Data processing method and device, computer readable storage medium and computer equipment

Abstract

This invention discloses a data processing method, apparatus, computer-readable storage medium, and computer device. The method includes: acquiring multiple first time-domain waveforms corresponding to different depth points of a target well; acquiring multiple first frequency-domain waveforms corresponding to the multiple first time-domain waveforms; acquiring reference frequency-domain waveforms corresponding to the multiple first frequency-domain waveforms; determining abnormal first frequency-domain waveforms among the multiple first frequency-domain waveforms based on the multiple first frequency-domain waveforms and their corresponding reference frequency-domain waveforms; removing the abnormal first time-domain waveforms from the multiple first time-domain waveforms to obtain multiple second time-domain waveforms; and determining the target time-domain waveform of the target well based on the multiple second time-domain waveforms. This invention solves the technical problems of inaccurate data analysis results caused by abnormal data and the high cost of re-acquiring data during well logging.

Description

Technical Field

[0001] This invention relates to the field of geophysical logging, and more specifically, to a data processing method, apparatus, computer-readable storage medium, and computer equipment. Background Technology

[0002] In related technologies, data loss or errors may occur during the process of using sonic logging. These abnormal data will affect the subsequent analysis and processing of sonic data, and re-acquiring data will increase the cost of data acquisition.

[0003] Therefore, in related technologies, there are technical problems such as inaccurate data analysis results caused by abnormal data during well logging and excessively high costs associated with re-acquiring data.

[0004] There is currently no effective solution to the above problems. Summary of the Invention

[0005] This invention provides a data processing method, apparatus, computer-readable storage medium, and computer equipment to at least solve the technical problems of inaccurate data analysis results caused by abnormal data during well logging and the high cost of re-acquiring data.

[0006] According to one aspect of the present invention, a data processing method is provided, comprising: acquiring a plurality of first time-domain waveforms corresponding to different depth points of a target well; acquiring a plurality of first frequency-domain waveforms corresponding to the plurality of first time-domain waveforms; acquiring reference frequency-domain waveforms corresponding to the plurality of first frequency-domain waveforms; determining abnormal first frequency-domain waveforms in the plurality of first frequency-domain waveforms based on the plurality of first frequency-domain waveforms and the corresponding reference frequency-domain waveforms; removing the abnormal first time-domain waveforms from the plurality of first time-domain waveforms to obtain a plurality of second time-domain waveforms; and determining the target time-domain waveform of the target well based on the plurality of second time-domain waveforms.

[0007] Optionally, obtaining reference frequency domain waveforms corresponding to multiple first frequency domain waveforms includes: dividing the multiple first frequency domain waveforms into multiple frequency domain waveform groups based on the order of the depth points corresponding to the multiple first frequency domain waveforms; determining the frequency domain waveform groups corresponding to the multiple first frequency domain waveforms; determining the target depth point located at the middle position among the depth points included in the frequency domain waveform groups corresponding to the multiple first frequency domain waveforms; and determining the reference frequency domain waveforms corresponding to the multiple first frequency domain waveforms based on the first frequency domain waveforms corresponding to the target depth point.

[0008] Optionally, based on the first frequency domain waveform corresponding to the target depth point, a reference frequency domain waveform corresponding to the multiple first frequency domain waveforms is determined, including: when the number of target depth points is 1, the first frequency domain waveform corresponding to the target depth point is determined as the reference frequency domain waveform corresponding to the multiple first frequency domain waveforms; when the number of target depth points is 2, the two first frequency domain waveforms corresponding to the target depth points are averaged to obtain a first frequency domain average waveform, and the first frequency domain average waveform is determined as the reference frequency domain waveform corresponding to the multiple first frequency domain waveforms.

[0009] Optionally, based on multiple first frequency domain waveforms and corresponding reference frequency domain waveforms, an abnormal first frequency domain waveform is determined among multiple first frequency domain waveforms, including: obtaining the difference coefficient between multiple first frequency domain waveforms and corresponding reference frequency domain waveforms; and determining the corresponding first frequency domain waveform as an abnormal first frequency domain waveform when the difference coefficient is greater than a first predetermined threshold.

