A seismic profile horizon tracking data separation method, medium, and computer program product
By using database programming techniques, especially PostgreSQL and PostGIS, combined with a preset distance determination model and expert experience, the problem of low efficiency in seismic profile layer-tracking data separation was solved, achieving efficient and accurate data separation and meeting actual production needs.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-12-10
- Publication Date
- 2026-06-12
AI Technical Summary
In existing technologies, the separation efficiency and accuracy of seismic profile layer-tracing data are low, which cannot meet the actual production needs.
By employing a database-based programming approach, particularly using the professional geospatial database PostgreSQL and its extended module PostGIS, data from different layers in the seismic profile are separated through spatial analysis and script editing. By utilizing a preset distance determination model and expert experience to set scatter distance thresholds, efficient data separation is achieved.
It significantly improves the efficiency and accuracy of seismic profile data processing, meets the needs of actual production, and has good scalability.
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Figure CN122194250A_ABST
Abstract
Description
Technical Field
[0001] This disclosure relates to the field of seismic exploration, and in particular to a method, medium, and computer program product for separating seismic profile layer-tracing data. Background Technology
[0002] Under current technology, in the acquisition design related to seismic exploration, it is necessary to use the surface data of the strata to create a three-dimensional geological model of the undulating surface.
[0003] However, the stratigraphic data from multiple seismic profiles cannot be directly used to generate surface data of the strata, and data preprocessing is required according to project needs.
[0004] Currently, the traditional preprocessing method is to load the data into commercial software, manually extract the data of the target layer through visual interpretation, and then combine multiple layer data from different profiles located in the same stratum, using surface interpolation to generate stratigraphic surface data.
[0005] The manual separation and layering of data described above is inefficient and inaccurate, and clearly cannot meet the needs of actual production. Summary of the Invention
[0006] The purpose of this invention is to provide at least one method, medium, and computer program product for separating seismic profile layer-by-layer data. Based on the big data processing capabilities of a database, the invention significantly improves data processing capabilities while obtaining the same processing results. It separates data from different layers in a seismic profile according to the distance between data points and provides corresponding theoretical proof.
[0007] One of the main technical problems that this invention aims to solve is to improve the efficiency of seismic profile data processing, specifically by separating data from different layers in a seismic profile.
[0008] This invention proposes a seismic profile layer data separation method based on database programming. By setting a distance threshold between scattered points at the same layer in each profile, the data of different layers in the seismic profile are separated so that separate layer surface data can be generated later.
[0009] Specifically, the theoretical basis for calculating the distance between scatter points on the stratigraphic level is as follows:
[0010] The Earth ellipsoid (also known as the "Earth ellipsoid" or "Earth oblate spheroid") is a mathematical surface representing the size and shape of the Earth, expressed by its major axis and flattening. Because it closely approximates an ellipsoid, the shape and size of the Earth ellipsoid are usually represented by a reference ellipsoid. It is the shape formed by rotating an ellipse around its minor axis and approximates the Earth's geoid. The shape of the geoid is expressed by its deviation from the reference ellipsoid. The parameters that determine the shape and size of the Earth ellipsoid are: major axis a (equatorial radius), minor axis b (polar radius), and the flattening f of the ellipsoid.
[0011]
[0012] Where e is the first eccentricity and e′ is the second eccentricity.
[0013] In practical engineering applications, based on the accuracy requirements of measurement work, within a certain range, the ellipsoid can be considered as a sphere with an appropriate radius. That is, taking the average value of all directions passing through a certain point on the ground as the radius of this sphere is appropriate. The radius of this sphere (mean radius of curvature) is defined as follows:
[0014]
[0015] Where W is the first fundamental latitude function.
[0016] To address the aforementioned technical problems, at least one embodiment of this application provides a method for separating seismic profile layer-tracing data, the method comprising:
[0017] Acquire seismic profile data, wherein the seismic profile data includes data from multiple scattered points;
[0018] The seismic profile data is saved to a preset database according to a preset saving strategy.
[0019] The seismic profile data stored in the preset database is preprocessed to clean up the scattered points with outliers and / or zero values, so as to obtain preprocessed seismic profile data.
[0020] Based on the preset distance determination model, functional components are generated to run in the preset database environment, and the distances between all adjacent scattered points in the preprocessed seismic profile data are determined by the functional components respectively.
[0021] If the distance between adjacent scattered points meets the preset conditions, it is determined that the adjacent scattered points are located in different layers, and the next scattered point in the adjacent scattered points is taken as the starting point of the next layer, and all scattered points before the starting point of the next layer are taken as scattered points located in the same layer.
[0022] At least one embodiment of this application also provides a computer device, including a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of the method described above.
[0023] At least one embodiment of this application also provides a computer-readable storage medium having a computer program stored thereon that, when executed by a processor, implements the steps of the method described above.
[0024] At least one embodiment of this application also provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the fiber optic detection method as described above.
[0025] The seismic profile layer-tracking data separation method, medium, and computer program product provided in this application belong to a data separation method based on database programming. Seismic profile data is characterized by its large volume and complexity. Traditional programming approaches lead to an enormous computational burden, while database programming, especially professional geospatial databases (such as PostgreSQL), offers significant advantages in processing large-scale datasets. During computation, the rich functions provided by the PostGIS extension module of PostgreSQL are utilized to perform spatial analysis. Scripts are edited to achieve the goal of separating the same layer data from different profiles, improving work efficiency to meet actual production needs. Compared to existing technologies, this invention significantly improves efficiency based on the big data processing capabilities of databases; furthermore, it achieves various data processing requirements through programming, demonstrating strong scalability.
