CN112083489B - Prestack depth migration speed updating method based on multi-information constraint - Google Patents
Prestack depth migration speed updating method based on multi-information constraint Download PDFInfo
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- CN112083489B CN112083489B CN202011139246.9A CN202011139246A CN112083489B CN 112083489 B CN112083489 B CN 112083489B CN 202011139246 A CN202011139246 A CN 202011139246A CN 112083489 B CN112083489 B CN 112083489B
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V1/00—Seismology; Seismic or acoustic prospecting or detecting
- G01V1/28—Processing seismic data, e.g. analysis, for interpretation, for correction
- G01V1/30—Analysis
- G01V1/301—Analysis for determining seismic cross-sections or geostructures
- G01V1/302—Analysis for determining seismic cross-sections or geostructures in 3D data cubes
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V1/00—Seismology; Seismic or acoustic prospecting or detecting
- G01V1/28—Processing seismic data, e.g. analysis, for interpretation, for correction
- G01V1/36—Effecting static or dynamic corrections on records, e.g. correcting spread; Correlating seismic signals; Eliminating effects of unwanted energy
- G01V1/362—Effecting static or dynamic corrections; Stacking
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V2210/00—Details of seismic processing or analysis
- G01V2210/50—Corrections or adjustments related to wave propagation
- G01V2210/51—Migration
- G01V2210/512—Pre-stack
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V2210/00—Details of seismic processing or analysis
- G01V2210/50—Corrections or adjustments related to wave propagation
- G01V2210/52—Move-out correction
Abstract
The invention provides a prestack depth migration speed updating method based on multi-information constraint, which comprises the following steps of: acquiring a three-dimensional seismic data volume, a common-center-point gather and a prestack time migration velocity in an exploration area; optimizing the three-dimensional seismic data volume and the common midpoint gather, and improving the signal-to-noise ratio of the three-dimensional seismic data volume and the common midpoint gather; carrying out manual tracking horizon on the three-dimensional seismic data volume to obtain a manual tracking horizon; under the constraint of the manual tracking horizon, automatically tracking the horizon to obtain an automatic tracking horizon; fusing the manual tracking horizon and the automatic tracking horizon to obtain fused multi-information data; arranging the fused multi-information data as speed updating points in the common-center-point gather data, and combining the existing dynamic correction speed data at the speed updating points to obtain the residual speed; combining the initial speed and the residual speed to form a new offset speed body; and performing prestack depth migration by using the updated speed data body.
Description
Technical Field
The invention relates to the technical field of geological exploration, in particular to a prestack depth migration speed updating method which is suitable for updating prestack depth migration speed of data with complex structures and low data signal-to-noise ratios.
Background
The current prestack depth migration speed updating method adopts a vertical speed updating method, and the updating method is to pick up the residual speed for speed updating according to the trace set leveling condition; an along-the-horizon speed updating method, which picks up different residual speeds according to the along-the-horizon energy mass; and (3) carrying out structural description according to the dip angle (D) and the azimuth angle (A) continuity (C) by using the grid chromatography, and arranging speed updating points.
Problems and disadvantages: 1. the traditional method needs a large amount of manual intervention, and has large workload and low efficiency.
2. The speed updating can not be carried out by accurately arranging the updating points under the condition of more complex structure and low signal-to-noise ratio, and the prestack depth migration effect is influenced.
Disclosure of Invention
The method aims to effectively solve the technical problems that the work efficiency is low in prestack depth migration, and speed updating points cannot be arranged in a region with a complex structure and a region with a low signal-to-noise ratio.
In order to solve the problems, the technical scheme adopted by the invention is as follows:
a prestack depth migration speed updating method based on multi-information constraint comprises the following steps:
s1, acquiring a three-dimensional seismic data volume, a common-center-point gather and a prestack time migration speed in an exploration area;
s2, optimizing the three-dimensional seismic data volume and the common midpoint gather, and improving the signal-to-noise ratio of the three-dimensional seismic data volume and the common midpoint gather;
s3, carrying out manual tracking horizon on the three-dimensional seismic data volume to obtain a manual tracking horizon; under the constraint of the manual tracking horizon, automatically tracking the horizon to obtain an automatic tracking horizon; fusing the manual tracking horizon and the automatic tracking horizon to obtain fused multi-information data;
s4, arranging the fused multi-information data serving as speed updating points into the common-center-point gather data;
s5, calculating a residual speed by combining the pre-stack time migration speed at the speed updating point;
s6, combining the pre-stack time migration speed and the residual speed to form a new migration speed body;
and S7, performing prestack depth migration by using the updated speed data body.