[0010] Optionally, determining the target time domain waveform of the target well based on multiple second time domain waveforms includes: acquiring multiple second frequency domain waveforms corresponding to the multiple second time domain waveforms; setting the amplitude of the signal in the multiple second frequency domain waveforms that is not greater than a second predetermined threshold to zero to obtain multiple target frequency domain waveforms; and determining multiple target time domain waveforms corresponding to the multiple target frequency domain waveforms.

[0011] Optionally, the amplitude of the signal in the second frequency domain waveform that is not greater than the second predetermined threshold is set to zero to obtain the target frequency domain waveform. This includes: using the method of updating the second predetermined threshold, the second frequency domain waveform is iteratively set to zero a predetermined number of times to obtain the target frequency domain waveform. The updating of the second predetermined threshold includes: updating the second predetermined threshold based on the maximum amplitude value corresponding to the second frequency domain waveform and predetermined parameters.

[0012] According to another aspect of the present invention, a data processing apparatus is also provided, comprising: a first acquisition module, configured to acquire a plurality of first time-domain waveforms corresponding to different depth points of a target well; a second acquisition module, configured to acquire a plurality of first frequency-domain waveforms corresponding to the plurality of first time-domain waveforms; a third acquisition module, configured to acquire reference frequency-domain waveforms corresponding to the plurality of first frequency-domain waveforms; a first determination module, configured to determine abnormal first frequency-domain waveforms among the plurality of first frequency-domain waveforms based on the plurality of first frequency-domain waveforms and the corresponding reference frequency-domain waveforms; a clearing module, configured to clear the abnormal first time-domain waveforms from the plurality of first time-domain waveforms to obtain a plurality of second time-domain waveforms; and a second determination module, configured to determine the target time-domain waveform of the target well based on the plurality of second time-domain waveforms.

[0013] Optionally, the third acquisition module includes: a division unit, configured to divide the multiple first frequency domain waveforms into multiple frequency domain waveform groups based on the order of depth points corresponding to the multiple first frequency domain waveforms; a first determination unit, configured to determine the frequency domain waveform groups corresponding to the multiple first frequency domain waveforms respectively; a second determination unit, configured to determine the target depth point located at the middle position among the depth points included in the frequency domain waveform groups corresponding to the multiple first frequency domain waveforms respectively; and a third determination unit, configured to determine the reference frequency domain waveforms corresponding to the multiple first frequency domain waveforms based on the first frequency domain waveforms corresponding to the target depth points respectively.

[0014] According to another aspect of the present invention, a computer-readable storage medium is also provided, the computer-readable storage medium including a stored program, wherein, when the program is executed, it controls the device where the computer-readable storage medium is located to perform the data processing method described above.

[0015] According to another aspect of the present invention, a computer device is also provided, comprising: a memory and a processor, wherein the memory stores a computer program; and the processor is configured to execute the computer program stored in the memory, wherein the computer program, when running, causes the processor to perform any of the above-described data processing methods.

[0016] In this embodiment of the invention, by converting the time-domain waveforms collected at different depth points of the target well into frequency-domain waveforms and comparing the frequency-domain waveforms with reference frequency-domain waveforms, frequency-domain waveform data with obvious abnormal data is identified. The waveform data corresponding to these frequency-domain waveforms with abnormal data in the time domain is then cleared, thereby achieving the purpose of clearing abnormal data from the collected time-domain waveform data. This achieves the technical effect of identifying and clearing abnormal data from the original time-domain waveform, and solves the technical problems of inaccurate data analysis results caused by abnormal data and excessively high costs associated with re-collecting data during well logging. Attached Figure Description