[0026] In some optional embodiments, the preset database includes:
[0027] Geospatial databases. Seismic profile data is characterized by its large volume and complexity. Traditional programming approaches would result in an enormous computational burden. Database programming, especially using specialized geospatial databases (such as PostgreSQL), offers significant advantages when handling large-scale datasets. During computation, the rich functions provided by PostgreSQL's PostGIS extension module are utilized to perform spatial analysis. Scripts are edited to separate data from the same stratigraphic level across different profiles, improving work efficiency and meeting actual production needs.
[0028] In some optional embodiments, each scatter point in the seismic profile data includes data in three directions, the three directions including:
[0029] Longitude, latitude, and depth.
[0030] In some optional embodiments, the method further includes:
[0031] Saving process: Determine the target layer of all scattered points before the starting point of the next layer, and save the data of all scattered points before the starting point of the next layer in the data table corresponding to the target layer; and filter new seismic profile data from the preprocessed seismic profile data starting from the starting point of the next layer.
[0032] Judgment process: If the new seismic profile data is not empty, for the new seismic profile data, if the distance between adjacent scattered points meets the preset conditions, it is determined that the adjacent scattered points are located in different layers, and the latter scattered point among the adjacent scattered points is taken as the starting point of the next layer, and all scattered points before the starting point of the next layer are taken as scattered points located in the same layer.
[0033] Repeat the saving process and the judgment process until all the scattered data in the preprocessed seismic profile data are saved in the data table.
[0034] In some optional embodiments, the preset conditions include:
[0035] The distance between adjacent scatter points is no greater than a preset scatter point distance threshold. The distribution of data in each layer follows a certain pattern, and when two adjacent layers of data appear, the great circle distance between the two points will change significantly.
[0036] In some optional embodiments, the method for determining the preset scatter distance threshold includes:
[0037] The preset scatter point distance threshold is determined based on the distance between adjacent scatter points and through expert experience. Determining the preset scatter point distance threshold based on the distance between two adjacent data points and through expert experience can further improve the accuracy of stratum data separation.
[0038] In some optional embodiments, the preset distance determination model includes:
[0039]
[0040] Where P1 is the first of two adjacent data points, P2 is the second of two adjacent data points, latP1 is the latitude of the first data point, latP2 is the latitude of the second data point, lonP1 is the longitude of the first data point, lonP2 is the longitude of the second data point, and R is the Earth's radius. Attached Figure Description
[0041] One or more embodiments are illustrated by way of example with reference numerals in the accompanying drawings. These illustrations do not constitute a limitation on the embodiments. Elements with the same reference numerals in the drawings are denoted as similar elements. Unless otherwise stated, the figures in the drawings are not to be limited by scale.
[0042] Figure 1 A flowchart of a seismic profile layer-tracing data separation method provided in this embodiment of the disclosure;
[0043] Figure 2 A schematic diagram of raw seismic profile data provided in an embodiment of this disclosure;
[0044] Figure 3 A schematic diagram of a separated single layer data provided in an embodiment of this disclosure;
[0045] Figure 4 A schematic diagram illustrating multiple stratigraphic data from different sections but located in the same stratum, provided as an embodiment of this disclosure;
[0046] Figure 5 A schematic diagram of interpolated formation surface data provided in an embodiment of this disclosure;
[0047] Figure 6 A flowchart of another seismic profile layer-tracking data separation method provided in this embodiment of the disclosure. Detailed Implementation
[0048] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the various embodiments of the present invention will be described in detail below with reference to the accompanying drawings. However, those skilled in the art will understand that many technical details have been presented in the various embodiments of the present invention to enable the reader to better understand the present invention. However, the technical solutions claimed in the present invention can be implemented even without these technical details and various changes and modifications based on the following embodiments.
[0049] In current technology, seismic exploration acquisition design requires stratigraphic surface data for 3D geological modeling of undulating surfaces. However, stratigraphic data from multiple seismic profiles cannot be directly used to generate stratigraphic surface data. Efficiently separating stratigraphic data from seismic profiles is crucial for improving work efficiency. Traditional methods involve loading this data into commercial software and manually extracting data from target stratigraphic segments through visual interpretation to generate individual stratigraphic surface data. However, the database programming approach not only enables efficient computation of large datasets but also allows for different processing objectives based on varying requirements, significantly improving efficiency. This makes the present invention highly valuable for practical data processing applications.
[0050] To address the shortcomings of existing technologies, the purpose of this invention is to provide a method, medium, and computer program product for separating seismic profile layer-by-layer data. This method utilizes the large-scale data processing capabilities of a database to significantly improve data processing capabilities while achieving the same processing results. It separates data from different layers within a seismic profile based on the distance between data points.
[0051] One of the main technical problems this invention aims to solve is improving the efficiency of seismic profile data processing, specifically, separating data from different layers within a seismic profile. This invention proposes a database-programmed method for separating seismic profile layer data. By setting a distance threshold between scatter points at the same layer within each profile, data from different layers in the seismic profile are separated, facilitating the subsequent generation of individual layer surface data.
