CN111965699A - Method and system for processing kirchhoff prestack depth migration seismic data - Google Patents
Method and system for processing kirchhoff prestack depth migration seismic data Download PDFInfo
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- CN111965699A CN111965699A CN202010940691.9A CN202010940691A CN111965699A CN 111965699 A CN111965699 A CN 111965699A CN 202010940691 A CN202010940691 A CN 202010940691A CN 111965699 A CN111965699 A CN 111965699A
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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
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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
- 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
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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
- G01V2210/30—Noise handling
- G01V2210/32—Noise reduction
- G01V2210/324—Filtering
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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
- G01V2210/53—Statics correction, e.g. weathering layer or transformation to a datum
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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
- G01V2210/60—Analysis
- G01V2210/62—Physical property of subsurface
- G01V2210/624—Reservoir parameters
Abstract
The invention relates to a method and a system for processing kirchhoff prestack depth migration seismic data, which comprise the following steps: s1, starting a plurality of asynchronous parallel IO data nodes on a cluster, dividing seismic data into a plurality of data blocks, and sending each data block to one data node; s2, performing kirchhoff prestack depth migration calculation on the data block on each data node to obtain a temporary imaging result, and storing the temporary imaging result into a distributed file system; s3, merging the temporary imaging results in the distributed file system to obtain a common imaging point gather; s4 generates an imaging profile of the geological structure from the common image point gathers. According to the invention, the Kchhoff prestack depth migration calculation of the seismic data is realized by adopting the asynchronous IO frame and the GPU for acceleration, so that the large-scale and ultra-large-scale seismic data can be conveniently processed, and the migration processing efficiency can be improved.
Description
Technical Field
The invention relates to a method and a system for processing kirchhoff prestack depth migration seismic data, and belongs to the technical field of geophysical exploration.
Background
In the oil and gas industry, the purpose of seismic data processing is to provide geophysical scientists with structural and stratigraphic details of the earth's subsurface to detect and predict the location of gas or oil. To achieve these goals, methods of seismic exploration are used to collect raw subsurface information and extract the final geologic image description. This will ultimately help to improve reservoir development decision making and reduce the risk of seismic exploration mining.
Currently, much of the existing research has focused on using seismic waveforms to obtain high-precision images depicting the subsurface media conditions. The kirchhoff prestack depth migration imaging technology plays an important role in seismic exploration in complex areas due to the advantages of simplicity, convenience, high efficiency, strong applicability and the like. However, in recent years, with the continuous development of exploration technology, the requirement on imaging accuracy is higher, kirchhoff prestack depth migration based on the isotropic theory cannot meet the requirement of practical production, and the work of anisotropic kirchhoff prestack depth migration is required to be carried out. The problem that the pre-stack kirchhoff depth migration always has a large calculation amount and contains a large amount of input and output data exists, and the anisotropic kirchhoff pre-stack depth migration further increases the calculation amount due to the existence of a large amount of anisotropic parameters and further increases the input and output data, so that a method for efficiently calculating the kirchhoff pre-stack depth migration is urgently needed.
Disclosure of Invention
In view of the above problems, the present invention aims to provide a method and a system for processing a kirchhoff prestack depth migration seismic data, which improve the computation speed of the kirchhoff prestack depth migration of the seismic data by using asynchronous parallel IO, facilitate the processing of large-scale and ultra-large-scale seismic data, and improve the migration processing efficiency.
In order to achieve the purpose, the invention adopts the following technical scheme: a kirchhoff prestack depth migration seismic data processing method comprises the following steps: s1, starting a plurality of asynchronous parallel IO data nodes on a cluster, dividing seismic data into a plurality of data blocks, and sending each data block to one data node; s2, performing kirchhoff prestack depth migration calculation on the data block on each data node to obtain a temporary imaging result, and storing the temporary imaging result into a distributed file system; s3, merging the temporary imaging results in the distributed file system to obtain a common imaging point gather; s4 generates an imaging profile of the geological structure from the common image point gathers.
Further, the seismic data in S1 is preprocessed seismic data, and the seismic data includes common shot gather data and a corresponding medium velocity model.
Further, the preprocessing includes at least one of static correction, deconvolution, and denoising.
Further, in step S1, the number of data blocks is the same as the number of data nodes, and when each data block is sent to a data node, the data node obtains a corresponding migration parameter of each data block and intercepts the seismic data in the migration aperture.
Further, the cluster in step S1 is a CPU/GPU heterogeneous cluster.