[0017] The accompanying drawings, which are included to provide a further understanding of the invention and form part of this application, illustrate exemplary embodiments of the invention and, together with their description, serve to explain the invention and do not constitute an undue limitation thereof. In the drawings:

[0018] Figure 1 This is a flowchart of a data processing method according to an embodiment of the present invention;

[0019] Figure 2 This is a flowchart of an adaptive identification and reconstruction method for bad passages in acoustic logging according to an optional embodiment of the present invention;

[0020] Figure 3 This is a schematic diagram of the difference coefficient distribution according to an optional embodiment of the present invention;

[0021] Figure 4 This is a schematic diagram of the bad sector identification results according to an optional embodiment of the present invention;

[0022] Figure 5 This is a schematic diagram of setting the bad sector depth segment to zero according to an optional embodiment of the present invention;

[0023] Figure 6 This is a comparison diagram of bad sector depth segment data and reconstruction results according to an optional embodiment of the present invention;

[0024] Figure 7 This is a structural block diagram of a data processing apparatus according to an embodiment of the present invention. Detailed Implementation

[0025] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0026] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0027] Terminology Explanation

[0028] Sonic logging is a logging method that uses the differences in acoustic properties, such as the speed, amplitude, and frequency of sound waves as they propagate through different rocks, to study the geological profile of a well and to determine the quality of cementing.

[0029] The coefficient of variation, also known as the coefficient of variability, is denoted by CV. It is the percentage of the standard deviation of a set of data to its mean, and is a relative indicator for measuring the degree of dispersion of data; it is a measure of relative variability.

[0030] According to an embodiment of the present invention, a method embodiment for data processing is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0031] Figure 1 This is a flowchart of a data processing method according to an embodiment of the present invention, such as... Figure 1 As shown, the method includes the following steps:

[0032] Step S102: Obtain multiple first time-domain waveforms corresponding to different depth points of the target well;

[0033] Step S104: Obtain multiple first frequency domain waveforms corresponding to multiple first time domain waveforms respectively;

[0034] Step S106: Obtain the reference frequency domain waveforms corresponding to the multiple first frequency domain waveforms respectively;

[0035] Step S108: Based on multiple first frequency domain waveforms and corresponding reference frequency domain waveforms, determine the abnormal first frequency domain waveforms among the multiple first frequency domain waveforms;

[0036] Step S110: Remove the abnormal first time-domain waveform from the multiple first time-domain waveforms to obtain multiple second time-domain waveforms;

[0037] Step S112: Determine the target time domain waveform of the target well based on multiple second time domain waveforms.

[0038] Through the above steps, the time-domain waveforms acquired at different depth points of the target well are converted into frequency-domain waveforms. The frequency-domain waveforms are then compared with reference frequency-domain waveforms to identify frequency-domain waveforms with obvious abnormal data. The corresponding waveforms in the time domain for these frequency-domain waveforms with abnormal data are then cleared, achieving the goal of removing abnormal data from the acquired time-domain waveform data. This achieves the technical effect of identifying and clearing abnormal data from the original time-domain waveforms, thereby solving the technical problems of inaccurate data analysis results caused by abnormal data and the high cost of re-acquiring data during well logging.

[0039] As an optional embodiment, when obtaining reference frequency domain waveforms corresponding to multiple first frequency domain waveforms, various methods can be used. For example, the following methods can be used: divide the multiple first frequency domain waveforms into multiple frequency domain waveform groups based on the order of the depth points corresponding to the multiple first frequency domain waveforms; determine the frequency domain waveform groups corresponding to the multiple first frequency domain waveforms; determine the target depth point located at the middle position among the depth points included in the frequency domain waveform groups corresponding to the multiple first frequency domain waveforms; and determine the reference frequency domain waveforms corresponding to the multiple first frequency domain waveforms based on the first frequency domain waveforms corresponding to the target depth points. When determining the reference frequency domain waveform corresponding to the first frequency domain waveform, considering that the waveform data obtained when the depth point positions are large may also differ to some extent, in order to ensure that the determined reference frequency domain waveform has sufficient reliability, a method can be adopted to first group the frequency domain waveforms according to the depth points and then determine the reference frequency domain waveform corresponding to each group of frequency domain waveforms. For example, the frequency domain waveforms corresponding to every 5 depth points can be determined as a frequency domain waveform group. In this way, different reference frequency domain waveforms can be used for different depth ranges, avoiding the situation where abnormal data judgment errors are caused by using a fixed reference frequency domain waveform when the depth point positions are large. At the same time, in order to determine a reference frequency domain waveform with good reference for each first frequency domain waveform in the frequency domain waveform group, a target depth point located at the middle position can be determined from the depth points included in the frequency domain waveform group, and the frequency domain waveform corresponding to the target depth point can be determined as the reference frequency domain waveform.

