Sound wave far detection imaging method, device, equipment, medium and program product
By pre-processing, filtering and imaging the logging data, more accurate virtual images of geological bodies are generated, which solves the problem of inaccurate images in the prior art and achieves better geological analysis.
Patent Information
- Application Number
- CN202510122761.2
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-01-26
- Publication Date
- 2025-04-11
AI Technical Summary
The virtual images of geological bodies displayed by existing reflective wave measurement instruments in the prior art are not accurate enough, and it is difficult to effectively understand the geological conditions.
By obtaining the original logging data of the target geological body, data preprocessing and data restoration processing are performed, filtering is performed, reflected wave signals are extracted, offset imaging and image denoising are performed, and virtual images of the target geological body are generated.
Improve the accuracy of virtual images of geological bodies and help better understand geological conditions.
Smart Images
Figure CN119805580A_ABST
Abstract
Description
Technical Field
[0001] The present disclosure relates to the field of well logging technology, and in particular to an acoustic wave remote detection imaging method, device, equipment, medium and program product. Background Art
[0002] Well logging is a method used in the field of geology and geophysics to study the underground rock structure and fluid state. It involves using specific testing instruments to conduct downhole tests in oil wells (such as oil wells, water injection wells, and observation wells) to obtain underground information.
[0003] In the prior art, logging imaging is to quickly detect the geological body to be measured by using the existing reflection wave measuring instrument to directly obtain the image of the geological body.
[0004] However, the virtual image of the geological body displayed by the existing reflection wave measuring instrument in the prior art is not accurate enough, which is not conducive to a better understanding of the geological conditions. Summary of the invention
[0005] In order to solve the above technical problems, the present disclosure provides an acoustic wave long-range detection imaging method, device, equipment, medium and program product.
[0006] A first aspect of an embodiment of the present disclosure provides an acoustic wave remote detection imaging method, comprising:
[0007] Obtaining original logging data corresponding to the target geological body;
[0008] Performing target processing on the original logging data to obtain logging waveform data, the target processing includes data preprocessing and data restoration processing;
[0009] Performing filtering processing on the logging waveform data to obtain target logging waveform data;
[0010] Extract the reflected wave signal corresponding to the target logging waveform data, and perform migration imaging processing and image noise reduction processing on the reflected wave signal to obtain the target reflected wave signal;
[0011] A virtual image corresponding to the target geological body is obtained based on the target reflection wave signal, and the virtual image is displayed.
[0012] A second aspect of the embodiments of the present disclosure provides an acoustic wave remote detection imaging device, comprising:
[0013] A well logging data acquisition module is used to acquire the original well logging data corresponding to the target geological body;
[0014] The first processing module is used to perform target processing on the original logging data to obtain logging waveform data, and the target processing includes data preprocessing and data restoration processing;
[0015] A filtering processing module is used to filter the logging waveform data to obtain target logging waveform data;
[0016] The second processing module is used to extract the reflected wave signal corresponding to the target logging waveform data, and perform offset imaging processing and image noise reduction processing on the reflected wave signal to obtain the target reflected wave signal;
[0017] The imaging processing module is used to obtain a virtual image corresponding to the target geological body based on the target reflection wave signal and display the virtual image.
[0018] A third aspect of the embodiments of the present disclosure provides an electronic device, including:
[0019] processor;
[0020] A memory for storing executable instructions;
[0021] The processor is used to read executable instructions from the memory and execute the executable instructions to implement the acoustic wave long-range detection imaging method provided in the first aspect above.
[0022] A fourth aspect of an embodiment of the present disclosure provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, the processor implements the acoustic wave long-range detection imaging method provided by the first aspect above.
[0023] A fifth aspect of an embodiment of the present disclosure provides a computer program product, which includes a computer program or instructions, and when the computer program or instructions are executed by a processor, the method for long-range acoustic wave detection imaging as described in the first aspect above is implemented.
[0024] Compared with the prior art, the technical solution provided by the embodiments of the present disclosure has the following advantages:
[0025] The acoustic wave long-range detection imaging method, device, equipment, medium and program product provided by the embodiments of the present disclosure can obtain the original logging data corresponding to the target geological body. After obtaining the original logging data, the original logging data is subjected to data preprocessing and data restoration processing to obtain logging waveform data, and then the logging waveform data is filtered to obtain target logging waveform data, and the corresponding reflection wave signal is extracted from the target logging waveform data, and the reflection wave signal is subjected to offset imaging processing and image noise reduction processing to obtain the target reflection wave signal, and a virtual image corresponding to the target geological body is obtained based on the target reflection wave signal, and the virtual image is displayed. Therefore, by obtaining the original logging data, a series of processing can be performed on the original logging data to obtain the target reflection wave signal, and the virtual image corresponding to the target geological body can be obtained according to the target reflection wave signal, thereby improving the accuracy of the obtained virtual image corresponding to the target geological body, which is conducive to a better understanding of the geological conditions. BRIEF DESCRIPTION OF THE DRAWINGS
[0026] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and, together with the description, serve to explain the principles of the present disclosure.
[0027] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.
[0028] Figure 1 is a flow chart of an acoustic wave remote detection imaging method provided by an embodiment of the present disclosure;
[0029] Figure 2 is a schematic diagram of an application scenario provided by an embodiment of the present disclosure;
[0030] Figure 3 is a flow chart of another acoustic wave remote detection imaging method provided by an embodiment of the present disclosure;
[0031] Figure 4 It is a structural schematic diagram of an acoustic wave remote detection imaging device provided by an embodiment of the present disclosure;
[0032] Figure 5 It is a structural schematic diagram of an electronic device provided by an embodiment of the present disclosure. DETAILED DESCRIPTION
[0033] In order to more clearly understand the above-mentioned objectives, features and advantages of the present disclosure, the scheme of the present disclosure will be further described below. It should be noted that the embodiments of the present disclosure and the features in the embodiments can be combined with each other without conflict.
[0034] In the following description, many specific details are set forth to facilitate a full understanding of the present disclosure, but the present disclosure may also be implemented in other ways different from those described herein; it is obvious that the embodiments in the specification are only part of the embodiments of the present disclosure, rather than all of the embodiments.
[0035] It should be understood that the various steps described in the method embodiments of the present disclosure may be performed in different orders and / or in parallel. In addition, the method embodiments may include additional steps and / or omit the steps shown. The scope of the present disclosure is not limited in this respect.
[0036] It should be noted that, in this article, relational terms such as "first" and "second" are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.