[0052] Example 1:
[0053] The embodiments of the present invention relate to a method for separating seismic profile layer-by-layer data.
[0054] The present invention discloses a data separation method based on database programming, compared to existing technologies. Seismic profile data is characterized by its large volume and complexity. Traditional programming approaches result in an enormous computational burden, while database programming, especially using specialized geospatial databases (such as PostgreSQL), offers significant advantages in processing large-scale datasets. During computation, the rich functions provided by the PostGIS extension module of PostgreSQL are utilized to perform spatial analysis. Scripts are edited to separate data from the same stratigraphic level across different profiles, improving work efficiency to meet actual production needs. Compared to existing technologies, this invention significantly improves efficiency based on the big data processing capabilities of databases; furthermore, it achieves various data processing requirements through programming, demonstrating strong scalability.
[0055] The following is a detailed description of the implementation details of the seismic profile layer-tracing data separation method in this embodiment. The following content is only for the convenience of understanding and is not necessary for implementing this solution.
[0056] The seismic profile layer-tracking data separation method of this embodiment can be applied to electronic devices with communication, computing, and data storage capabilities. For example... Figure 1 As shown, the seismic profile layer-tracing data separation method provided in this embodiment includes the following steps:
[0057] Step 110: Obtain seismic profile data, wherein the seismic profile data includes data from multiple scattered points.
[0058] Step 120: Save the seismic profile data to the preset database according to the preset saving strategy.
[0059] The preset save strategy can be set according to actual needs.
[0060] For example, seismic profile data is saved to a table in a preset database, with three preset directions as the table headers.
[0061] Step 130: Preprocess the seismic profile data stored in the preset database to clean up the scattered points with outliers and / or zero values, and obtain the preprocessed seismic profile data.
[0062] The purpose of cleaning is to remove dirty data from seismic profile data, thereby cleaning out anomalies such as outliers and / or zero values, in order to prepare for subsequent data separation.
[0063] Step 140: Based on the preset distance, determine the functional components that run in the preset database environment, and use the functional components to determine the distance between all adjacent scattered points in the preprocessed seismic profile data.
[0064] Optionally, in the preset database environment, a corresponding functional component is generated based on the preset distance determination model (e.g., a program / script written based on the preset distance determination model, which can be executed in the preset database to complete the function implemented based on the preset distance determination model), and the functional component is run in the preset database environment to execute and complete the function implemented by the preset distance determination model.
[0065] Specifically, by using a preset distance determination model, the distance between all two adjacent data points in the preprocessed seismic profile data can be determined.
[0066] For example, if the data in a certain preset direction in the preprocessed seismic profile data includes: a0, a1, a2, a3, a4, a5, a6..., then the distance between a0 and a1, the distance between a1 and a2, the distance between a2 and a3, and so on can be determined by the preset distance determination model.
[0067] Step 150: If the distance between adjacent scattered points meets the preset conditions, determine that the adjacent scattered points are located in different layers, and take the next scattered point in the adjacent scattered points as the starting point of the next layer, and take all scattered points before the starting point of the next layer as scattered points located in the same layer.
[0068] Specifically, if the distance between adjacent scattered points meets the preset conditions, the adjacent scattered points are determined to be located on different floors; if the distance between adjacent scattered points does not meet the preset conditions, the adjacent scattered points are determined to be located on the same floor.
[0069] Furthermore, if the distance between adjacent scattered points meets the preset conditions, the next scattered point among the adjacent scattered points is taken as the starting point of the next layer, and all scattered points before the starting point of the next layer are taken as scattered points located in the same layer.
[0070] The seismic profile layer-tracing data separation method provided in this embodiment significantly improves efficiency compared to existing technologies due to its large-scale database processing capabilities; furthermore, it offers strong scalability by implementing various data processing requirements through programming.
[0071] Example 2:
[0072] Based on the above embodiments, this embodiment further explains and illustrates the seismic profile layer-tracing data separation method provided in the above embodiments.
[0073] In step 110: Seismic profile data is acquired, wherein the seismic profile data includes data from multiple scattered points.
[0074] In some embodiments, each scatter point in the seismic profile data includes data in three directions, the three directions being:
[0075] Longitude, latitude, and depth.
[0076] In step 120: The seismic profile data is saved to a preset database according to a preset saving strategy.
[0077] In some embodiments, the preset database includes:
[0078] Geospatial database.
[0079] The preset save strategy can be set according to actual needs.
[0080] For example, seismic profile data is saved to a table in a preset database, with three preset directions as the table headers.
[0081] In step 130: the seismic profile data stored in the preset database is preprocessed to clean up the scattered points with outliers and / or zero values, so as to obtain preprocessed seismic profile data.
[0082] The purpose of cleaning is to remove dirty data from seismic profile data, thereby cleaning out anomalies such as outliers and / or zero values, in order to prepare for subsequent data separation.
[0083] In step 140: Based on the preset distance, the model generates functional components that run in the preset database environment, and the functional components determine the distances between all adjacent scattered points in the preprocessed seismic profile data.
[0084] In some embodiments, the preset distance determination model includes:
[0085]
[0086] Where P1 is the first of two adjacent data points, P2 is the second of two adjacent data points, latP1 is the latitude of the first data point, latP2 is the latitude of the second data point, lonP1 is the longitude of the first data point, lonP2 is the longitude of the second data point, and R is the Earth's radius.
