of the ant,
represents the average value of the sampling points included in the positive waveform of the tracked reliable first-arrival wavelet near the position of the ant,
indicating the next adjacent lane where ants are at a given steepness
And the energy of the wave peak point of the first arrival wave in the range of the time window w,
indicating the next adjacent lane where ants are at a given steepness
And the number of samples included in the positive waveform of the reliable first-arrival wavelet over the time window w,
is shown in
The surrounding already tracks the steepness of the reliable first arrival wave.
16. The apparatus of claim 10, wherein the pheromone concentration path determining module is specifically configured to:
randomly placing ants at the position of the reliable first arrival wave peak point in the selected first arrival time window;
randomly placing ants at the positions of the peak points of the wavelets of the reliable first-motion waves or the abnormal first-motion waves for the abnormal first-motion waves in the selected first-motion time window;
and searching each ant on the seismic data classified according to the positive and negative waveforms one by one according to an evaluation function, searching a first-arrival wave peak point in a selected first-arrival time window according to the gradient of a given first-arrival wave in the next adjacent channel, and forming an pheromone concentration path by taking the first-arrival wave peak point as an identifier.
17. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the abnormal first-arrival correction method according to any one of claims 1 to 9 when executing the computer program.
18. A computer-readable storage medium storing a computer program for executing the abnormal first-arrival wave correction method according to any one of claims 1 to 9.
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