[0037] It should be noted that the modifications of "one" and "plurality" mentioned in the present disclosure are illustrative rather than restrictive, and those skilled in the art should understand that unless otherwise clearly indicated in the context, it should be understood as "one or more".
[0038] Generally speaking, well logging is a method used in the fields of geology and geophysics to study underground rock structure and fluid state. It involves the use of specific testing instruments to conduct downhole testing in oil wells (such as oil wells, water injection wells, and observation wells, etc.) to obtain underground information. Among them, acoustic logging is an important means of well logging. When sound waves propagate in different media, the acoustic characteristics such as changes in speed, amplitude, and frequency are also different. Acoustic logging is a well logging method that uses these acoustic properties of rocks to study the geological profile of drilling and judge the quality of cementing. In the prior art, logging imaging is to quickly detect the geological body to be measured through existing reflection wave measuring instruments to directly obtain the image of the geological body.
[0039] However, the virtual image of the geological body displayed by the existing reflection wave measuring instrument in the prior art is not accurate enough, which is not conducive to a better understanding of the geological situation. To address this problem, the embodiment of the present disclosure provides an acoustic wave remote detection imaging method, which is introduced below in conjunction with a specific embodiment.
[0040] Figure 1 This is a flowchart of an acoustic wave long-range detection imaging method provided by an embodiment of the present disclosure. The method can be executed by an acoustic wave long-range detection imaging device. The acoustic wave long-range detection imaging device can be implemented in software and / or hardware. The acoustic wave long-range detection imaging device can be configured in an electronic device, such as a server or a terminal, wherein the terminal specifically includes a mobile phone, a computer or a tablet computer, etc. In addition, the method can be applied to Figure 2 The application scenario shown includes a well logging device 10 and an electronic device 20. It can be understood that the acoustic wave remote detection imaging method provided in the embodiment of the present disclosure can also be applied in other scenarios.
[0041] like Figure 2 As shown, network communication can be performed between the logging device 10 and the electronic device 20 .
[0042] The logging equipment 10 includes a logging instrument, a logging cable, a sensor and other devices.
[0043] The electronic device 20 may be a terminal or a server, for example, an independent computer or a cluster composed of multiple computers.
[0044] The logging device 10 is used to collect original logging data corresponding to the geological body, and transmit the collected original logging data to the electronic device 20 through a network communication method such as a wireless network.
[0045] The electronic device 20 is used to perform a series of operations such as data preprocessing, data restoration processing, filtering processing, signal extraction processing, etc. on the original logging data after acquiring the original logging data collected by the logging equipment 10, so as to obtain a reflection wave signal, and then perform offset imaging processing and image noise reduction processing on the reflection wave signal to obtain a processed target reflection wave signal, and then generate a virtual image corresponding to the geological body according to the processed target reflection wave signal, and display the virtual image to facilitate users to view and analyze the virtual image.
[0046] Combine the following Figure 2 The application scenario shown is Figure 1 The acoustic wave remote detection imaging method shown is introduced, for example, Figure 2 The electronic device 20 in the embodiment can perform the method. Figure 1 As shown, the acoustic wave remote detection imaging method provided in this embodiment includes the following steps.
[0047] S110, obtaining original logging data corresponding to the target geological body.
[0048] In the disclosed embodiment, a geological body is a spatial region in the earth's crust composed of one or more rocks, minerals, soil, water and other substances, and having clear boundaries and certain address characteristics.
[0049] The target geological body can be understood as the geological body that needs geological analysis and exploration.
[0050] Raw logging data can be understood as the initial data set collected by logging equipment.
[0051] In some embodiments of the present disclosure, the electronic device may communicate with the logging device, and receive the original logging data corresponding to the target geological body collected by the logging device in real time or at a fixed time, thereby acquiring the original logging data.
[0052] In other embodiments of the present disclosure, the electronic device can receive the acoustic wave long-range detection imaging instruction, parse the acoustic wave long-range detection imaging instruction, obtain the parsing result, and directly obtain the original logging data corresponding to the target geological body when the parsing result includes the original logging data.
[0053] In some other embodiments of the present disclosure, the electronic device can receive the acoustic wave long-range detection imaging instruction, parse the acoustic wave long-range detection imaging instruction, and obtain the parsing result. When the parsing result includes identification information corresponding to the target geological body, the original logging data corresponding to the target geological body can be obtained from a preset database based on the identification information corresponding to the target geological body.
[0054] S120, target processing is performed on the original logging data to obtain logging waveform data, where the target processing includes data preprocessing and data restoration processing.
[0055] In the embodiments of the present disclosure, data preprocessing may include one or more processes of data cleaning, data integration, data transformation, data reduction, etc.
[0056] The data restoration process can be understood as restoring the original logging data in combination with the gain curve and the delay curve to obtain the original real waveform data.
[0057] Among them, the gain curve is a curve that randomly amplifies the received acoustic reflection signal during acoustic logging, so that it can more clearly reflect the waveform characteristics and identify the reflected wave. Specifically, the gain curve is restored to truly restore the original waveform form. According to the exponential attenuation characteristics of the amplitude expansion along the spherical surface when the acoustic wave propagates in a uniform non-perfectly elastic medium, the wavefront amplitude compensation coefficient is established to unify the acoustic wave amplitude to the proper state.
[0058] The delay curve refers to the curve in which the phase delay of the signal in the frequency response changes with the frequency. Specifically, the delay curve is used to restore the acoustic wave signals of different channel sets with a common center point received during acoustic logging. Since the paths of the reflected wave signals under the combination of each sound source and receiver are different, the reflected waves are corrected to the same channel through dynamic correction.
[0059] Specifically, after acquiring the original logging data, the electronic device performs data preprocessing on the original logging data, obtains the gain curve and delay curve corresponding to the original logging data, and performs data restoration processing on the preprocessed original logging data in combination with the gain curve and the delay curve to obtain logging waveform data.
[0060] In some examples, after acquiring the original well logging data, the electronic device performs data preprocessing on the original well logging data, performs Radon transformation on the well logging data, converts the acoustic wave data in the time-space domain of the original well logging data into the slope-intercept domain, makes various waveforms converge into separated points, and separates the wave field in the slope-intercept domain. After the wave field is separated, it is then inversely transformed and re-transformed into the time-depth domain.
[0061] S130, filtering the well logging waveform data to obtain target well logging waveform data.
[0062] In the embodiments of the present disclosure, the filtering processing method may include a fast Fourier transform method, a filter processing method or other filtering methods, which are not limited here.
