Real-time rapid extraction method and device for underground interval transit time

Abstract

The invention relates to the technical field of well logging, in particular to an underground interval transit time real-time rapid extraction method which comprises the following steps: S1, collecting acoustic waveform data at different stratum depths through an underground interval transit time real-time rapid extraction device; s2, carrying out band-pass filtering processing on the sound wave waveform data; s3, waveform discrete binarization processing is carried out on the filtered waveform data; s4, performing cross-correlation calculation on the waveform data subjected to waveform discrete binarization processing based on wave arrival time and time difference windows to obtain two-dimensional correlation coefficients under different wave arrival time and time difference windows; s5, obtaining one-dimensional correlation coefficients corresponding to different time differences according to the two-dimensional correlation coefficients; and S6, searching the maximum value of the one-dimensional correlation coefficient, and obtaining time difference values corresponding to the longitudinal wave, the transverse wave and the stoneley wave. According to the method, the time complexity of calculation is reduced, the data processing speed is increased, and the requirement that the underground instrument uploads the stratum time difference measurement information in real time can be met.

Description

Technical Field

[0001] The invention relates to the technical field of well logging in petroleum exploration and development, and in particular to a method and a device for real-time rapid extraction of downhole acoustic wave time difference. Background Art

[0002] Acoustic time difference is one of the key physical parameters for petroleum logging reservoir evaluation. Acoustic full-wave logging extracts time difference information of downhole reservoirs. Time difference is defined as the inverse of the acoustic wave velocity, which can indirectly reflect the pore characteristics of the reservoir. The smaller the time difference, the faster the acoustic wave propagates in the reservoir and the denser the reservoir. Combined with relevant waveform processing technology, it can measure the velocity of longitudinal waves, transverse waves and Stoneley waves in the formation, and can also identify the properties of porous fluids, estimate formation permeability, evaluate formation anisotropy and identify fractures.

[0003] The measurement principle of the sonic full-wave logging instrument is to adopt a single-transmitter-multiple-receiver instrument structure, transmit sound waves to the formation through the transmitting transducer, and receive the sound wave signal from the formation at given different source distances. In this sonic full-wave logging method based on a monopole sound source, the waveform signals received in sequence are three mode waves: longitudinal wave, shear wave and Stoneley wave.

[0004] At present, the mainstream acoustic full-wave logging instrument adopts a single-transmitter-eight-receiver structure to receive acoustic waveforms from 8 different source distances in the formation, and calculates the formation time difference using the time difference-wave arrival time similarity principle of waveforms with different source distances. However, due to the huge amount of waveform data collected by the downhole instrument, it is impossible to meet the demand for real-time uploading. Therefore, it is necessary to implement time difference extraction based on waveform data in the downhole instrument processing chip, so as to upload the calculated time difference data, which can greatly compress the amount of uploaded data. However, the current conventional similarity algorithm has high time complexity and requires more chip resources, which makes it impossible to meet the demand for real-time calculation and uploading of acoustic time difference data in the well logging operation. Therefore, a more urgent demand is put forward for a real-time and fast extraction method of acoustic time difference. Summary of the invention

[0005] The purpose of the present invention is to propose a method and device for real-time rapid extraction of downhole acoustic wave time difference, which simplifies the design of the FPGA processing chip of the downhole instrument hardware circuit without changing the mechanical structure of the instrument. Based on the extraction method, the design of a 2-bit downhole FPGA adder can be realized, and fewer FPGA processing chip resources can be used to reduce the time complexity of the time difference extraction algorithm, so as to meet the demand of the downhole instrument for real-time uploading of formation time difference measurement information during the logging operation, and provide reliable data for real-time rapid monitoring of downhole formation acoustic wave time difference data for deep oil and gas reservoir evaluation.

[0006] The technical solution adopted by the present invention to solve the technical problem is: to provide a method for real-time rapid extraction of downhole acoustic wave time difference, comprising the following steps: S1, collecting acoustic waveform data at different formation depths through a downhole acoustic wave time difference real-time rapid extraction device; S2, performing bandpass filtering on the acoustic waveform data; S3, performing waveform discrete binarization processing on the filtered waveform data; S4, using cross-correlation calculation based on wave arrival time and time difference window to obtain two-dimensional correlation coefficients under different wave arrival time and time difference windows for the waveform data processed by waveform discrete binarization; S5. According to the two-dimensional correlation coefficient, obtain the one-dimensional correlation coefficient corresponding to different time differences; S6. Search for the maximum value of the one-dimensional correlation coefficient to obtain the time difference values ​​corresponding to the longitudinal wave, transverse wave and Stoneley wave.