[0040] As an optional embodiment, when determining the reference frequency domain waveform corresponding to multiple first frequency domain waveforms based on the first frequency domain waveform corresponding to each target depth point, various methods can be adopted. For example, the following methods can be used: when there is one target depth point, the first frequency domain waveform corresponding to the target depth point is determined as the reference frequency domain waveform corresponding to multiple first frequency domain waveforms; when there are two target depth points, the two first frequency domain waveforms corresponding to the target depth points are averaged to obtain the first frequency domain average waveform, and the first frequency domain average waveform is determined as the reference frequency domain waveform corresponding to multiple first frequency domain waveforms. When determining the reference frequency domain waveform corresponding to a target depth point, if there is only one target depth point, the frequency domain waveform corresponding to that depth point can be directly determined as the reference frequency domain waveform; if there are two target depth points, the frequency domain waveforms corresponding to these two target depth points can be averaged, and the averaged frequency domain waveform is determined as the reference frequency domain waveform.

[0041] As an optional embodiment, when determining abnormal first frequency domain waveforms among multiple first frequency domain waveforms and corresponding reference frequency domain waveforms, various methods can be used. For example, the following method can be used: obtain the difference coefficients between the multiple first frequency domain waveforms and the corresponding reference frequency domain waveforms respectively; if the difference coefficient is greater than a first predetermined threshold, determine that the corresponding first frequency domain waveform is an abnormal first frequency domain waveform. After determining the reference frequency domain waveform corresponding to the first frequency domain waveform, the difference between the first frequency domain waveform and the reference frequency domain waveform can be judged by calculating the difference coefficient between the two. If the calculated difference coefficient is greater than the first predetermined threshold, it can be considered that the first frequency domain waveform differs significantly from the reference frequency domain waveform, that is, the waveform data of the first frequency domain waveform is abnormal, with obvious data missing or data errors. Thus, all abnormal data in the first frequency domain waveform can be determined by the above method.

[0042] As an optional embodiment, when determining the target time-domain waveform of the target well based on multiple second time-domain waveforms, various methods can be adopted. For example, the following methods can be used: acquiring multiple second frequency-domain waveforms corresponding to the multiple second time-domain waveforms; setting the amplitudes of the signal in the multiple second frequency-domain waveforms that are not greater than a second predetermined threshold to zero to obtain multiple target frequency-domain waveforms; and determining the multiple target time-domain waveforms corresponding to the multiple target frequency-domain waveforms. After clearing the time-domain waveforms containing abnormal data from the first time-domain waveform, there may still be some data affected by abnormal data in the remaining second time-domain waveforms. For example, for waveforms containing abnormal data, the abnormal data may reduce the amplitude value of nearby waveforms, causing other waveforms to exhibit weak amplitudes. Therefore, in order to eliminate the influence of abnormal data, a second predetermined threshold can be used to judge the amplitude of the second frequency-domain waveforms corresponding to the second time-domain waveforms. The portion of the second frequency-domain waveform with an amplitude less than the second predetermined threshold is determined to be affected by abnormal data, and the influence of abnormal data in the second time-domain waveforms or second frequency-domain waveforms is eliminated by setting this portion of data to zero.