[0063] Specifically, after obtaining the logging waveform data, the electronic device performs filtering processing on the logging waveform data based on a preset filtering processing method to obtain target logging waveform data.
[0064] S140, extracting the reflected wave signal corresponding to the target logging waveform data, and performing migration imaging processing and image noise reduction processing on the reflected wave signal to obtain the target reflected wave signal.
[0065] In the embodiment of the present disclosure, the reflected wave signal is a signal generated when the sound wave is reflected and refracted at the interface of media with different densities.
[0066] The electronic device can extract the reflected wave signal by a preset reflected wave signal extraction method, wherein the preset reflected wave signal extraction method may include a median filtering method, a FK filtering method, a τ-p transformation, and a wave field separation method.
[0067] Specifically, the electronic device can extract the reflected wave through the value filtering method, the FK filtering method, and the τ-p transformation. The extracted reflected wave includes the uplink reflected wave and the downlink reflected wave. The two are separated through the wave field separation method, and then the reflected waves at the same time are superimposed. Due to the same phase, the reflected wave increases exponentially, suppresses the interference noise, improves the signal-to-noise ratio, and facilitates the subsequent migration imaging processing.
[0068] In the embodiment of the present disclosure, the migration imaging process includes pre-stack migration process, post-stack migration process and near-horizontal migration process. In the migration imaging process, the focus is on the radiation area of the logging tool, and the imaging is scanned point by point along the preset trajectory in the logging.
[0069] In the embodiment of the present disclosure, the image noise reduction processing may specifically include eliminating digital noise, suppressing residual noise of direct waves, and highlighting effective reflectors according to a preset image noise reduction processing method.
[0070] The preset image noise reduction processing method may include a method of removing straight lines and retaining oblique lines, an fk domain filtering method, and other image noise reduction processing methods.
[0071] A direct wave is a wave that propagates directly from the source or transmitter to the observation point or receiving point in a uniform formation; a reflector is an object that reflects sound waves.
[0072] Specifically, after extracting the reflected wave signal corresponding to the target logging waveform data by a preset reflected wave signal extraction method, the electronic device performs offset processing on the reflected wave signal, and performs image noise reduction processing based on a preset image noise reduction processing method to obtain the target reflected wave signal.
[0073] In some embodiments of the present disclosure, the electronic device may also perform inclination correction on the propagation path of the reflected wave signal based on a preset correction method, so as to select a suitable offset method according to the different inclination angles of the reflection interface, thereby improving data processing efficiency.
[0074] S150 . Acquire a virtual image corresponding to the target geological body based on the target reflection wave signal, and display the virtual image.
[0075] Specifically, after obtaining the target reflected wave signal, the electronic device draws a virtual image of the target geological body based on the target reflected wave signal through a preset drawing tool, thereby obtaining a virtual image corresponding to the target geological body, and displays the virtual image.
[0076] The preset drawing tool may be any tool that can draw a geological body image according to the reflection wave signal, and will not be described in detail here.
[0077] In the disclosed embodiment, the original logging data corresponding to the target geological body can be obtained. After the original logging data is obtained, the original logging data is subjected to data preprocessing and data restoration processing to obtain logging waveform data, and then the logging waveform data is subjected to filtering processing to obtain target logging waveform data, and the corresponding reflection wave signal is extracted from the target logging waveform data, and the reflection wave signal is subjected to offset imaging processing and image noise reduction processing to obtain the target reflection wave signal, and a virtual image corresponding to the target geological body is obtained based on the target reflection wave signal, and the virtual image is displayed. Thus, by obtaining the original logging data, a series of processing can be performed on the original logging data to obtain the target reflection wave signal, and the virtual image corresponding to the target geological body can be obtained according to the target reflection wave signal, thereby improving the accuracy of the obtained virtual image corresponding to the target geological body, which is conducive to a better understanding of the geological conditions.
[0078] On the basis of the above-mentioned embodiments of the present disclosure, during the offset imaging process, the focus is on the radiation area of the logging instrument, and the imaging is scanned point by point along the preset trajectory in the logging, so as to realize all-round continuous scanning of the radiation area of the logging instrument beside the wellbore; by controlling the scanning speed, the data acquisition density is increased, and the imaging effect is enhanced.
[0079] In the embodiment of the present disclosure, the electronic device can filter the logging waveform data by a preset filtering method, wherein the preset filtering method may include a fast Fourier transform method, a filter processing method, and the like.
[0080] In some embodiments of the present disclosure, filtering the logging waveform data to obtain target logging waveform data may specifically include: filtering the logging waveform data based on a fast Fourier transform method to obtain target logging waveform data.
[0081] Furthermore, filtering is performed on the logging waveform data based on the fast Fourier transform method to obtain target logging waveform data, which may specifically include: performing discrete Fourier transform on the logging waveform data to obtain frequency domain data corresponding to the logging waveform data; filtering the frequency domain data to obtain filtered target frequency domain data; performing inverse discrete Fourier transform on the target frequency domain data to obtain time domain data corresponding to the logging waveform data, and determining the time domain data as the target logging waveform data.
[0082] In the embodiment of the present disclosure, the discrete Fourier transform is in discrete form in both the time domain and the frequency domain, and transforms the sampling of the time domain signal into sampling in the discrete time Fourier transform frequency domain.
[0083] Inverse discrete Fourier transform is a digital signal processing method used to convert frequency domain data into time domain data.
[0084] The frequency domain data can be understood as the measurement data of the system input and output variables recorded or stored in the frequency domain.
[0085] In the disclosed embodiment, the frequency domain data is logging waveform data in the frequency domain.
[0086] In the embodiment of the present disclosure, filtering the frequency domain data may be performed by setting the frequency corresponding to the noise or interference in the frequency domain data to 0.
[0087] Specifically, after acquiring the logging waveform data, the electronic device can transform the logging waveform data from the time domain to the frequency domain based on the discrete Fourier transform, obtain the frequency domain data corresponding to the logging waveform data, and determine the noise or interference data in the frequency domain data, set the frequency corresponding to the noise or interference data to 0, filter the frequency domain data to obtain filtered target frequency domain data, perform an inverse discrete Fourier transform on the target frequency domain data, convert the target frequency domain data into time domain data, and then obtain the time domain data corresponding to the logging waveform data, and determine the time domain data as the target logging waveform data.