[0087] Optionally, in the preset database environment, a corresponding functional component is generated based on the preset distance determination model (e.g., a program / script written based on the preset distance determination model, which can be executed in the preset database to complete the function implemented based on the preset distance determination model), and the functional component is run in the preset database environment to execute and complete the function implemented by the preset distance determination model.
[0088] Specifically, by using a preset distance determination model, the distance between all two adjacent data points in the preprocessed seismic profile data can be determined.
[0089] For example, if the data in a certain preset direction in the preprocessed seismic profile data includes: a0, a1, a2, a3, a4, a5, a6..., then the distance between a0 and a1, the distance between a1 and a2, the distance between a2 and a3, and so on can be determined by the preset distance determination model.
[0090] In step 150: if the distance between adjacent scattered points meets the preset conditions, it is determined that the adjacent scattered points are located in different layers, and the next scattered point among the adjacent scattered points is taken as the starting point of the next layer, and all scattered points before the starting point of the next layer are taken as scattered points located in the same layer.
[0091] Specifically, if the distance between adjacent scattered points meets the preset conditions, the adjacent scattered points are determined to be located on different floors; if the distance between adjacent scattered points does not meet the preset conditions, the adjacent scattered points are determined to be located on the same floor.
[0092] Furthermore, if the distance between adjacent scattered points meets the preset conditions, the next scattered point among the adjacent scattered points is taken as the starting point of the next layer, and all scattered points before the starting point of the next layer are taken as scattered points located in the same layer.
[0093] In some embodiments, the preset conditions include:
[0094] The distance between adjacent scattered points is not greater than the preset scattered point distance threshold.
[0095] In some embodiments, the method for determining the preset scatter distance threshold includes:
[0096] The preset scatter point distance threshold is determined based on the distance between adjacent scatter points and through expert experience.
[0097] The preset scatter distance threshold is not fixed. It can be determined by experts through analysis and evaluation based on geological conditions and / or the collected seismic profile layer data, so as to determine the preset scatter distance threshold applicable to the current seismic profile layer data.
[0098] In some embodiments, the method further includes:
[0099] Saving process: Determine the target layer of all scattered points before the starting point of the next layer, and save the data of all scattered points before the starting point of the next layer in the data table corresponding to the target layer; and filter new seismic profile data from the preprocessed seismic profile data starting from the starting point of the next layer.
[0100] Judgment process: If the new seismic profile data is not empty, for the new seismic profile data, if the distance between adjacent scattered points meets the preset conditions, it is determined that the adjacent scattered points are located in different layers, and the latter scattered point among the adjacent scattered points is taken as the starting point of the next layer, and all scattered points before the starting point of the next layer are taken as scattered points located in the same layer.
[0101] Repeat the saving process and the judgment process until all the scattered data in the preprocessed seismic profile data are saved in the data table.
[0102] It is understood that selecting new seismic profile data from the preprocessed seismic profile data starting from the starting point of the next layer can specifically include: taking all data in the preprocessed seismic profile data that are located after the data corresponding to the starting point of the next layer as the starting point, as new seismic profile data.
[0103] The seismic profile layer-tracing data separation method provided in this embodiment significantly improves efficiency compared to existing technologies due to its large-scale database processing capabilities; furthermore, it offers strong scalability by implementing various data processing requirements through programming.
[0104] The seismic profile stratigraphic data separation method provided in this application has significant advantages over existing technologies when processing large-scale datasets due to the use of database programming, particularly specialized geospatial databases (such as PostgreSQL). During computation, the rich functions provided by the PostGIS extension module of PostgreSQL are utilized to perform spatial analysis, and scripts are edited to separate the same stratigraphic data from different profiles, thereby improving work efficiency and meeting actual production needs.
[0105] Example 3:
[0106] Based on the above embodiments, this embodiment provides a specific example.
[0107] In this embodiment, by setting a threshold for the distance between scatter points at the same level in each profile, the data of different levels in the seismic profile are divided so that separate level surface data can be generated later.
[0108] The theoretical proof for calculating the distance between scatter points on the stratigraphic level is as follows:
[0109] The Earth ellipsoid (also known as the "Earth ellipsoid" or "Earth oblate spheroid") is a mathematical surface representing the size and shape of the Earth, expressed by its major axis and flattening. Because it closely approximates an ellipsoid, the shape and size of the Earth ellipsoid are usually represented by a reference ellipsoid. It is the shape formed by rotating an ellipse around its minor axis and approximates the Earth's geoid. The shape of the geoid is expressed by its deviation from the reference ellipsoid. The parameters that determine the shape and size of the Earth ellipsoid are: major axis a (equatorial radius), minor axis b (polar radius), and the flattening f of the ellipsoid.
[0110]
[0111] Where e is the first eccentricity and e′ is the second eccentricity.
[0112] In practical engineering applications, based on the accuracy requirements of measurement work, within a certain range, the ellipsoid can be considered as a sphere with an appropriate radius. That is, taking the average value of all directions passing through a certain point on the ground as the radius of this sphere is appropriate. The radius of this sphere (mean radius of curvature) is defined as follows:
[0113]
[0114]
[0115] Where W is the first fundamental latitude function.