[0043] As an optional embodiment, when zeroing the amplitude of the signal in the second frequency domain waveform that is not greater than a second predetermined threshold to obtain the target frequency domain waveform, various methods can be used. For example, the following method can be used: updating the second predetermined threshold by iteratively zeroing the second frequency domain waveform a predetermined number of times to obtain the target frequency domain waveform. Updating the second predetermined threshold includes updating the second predetermined threshold based on the maximum amplitude value corresponding to the second frequency domain waveform and predetermined parameters. To achieve the accuracy requirements of the target time domain waveform, the second predetermined threshold can be continuously updated using the amplitude value corresponding to the newly obtained frequency domain waveform and predetermined parameters. The updated second predetermined threshold is then used to perform a new round of zeroing operations on the newly obtained frequency domain waveform. After the second frequency domain waveform has undergone a predetermined number of instruction operations, it can be considered that the obtained target frequency domain waveform meets the accuracy requirements. This means that the target frequency domain waveform corresponds to the target time domain waveform, i.e., the target time domain waveform corresponding to the target waveform.

[0044] It should be noted that the Fourier transform can be used to convert the first time-domain waveform to the frequency domain, while the inverse Fourier transform can be used to convert the first frequency-domain waveform to the time domain. Similarly, the two-dimensional Fourier transform can be used to convert the second time-domain waveform to the frequency domain, while the inverse two-dimensional Fourier transform can be used to convert the target frequency-domain waveform to the target time-domain waveform.

[0045] Based on the above embodiments and optional embodiments, the present invention proposes an optional implementation method, which will be described below.

[0046] During sonic logging, issues such as excessively high logging speeds, obstructions, and jamming often lead to missing or erroneous data in the acquired sonic array data, resulting in bad channels. Bad channels negatively impact subsequent sonic data processing and interpretation, and re-acquiring data significantly increases costs. Therefore, this invention proposes a novel technical process for adaptive identification and reconstruction of bad channels in sonic logging. This method includes targeted automatic identification of bad channels and adaptive reconstruction of sonic data based on convex set projection technology.

[0047] Figure 2 This is a flowchart of an adaptive identification and reconstruction method for bad passages in acoustic logging according to an optional embodiment of the present invention, such as... Figure 2 As shown, an optional embodiment of the present invention specifically includes the following steps:

[0048] (1) Perform acoustic logging (such as digital acoustic logging, variable density acoustic logging, array acoustic logging, etc.) to acquire data. Starting from a certain depth, take the original data X(t) and input it into the analysis process.

[0049] (2) In an optional embodiment of the present invention, bad channel data is identified by judging obviously inconsistent waveform data in the waveform data. Since the amplitude, shape and other properties of bad channel waveform data will be different from normal data, reference waveform data is selected, and the difference coefficient of each waveform data obtained by acoustic logging is calculated with the reference data along the depth direction. The difference coefficient is used to determine the difference between the waveform amplitude and the reference waveform amplitude. Specifically, the data X(t) obtained in (1) is subjected to fast Fourier transform to obtain spectrum data S(k). In order to simplify the reference waveform data selection process, in an optional embodiment of the present invention, the obtained Fourier transform data is set as a window along the depth direction, with each L depth point as a window, and the middle data of the window is taken as the reference data rf(k).

[0050] (3) After defining the reference data rf(k), compare each depth data within the window L with rf(k) and calculate the difference coefficient. The calculation formula is as follows:

[0051]

[0052] Among them, S i (k) is the waveform function, rf w (k) is the selected reference waveform data, C i It is the difference coefficient.