[0088] In some examples, after obtaining the filtered target frequency domain data, the truncation boundary of the signal can be smoothed by adjusting the window function; by adjusting the signal frequency or sampling rate, the acquisition length can accommodate an integer number of cycles to greatly reduce the frequency leakage effect caused by filtering.
[0089] In the disclosed embodiment, a discrete Fourier transform is performed on the logging waveform data to obtain frequency domain data corresponding to the logging waveform data, and the frequency domain data is filtered; a discrete Fourier inverse transform is performed on the filtered target frequency domain data to obtain time domain data corresponding to the logging waveform data; the time domain data is determined as the target logging waveform data, so that the zero-frequency offset of the logging waveform data can be eliminated, and at the same time, the interference signals at the low-frequency and high-frequency ends of the logging waveform data can be eliminated, so that the virtual image of the displayed geological body is more accurate, which is conducive to a better understanding of the geological conditions.
[0090] In other embodiments of the present disclosure, filtering is performed on the logging waveform data to obtain target logging waveform data, which may specifically include: filtering is performed on the logging waveform data based on a filter processing method to obtain target logging waveform data.
[0091] Further, filtering is performed on the logging waveform data based on the filter processing method to obtain target logging waveform data, which may specifically include: determining the current time point and the current filter order corresponding to the logging waveform data; performing calculations based on the current time point and the current filter order to obtain first logging waveform signal data input to the filter; obtaining the filter coefficient corresponding to the logging waveform signal value in the first logging waveform signal data, and calculating the first product of the filter coefficient and the logging waveform signal value; obtaining the target logging waveform signal values and the target filter coefficients corresponding to the logging waveform data at multiple preset time points other than the current time point, and respectively calculating the second product of each target logging waveform signal value and the corresponding target filter coefficient; accumulating the first product and the second product to obtain the second logging waveform signal data output by the filter, and determining the second logging waveform signal data output by the filter as the target logging waveform data.
[0092] In the embodiment of the present disclosure, the current time point may be understood as the time point corresponding to the acquisition of the logging waveform data.
[0093] The filter coefficients may be coefficients corresponding to a filter that is preset and stored.
[0094] The current time point and the multiple preset time points can be understood as all the time points corresponding to the preset acquisition of the logging waveform signal data. All the time points can be any number of 10, 100 or 1000 time points, or other number of time points. The order k of the filter corresponding to the multiple logging waveform signal values at all time points should start from 0.
[0095] Based on the current time point and the current filter order, the calculation formula for obtaining the logging waveform signal value corresponding to the first logging waveform signal data input to the filter is as follows:
[0096] f=x(nk)
[0097] Where f is the logging waveform signal value of the input filter; n is the current time point; k is the current filter order; x(nk) is the logging waveform signal value at time point nk.
[0098] The calculation formula for calculating the first product of the filter coefficient and the logging waveform signal value is as follows:
[0099] F=h k f=h k x(nk)
[0100] Where F is the product of the logging waveform signal value and the filter coefficient; h k is the filter coefficient; x(nk) is the logging waveform signal value of the input filter.
[0101] It should be noted that the calculation formula for the second product is similar to the calculation formula for the first product, and will not be described in detail here.
[0102] In the embodiment of the present disclosure, the calculation formula for accumulating the first product and the second product is as follows:
[0103]
[0104] After substituting the calculation formula F of the product of the logging waveform signal value and the filter coefficient into the above formula, multiple products are accumulated to obtain the calculation formula of the logging waveform signal data output by the filter:
[0105]
[0106] Where y(n) is the logging waveform signal value output by the filter; N is the order of the preset filter; k is the order of the current filter; hk is the filter coefficient; x(nk) is the logging waveform signal value input to the filter; n is the current time point.
[0107] In the disclosed embodiment, the logging waveform signal data of the input filter can be calculated according to the current time point and the current filter order corresponding to the logging waveform data; the filter coefficient corresponding to the logging waveform signal value is obtained, and the product of the logging waveform signal value and the filter coefficient is calculated; the multiple calculated products are accumulated to obtain the logging waveform signal data output by the filter; the output logging waveform signal data is determined as the processed logging waveform data, which can eliminate the zero-frequency offset of the logging waveform data and eliminate the interference signals at the low-frequency and high-frequency ends of the logging waveform data, so that the virtual image of the displayed geological body is more accurate, which is conducive to a better understanding of the geological conditions.
[0108] In the disclosed embodiment, after filtering the logging waveform data to obtain the target logging waveform data, the acoustic wave long-range detection imaging method may further include: calculating the correlation coefficient of the target logging waveform data to obtain a correlation coefficient matrix between slowness and time; determining the P-wave time difference, S-wave time difference and / or Stoneley wave time difference corresponding to the target logging waveform data based on the correlation coefficient matrix; determining the time difference curve corresponding to the target logging waveform data based on the P-wave time difference, S-wave time difference and / or Stoneley wave time difference; calculating the error value of the time difference curve, and generating an error curve based on the error value.
[0109] In the disclosed embodiment, the correlation coefficient can be understood as a statistic used to measure the strength and direction of the linear relationship between the two variables of slowness and time, and can be used to evaluate the quality of well logging data.
[0110] The correlation coefficient of the target logging waveform data is calculated, and the calculation formula of the correlation coefficient matrix between slowness and time is obtained as follows:
[0111]
[0112] Where ρ is the correlation coefficient between slowness and time; τ is the time when the first wave arrives in the logging waveform; r m [T] is the sound wave signal at time T; Tw is the time window length; M is the preset number of channels; m is the current related channel number; t is the position of the first channel; Δz is the channel spacing; s is the slowness.
[0113] Among them, T = t + s (m-1) Δz + τ.
[0114] The calculation formula for slowness is:
[0115]
[0116] Where s is slowness and v is waveform speed.
[0117] In the embodiment of the present disclosure, the slowness and time correlation method opens a time window in a group of full wave trains, moves the time window with a certain slowness (time difference) to find the coherent energy spectrum of the group velocity of waveforms such as longitudinal waves, transverse waves and / or Stoneley waves, and determines the time difference of each wave group by calculating the correlation coefficient.
[0118] The coherent energy spectrum represents the distribution of waveform signal energy at each frequency. By integrating the energy spectrum at the frequency, the corresponding waveform signal energy can be obtained.
[0119] Specifically, the electronic device substitutes different slownesses into the above formula to calculate the corresponding correlation coefficients; when the waveform signal in the time window has the maximum correlation coefficient, the value corresponding to the slowness corresponding to the maximum correlation coefficient is the time difference of the waveform signal.
