A method, system and device for converting acoustic remote sensing data

Abstract

The present application relates to the technical field of acoustic wave detection, and more particularly to a method, system and device for converting acoustic wave remote detection data, the method comprising the following steps: S1, constructing a data format template; S2, obtaining acoustic wave remote detection data, which includes well name, data set name, depth value and total amplitude data, and storing the acoustic wave remote detection data in the data format template; S3, converting the total amplitude data into a plurality of single amplitude data, and storing all the converted single amplitude data in the data format template; S4, converting the acoustic wave remote detection data stored in the data format template by S2 and S3 into acoustic wave remote detection data in seismic data format; the present application improves the utilization degree of acoustic wave remote detection data.

Description

Technical Field

[0001] This invention relates to the field of acoustic wave detection technology, and in particular to a method, system and device for converting acoustic wave remote detection data. Background Technology

[0002] Acoustic long-range detection technology is a technology that uses sound waves for long-distance detection and imaging. Based on acoustic logging and its data processing results, it uses the reflected wave components in the wave field for corresponding processing, thereby realizing the identification of reflection interfaces such as strata and structures near the well. Similar to seismic exploration technology, it is a geophysical technology in a certain mode.

[0003] As a type of depth-domain waveform data, acoustic remote sensing data contains information such as energy, amplitude, and frequency in the depth domain. However, acoustic remote sensing data can currently only be processed and viewed in logging software, resulting in low utilization of the information it contains. It is impossible to analyze the acoustic remote sensing data in the software using analysis tools, and it is impossible to extract parameters such as energy, amplitude, and frequency from the acoustic remote sensing data. Therefore, the utilization of acoustic remote sensing data is low.

[0004] Therefore, there is an urgent need to provide a method, system, and device for converting acoustic remote detection data, which can improve the utilization of acoustic remote detection data compared with existing technologies. Summary of the Invention

[0005] This invention addresses the technical problems existing in the prior art and provides a method, system, and device for converting acoustic wave remote detection data.

[0006] To achieve the above objectives, the technical solution adopted by the present invention is as follows:

[0007] A method for converting acoustic long-range detection data includes the following steps:

[0008] S1. Construct a data format template;

[0009] S2. Obtain acoustic remote sounding data, which includes well name, dataset name, depth value and total amplitude data. Store the acoustic remote sounding data in the data format template respectively.

[0010] S3. Perform data conversion on the total amplitude data, converting it into multiple single amplitude data, and store all the converted single amplitude data into a data format template;

[0011] S4. Convert the acoustic remote sounding data stored in the data format template after steps S2 and S3 into acoustic remote sounding data in seismic data format.

[0012] Furthermore, the data format template in step S1 includes a first column, a second column, a third column, a fourth column, and a fifth column, which respectively store different acoustic remote detection data.

[0013] Furthermore, the first column is used to store the well name, the second column is used to store the dataset name, the third column is used to store the depth value, the fourth column is used to store the total amplitude data, and the fifth column is used to store the single amplitude data.

[0014] Furthermore, the total amplitude data corresponding to each depth value is composed of the sum of data received by multiple receivers set at that depth location at the same sampling time.

[0015] Furthermore, the fifth column comprises multiple sub-columns, the number of which is the same as the number of receivers set at the same depth location.

[0016] Furthermore, the number of single amplitude data points corresponding to each depth value after the S3 step transformation is the same as the number of sub-columns.

[0017] Furthermore, in step S3, the reshape function in Python is used to transform the total amplitude data.

[0018] Furthermore, in step S4, the acoustic remote sensing data stored in the data format template after steps S2 and S3 is converted into acoustic remote sensing data in seismic data format using the pandas and obspy modules in Python.

[0019] Furthermore, S4 specifically includes the following steps:

[0020] S41. In Python, set the number of rows to skip. Based on the number of rows to skip, load the data in the fifth column first, and replace any gaps in the loaded data in the fifth column with spaces.

[0021] S42. For the acoustic remote detection data stored in the data format template after steps S2 and S3, change the data type of the text data to numeric type.

[0022] S43. Filter out invalid data from the acoustic remote detection data converted into numerical data, and delete the filtered invalid acoustic remote detection data directly.

[0023] S44. Change the data type of the acoustic remote detection data after the filtering in step S43 to a 32-bit floating-point number type, and store the modified acoustic remote detection data in a dataFrame in the pandas module.

[0024] S45. Create the segy file header in the obspy module;

[0025] S46. Add the acoustic remote sensing data stored in the dataFrame to the Steam object in Python;

[0026] S47. Save the Steam object, which has had acoustic remote sensing data added in step S45, into the segy file header; thus obtaining acoustic remote sensing data in the same format as seismic data.

[0027] Furthermore, in step S42, the to_numetric() function from the pandas module is used to convert text data into numerical data.

[0028] Furthermore, in step S43, the pd.isna() function in the pandas module is used to filter out invalid acoustic remote sensing data.