[0053] Figure 3 This is a schematic diagram of the difference coefficient distribution according to an optional embodiment of the present invention, such as... Figure 3 As shown, the difference coefficient C i The magnitude can determine the difference between the waveform amplitude and the reference waveform amplitude. It can be seen in the figure that C... i High values ​​are mainly distributed between depths of 4940m and 5060m;

[0054] (4) Analysis steps (3) Difference coefficient C i The size distribution is considered, and an appropriate bad passage judgment value m is selected based on the actual situation. In sonic logging data bad passage identification, m is generally taken as 0.2-4; if C i If the amplitude is >m, it indicates that the data has a significant difference from the reference data, and the data is therefore identified as bad track data.

[0055] Figure 4 This is a schematic diagram of the bad sector identification results according to an optional embodiment of the present invention, such as... Figure 4 As shown, when C i When the amplitude is greater than m, the amplitude of this data differs significantly from that of the reference data. Therefore, C in this data is... i The portion greater than m is identified as bad sector data. In this figure, the bad sector identification value m is assigned a value of 3.5.

[0056] Figure 5This is a schematic diagram of zeroing the bad sector depth segment according to an optional embodiment of the present invention, as shown below. Figure 5 As shown, almost all bad sector data is set to zero, which further proves that the bad sector identification technology in the optional embodiment of the present invention can identify bad sector data relatively accurately.

[0057] (5) Steps (2), (3), and (4) completed the identification process of bad passage data in the acoustic logging data. In order to complete the reconstruction process of bad passage data of the acoustic wave train, the optional implementation of the present invention first sets all bad passage data in the original waveform to zero according to the result of bad passage identification, so as to eliminate the adverse effect of bad passage data on acoustic waveform data. Specifically, according to the bad passage identification result of (4), the bad passage data in the original acoustic waveform data X(t) is first set to zero to obtain new waveform data X0(t), and then a two-dimensional Fourier transform is performed on the waveform data X0(t) after the zeroing process to obtain S0(k);

[0058] (6) Set the parameter λ(i) as shown in the formula below, where a represents the percentage of the data to be reconstructed in the total data, which is generally taken as 0.5-0.9; b represents the step size; i = 1, 2, ..., a / b, where a / b represents the number of iterations; c represents the percentage of noise, which is generally taken as 0.01.

[0059] λ(i) = [a, -b, c]

[0060] (7) Set the threshold parameter Threshod(i) as shown in the formula below, judge the magnitude of S0(k) and Threshod(i), and set S0(k) that is less than or equal to Threshod to zero in order to eliminate the influence of weak amplitude data.

[0061] Threshod(i)=λ(i)×max(|S0(k)|)

[0062] (8) Perform a two-dimensional Fourier transform on the data obtained in step (7) to reconstruct the acoustic logging waveform data;

[0063] (9) Repeat steps (6), (7), and (8) to iterate a / b times until the ideal accuracy is achieved, and complete the reconstruction of bad sector data.

[0064] Figure 6 This is a comparison diagram of bad sector depth segment data and reconstruction results according to an optional embodiment of the present invention, such as... Figure 6 As shown, Figure 6Taking λ(i) = [0.5, -0.01, 0.01] as an example, assuming that the data to be reconstructed accounts for 50% of the total data, the noise accounts for 1%, the iteration step size is 0.01, and the number of iterations is 50. The comparison chart of the original data and the reconstructed data shows that the bad sector data in the original data has achieved a good reconstruction effect, which also proves that the bad sector reconstruction technology in the invention method can accurately reconstruct bad sector data.

[0065] According to embodiments of the present invention, a data processing apparatus is also provided. Figure 7 This is a structural block diagram of a data processing apparatus according to an embodiment of the present invention, such as... Figure 7 As shown, the device includes: a first acquisition module 71, a second acquisition module 72, a third acquisition module 73, a first determination module 74, a clearing module 75, and a second determination module 76. The device will be described below.