[0120] In the disclosed embodiment, there are 7 combinations of longitudinal waves, transverse waves and / or Stoneley waves, which may specifically include: longitudinal waves; transverse waves; Stoneley waves; longitudinal waves and transverse waves; longitudinal waves and Stoneley waves; transverse waves and Stoneley waves; longitudinal waves, transverse waves and Stoneley waves. The above specific combinations need to be selected according to specific imaging requirements.
[0121] Furthermore, after determining the P-wave time difference, S-wave time difference and / or Stoneley wave time difference corresponding to the target logging waveform data, the electronic device plots the P-wave time difference, S-wave time difference and / or Stoneley wave time difference corresponding to the target logging waveform data into a unified acoustic wave time difference curve table to obtain a time difference curve, and calculates the error value of the time difference curve according to a preset prediction method, and generates an error curve according to the error value, wherein the preset prediction method may be a linear prediction method or other prediction method capable of calculating the error of the time difference curve.
[0122] The linear prediction method is a method for predicting future or unknown data based on existing data samples.
[0123] For the time difference curve, the basic model of the linear prediction method is used to preset subsequent data points based on the existing partial curve data, and the difference between the predicted value and the actual value is found and determined as the error value.
[0124] In the embodiment of the present disclosure, after generating the error curve based on the error value, the acoustic wave long-range detection imaging method may further include: evaluating the quality reliability of the target logging waveform data based on the error curve to obtain an evaluation result.
[0125] Furthermore, extracting the reflected wave signal corresponding to the target logging waveform data may specifically include: when the evaluation result shows that the quality of the target logging waveform data is reliable, extracting the reflected wave signal corresponding to the target logging waveform data.
[0126] In the disclosed embodiment, the reliability of the time difference curve is evaluated by the error curve, and subsequent operations are performed after the time difference curve is determined to be reliable, thereby further improving the accuracy of the obtained virtual image corresponding to the target geological body.
[0127] In the embodiment of the present disclosure, before performing offset imaging processing and image noise reduction processing on the reflected wave signal to obtain the target reflected wave signal, the acoustic wave long-range detection imaging method may also include: performing preset processing on the reflected wave signal based on the least squares method to obtain a first reflected wave signal; performing direct wave filtering on the first reflected wave signal based on an adaptive filtering algorithm to obtain a filtered second reflected wave signal; and performing amplitude compensation operation on the second reflected wave signal based on an inverse attenuation filtering method to obtain a third reflected wave signal.
[0128] In the disclosed embodiment, the least square method is used to provide waveform data fitting results and provide waveform data characteristics and rules.
[0129] The reflected wave signal is sorted by reducing the waveform oscillation period and accumulating the reflected wave energy according to the least square method. Specifically, the reflected wave signal is regarded as a function of time, such as s(t) represents the change of the reflected wave signal over time, and a suitable basis function is selected to fit the reflected wave signal, such as a polynomial function (where a k is the polynomial coefficient, m is the order of the polynomial) According to the least squares method, a set of coefficients a can be obtained k Make By solving this least squares problem, we can get the fitted function p(t). The fitted function p(t) is smoother than the original reflected wave signal s(t). In polynomial fitting, a lower-order polynomial (such as second-order or third-order) tends to reduce the high-frequency components in the signal, thereby reducing the oscillation period of the waveform.
[0130] The function p(t) obtained by the least squares fitting method can resample or reconstruct the signal so that the reflected wave energy can be concentrated to a certain extent. For example, during the fitting process, you can choose to emphasize the main peak part of the signal. By adjusting the coefficients of the fitting function, the fitted signal is closer to the original signal in the main peak area of the reflected wave, and smoothing is performed in other areas (such as the oscillation part). In this way, when recalculating the energy, the reflected wave energy is accumulated to a certain extent because the main peak of the signal is better retained and emphasized, and the energy dispersion of the oscillation part is improved.
[0131] Furthermore, the least square method is used to optimize the signal superposition. Assuming that there are multiple reflected wave signal segments, the energy of these signal segments may be dispersed due to noise and other reasons. By fitting these signal segments into a unified function form through the least square method and then superimposing them, the reflected wave energy can be more concentrated. For example, the reflected wave signals in different time windows are fitted with the least square method to obtain their respective fitting functions, and then these fitting functions are superimposed according to certain rules, so that the reflected wave energy is enhanced during the superposition process, while reducing the energy dispersion caused by the oscillation difference between different signal segments.
[0132] Adaptive filtering algorithms can be used for noise reduction, echo cancellation, and reflection enhancement.
[0133] Specifically, the electronic device can reduce the waveform oscillation period and accumulate the reflected wave energy of the reflected wave signal based on the least squares method to obtain a first reflected wave signal. After obtaining the first reflected wave signal, the electronic device can perform direct wave filtering on the first reflected wave signal based on an adaptive filtering algorithm to obtain a second reflected wave signal. The second reflected wave signal is amplitude compensated based on the inverse attenuation filtering method to obtain a third reflected wave signal.
[0134] Further, performing offset imaging processing and image noise reduction processing on the reflected wave signal to obtain the target reflected wave signal may specifically include: performing offset imaging processing and image noise reduction processing on the third reflected wave signal to obtain the target reflected wave signal.
[0135] In the disclosed embodiment, the reflected wave signal can be preset processed based on the least squares method to obtain a first reflected wave signal, the first reflected wave signal can be directly filtered based on an adaptive filtering algorithm to obtain a filtered second reflected wave signal, and then the second reflected wave signal can be amplitude compensated based on an inverse attenuation filtering method to obtain a third reflected wave signal, and the third reflected wave signal can be subjected to offset imaging processing and image noise reduction processing to obtain a target reflected wave signal, thereby improving the precision and accuracy of the obtained target reflected wave signal, and further improving the precision and accuracy of the obtained virtual image corresponding to the target geological body.
[0136] Figure 3 is a flow chart of another acoustic wave remote detection imaging method provided by an embodiment of the present disclosure, such as Figure 3 As shown, the acoustic wave remote detection imaging method may specifically include the following steps:
[0137] S310, obtaining original logging data corresponding to the target geological body.
[0138] S320, target processing is performed on the original logging data to obtain logging waveform data, where the target processing includes data preprocessing and data restoration processing.
[0139] S330, filtering the well logging waveform data to obtain target well logging waveform data.