The S2 comprises the following steps: obtaining an optimized high signal-to-noise ratio three-dimensional seismic data volume by high-order fitting filtering: solving a high-order fitting polynomial according to the amplitude values of the three adjacent points, and solving and recalculating the amplitude values of all the points according to the fitting polynomial to obtain an optimized high signal-to-noise ratio data volume; and (3) obtaining an optimized common-center-point gather through four-dimensional denoising: the three-dimensional pre-stack seismic data is regarded as a four-dimensional data body, one dimension is a line number, the second dimension is a CMP number, the third dimension is offset or trace in CMP, the fourth dimension is recording time, a predictor of each frequency component is obtained by utilizing an F-XYO prediction theory, and the predictor is applied to the three-dimensional pre-stack seismic data to achieve the purpose of attenuating three-dimensional pre-stack random noise.
The S3 comprises the following steps: and respectively exporting two x, y and z format text files from the manually interpreted layer and the automatically interpreted layer, wherein x represents an east coordinate, y represents a north coordinate, and z represents a time value, combining the two text files into a new text file, wherein the new text file is a plurality of rows of x, y and z three-column data, thinning the three rows of x, y and z three-column data according to a user-defined interval, and finally forming multi-information data.
In S4, the speed update point is a point for calculating the remaining speed, and in S4, a part of the gather data is extracted from all the gather data according to the x and y coordinates of the multi-information data, and the remaining speed is calculated for the part of the gather data.
The S5 comprises the following steps: and performing dynamic correction according to different residual velocities at the extracted x, y and z positions corresponding to the gather, then performing superposition, and finally selecting R with the maximum superposition energy as the residual velocity of the point.
In S6, the operation method is as follows: formula Vn = Vo (1 + R), vn is the updated speed, vo is the motion correction speed, and R is the remaining speed.
The S7 comprises the following steps: and (3) carrying out prestack depth migration by using the updated speed data volume, checking whether the gather is leveled after migration, and whether the migration profile imaging result is improved, and if not, adjusting parameters until the working requirement is met.
After the deviation, checking whether the gather is leveled up or not manually according to a certain interval
Compared with the prior art, the invention has the beneficial effects that:
the invention reduces the workload of people, saves the labor cost, realizes the speed updating of the high-density arrangement of the updating points in the areas with more complex structures and lower signal-to-noise ratios, improves the speed updating speed and improves the effect of pre-stack depth migration.
Drawings
FIG. 1 is an original prestack depth migration offset profile, with the left graph line manually interpreted and the right graph line interpreted using a neural network algorithm under the manually interpreted horizon constraint;
FIG. 2 is a trace gather after prestack depth migration at different speeds, the left plot being the trace gather after prestack depth migration at the initial speed; the middle diagram is that speed updating is carried out according to the speed updating points arranged at the manually explained horizon to obtain a speed 1, and the gather after pre-stack depth deviation is carried out by using the speed 1 is leveled to a certain degree; the right graph is that speed updating is carried out according to the speed updating points arranged at the manual interpretation horizon and the automatic interpretation horizon to obtain a speed 2, and a gather after pre-stack depth deviation is carried out by using the speed 2 is leveled to a certain degree;
FIG. 3 is a graph of pre-stack depth migration at different velocities, with the top graph being a cross-section of the initial velocity after pre-stack depth migration; the middle diagram is a section obtained by performing speed updating according to the speed updating points arranged on the manual explained horizon to obtain the speed 1 and performing prestack depth migration by using the speed 1; the lower graph is a section obtained by arranging speed updating points according to the manual interpretation horizon and the automatic interpretation horizon to update the speed, obtaining the speed 2 and performing prestack depth migration by using the speed 2.