[0066] A first acquisition module 71 is used to acquire multiple first time-domain waveforms corresponding to different depth points of the target well; a second acquisition module 72 is connected to the first acquisition module 71 and is used to acquire multiple first frequency-domain waveforms corresponding to the multiple first time-domain waveforms; a third acquisition module 73 is connected to the second acquisition module 72 and is used to acquire reference frequency-domain waveforms corresponding to the multiple first frequency-domain waveforms; a first determination module 74 is connected to the third acquisition module 73 and is used to determine abnormal first frequency-domain waveforms in the multiple first frequency-domain waveforms based on the multiple first frequency-domain waveforms and the corresponding reference frequency-domain waveforms; a clearing module 75 is connected to the first determination module 74 and is used to clear the abnormal first time-domain waveforms from the multiple first time-domain waveforms to obtain multiple second time-domain waveforms; a second determination module 76 is connected to the clearing module 75 and is used to determine the target time-domain waveform of the target well based on the multiple second time-domain waveforms.

[0067] As an optional embodiment, the third acquisition module 73 includes: a division unit, configured to divide the multiple first frequency domain waveforms into multiple frequency domain waveform groups based on the order of depth points corresponding to the multiple first frequency domain waveforms; a first determination unit, configured to determine the frequency domain waveform groups corresponding to the multiple first frequency domain waveforms respectively; a second determination unit, configured to determine the target depth point located at the middle position among the depth points included in the frequency domain waveform groups corresponding to the multiple first frequency domain waveforms respectively; and a third determination unit, configured to determine the reference frequency domain waveforms corresponding to the multiple first frequency domain waveforms based on the first frequency domain waveforms corresponding to the target depth points respectively.

[0068] According to an embodiment of the present invention, a computer-readable storage medium is also provided, the computer-readable storage medium including a stored program, wherein, when the program is running, it controls the device where the computer-readable storage medium is located to execute the data processing method described above.

[0069] According to an embodiment of the present invention, a computer device is also provided, comprising: a memory and a processor, wherein the memory stores a computer program; and the processor is configured to execute the computer program stored in the memory, wherein the computer program, when running, causes the processor to perform any of the above-described data processing methods.

[0070] The sequence numbers of the above embodiments of the present invention are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0071] In the above embodiments of the present invention, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0072] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. The device embodiments described above are merely illustrative; for example, the division of units can be a logical functional division, and in actual implementation, there may be other division methods. For instance, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual coupling, direct coupling, or communication connection may be through some interfaces; the indirect coupling or communication connection between units or modules may be electrical or other forms.

[0073] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0074] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0075] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, or optical disks.

[0076] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A data processing method, characterized in that, include: Acquire multiple first-time-domain waveforms corresponding to different depth points of the target well; Each of the multiple first frequency domain waveforms corresponding to the multiple first time domain waveforms is acquired; Each of the plurality of first frequency domain waveforms is obtained as a reference frequency domain waveform; Based on the plurality of first frequency domain waveforms and the corresponding reference frequency domain waveforms, respectively, abnormal first frequency domain waveforms are determined among the plurality of first frequency domain waveforms; The abnormal first frequency domain waveform is converted into an abnormal first time domain waveform using inverse Fourier transform; the abnormal first time domain waveform is then removed from the plurality of first time domain waveforms to obtain a plurality of second time domain waveforms; Based on the plurality of second time-domain waveforms, the target time-domain waveform of the target well is determined.

2. The method according to claim 1, characterized in that, The step of obtaining reference frequency domain waveforms corresponding to the plurality of first frequency domain waveforms includes: Based on the order of the depth points corresponding to the plurality of first frequency domain waveforms, the plurality of first frequency domain waveforms are divided into a plurality of frequency domain waveform groups; Each of the multiple first frequency domain waveforms is determined as a frequency domain waveform group; Determine the target depth point located at the middle position among the depth points included in the frequency domain waveform group corresponding to the plurality of first frequency domain waveforms; Based on the first frequency domain waveform corresponding to the target depth point, a reference frequency domain waveform corresponding to the plurality of first frequency domain waveforms is determined.