[0116] The seismic profile layer-tracing data separation method provided in this embodiment can be found in the following reference. Figure 1and Figure 6 .
[0117] In step 110: Seismic profile data is acquired, wherein the seismic profile data includes data from multiple scattered points.
[0118] As an example, seismic profile data can be referenced. Figure 2 .
[0119] In some embodiments, each scatter point in the seismic profile data includes data in three directions, the three directions being:
[0120] Longitude, latitude, and depth.
[0121] In step 120: The seismic profile data is saved to a preset database according to a preset saving strategy.
[0122] For example, importing data into a database and building tables according to specifications.
[0123] In some embodiments, the preset database includes:
[0124] Geospatial database.
[0125] The preset save strategy can be set according to actual needs.
[0126] For example, seismic profile data is saved to a table in a preset database, with three preset directions as the table headers.
[0127] In step 130: the seismic profile data stored in the preset database is preprocessed to clean up the scattered points with outliers and / or zero values, so as to obtain preprocessed seismic profile data.
[0128] The purpose of cleaning is to remove dirty data from seismic profile data, thereby cleaning out anomalies such as outliers and / or zero values, in order to prepare for subsequent data separation.
[0129] In step 140: Based on the preset distance, the model generates functional components that run in the preset database environment, and the functional components determine the distances between all adjacent scattered points in the preprocessed seismic profile data.
[0130] The Haversine formula is a precise method for calculating the distance between two points on Earth, taking into account the Earth's curvature. Based on spherical trigonometry, the Haversine formula assumes the Earth is a perfect sphere. The formula considers the Earth's radius and the difference in latitude and longitude between the two points to calculate the shortest distance between them (i.e., the great circle distance). The specific formula (i.e., the preset distance determination model described in the foregoing embodiments) can be expressed as follows:
[0131]
[0132] Where P1 is the first of two adjacent data points, P2 is the second of two adjacent data points, latP1 is the latitude of the first data point, latP2 is the latitude of the second data point, lonP1 is the longitude of the first data point, lonP2 is the longitude of the second data point, and R is the Earth's radius.
[0133] Optionally, in the preset database environment, a corresponding functional component is generated based on the preset distance determination model (e.g., a program / script written based on the preset distance determination model, which can be executed in the preset database to complete the function implemented based on the preset distance determination model), and the functional component is run in the preset database environment to execute and complete the function implemented by the preset distance determination model.
[0134] Specifically, by using a preset distance determination model, the distance between all two adjacent data points in the preprocessed seismic profile data can be determined.
[0135] For example, if the data in a certain preset direction in the preprocessed seismic profile data includes: a0, a1, a2, a3, a4, a5, a6..., then the distance between a0 and a1, the distance between a1 and a2, the distance between a2 and a3, and so on can be determined by the preset distance determination model.
[0136] In this step, database programming can be performed based on formula (6), and the distance between two adjacent scattered points can be determined by running the database program.
[0137] In step 150: if the distance between adjacent scattered points meets the preset conditions, it is determined that the adjacent scattered points are located in different layers, and the next scattered point among the adjacent scattered points is taken as the starting point of the next layer, and all scattered points before the starting point of the next layer are taken as scattered points located in the same layer.
[0138] As an example, a single layer of data can be referenced. Figure 3 .
[0139] In this step, after determining the distance between two adjacent scatter points by running the database program, a preset scatter point distance threshold is set, and the layers in each profile are separated based on the distance between all adjacent scatter points and the preset scatter point distance threshold.
[0140] Specifically, if the distance between adjacent scattered points meets the preset conditions, the adjacent scattered points are determined to be located on different floors; if the distance between adjacent scattered points does not meet the preset conditions, the adjacent scattered points are determined to be located on the same floor.
[0141] Furthermore, if the distance between adjacent scattered points meets the preset conditions, the next scattered point among the adjacent scattered points is taken as the starting point of the next layer, and all scattered points before the starting point of the next layer are taken as scattered points located in the same layer.
[0142] In some embodiments, the preset conditions include:
[0143] The distance between adjacent scattered points is not greater than the preset scattered point distance threshold.
[0144] In some embodiments, the method for determining the preset scatter distance threshold includes:
[0145] The preset scatter point distance threshold is determined based on the distance between adjacent scatter points and through expert experience.
[0146] The preset scatter distance threshold is not fixed. It can be determined by experts through analysis and evaluation based on geological conditions and / or the collected seismic profile layer data, so as to determine the preset scatter distance threshold applicable to the current seismic profile layer data.
[0147] In some embodiments, the method further includes:
[0148] Saving process: Determine the target layer of all scattered points before the starting point of the next layer, and save the data of all scattered points before the starting point of the next layer in the data table corresponding to the target layer; and filter new seismic profile data from the preprocessed seismic profile data starting from the starting point of the next layer.
[0149] Judgment process: If the new seismic profile data is not empty, for the new seismic profile data, if the distance between adjacent scattered points meets the preset conditions, it is determined that the adjacent scattered points are located in different layers, and the latter scattered point among the adjacent scattered points is taken as the starting point of the next layer, and all scattered points before the starting point of the next layer are taken as scattered points located in the same layer.
[0150] Repeat the saving process and the judgment process until all the scattered data in the preprocessed seismic profile data are saved in the data table.