Detailed Description
The principles and features of this invention are described below in conjunction with examples which are set forth to illustrate, but are not to be construed to limit the scope of the invention.
The embodiment provides a prestack depth migration speed updating method based on multi-information constraint, which comprises the following steps:
1. carrying out data processing according to single shot data of field construction to obtain a three-dimensional seismic data volume, a common-center gather and a prestack time migration speed;
2. obtaining an optimized high signal-to-noise ratio three-dimensional seismic data volume by high-order fitting filtering: solving a high-order fitting polynomial according to the amplitude values of the three adjacent points, and solving and recalculating the amplitude values of all the points according to the fitting polynomial to obtain an optimized high signal-to-noise ratio data volume; and (3) obtaining an optimized common-center-point gather through four-dimensional denoising: the three-dimensional pre-stack seismic data is regarded as a four-dimensional data body, one dimension is a line number, the other dimension is a CMP number, the other dimension is offset or trace in CMP, the other dimension is recording time, a predictor of each frequency component is obtained by utilizing an F-XYO prediction theory, and the predictor is applied to the three-dimensional pre-stack seismic data to achieve the purpose of attenuating three-dimensional pre-stack random noise;
3. selecting positions with obvious speed difference and uniform distribution, and performing artificial position tracking interpretation on the three-dimensional seismic data volume; utilizing the manually explained layer position to carry out constraint, and adopting a neural network algorithm to automatically track the interlayer small layer; fusing the manually interpreted and automatically interpreted horizon data to form multi-information data: and respectively deriving two x, y and z format text files of the manually interpreted horizon and the automatically interpreted horizon, wherein x represents an east coordinate, y represents a north coordinate, and z represents a time value. Merging the two text files into a new text file, wherein the new text file is a plurality of rows of data of three columns of x, y and z, thinning is carried out according to a user-defined interval, such as 4, and finally multi-information data is formed;
4. taking the multi-information data as a speed updating point to update the speed;
the speed update point is a point for calculating the remaining speed, and the step is to extract a part of gather data from all the gather data according to the x and y coordinates of the multi-information data, and calculate the remaining speed for the part of gather data.
5. On the gather after the initial speed deviation, calculating the relative residual speed at the speed updating point;
the method specifically comprises the following steps: dynamically correcting the extracted x, y and z positions corresponding to the gather according to different residual velocities, then performing superposition, and finally selecting R with the maximum superposition energy as the residual velocity of the point;
6. calculating the existing dynamic correction speed and residual speed to obtain an updated speed data body for pre-stack depth migration;
the operation method comprises the following steps: formula Vn = Vo (1 + R), vn is the updated speed, vo is the motion correction speed, and R is the remaining speed.
7. And (3) carrying out prestack depth migration by using the updated speed data volume, checking whether the gather is leveled after migration, and whether the migration profile imaging result is improved, and if not, adjusting parameters until the working requirement is met.
And after the deviation, checking whether the gather is leveled up, namely manually checking whether the gather is leveled up according to a certain interval.
Fig. 1 is an original prestack depth migration profile, the line of the left graph is a result of manual interpretation, only 4 geological horizons are explained due to large workload and time and labor waste, the line of the right graph is a horizon explained by a neural network algorithm under the constraint of the manually explained horizon, and small horizons among a plurality of horizons are automatically explained due to high efficiency and automation of a computer.
FIG. 2 is a trace gather after prestack depth migration at different speeds, the left trace being a trace gather after prestack depth migration at an initial speed, the trace gather not being leveled due to speed inaccuracy; the middle diagram is that speed updating is carried out according to the speed updating points arranged at the position manually explained to obtain the speed 1, and the gather after the prestack depth deviation is carried out by using the speed 1 is leveled to a certain degree; and the right graph is used for arranging speed updating points according to the manual interpretation horizon and the automatic interpretation horizon to update the speed to obtain a speed 2, and the gather after pre-stack depth deviation is carried out by using the speed 2 to further level the gather.