[0140] S340, calculate the correlation coefficient of the target logging waveform data to obtain the correlation coefficient matrix between slowness and time; determine the P-wave time difference, S-wave time difference and / or Stoneley wave time difference corresponding to the target logging waveform data based on the correlation coefficient matrix; determine the time difference curve corresponding to the target logging waveform data based on the P-wave time difference, S-wave time difference and / or Stoneley wave time difference; calculate the error value of the time difference curve, and generate an error curve based on the error value.
[0141] S350, evaluating the quality reliability of the target logging waveform data based on the error curve to obtain an evaluation result.
[0142] S360: When the evaluation result shows that the quality of the target logging waveform data is reliable, extract the reflected wave signal corresponding to the target logging waveform data.
[0143] S370, perform preset processing on the reflected wave signal based on the least squares method to obtain a first reflected wave signal; perform direct wave filtering on the first reflected wave signal based on an adaptive filtering algorithm to obtain a filtered second reflected wave signal; perform amplitude compensation operation on the second reflected wave signal based on an inverse attenuation filtering method to obtain a third reflected wave signal.
[0144] S380: Perform offset imaging processing and image noise reduction processing on the third reflected wave signal to obtain a target reflected wave signal.
[0145] S390, acquiring a virtual image corresponding to the target geological body based on the target reflection wave signal, and displaying the virtual image.
[0146] It should be noted that the specific implementation of steps S310-S390 is similar to the implementation of the relevant steps in the above-mentioned embodiment of the present disclosure, and will not be repeated here.
[0147] In the disclosed embodiment, it is possible to obtain logging waveform data by performing data preprocessing and data restoration processing on the original logging data, filter the logging waveform data to obtain target logging waveform data, determine the time difference curve corresponding to the target logging waveform data, and generate a corresponding error curve based on the time difference curve. The quality reliability of the target logging waveform data is evaluated according to the error curve. When the evaluation result shows that the quality of the target logging waveform data is reliable, the reflected wave signal corresponding to the target logging waveform data is extracted, and a series of processing such as preset processing, direct wave filtering, amplitude compensation operation, etc. is performed on the reflected wave signal to obtain a third reflected wave signal. Then, the third reflected wave signal is subjected to offset imaging processing and image noise reduction processing to obtain a target reflected wave signal. Based on the target reflected wave signal, a virtual image corresponding to the target geological body is obtained, and the virtual image is displayed. Thus, the accuracy of the obtained virtual image corresponding to the target geological body is improved, which is conducive to a better understanding of the geological conditions. At the same time, the imaging effect and the efficiency are improved.
[0148] In the disclosed embodiment, the acoustic wave remote detection imaging method may further include, after acquiring the original logging data corresponding to the target geological body, performing data decoding processing on the original logging data.
[0149] The specific process of data decompilation is: decompilation of data files in specific formats during data processing into general data formats.
[0150] Specifically, after the original logging data corresponding to the target geological body is acquired, the format of the original logging data is compiled into a universal data format.
[0151] The specific data format file is a specific rule describing data stored in a file or record; it can be a text format in character form or a compressed format in binary data form.
[0152] Among them, the common data formats include BIT format, 3317 format, LA716 format and other common data formats.
[0153] In the embodiments of the present disclosure, data decompilation can be performed to facilitate subsequent data processing and drawing.
[0154] In the embodiment of the present disclosure, when processing the logging waveform data, the acoustic wave remote detection imaging method may also include: obtaining conventional logging curves corresponding to conventional logging data matching the logging waveform data, and importing the conventional logging curves into the array data curve group after data processing for subsequent data processing and related interpretation.
[0155] In the disclosed embodiment, the parameter requirements of the logging equipment may specifically be: the processing speed of waveform time difference extraction is not less than 1000 m / min; the processing speed of long-range detection imaging is not less than 500 m / min; and the circumferential resolution of long-range detection imaging is not less than 22.5 pixels.
[0156] In the embodiment of the present disclosure, the operating environment of the electronic device may specifically be: the processing frequency of the processor of the electronic device is not less than 2.5 GHz; the hard disk memory is not less than 8 GB; and the disk space is not less than 20 GB.
[0157] It should be noted that the software provided by the acoustic wave remote detection imaging processing method in the above-mentioned embodiment of the present disclosure has a user-friendly software interface, simple operation and convenient interaction.
[0158] Figure 4 It is a structural schematic diagram of an acoustic wave long-range detection imaging device provided in an embodiment of the present disclosure.
[0159] In the disclosed embodiment, the acoustic wave remote detection imaging device can be arranged in an electronic device, and is understood as a part of the functional modules in the above electronic device. Specifically, the electronic device can be a server or a terminal, wherein the terminal specifically includes a mobile phone, a computer or a tablet computer, etc., which is not limited here.
[0160] like Figure 4 As shown, the acoustic wave remote detection imaging device 400 may include a logging data acquisition module 410 , a first processing module 420 , a filtering processing module 430 , a second processing module 440 and an imaging processing module 450 .
[0161] The logging data acquisition module 410 may be used to acquire original logging data corresponding to the target geological body.
[0162] The first processing module 420 can be used to perform target processing on the original logging data to obtain logging waveform data. The target processing includes data preprocessing and data restoration processing.
[0163] The filtering processing module 430 can be used to perform filtering processing on the logging waveform data to obtain target logging waveform data.
[0164] The second processing module 440 may be used to extract the reflected wave signal corresponding to the target logging waveform data, and perform offset imaging processing and image noise reduction processing on the reflected wave signal to obtain the target reflected wave signal.
[0165] The imaging processing module 450 may be used to acquire a virtual image corresponding to the target geological body based on the target reflection wave signal, and display the virtual image.
[0166] In the disclosed embodiment, the original logging data corresponding to the target geological body can be obtained. After the original logging data is obtained, the original logging data is subjected to data preprocessing and data restoration processing to obtain logging waveform data, and then the logging waveform data is subjected to filtering processing to obtain target logging waveform data, and the corresponding reflection wave signal is extracted from the target logging waveform data, and the reflection wave signal is subjected to offset imaging processing and image noise reduction processing to obtain the target reflection wave signal, and a virtual image corresponding to the target geological body is obtained based on the target reflection wave signal, and the virtual image is displayed. Thus, by obtaining the original logging data, a series of processing can be performed on the original logging data to obtain the target reflection wave signal, and the virtual image corresponding to the target geological body can be obtained according to the target reflection wave signal, thereby improving the accuracy of the obtained virtual image corresponding to the target geological body, which is conducive to a better understanding of the geological conditions.