Further, the method of obtaining the provisional imaging result in step S2 is: copying the data block in each data node from the CPU to the GPU; carrying out shot set kirchhoff prestack depth calculation in a GPU to obtain a calculation result; and transmitting the calculation result to the CPU and forming a temporary imaging result.
Further, step S2 specifically includes the following steps: s2.1, performing kirchhoff prestack depth migration calculation on the data block on each data node to obtain a temporary imaging result, and accumulating the temporary imaging result into a local temporary file; s2.2, copying the temporary imaging result in the local temporary file to a distributed file system, and deleting the local temporary file.
Further, after the common imaging point gather is obtained in S3, noise in the common imaging point gather is removed through the cutting and stacking process, and an imaging profile of the geological structure is formed according to the common imaging point gather subjected to the cutting and stacking process.
The invention also discloses a kirchhoff prestack depth migration seismic data processing system, which comprises: the data management and access module is used for starting a plurality of asynchronous parallel IO data nodes on the cluster, dividing the seismic data into a plurality of data blocks and sending each data block to one data node; the data migration module is used for performing kirchhoff prestack depth migration calculation on the data block on each data node to obtain a temporary imaging result, and storing the temporary imaging result into the distributed file system; the data summarization module is used for merging temporary imaging results in the distributed file system to obtain a common imaging point gather; and the output module is used for generating an imaging profile of the geological structure according to the common imaging point gather.
Further, the system also comprises an image processing module; and the image processing module is used for carrying out cutting and overlapping processing on the common imaging point gather obtained after the temporary imaging results are combined.
Due to the adoption of the technical scheme, the invention has the following advantages:
1. according to the invention, the calculation speed of the kirchhoff prestack depth migration of the seismic data is increased by adopting asynchronous parallel IO, so that the large-scale and super-large-scale seismic data can be conveniently processed, and the migration processing efficiency can be improved. Compared with the traditional pre-stack migration method based on the CPU cluster, the computational efficiency of the kirchhoff pre-stack depth migration of the seismic data is greatly improved, and the seismic data processing time is shortened.
2. Because the GPU is adopted to carry out the calculation of the kirchhoff prestack depth migration, the seismic data with the same scale are processed, the consumed electric energy is greatly reduced relative to CPU equipment, and the resources and the cost are saved.
3. Through the cutting and overlapping processing, the imaging profile of the geological structure is more accurate.
Drawings
FIG. 1 is a flow chart of a method of processing kirchhoff prestack depth migration seismic data in accordance with an embodiment of the present invention;
FIG. 2 is a schematic diagram of computing kirchhoff prestack depth migration seismic data in an embodiment of the invention, FIG. 2(a) is a schematic diagram of a prior art computing method, and FIG. 2(b) is a schematic diagram of an asynchronous parallel IO computing method in the invention;
FIG. 3 is a flow chart of computing kirchhoff prestack depth migration seismic data in an embodiment of the invention;
fig. 4 is an IO read-write performance characterization diagram for calculating a result of the kirchhoff prestack depth migration in an embodiment of the present invention, where fig. 4(a) characterizes a read operation IO speed, and fig. 4(b) characterizes a write operation IO speed;
FIG. 5 is a schematic diagram of a system for processing kirchhoff prestack depth migration seismic data in accordance with an embodiment of the invention.
Detailed Description
The present invention is described in detail by way of specific embodiments in order to better understand the technical direction of the present invention for those skilled in the art. It should be understood, however, that the detailed description is provided for a better understanding of the invention only and that they should not be taken as limiting the invention. In describing the present invention, it is to be understood that the terminology used is for the purpose of description only and is not intended to be indicative or implied of relative importance.
Example one
The embodiment discloses a kirchhoff prestack depth migration seismic data processing method, as shown in fig. 1, including the following steps:
s1 initiates a plurality of asynchronous parallel IO data nodes on a cluster, divides the seismic data into a plurality of data blocks, and sends each data block to one data node.
The cluster in step S1 is a CPU/GPU heterogeneous cluster. The CPU/CPU heterogeneous cluster is formed by combining two processors with different architectures, namely a GPU and a CPU, to form a hardware collaborative parallel mode, and simultaneously realizes the collaborative parallel computation of GPU and CPU software on an application program. The CPU is mainly responsible for control of the GPU, preparation of data, sending and receiving of the data among the nodes and the like, namely parallel control is carried out; the GPU mainly carries out the wave field extrapolation calculation which is most time-consuming in the depth of the kirchhoff pre-stack, namely, the parallel calculation. At present, the wave field extrapolation based on the finite difference method commonly adopted in the industry is the most typical single instruction multiple data (simd) calculation mode, and is very suitable for GPU processing, for example, Tesla K80 has 2880 cores, and can process 2880 data samples simultaneously. In addition, the kirchhoff prestack depth algorithm generally adopts single precision to calculate, and has higher processing efficiency.