[0007] Furthermore, S2 bandpass filtering preprocessing includes: Set the operating frequency range of the transmitting transducer [f1, f2]; Transforming the time domain acoustic wave signal of the receiving transducer into a frequency domain signal; Perform bandpass filtering within the set frequency range [f1, f2] to retain the signals within the frequency range and filter out the interference signals outside the range; Perform an inverse transform on the frequency domain signal after bandpass filtering and convert it back to the time domain signal.

[0008] Furthermore, the S3 waveform is discretely binarized and preprocessed, including: Set the positive threshold PosThrehold and the negative threshold NegThrehold; ; in: Wave represents the waveform after bandpass filtering; SWave represents the waveform after discrete binarization; i represents the serial number of the receiving transducer; j represents the number of sampling points of the waveform; Compare the actual sound wave signal amplitude with the set positive and negative thresholds; When the amplitude of the acoustic wave signal is greater than the positive threshold, the signal amplitude is set to +1; When the amplitude of the sound wave signal is less than the negative threshold, the signal amplitude is set to -1; When the amplitude of the sound wave signal does not meet the above two conditions, the signal amplitude is set to 0.

[0009] Furthermore, the setting of the positive threshold PosThrehold and the negative threshold NegThrehold takes into account the minimum signal amplitude of the background noise, and the steps include: Analyze the amplitude distribution of background noise and determine the minimum signal amplitude of background noise; Based on the minimum signal amplitude of the background noise, the positive threshold PosThrehold and the negative threshold NegThrehold are set.

[0010] Further, the S4 cross-correlation calculation includes the following steps: At different depth points, the time difference range [s1, s2] and arrival time range [t1, t2] are given; The outer loop traverses the time difference variable s, and the inner loop traverses to the time variable t, and a time window is determined under a set of (s, t) loop variables; In each determined time window, a two-dimensional cross-correlation calculation is performed on the received waveform data to obtain a two-dimensional correlation coefficient in the time window; The above process is repeated until all possible combinations of time difference and arrival time variable values ​​are traversed to complete the cross-correlation calculation process.

[0011] Furthermore, the cross-correlation calculation formula is: ; in: R2D represents the two-dimensional correlation coefficient; S[k] is the time difference sequence; ; s1 represents the starting time difference; s2 represents the termination time difference; ; t1 represents the start time of the calculation area; t2 represents the end time of the calculation area; Twin indicates the calculation window length; int represents rounding operation; ts represents the sampling time interval of each waveform.

[0012] Furthermore, the calculation formula of the S5 one-dimensional correlation coefficient R1D is: ; Among them, R1D(S[k]) represents the one-dimensional correlation coefficient corresponding to the time difference value. During the calculation, each S[k] value is fixed, and the maximum value of the corresponding two-dimensional correlation coefficient within the range of m is calculated.

[0013] Further, S6 searches for a maximum value of a one-dimensional correlation coefficient including: Set the time difference search range for longitudinal waves, shear waves and Stoneley waves respectively; The maximum value of the one-dimensional correlation coefficient is searched within the time difference range corresponding to the longitudinal wave, the transverse wave and the Stoneley wave, and the time difference value corresponding to the local maximum value of the corresponding coefficient is selected as the time difference value of the longitudinal wave, the transverse wave and the Stoneley wave.

[0014] Furthermore, the setting of the time difference search range of the longitudinal wave, the shear wave and the Stoneley wave includes: generating the time difference search range of the longitudinal wave, the shear wave and the Stoneley wave based on the lithology parameters of the target formation.

[0015] The present application also provides a downhole acoustic wave time difference real-time rapid extraction device, comprising: A full-wave acoustic logging tool includes a transmitting transducer and a number of receiving transducers; The transmitting transducer and a plurality of receiving transducers are mounted on the metal core rod and arranged coaxially with the metal core rod; A plurality of receiving transducers are located on the same side of the transmitting transducer, wherein the distance between the first receiving transducer and the transmitting transducer is L; The distance between two adjacent receiving transducers is S; The sound insulator is used to isolate the sound wave signal that is directly transmitted along the metal core rod to the receiving transducer. The sound insulator is installed on the metal rod between the first receiving transducer and the transmitting transducer.

[0016] Compared with the prior art, the present invention has the following beneficial effects: (1) The present invention uses bandpass filtering preprocessing and waveform discrete binarization to convert the original high-precision acoustic wave signal into simplified binary waveform data, making the subsequent cross-correlation calculation more efficient. The present invention reduces the time complexity of the calculation, improves the data processing speed, and meets the needs of downhole instruments to upload formation time difference measurement information in real time.