[0167] In some embodiments of the present disclosure, the filtering processing module 430 may be specifically used to perform filtering processing on the logging waveform data based on the fast Fourier transform method to obtain target logging waveform data.
[0168] The filter processing module 430 can also be specifically used to perform discrete Fourier transform on the logging waveform data to obtain frequency domain data corresponding to the logging waveform data;
[0169] Performing filtering on the frequency domain data to obtain filtered target frequency domain data;
[0170] The target frequency domain data is subjected to an inverse discrete Fourier transform to obtain the time domain data corresponding to the logging waveform data, and the time domain data is determined as the target logging waveform data.
[0171] In some embodiments of the present disclosure, the filter processing module 430 may also be specifically used to perform filter processing on the logging waveform data based on a filter processing method to obtain target logging waveform data.
[0172] The filter processing module 430 can also be specifically used to determine the current time point and the current filter order corresponding to the logging waveform data; perform calculations based on the current time point and the current filter order to obtain the first logging waveform signal data input to the filter;
[0173] Obtaining a filter coefficient corresponding to the well logging waveform signal value in the first well logging waveform signal data, and calculating a first product of the filter coefficient and the well logging waveform signal value;
[0174] Obtain target logging waveform signal values and target filter coefficients corresponding to the logging waveform data at multiple preset time points other than the current time point, and calculate the second product of each target logging waveform signal value and the target filter coefficient corresponding thereto;
[0175] The first product and the second product are accumulated to obtain second logging waveform signal data output by the filter, and the second logging waveform signal data output by the filter is determined as target logging waveform data.
[0176] In some embodiments of the present disclosure, the acoustic wave long-range detection imaging device 400 may further include an error curve generating module.
[0177] The error curve generation module can be used to perform filtering processing on the logging waveform data to obtain the target logging waveform data, and then calculate the correlation coefficient of the target logging waveform data to obtain the correlation coefficient matrix between slowness and time;
[0178] Determine the P-wave time difference, S-wave time difference and / or Stoneley wave time difference corresponding to the target logging waveform data based on the correlation coefficient matrix;
[0179] Determine a time difference curve corresponding to target logging waveform data based on the P-wave time difference, S-wave time difference and / or Stoneley wave time difference;
[0180] An error value of the time difference curve is calculated, and an error curve is generated based on the error value.
[0181] In some embodiments of the present disclosure, the acoustic wave long-range detection imaging device 400 may further include a reliability evaluation module.
[0182] The reliability evaluation module can be used to evaluate the quality reliability of the target logging waveform data based on the error curve after generating the error curve based on the error value to obtain an evaluation result.
[0183] The second processing module 440 may be specifically configured to extract a reflection wave signal corresponding to the target logging waveform data when the evaluation result indicates that the quality of the target logging waveform data is reliable.
[0184] In some embodiments of the present disclosure, the acoustic wave long-range detection imaging device 400 may further include a reflected wave processing module.
[0185] The reflected wave processing module can be used to perform preset processing on the reflected wave signal based on the least square method to obtain a first reflected wave signal before performing offset imaging processing and image noise reduction processing on the reflected wave signal to obtain a target reflected wave signal;
[0186] Performing direct wave filtering on the first reflected wave signal based on an adaptive filtering algorithm to obtain a filtered second reflected wave signal;
[0187] An amplitude compensation operation is performed on the second reflected wave signal based on an inverse attenuation filtering method to obtain a third reflected wave signal.
[0188] The second processing module 440 may be specifically configured to perform offset imaging processing and image noise reduction processing on the third reflected wave signal to obtain a target reflected wave signal.
[0189] It should be noted that Figure 4 The acoustic wave long-range detection imaging device 400 shown can execute each step in the above method embodiment and realize each process and effect in the above method embodiment, which will not be described in detail here.
[0190] Figure 5 It is a structural schematic diagram of an electronic device provided by an embodiment of the present disclosure.
[0191] In the disclosed embodiment, Figure 5 The electronic device shown may be a server or a terminal, wherein the terminal specifically includes a mobile phone, a computer or a tablet computer, etc., which is not limited here.
[0192] like Figure 5 As shown, the electronic device may include a processor 510 and a memory 520 storing computer program instructions.
[0193] Specifically, the processor 510 may include a central processing unit (CPU), or other general-purpose processors, a digital signal processor (DSP) or an application-specific integrated circuit (ASIC), or may be configured to implement one or more integrated circuits of the embodiments of the present disclosure.
[0194] The memory 520 may include a large capacity memory for information or instructions. By way of example and not limitation, the memory 520 may include a hard disk drive (HDD), a floppy disk drive, a flash memory, an optical disk, a magneto-optical disk, a tape, or a universal serial bus (USB) drive, or a combination of two or more of these. Where appropriate, the memory 520 may include a removable or non-removable (or fixed) medium. Where appropriate, the memory 520 may be inside or outside the integrated gateway device. In a particular embodiment, the memory 520 is a non-volatile solid-state memory. In a particular embodiment, the memory 520 includes a read-only memory (ROM). Where appropriate, the ROM may be a mask-programmed ROM, a programmable ROM (PROM), an erasable PROM (EPROM), an electrically erasable PROM (Electrically Erasable Programmable ROM, EEPROM), an electrically rewritable ROM (EAROM), or a flash memory, or a combination of two or more of these.
[0195] The processor 510 reads and executes the computer program instructions stored in the memory 520 to perform the steps of the acoustic wave remote detection imaging method provided in the embodiment of the present disclosure.
[0196] In one example, the electronic device may further include a transceiver 530 and a bus 540. Figure 5 As shown, the processor 510, the memory 520 and the transceiver 530 are connected via a bus 540 and communicate with each other.
[0197] The bus 540 includes hardware, software, or both. For example, but not limitation, the bus may include an Accelerated Graphics Port (AGP) or other graphics bus, an Extended Industry Standard Architecture (EISA) bus, a Front Side Bus (FSB), a Hyper Transport (HT) interconnect, an Industrial Standard Architecture (ISA) bus, an InfiniBand interconnect, a Low Pin Count (LPC) bus, a Memory bus, a MicroChannel Architecture (MCA) bus, a Peripheral Component Interconnect (PCI) bus, a PCI-Express (PCI-X) bus, a Serial Advanced Technology Attachment (SATA) bus, a Video Electronics Standards Association Local Bus (VLB) bus, or other suitable buses or a combination of two or more of these. Where appropriate, the bus 540 may include one or more buses.