The asynchronous IO framework is a programming model, data are stored and deployed on each computing node by adopting a distributed file system (HDFS), the high fault tolerance is achieved, failed nodes can be automatically processed, the performance is stable, and the asynchronous IO framework is very suitable for large-scale data set (larger than 1TB) management and parallel operation. The main idea of the asynchronous IO framework is derived from a functional programming language, and the asynchronous IO framework greatly facilitates programmers to operate own programs on a distributed system under the condition that the programmers do not know distributed parallel programming. Fig. 2 is a schematic diagram of computing kirchhoff prestack depth migration seismic data in an embodiment of the present invention, fig. 2(a) is a schematic diagram of a computing method in the prior art, and fig. 2(b) is a schematic diagram of an asynchronous parallel IO computing method in the present invention. As shown in fig. 2, in the prior art, only 1MPI task can be completed at the same time, while the asynchronous parallel IO calculation method in this embodiment can complete 32MPI tasks at the same time, which greatly improves the data processing efficiency.
The GPU terminal in the CPU/GPU heterogeneous cluster realizes asynchronous parallel IO and depends on a multi-stream mechanism, and the data processing process of the multi-stream mechanism mainly comprises the following steps:
a seismic data management and access mechanism based on asynchronous IO framework:
each asynchronous parallel IO data node is started on the cluster and the seismic data set is distributed to each node on the network. Firstly, reading in seismic channel set data and velocity data from a distributed file system, then carrying out kirchhoff prestack depth migration calculation, and accumulating the result to a local temporary file; and then copying the local temporary file to the distributed file system, deleting the local temporary file after the copying is successful, and finally starting a program to synthesize the temporary file on the HDFS and generate an imaging gather to finish the offset calculation.
b, performing a kirchhoff prestack depth migration algorithm based on a GPU/CPU heterogeneous cluster:
first, the asynchronous IO framework mechanism acquires seismic gather data and velocity data in each data node. And then copying the data from the CPU to the GPU, performing kirchhoff prestack depth calculation on a GPU card, transmitting the calculation result to the CPU after the calculation is finished, and finally writing a temporary imaging result.
The seismic data in S1 are preprocessed seismic data, which include common shot gather data and corresponding media velocity models. Wherein the preprocessing includes at least one of static correction, deconvolution, and denoising.
The number of the data blocks in the step S1 is matched with the number of the data nodes, the number of the data blocks may be the same as the number of the data nodes, or a certain proportional relationship may be formed, and when each data block is sent to a data node, the data node obtains the corresponding migration parameter of each data block, and intercepts the seismic data in the migration aperture.
S2, performing kirchhoff prestack depth migration calculation on the data blocks on each data node to obtain a temporary imaging result, and storing the temporary imaging result into the distributed file system.
The method for obtaining the temporary imaging result in step S2, as shown in fig. 3, includes: copying the data block in each data node from the CPU to the GPU; carrying out shot set kirchhoff prestack depth calculation in a GPU to obtain a calculation result; and transmitting the calculation result to the CPU and forming a temporary imaging result.
Step S2 specifically includes the following steps: s2.1, performing kirchhoff prestack depth migration calculation on the data block on each data node to obtain a temporary imaging result, and accumulating the temporary imaging result into a local temporary file; s2.2, copying the temporary imaging result in the local temporary file to a distributed file system, and deleting the local temporary file.
And S3, merging the temporary imaging results in the distributed file system to obtain a common imaging point gather.
The provisional imaging results are combined by Reduce operation in S3. And after the common imaging point gather is obtained, removing noise in the common imaging point gather through cutting and stacking processing, and forming an imaging profile of the geological structure according to the common imaging point gather subjected to cutting and stacking processing.
S4 generates an imaging profile of the geological structure from the common image point gathers. This is the IO read-write performance of the kirchhoff prestack depth migration result obtained by the specific example of the present invention.
Fig. 4 is an IO read-write performance characterization diagram for calculating a result of the kirchhoff prestack depth migration in an embodiment of the present invention, where fig. 4(a) characterizes a read operation IO speed, and fig. 4(b) characterizes a write operation IO speed. As shown in fig. 4, the method in this embodiment obtains a better result through numerical calculation, and the processing efficiency of the kirchhoff prestack depth migration GPU acceleration method implemented based on the asynchronous IO frame is improved by 15-20 times compared with the efficiency of the conventional CPU cluster.