[0151] Furthermore, multiple stratigraphic data from different sections but located in the same stratum are combined, such as... Figure 4 As shown; then perform surface interpolation to obtain a stratigraphic surface, as shown. Figure 5 As shown.
[0152] In some embodiments, the method further includes:
[0153] Export the layered data as required.
[0154] The seismic profile layer-tracing data separation method provided in this embodiment significantly improves efficiency compared to existing technologies due to its large-scale database processing capabilities; furthermore, it offers strong scalability by implementing various data processing requirements through programming.
[0155] The seismic profile stratigraphic data separation method provided in this application has significant advantages over existing technologies when processing large-scale datasets due to the use of database programming, particularly specialized geospatial databases (such as PostgreSQL). During computation, the rich functions provided by the PostGIS extension module of PostgreSQL are utilized to perform spatial analysis, and scripts are edited to separate the same stratigraphic data from different profiles, thereby improving work efficiency and meeting actual production needs.
[0156] Example 4:
[0157] Another embodiment of this application relates to a seismic profile layer-tracking data separation device.
[0158] The implementation details of the seismic profile layer-tracing data separation device in this embodiment are described below. The following implementation details are provided for ease of understanding and are not essential for implementing this solution. The seismic profile layer-tracing data separation device provided in this embodiment includes:
[0159] An acquisition module is used to acquire seismic profile data, wherein the seismic profile data includes data from multiple scattered points;
[0160] The storage module is used to save the seismic profile data to a preset database according to a preset storage strategy;
[0161] The preprocessing module is used to preprocess the seismic profile data stored in the preset database to clean up the scattered points with outliers and / or zero values, and obtain preprocessed seismic profile data.
[0162] The distance determination module is used to generate functional components that run in the preset database environment based on a preset distance determination model, and to determine the distances between all adjacent scattered points in the preprocessed seismic profile data through the functional components.
[0163] The separation module is used to determine that adjacent scattered points are located in different layers when the distance between adjacent scattered points meets a preset condition, and to take the next scattered point in the adjacent scattered points as the starting point of the next layer, and to take all scattered points before the starting point of the next layer as scattered points located in the same layer.
[0164] In this embodiment, by setting a threshold for the distance between scatter points at the same level in each profile, the data of different levels in the seismic profile are divided so that separate level surface data can be generated later.
[0165] The theoretical proof for calculating the distance between scatter points on the stratigraphic level is as follows:
[0166] The Earth ellipsoid (also known as the "Earth ellipsoid" or "Earth oblate spheroid") is a mathematical surface representing the size and shape of the Earth, expressed by its major axis and flattening. Because it closely approximates an ellipsoid, the shape and size of the Earth ellipsoid are usually represented by a reference ellipsoid. It is the shape formed by rotating an ellipse around its minor axis and approximates the Earth's geoid. The shape of the geoid is expressed by its deviation from the reference ellipsoid. The parameters that determine the shape and size of the Earth ellipsoid are: major axis a (equatorial radius), minor axis b (polar radius), and the flattening f of the ellipsoid.
[0167]
[0168] Where e is the first eccentricity and e′ is the second eccentricity.
[0169] In practical engineering applications, based on the accuracy requirements of measurement work, within a certain range, the ellipsoid can be considered as a sphere with an appropriate radius. That is, taking the average value of all directions passing through a certain point on the ground as the radius of this sphere is appropriate. The radius of this sphere (mean radius of curvature) is defined as follows:
[0170]
[0171]
[0172] Where W is the first fundamental latitude function.
[0173] In the acquisition module: acquire seismic profile data, wherein the seismic profile data includes data from multiple scattered points.
[0174] In some embodiments, each scatter point in the seismic profile data includes data in three directions, the three directions being:
[0175] Longitude, latitude, and depth.
[0176] In the storage module: the seismic profile data is saved to the preset database according to the preset storage strategy.
[0177] For example, importing data into a database and building tables according to specifications.
[0178] In some embodiments, the preset database includes:
[0179] Geospatial database.
[0180] The preset save strategy can be set according to actual needs.
[0181] For example, seismic profile data is saved to a table in a preset database, with three preset directions as the table headers.
[0182] In the preprocessing module: the seismic profile data stored in the preset database is preprocessed to clean up the scattered points with outliers and / or zero values, so as to obtain preprocessed seismic profile data.
[0183] The purpose of cleaning is to remove dirty data from seismic profile data, thereby cleaning out anomalies such as outliers and / or zero values, in order to prepare for subsequent data separation.
[0184] In the distance determination module: a functional component is generated based on a preset distance determination model to run in the preset database environment, and the distance between all adjacent scattered points in the preprocessed seismic profile data is determined by the functional component.
[0185] The Haversine formula is a precise method for calculating the distance between two points on Earth, taking into account the Earth's curvature. Based on spherical trigonometry, the Haversine formula assumes the Earth is a perfect sphere. The formula considers the Earth's radius and the difference in latitude and longitude between the two points to calculate the shortest distance between them (i.e., the great circle distance). The specific formula (i.e., the preset distance determination model described in the foregoing embodiments) can be expressed as follows:
[0186]
[0187] Where P1 is the first of two adjacent data points, P2 is the second of two adjacent data points, latP1 is the latitude of the first data point, latP2 is the latitude of the second data point, lonP1 is the longitude of the first data point, lonP2 is the longitude of the second data point, and R is the Earth's radius.