[0017] (2) The present invention effectively removes interference signals through bandpass filtering preprocessing and retains the acoustic wave signals within the effective frequency band related to the formation characteristics. This not only improves the data quality, but also enhances the accuracy and reliability of subsequent analysis results.

[0018] (3) As oil and gas exploration and development gradually move towards complex geological conditions such as deep and ultra-deep layers, the technical solution provided by the present invention can provide timely, fast and accurate formation acoustic time difference data, which helps to more accurately evaluate reservoir characteristics, identify pore fluid properties, estimate formation permeability, evaluate formation anisotropy and identify fractures.

[0019] (4) Since the amount of data transmission is reduced and the processing speed is improved, the present invention enables on-site well logging operations to obtain required data and make decisions in a shorter time, thereby greatly improving work efficiency and response speed. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 A schematic diagram of the real-time rapid extraction steps of downhole acoustic wave time difference provided by an embodiment of the present invention; Figure 2 A schematic diagram of a sound wave emission and reception measurement model provided in an embodiment of the present invention; Figure 3 The full wave train 8-channel original waveform diagram provided by the embodiment of the present invention; Figure 4 The effect diagram of the full wave train data bandpass filtering and waveform discrete binarization processing provided by the embodiment of the present invention; Figure 5 A two-dimensional contour map of correlation coefficients of eight received waveforms provided in an embodiment of the present invention; Figure 6 A one-dimensional graph of correlation coefficients of eight received waveforms provided in an embodiment of the present invention; Figure 7 This is a full wave train acoustic wave time difference curve diagram provided by an embodiment of the present invention.

[0021] Figure 8 A schematic structural diagram of a full-wave acoustic logging device provided by an embodiment of the present invention; DETAILED DESCRIPTION

[0022] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention. Example

[0023] like Figure 1 As shown, a method for real-time rapid extraction of downhole acoustic wave time difference comprises the following steps: S1. Record 8 channels of acoustic waveform data of 8 receiving transducers at different formation depths through a downhole acoustic wave time difference real-time rapid extraction device; S2, performing bandpass filtering on the acoustic waveform data; S3, performing waveform discrete binarization processing on the filtered waveform data to retain the phase information of the waveform data; S4, using cross-correlation calculation based on wave arrival time and time difference window for 8 waveform data processed by waveform discrete binarization to obtain two-dimensional correlation coefficients under different wave arrival time and time difference windows; S5. According to the two-dimensional correlation coefficient, obtain the one-dimensional correlation coefficient corresponding to different time differences; S6. Search for the maximum value of the one-dimensional correlation coefficient to obtain the time difference values ​​corresponding to the longitudinal wave, the transverse wave and the Stoneley wave.

[0024] A single-shot-eight-receiver full-wave acoustic logging instrument is used to collect 8 original acoustic waveform data at different depth measurement points during the underground movement. The sampling time interval of each waveform is ts, and the number of data points collected is Ns. First, given the bandpass frequency range [f1, f2], the 8 collected original waveforms are bandpass filtered to remove the influence of interference signals. On this basis, the positive threshold PosThrehold and negative threshold NegThrehold of the acoustic signal are set, and the waveform amplitude is discretely binarized to retain the phase information of the 8 waveforms. Further, given the wave arrival time window calculation range [t1, t2] and the time difference window calculation range [s1, s2], the 8 discrete binary waveforms are cross-correlated and calculated to obtain the two-dimensional correlation coefficient about the wave arrival time and time difference. The two-dimensional correlation coefficient is projected onto the time difference axis and converted into a one-dimensional correlation coefficient of the time difference. Finally, the maximum value of the one-dimensional correlation coefficient is searched to obtain the time difference values ​​of different longitudinal waves, shear waves, Stoneley waves and other mode waves. Through the above data processing steps, the downhole formation acoustic wave time difference information can be quickly obtained.

[0025] like Figure 2 As shown in the figure, the measurement model of the full-wave acoustic logging device in the well is expressed. The measurement model includes three parts: wellbore, measurement device and formation. The transmitting transducer transmits an acoustic signal in a certain frequency range. The path passed through during the propagation process is the wellbore, the formation and then back to the wellbore. The acoustic signal is received by 8 receiving transducers. According to the difference in propagation speed of different mode waves, the acoustic signals received by the receiving transducers are the formation longitudinal wave Vp, shear wave Vs and Stoneley wave Vst, respectively. As the transmitting-receiving distance increases, the receiving waveform increases in time. R1 receives the acoustic signal earliest, and R8 receives the acoustic signal latest.