Example two
Based on the same inventive concept, the present embodiment discloses a kirchhoff prestack depth migration seismic data processing system, as shown in fig. 5, including:
the data management and access module is used for starting a plurality of asynchronous parallel IO data nodes on the cluster, dividing the seismic data into a plurality of data blocks and sending each data block to one data node;
the data migration module is used for performing kirchhoff prestack depth migration calculation on the data block on each data node to obtain a temporary imaging result, and storing the temporary imaging result into the distributed file system;
the data summarization module is used for merging temporary imaging results in the distributed file system to obtain a common imaging point gather;
and the output module is used for generating an imaging profile of the geological structure according to the common imaging point gather.
The processing system preferred in this embodiment further includes an image processing module; the image processing module is used for carrying out cutting and overlapping processing on the common imaging point gather obtained after the temporary imaging results are combined.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solutions of the present invention and not for limiting the same, and although the present invention is described in detail with reference to the above embodiments, those of ordinary skill in the art should understand that: modifications and equivalents may be made to the embodiments of the invention without departing from the spirit and scope of the invention, which is to be covered by the claims. The above description is only for the specific embodiments of the present application, but the scope of the present application is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present application, and shall be covered by the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
Claims (10)
1. A kirchhoff prestack depth migration seismic data processing method is characterized by comprising the following steps:
s1, starting a plurality of asynchronous parallel IO data nodes on a cluster, dividing seismic data into a plurality of data blocks, and sending each data block to one data node;
s2, performing kirchhoff prestack depth migration calculation on the data block on each data node to obtain a temporary imaging result, and storing the temporary imaging result into a distributed file system;
s3, merging the temporary imaging results in the distributed file system to obtain a common imaging point gather;
s4 an imaging profile of the geological structure is generated from the common imaging point gather.
2. The method of kchoff prestack depth migration seismic data processing of claim 1, wherein the seismic data in S1 is preprocessed seismic data that includes common shot gather data and corresponding media velocity models.
3. The method of kirchhoff prestack depth migration seismic data processing of claim 2, wherein the preprocessing comprises at least one of statics, deconvolution, and denoising.
4. The method for processing the kexiff prestack depth migration seismic data according to claim 1, wherein the number of the data blocks is the same as the number of the data nodes in step S1, and when each data block is sent to a data node, the data node obtains the corresponding migration parameter of each data block and intercepts the seismic data within a migration aperture.
5. The method for kirchhoff prestack depth migration seismic data processing according to any one of claims 1 to 4, wherein the clusters in step S1 are CPU/GPU heterogeneous clusters.
6. The method for processing the kirchhoff prestack depth migration seismic data according to claim 5, wherein the step S2 is performed by: copying the data block in each data node from the CPU to the GPU; carrying out shot set kirchhoff prestack depth calculation in a GPU to obtain a calculation result; and transmitting the calculation result to the CPU and forming a temporary imaging result.
7. The method for processing the kirchhoff prestack depth migration seismic data according to claim 6, wherein the step S2 specifically includes the steps of:
s2.1, performing kirchhoff prestack depth migration calculation on the data block on each data node to obtain a temporary imaging result, and accumulating the temporary imaging result into a local temporary file;
s2.2, copying the temporary imaging result in the local temporary file to the distributed file system, and deleting the local temporary file.
8. The method for processing the kirchhoff prestack depth migration seismic data according to any one of claims 1 to 4, wherein after the common imaging point gather is obtained in S3, noise in the common imaging point gather is removed through a cutting and stacking process, and an imaging section of a geological structure is formed according to the common imaging point gather subjected to the cutting and stacking process.
9. A kirchhoff prestack depth migration seismic data processing system, comprising:
the data management and access module is used for starting a plurality of asynchronous parallel IO data nodes on the cluster, dividing the seismic data into a plurality of data blocks and sending each data block to one data node;
the data migration module is used for performing kirchhoff prestack depth migration calculation on the data block on each data node to obtain a temporary imaging result, and storing the temporary imaging result into a distributed file system;
the data summarization module is used for merging the temporary imaging results in the distributed file system to obtain a common imaging point gather;
and the output module is used for generating an imaging profile of the geological structure according to the common imaging point gather.
10. The system for kirchhoff prestack depth migration seismic data processing according to claim 9, further comprising an image processing module; and the image processing module is used for carrying out excision and superposition processing on the common imaging point gather obtained after the temporary imaging results are combined.
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Application publication date: 20201120 |