3. The method according to claim 2, characterized in that, The step of determining the reference frequency domain waveform corresponding to the plurality of first frequency domain waveforms based on the first frequency domain waveforms corresponding to the target depth points includes: When the number of target depth points is 1, the first frequency domain waveform corresponding to the target depth point is determined as the reference frequency domain waveform corresponding to the plurality of first frequency domain waveforms; When the number of target depth points is 2, the two first frequency domain waveforms corresponding to the target depth points are averaged to obtain the first frequency domain average waveform, and the first frequency domain average waveform is determined as the reference frequency domain waveform corresponding to the plurality of first frequency domain waveforms.

4. The method according to claim 1, characterized in that, The step of determining the abnormal first frequency domain waveform among the plurality of first frequency domain waveforms based on the plurality of first frequency domain waveforms and the corresponding reference frequency domain waveforms includes: The difference coefficients between the plurality of first frequency domain waveforms and the corresponding reference frequency domain waveforms are obtained respectively; If the difference coefficient is greater than a first predetermined threshold, the corresponding first frequency domain waveform is determined to be the abnormal first frequency domain waveform.

5. The method according to any one of claims 1 to 4, characterized in that, Determining the target time-domain waveform of the target well based on the plurality of second time-domain waveforms includes: Each of the multiple second time-domain waveforms is acquired; The amplitudes of the signals in the plurality of second frequency domain waveforms that are not greater than a second predetermined threshold are set to zero to obtain a plurality of target frequency domain waveforms; Each of the multiple target time-domain waveforms corresponding to the multiple target frequency-domain waveforms is determined.

6. The method according to claim 5, characterized in that, The step of setting the amplitude of the signal in the second frequency domain waveform, which is not greater than a second predetermined threshold, to zero to obtain the target frequency domain waveform includes: The target frequency domain waveform is obtained by iteratively setting the second frequency domain waveform to zero a predetermined number of times using the method of updating the second predetermined threshold. The updating of the second predetermined threshold includes updating the second predetermined threshold based on the maximum amplitude value corresponding to the second frequency domain waveform and predetermined parameters.

7. A data processing apparatus, characterized in that, include: The first acquisition module is used to acquire multiple first time-domain waveforms corresponding to different depth points of the target well; The second acquisition module is used to acquire multiple first frequency domain waveforms corresponding to the multiple first time domain waveforms respectively; The third acquisition module is used to acquire reference frequency domain waveforms corresponding to the plurality of first frequency domain waveforms respectively; The first determining module is used to determine the abnormal first frequency domain waveform among the plurality of first frequency domain waveforms based on the plurality of first frequency domain waveforms and the corresponding reference frequency domain waveforms respectively; The abnormal first frequency domain waveform is converted into an abnormal first time domain waveform using inverse Fourier transform; The clearing module is used to clear the abnormal first time-domain waveform from the plurality of first time-domain waveforms to obtain a plurality of second time-domain waveforms; The second determining module is used to determine the target time domain waveform of the target well based on the plurality of second time domain waveforms.

8. The apparatus according to claim 7, characterized in that, The third acquisition module includes: A partitioning unit is used to divide the plurality of first frequency domain waveforms into a plurality of frequency domain waveform groups based on the order of the depth points corresponding to the plurality of first frequency domain waveforms; The first determining unit is used to determine the frequency domain waveform groups corresponding to the plurality of first frequency domain waveforms respectively; The second determining unit is used to determine the target depth point located at the middle position among the depth points included in the frequency domain waveform group corresponding to the plurality of first frequency domain waveforms; The third determining unit is used to determine a reference frequency domain waveform corresponding to the plurality of first frequency domain waveforms based on the first frequency domain waveform corresponding to the target depth point.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a stored program, wherein, when the program is executed, it controls the device on which the computer-readable storage medium is located to perform the data processing method according to any one of claims 1 to 6.

10. A computer device, characterized in that, include: Memory and processor The memory stores computer programs; The processor is configured to execute a computer program stored in the memory, wherein when the computer program is executed, the processor performs the data processing method according to any one of claims 1 to 6.

Images