FIG. 3 is a cross section of prestack depth migration at different speeds, the upper graph is a cross section of prestack depth migration at an initial speed, the cross section is aberration, the layer is discontinuous, and the breakpoint is unclear; the middle diagram is that the speed is updated according to the speed updating points arranged at the manually explained layer position, so that the speed 1 is obtained, the section is subjected to prestack depth migration by using the speed 1, the section imaging is improved, the layer position continuity is improved, and the break point is not clear; the lower graph is subjected to speed updating according to the speed updating points arranged on the manual interpretation horizon and the automatic interpretation horizon to obtain a speed 2, and the section after pre-stack depth deviation is carried out by using the speed 2, so that the section imaging is good, the horizons are continuous, and the break points are clear.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like made within the spirit and principle of the present invention should be included in the scope of the present invention.
Claims (8)
1. A prestack depth migration speed updating method based on multi-information constraint is characterized by comprising the following steps:
s1, acquiring a three-dimensional seismic data volume, a common-center-point gather and a prestack time migration speed in an exploration area;
s2, optimizing the three-dimensional seismic data volume and the common midpoint gather, and improving the signal-to-noise ratio of the three-dimensional seismic data volume and the common midpoint gather;
s3, carrying out manual tracking horizon on the three-dimensional seismic data volume to obtain a manual tracking horizon; under the constraint of the manual tracking horizon, automatically tracking the horizon to obtain an automatic tracking horizon; fusing the manual tracking horizon and the automatic tracking horizon to obtain fused multi-information data;
s4, arranging the fused multi-information data serving as speed updating points into the common-center-point gather data;
s5, calculating a residual speed at the arranged speed updating point by combining the pre-stack time migration speed;
s6, combining the pre-stack time migration speed and the residual speed to form a new migration speed body;
and S7, performing prestack depth migration by using the updated speed data body.
2. The method according to claim 1, wherein S2 specifically comprises: obtaining an optimized high signal-to-noise ratio three-dimensional seismic data volume by high-order fitting filtering: according to the amplitude values of the three adjacent points, solving a high-order fitting polynomial, and recalculating the amplitude values of all the points according to the fitting polynomial to obtain an optimized high signal-to-noise ratio data volume; and (3) obtaining an optimized common-center-point gather through four-dimensional denoising: the three-dimensional pre-stack seismic data is regarded as a four-dimensional data body, one dimension is a line number, the second dimension is a CMP number, the third dimension is offset or trace in CMP, the fourth dimension is recording time, a predictor of each frequency component is obtained by utilizing an F-XYO prediction theory, and the predictor is applied to the three-dimensional pre-stack seismic data to achieve the purpose of attenuating three-dimensional pre-stack random noise.
3. The method according to claim 1, wherein S3 specifically comprises: and respectively exporting two x, y and z format text files from the manual tracking layer and the automatic tracking layer, wherein x represents an east coordinate, y represents a north coordinate, and z represents a time value, combining the two text files into a new text file, wherein the new text file is a plurality of rows of x, y and z three-column data, thinning the three-column data according to a user-defined interval, and finally forming multi-information data.
4. The method according to claim 1, wherein the speed update point in S4 is a point for calculating a residual speed, and the step S4 is a step of extracting a part of the gather data from all the gather data according to x and y coordinates of the multi-information data, and calculating the residual speed for the part of the gather data.
5. The method according to claim 1, wherein the S5 comprises: and performing dynamic correction according to different residual velocities at the extracted x, y and z positions corresponding to the gather, then performing superposition, and finally selecting the R with the maximum superposition energy as the residual velocity of the point.
6. The method of claim 1, wherein said combining said pre-stack time migration velocity and residual velocity in S6 to form a new migration velocity body is performed by: formula Vn = Vo (1 + R), vn is the updated speed, vo is the dynamic correction speed, and R is the remaining speed.
7. The method according to claim 1, wherein the S7 comprises: and performing prestack depth migration by using the updated speed data volume, checking whether the gather is leveled up after migration, and whether the migration profile imaging result is improved, and if not, adjusting parameters until the working requirement is met.
8. The method of claim 7 wherein the post-migration checks whether the gather is flattened by manually checking at regular intervals.
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