[0198] The embodiment of the present disclosure further provides a computer-readable storage medium, which may store a computer program. When the computer program is executed by a processor, the processor implements the acoustic wave long-range detection imaging method provided by the embodiment of the present disclosure.
[0199] The above-mentioned storage medium may, for example, include a memory 520 of computer program instructions, and the above-mentioned instructions may be executed by the processor 510 of the electronic device to complete the acoustic wave remote detection imaging method provided by the embodiment of the present disclosure. Optionally, the storage medium may be a non-temporary computer-readable storage medium, for example, the non-temporary computer-readable storage medium may be a ROM, a random access memory (Random Access Memory, RAM), a compact disc read-only memory (Compact Disc ROM, CD-ROM), a magnetic tape, a floppy disk, and an optical data storage device, etc.
[0200] The embodiments of the present disclosure also provide a computer program product, which includes a computer program or instructions. When the computer program or instructions are executed by a processor, the method for long-range acoustic wave detection imaging provided by the embodiments of the present disclosure is implemented, and the various processes and effects in the above-mentioned embodiments of the present disclosure can be implemented, which will not be elaborated here.
[0201] The above description is only a specific embodiment of the present disclosure, so that those skilled in the art can understand or implement the present disclosure. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present disclosure. Therefore, the present disclosure will not be limited to the embodiments described herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.
Claims
1. A method for long-range acoustic wave detection imaging, characterized in that: include: Obtaining original logging data corresponding to the target geological body; Performing target processing on the original logging data to obtain logging waveform data, wherein the target processing includes data preprocessing and data restoration processing; Performing filtering processing on the logging waveform data to obtain target logging waveform data; Extracting the reflected wave signal corresponding to the target logging waveform data, and performing offset imaging processing and image noise reduction processing on the reflected wave signal to obtain the target reflected wave signal; A virtual image corresponding to the target geological body is acquired based on the target reflected wave signal, and the virtual image is displayed.
2. The method according to claim 1, characterized in that: The filtering process of the well logging waveform data to obtain target well logging waveform data includes: Performing filtering processing on the logging waveform data based on a fast Fourier transform method to obtain target logging waveform data; The filtering process based on the fast Fourier transform method on the logging waveform data to obtain target logging waveform data includes: Performing discrete Fourier transform on the logging waveform data to obtain frequency domain data corresponding to the logging waveform data; Performing filtering on the frequency domain data to obtain filtered target frequency domain data; Performing an inverse discrete Fourier transform on the target frequency domain data to obtain time domain data corresponding to the logging waveform data, and determining the time domain data as the target logging waveform data.
3. The method according to claim 1, characterized in that The filtering process of the well logging waveform data to obtain target well logging waveform data includes: Performing filtering processing on the logging waveform data based on a filter processing method to obtain target logging waveform data; The filtering process based on the filter processing method is performed on the logging waveform data to obtain target logging waveform data, including: Determine the current time point and the current filter order corresponding to the logging waveform data; perform calculation based on the current time point and the current filter order to obtain first logging waveform signal data input to the filter; Obtaining a filter coefficient corresponding to a well logging waveform signal value in the first well logging waveform signal data, and calculating a first product of the filter coefficient and the well logging waveform signal value; Obtaining target logging waveform signal values and target filter coefficients corresponding to the logging waveform data at a plurality of preset time points other than the current time point, and respectively calculating a second product of each target logging waveform signal value and the target filter coefficient corresponding thereto; The first product and the second product are accumulated to obtain second logging waveform signal data output by the filter, and the second logging waveform signal data output by the filter is determined as the target logging waveform data.
4. The method according to claim 1, characterized in that: After filtering the well logging waveform data to obtain target well logging waveform data, the method further includes: Calculating the correlation coefficient of the target logging waveform data to obtain a correlation coefficient matrix between slowness and time; Determine the P-wave time difference, S-wave time difference and / or Stoneley wave time difference corresponding to the target logging waveform data based on the correlation coefficient matrix; Determine a time difference curve corresponding to the target logging waveform data based on the P-wave time difference, S-wave time difference and / or Stoneley wave time difference; An error value of the time difference curve is calculated, and an error curve is generated based on the error value.
5. The method according to claim 4, characterized in that After generating the error curve based on the error value, the method further includes: Evaluate the quality reliability of the target logging waveform data based on the error curve to obtain an evaluation result; The extracting of the reflected wave signal corresponding to the target logging waveform data comprises: When the evaluation result indicates that the quality of the target logging waveform data is reliable, a reflection wave signal corresponding to the target logging waveform data is extracted.
6. The method according to any one of claims 1 to 5, characterized in that: Before performing offset imaging processing and image noise reduction processing on the reflected wave signal to obtain the target reflected wave signal, the method further includes: Performing preset processing on the reflected wave signal based on a least square method to obtain a first reflected wave signal; Performing direct wave filtering on the first reflected wave signal based on an adaptive filtering algorithm to obtain a filtered second reflected wave signal; Performing an amplitude compensation operation on the second reflected wave signal based on an inverse attenuation filtering method to obtain a third reflected wave signal; The performing offset imaging processing and image noise reduction processing on the reflected wave signal to obtain the target reflected wave signal includes: The third reflected wave signal is subjected to offset imaging processing and image noise reduction processing to obtain the target reflected wave signal.
7. An acoustic wave long-range detection imaging device, characterized in that: include: A well logging data acquisition module is used to acquire the original well logging data corresponding to the target geological body; A first processing module, used for performing target processing on the original logging data to obtain logging waveform data, wherein the target processing includes data preprocessing and data restoration processing; A filtering processing module, used for filtering the well logging waveform data to obtain target well logging waveform data; A second processing module is used to extract the reflected wave signal corresponding to the target logging waveform data, and perform offset imaging processing and image noise reduction processing on the reflected wave signal to obtain the target reflected wave signal; The imaging processing module is used to obtain a virtual image corresponding to the target geological body based on the target reflection wave signal, and display the virtual image.
8. An electronic device, characterized in that: include: processor; A memory for storing executable instructions; The processor is used to read the executable instructions from the memory and execute the executable instructions to implement the acoustic wave remote detection imaging method described in any one of claims 1 to 6.
9. A computer-readable storage medium, characterized in that: The storage medium stores a computer program, and when the computer program is executed by the processor, the processor implements the acoustic wave remote detection imaging method according to any one of claims 1 to 6.
10. A computer program product, comprising a computer program or instructions, characterized in that: When the computer program or instruction is executed by a processor, the acoustic wave remote detection imaging method according to any one of claims 1 to 6 is implemented.