[0188] Optionally, in the preset database environment, a corresponding functional component is generated based on the preset distance determination model (e.g., a program / script written based on the preset distance determination model, which can be executed in the preset database to complete the function implemented based on the preset distance determination model), and the functional component is run in the preset database environment to execute and complete the function implemented by the preset distance determination model.
[0189] Specifically, by using a preset distance determination model, the distance between all two adjacent data points in the preprocessed seismic profile data can be determined.
[0190] For example, if the data in a certain preset direction in the preprocessed seismic profile data includes: a0, a1, a2, a3, a4, a5, a6..., then the distance between a0 and a1, the distance between a1 and a2, the distance between a2 and a3, and so on can be determined by the preset distance determination model.
[0191] In this module, database programming can be performed based on formula (6), and the distance between two adjacent scattered points can be determined by running the database program.
[0192] In the separation module: if the distance between adjacent scattered points meets the preset conditions, it is determined that the adjacent scattered points are located in different layers, and the next scattered point in the adjacent scattered points is taken as the starting point of the next layer, and all scattered points before the starting point of the next layer are taken as scattered points located in the same layer.
[0193] In this module, after determining the distance between two adjacent scatter points by running a database program, a preset scatter point distance threshold is set, and the layers in each profile are separated based on the distances between all adjacent scatter points and the preset scatter point distance threshold.
[0194] Specifically, if the distance between adjacent scattered points meets the preset conditions, the adjacent scattered points are determined to be located on different floors; if the distance between adjacent scattered points does not meet the preset conditions, the adjacent scattered points are determined to be located on the same floor.
[0195] Furthermore, if the distance between adjacent scattered points meets the preset conditions, the next scattered point among the adjacent scattered points is taken as the starting point of the next layer, and all scattered points before the starting point of the next layer are taken as scattered points located in the same layer.
[0196] In some embodiments, the preset conditions include:
[0197] The distance between adjacent scattered points is not greater than the preset scattered point distance threshold.
[0198] In some embodiments, the method for determining the preset scatter distance threshold includes:
[0199] The preset scatter point distance threshold is determined based on the distance between adjacent scatter points and through expert experience.
[0200] The preset scatter distance threshold is not fixed. It can be determined by experts through analysis and evaluation based on geological conditions and / or the collected seismic profile layer data, so as to determine the preset scatter distance threshold applicable to the current seismic profile layer data.
[0201] In some embodiments, the apparatus further includes:
[0202] The saving module is used to execute the saving process: determine the target layer of all scattered points before the starting point of the next layer, and save the data of all scattered points before the starting point of the next layer in the data table corresponding to the target layer; and filter new seismic profile data from the preprocessed seismic profile data starting from the starting point of the next layer.
[0203] The determination module is used to execute the determination process: when the new seismic profile data is not empty, for the new seismic profile data, if the distance between adjacent scattered points meets the preset conditions, it determines that the adjacent scattered points are located in different layers, and takes the last scattered point among the adjacent scattered points as the starting point of the next layer, and takes all scattered points before the starting point of the next layer as scattered points located in the same layer.
[0204] The polling module is used to repeatedly execute the saving process and the judgment process until the data of all scattered points in the preprocessed seismic profile data are saved in the data table.
[0205] In some embodiments, the apparatus further includes:
[0206] The export module is used to export the layered data as required.
[0207] The seismic profile layer-tracing data separation method provided in this embodiment significantly improves efficiency compared to existing technologies due to its large-scale database processing capabilities; furthermore, it offers strong scalability by implementing various data processing requirements through programming.
[0208] The seismic profile stratigraphic data separation method provided in this application has significant advantages over existing technologies when processing large-scale datasets due to the use of database programming, particularly specialized geospatial databases (such as PostgreSQL). During computation, the rich functions provided by the PostGIS extension module of PostgreSQL are utilized to perform spatial analysis, and scripts are edited to separate the same stratigraphic data from different profiles, thereby improving work efficiency and meeting actual production needs.
[0209] It is worth mentioning that all modules involved in this embodiment are logical modules. In practical applications, a logical unit can be a physical unit, a part of a physical unit, or a combination of multiple physical units. Furthermore, to highlight the innovative aspects of this application, this embodiment does not introduce units that are not closely related to solving the technical problems proposed in this application; however, this does not mean that other units are absent in this embodiment.
[0210] Example 5:
[0211] Another embodiment of this application relates to an electronic device comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to enable the at least one processor to perform the seismic profile layer-by-layer data separation method of the above embodiments:
[0212] Acquire seismic profile data, wherein the seismic profile data includes data from multiple scattered points;
[0213] The seismic profile data is saved to a preset database according to a preset saving strategy.
[0214] The seismic profile data stored in the preset database is preprocessed to clean up the scattered points with outliers and / or zero values, so as to obtain preprocessed seismic profile data.
[0215] Based on the preset distance determination model, functional components are generated to run in the preset database environment, and the distances between all adjacent scattered points in the preprocessed seismic profile data are determined by the functional components respectively.
[0216] If the distance between adjacent scattered points meets the preset conditions, it is determined that the adjacent scattered points are located in different layers, and the next scattered point in the adjacent scattered points is taken as the starting point of the next layer, and all scattered points before the starting point of the next layer are taken as scattered points located in the same layer.