[0029] Furthermore, in step S44, the astype function in the pandas module is used to convert the data into a 32-bit floating-point number.

[0030] A acoustic long-range detection data conversion system includes a first module, a second module, a third module, and a fourth module. The first module is used to execute the contents of step S1, the second module is used to execute the contents of step S2, the third module is used to execute the contents of step S3, and the fourth module is used to execute the contents of step S4.

[0031] A remote acoustic detection data conversion device includes a storage medium and a processor. The storage medium stores a computer program, and the processor is used to implement a remote acoustic detection data conversion method when executing the computer program.

[0032] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0033] This invention converts acoustic remote sensing data into a seismic data format, enabling it to be loaded into seismic processing software. The analysis tools within the seismic processing software can then be used to analyze the data, allowing for viewing, processing, and application within the seismic software. Parameters such as energy, amplitude, and frequency of the acoustic remote sensing data can be extracted, thereby improving the utilization of acoustic remote sensing data. Attached Figure Description

[0034] Figure 1 This is a flowchart of the method of the present invention.

[0035] Figure 2 This is a schematic diagram of the data after the total amplitude data has been transformed using the reshape function in Python according to the present invention.

[0036] Figure 3 This is a schematic diagram of acoustic remote sensing data converted by the present invention and in the same format as earthquake data. Detailed Implementation

[0037] The technical solution of the present invention will be clearly described below with reference to the accompanying drawings. Obviously, the described embodiments are not all embodiments of the present invention. All other embodiments obtained by those skilled in the art without creative effort are within the protection scope of the present invention.

[0038] like Figure 1 As shown, the present invention provides a method for converting acoustic long-range detection data, comprising the following steps:

[0039] S1. Construct a data format template. The data format template includes a first column, a second column, a third column, a fourth column, and a fifth column. The first column is used to store the well name, the second column is used to store the dataset name, the third column is used to store the depth value, the fourth column is used to store the total amplitude data, and the fifth column is used to store the single amplitude data. The fifth column includes multiple sub-columns, preferably eight sub-columns.

[0040] S2. Acquire acoustic remote sensing data, divide the acoustic remote sensing data into well names, dataset names, depth values, and total amplitude data, and store the divided well names in the first column of the data format template, the divided dataset names in the second column, the divided depth values ​​in the third column, and the divided total amplitude data in the fourth column.

[0041] The total amplitude data consists of data received by eight receivers. That is, eight receivers are set up at the same depth position and arranged horizontally. The sum of the data received by the eight receivers at the same depth position at the same sampling time is the total amplitude data.

[0042] S3. Convert the total amplitude data obtained in step S2 into eight single amplitude data points arranged horizontally at each depth position. Each single amplitude data point corresponds to the data received by a receiver at that depth position. Store the eight single amplitude data points into eight columns of the data format template.

[0043] In step S3, the `reshape` function in Python is used to transform the total amplitude data; each single amplitude data point includes both direct and reflected waves, such as... Figure 2 As shown.

[0044] S4. Convert the acoustic remote sensing data stored in the data format template after steps S2 and S3 into seismic data format. This is done using the pandas and obspy modules in Python, and includes the following steps:

[0045] S41. In Python, set the number of rows to skip. Based on the set number of rows to skip, load the data in the fifth column first, and replace any gaps in the loaded data in the fifth column with spaces.

[0046] S42. For the acoustic remote sensing data stored in the data format template after steps S2 and S3, change the data type of the text data to numeric data; specifically, use the to_numetric() function in the pandas module of Python to convert the text data into numeric data.

[0047] S43. Filter out invalid data from the acoustic remote sensing data converted to numerical data. Specifically, use the pd.isna() function in the pandas module of Python to identify the numerical acoustic remote sensing data, filter out invalid acoustic remote sensing data, and delete the filtered invalid acoustic remote sensing data directly.

[0048] S44. Change the data type of the acoustic remote sensing data filtered in step S43 to a 32-bit floating-point number type. Specifically, use the astype function in the pandas module of Python to convert it to a 32-bit floating-point number type. Store the acoustic remote sensing data processed in this step in a dataFrame in the pandas module.

[0049] S45. Create the segy file header in the obspy module of Python.

[0050] S46. Add the acoustic remote sensing data stored in the dataFrame to the Steam object in Python.

[0051] S47. Save the Steam object, after adding acoustic remote sensing data in step S45, into the Segy file header; this yields acoustic remote sensing data in the same format as seismic data. The acoustic remote sensing data with the same format as seismic data is as follows: Figure 3 As shown.

[0052] The present invention also provides a sound wave remote detection data conversion system, including a first module, a second module, a third module and a fourth module. The first module is used to execute the contents of step S1, the second module is used to execute the contents of step S2, the third module is used to execute the contents of step S3, and the fourth module is used to execute the contents of step S4.