[0217] The memory and processor are connected via a bus, which can include any number of interconnecting buses and bridges, connecting various circuits of one or more processors and memories. The bus can also connect various other circuits, such as peripheral devices, voltage regulators, and power management circuits, which are well known in the art and will not be described further herein. The bus interface provides an interface between the bus and the transceiver. The transceiver can be a single element or multiple elements, such as multiple receivers and transmitters, providing a unit for communicating with various other devices over a transmission medium. Data processed by the processor is transmitted over the wireless medium via an antenna, which further receives data and transmits it to the processor.
[0218] The processor manages the bus and general processing, and also provides various functions, including timing, peripheral interfaces, voltage regulation, power management, and other control functions. Memory is used to store data used by the processor during operation.
[0219] Example 6:
[0220] Another embodiment of this application relates to a computer-readable storage medium storing a computer program. When executed by a processor, the computer program implements the seismic profile layer-tracking data separation method described in the above embodiments:
[0221] Acquire seismic profile data, wherein the seismic profile data includes data from multiple scattered points;
[0222] The seismic profile data is saved to a preset database according to a preset saving strategy.
[0223] The seismic profile data stored in the preset database is preprocessed to clean up the scattered points with outliers and / or zero values, so as to obtain preprocessed seismic profile data.
[0224] Based on the preset distance determination model, functional components are generated to run in the preset database environment, and the distances between all adjacent scattered points in the preprocessed seismic profile data are determined by the functional components respectively.
[0225] If the distance between adjacent scattered points meets the preset conditions, it is determined that the adjacent scattered points are located in different layers, and the next scattered point in the adjacent scattered points is taken as the starting point of the next layer, and all scattered points before the starting point of the next layer are taken as scattered points located in the same layer.
[0226] That is, those skilled in the art will understand that all or part of the steps in the methods of the above embodiments can be implemented by a program instructing related hardware. This program is stored in a storage medium and includes several instructions to cause a device (which may be a microcontroller, chip, etc.) or processor to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.
[0227] In some embodiments of this application, a computer program product is also provided, including a computer program that, when executed by a processor, implements the steps of the methods described in the above embodiments.
[0228] Those skilled in the art will understand that the above embodiments are specific embodiments for implementing this application, and in practical applications, various changes can be made to them in form and detail without departing from the spirit and scope of this application.
Claims
1. A method for separating seismic profile layer-by-layer data, characterized in that, include: Acquire seismic profile data, wherein the seismic profile data includes data from multiple scattered points; The seismic profile data is saved to a preset database according to a preset saving strategy. The seismic profile data stored in the preset database is preprocessed to clean up the scattered points with outliers and / or zero values, so as to obtain preprocessed seismic profile data. Based on the preset distance determination model, functional components are generated to run in the preset database environment, and the distances between all adjacent scattered points in the preprocessed seismic profile data are determined by the functional components respectively. If the distance between adjacent scattered points meets the preset conditions, it is determined that the adjacent scattered points are located in different layers, and the next scattered point in the adjacent scattered points is taken as the starting point of the next layer, and all scattered points before the starting point of the next layer are taken as scattered points located in the same layer.
2. The method according to claim 1, characterized in that, The preset database includes: Geospatial database.
3. The method according to claim 1, characterized in that, Each scatter point in the seismic profile data includes data in three directions, namely: Longitude, latitude, and depth.
4. The method according to claim 1, characterized in that, The method further includes: Saving process: Determine the target layer of all scattered points before the starting point of the next layer, and save the data of all scattered points before the starting point of the next layer in the data table corresponding to the target layer; and filter new seismic profile data from the preprocessed seismic profile data starting from the starting point of the next layer. Judgment process: If the new seismic profile data is not empty, for the new seismic profile data, if the distance between adjacent scattered points meets the preset conditions, it is determined that the adjacent scattered points are located in different layers, and the latter scattered point among the adjacent scattered points is taken as the starting point of the next layer, and all scattered points before the starting point of the next layer are taken as scattered points located in the same layer. Repeat the saving process and the judgment process until all the scattered data in the preprocessed seismic profile data are saved in the data table.
5. The method according to claim 1, characterized in that, The preset conditions include: The distance between adjacent scattered points is not greater than the preset scattered point distance threshold.
6. The method according to claim 5, characterized in that, The method for determining the preset scatter distance threshold includes: The preset scatter point distance threshold is determined based on the distance between adjacent scatter points and through expert experience.
7. The method according to claim 1, characterized in that, The preset distance determination model includes: Where P1 is the first of two adjacent data points, P2 is the second of two adjacent data points, latP1 is the latitude of the first data point, latP2 is the latitude of the second data point, lonP1 is the longitude of the first data point, lonP2 is the longitude of the second data point, and R is the Earth's radius.
8. A computer device, comprising a memory, a processor, and a computer program stored in the memory, characterized in that, The processor executes the computer program to implement the steps of the method according to any one of claims 1 to 7.
9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by a processor, the computer program implements the steps of the method according to any one of claims 1 to 7.
10. A computer program product, comprising a computer program, characterized in that, When executed by a processor, the computer program implements the steps of the method according to any one of claims 1 to 7.