[0053] The present invention also provides a sound wave remote detection data conversion device, including a storage medium and a processor. The storage medium stores a computer program, and the processor is used to implement the sound wave remote detection data conversion method provided by the present invention when executing the computer program.

[0054] Currently, acoustic remote sensing data can only be processed and viewed in well logging software. As a type of depth-domain waveform data, its inherent data format is similar to that of seismic data. This invention converts the acoustic remote sensing data format into a seismic data format, enabling it to be loaded into seismic processing software. Then, the analysis tools in the seismic processing software can be used to analyze it, allowing it to be viewed, processed, and applied within the seismic software. Parameters such as energy, amplitude, and frequency of the acoustic remote sensing data can be extracted, thereby improving the utilization of acoustic remote sensing data.

[0055] Finally, it should be noted that the above content is only used to illustrate the technical solution of the present invention, and is not intended to limit the scope of protection of the present invention. Simple modifications or equivalent substitutions made by those skilled in the art to the technical solution of the present invention do not depart from the essence and scope of the technical solution of the present invention.

Claims

1. A method for converting acoustic long-range detection data, characterized in that, Includes the following steps: S1. Construct a data format template; S2. Obtain acoustic remote sounding data, which includes well name, dataset name, depth value and total amplitude data. Store the acoustic remote sounding data in the data format template respectively. S3. Perform data conversion on the total amplitude data, converting it into multiple single amplitude data, and store all the converted single amplitude data into a data format template; S4. Convert the acoustic remote sounding data stored in the data format template after steps S2 and S3 into acoustic remote sounding data in seismic data format.

2. The acoustic long-range detection data conversion method according to claim 1, characterized in that, The data format template in step S1 includes columns 1, 2, 3, 4, and 5, which store different acoustic remote detection data respectively.

3. The acoustic long-range detection data conversion method according to claim 2, characterized in that, The first column stores the well name, the second column stores the dataset name, the third column stores the depth value, the fourth column stores the total amplitude data, and the fifth column stores the single amplitude data.

4. The acoustic long-range detection data conversion method according to claim 3, characterized in that, The total amplitude data corresponding to each depth value is composed of the sum of data received by multiple receivers set at that depth location at the same sampling time.

5. The acoustic long-range detection data conversion method according to claim 4, characterized in that, The fifth column comprises multiple sub-columns, the number of which is the same as the number of receivers set at the same depth location.

6. The acoustic long-range detection data conversion method according to claim 5, characterized in that, After the S3 step transformation, the number of single amplitude data corresponding to each depth value is the same as the number of sub-columns.

7. The acoustic long-range detection data conversion method according to claim 1, characterized in that, In step S3, the reshape function in Python is used to transform the total amplitude data.

8. The acoustic long-range detection data conversion method according to claim 2, characterized in that, In step S4, the pandas and obspy modules in Python are used to convert the acoustic remote sensing data stored in the data format template after steps S2 and S3 into acoustic remote sensing data in seismic data format.

9. The acoustic long-range detection data conversion method according to claim 8, characterized in that, S4 specifically includes the following steps: S41. In Python, set the number of rows to skip. Based on the number of rows to skip, load the data in the fifth column first, and replace any gaps in the loaded data in the fifth column with spaces. S42. For the acoustic remote detection data stored in the data format template after steps S2 and S3, change the data type of the text data to numeric type. S43. Filter out invalid data from the acoustic remote detection data converted into numerical data, and delete the filtered invalid acoustic remote detection data directly. S44. Change the data type of the acoustic remote detection data after the filtering in step S43 to a 32-bit floating-point number type, and store the modified acoustic remote detection data in a dataFrame in the pandas module. S45. Create the segy file header in the obspy module; S46. Add the acoustic remote sensing data stored in the dataFrame to the Steam object in Python; S47. Save the Steam object, which has had acoustic remote sensing data added in step S45, into the segy file header; thus obtaining acoustic remote sensing data in the same format as seismic data.

10. A method for converting acoustic long-range detection data according to claim 9, characterized in that, In step S42, the to_numetric() function from the pandas module is used to convert text data into numerical data.

11. The acoustic long-range detection data conversion method according to claim 9, characterized in that, In step S43, the pd.isna() function in the pandas module is used to filter out invalid acoustic remote sensing data.

12. The acoustic long-range detection data conversion method according to claim 9, characterized in that, In step S44, the astype function in the pandas module is used to convert the data into a 32-bit floating-point number.

13. A acoustic long-range detection data conversion system, characterized in that, The method for converting acoustic remote detection data according to any one of claims 1-14 includes a first module, a second module, a third module, and a fourth module. The first module is used to execute the content of step S1, the second module is used to execute the content of step S2, the third module is used to execute the content of step S3, and the fourth module is used to execute the content of step S4.

14. A data conversion device for acoustic long-range detection, characterized in that, It includes a storage medium and a processor, wherein the storage medium stores a computer program, and the processor is used to implement the acoustic remote detection data conversion method according to any one of claims 1-14 when executing the computer program.

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