[0026] Further, the S2 bandpass filtering process includes the following steps: Determine the operating frequency range [f1, f2] of the transmitting transducer; Performing Fourier transformation on the time domain acoustic wave signal of the receiving transducer to convert it into a frequency domain signal; Perform bandpass filtering within the set frequency range [f1, f2] to retain the signals within the frequency range and filter out the interference signals outside the range; Perform inverse Fourier transform on the frequency domain signal after bandpass filtering and convert it back to time domain signal.

[0027] Further, S3 performs waveform discrete binarization processing on the filtered waveform data, including the following steps: Set the positive threshold PosThrehold and the negative threshold NegThrehold; Compare the actual sound wave signal amplitude with the set positive and negative thresholds; When the amplitude of the acoustic wave signal is greater than the positive threshold, the signal amplitude is set to +1; When the amplitude of the sound wave signal is less than the negative threshold, the signal amplitude is set to -1; When the amplitude of the sound wave signal does not meet the above two conditions, the signal amplitude is set to 0.

[0028] Furthermore, the setting of the positive threshold PosThrehold and the negative threshold NegThrehold takes into account the minimum signal amplitude of the background noise, and the steps include: Analyze the amplitude distribution of background noise and determine the minimum signal amplitude of background noise; Based on the minimum signal amplitude of the background noise, the positive threshold PosThrehold and the negative threshold NegThrehold are set.

[0029] In logging operations, acoustic signals are usually interfered by background noise. In order to ensure the reliability of the signal, the collected acoustic waveform data needs to be analyzed for background noise. The amplitude of the background noise is usually small, so the minimum signal amplitude can be determined by analyzing the amplitude distribution of the background noise. The setting of positive and negative thresholds needs to consider the minimum signal amplitude to ensure that the signal and noise can be effectively distinguished while avoiding missing important signal features. The specific steps include: analyzing the waveform data after bandpass filtering and calculating the amplitude mean and standard deviation of the background noise. The amplitude of the background noise is usually small, so it can be used as a reference. According to the amplitude distribution of the background noise, set the positive and negative thresholds. The positive threshold is set to the background noise mean plus a certain multiple of the standard deviation, and the negative threshold is set to the background noise mean minus a certain multiple of the standard deviation. The formulas are: PosThreshold=μ+nσ and NegThreshold=μ−nσ; n is a multiple, usually 2-5. This ensures that the threshold can effectively filter noise while retaining the key features of the signal.

[0030] Furthermore, the discrete binarization processing formula of the S3 waveform is: ; Formula 1; in: Wave represents the waveform after bandpass filtering; SWave represents the waveform after discrete binarization; i represents the serial number of the receiving transducer (i=1, 2, …, 8); j represents the number of sampling points of the waveform (j=1, 2, …, Ns).

[0031] The waveform data SWave obtained by processing Formula 1 will have a signal amplitude represented by three values: 1, -1 and 0. The signal amplitude can be represented by a 2-bit binary number, while the existing acoustic wave signal amplitude is represented by a 16-bit binary number. Therefore, the 16-bit FPGA adder design can be simplified to a 2-bit FPGA adder design, and real-time calculation can be performed downhole. Compared with the 16-bit FPGA adder design using the real acoustic wave signal amplitude, the 2-bit FPGA adder design is simpler, and the calculation efficiency is significantly improved, and less chip resources are used.

[0032] like Figure 3 and 4 As shown in the figure, they represent the original 8 waveform data collected by the full wave acoustic logging device and the waveform curve after preprocessing such as bandpass filtering and waveform discrete binarization. Figure 4 It can be seen that the waveform amplitude has been limited, only the phase information of the waveform is retained, and the original floating-point waveform data is converted into integer binary data.

[0033] Further, the S4 cross-correlation calculation includes the following steps: At different depth points, the time difference range [s1, s2] and arrival time range [t1, t2] are given; The outer loop traverses the time difference variable s, and the inner loop traverses to the time variable t, and a time window is determined under a set of (s, t) loop variables; In each determined time window, two-dimensional cross-correlation calculation is performed on 8 received waveform data to obtain the two-dimensional correlation coefficient in the time window; The above process is repeated until all possible combinations of time difference and arrival time variable values ​​are traversed, completing the entire cross-correlation calculation process.

[0034] Furthermore, the cross-correlation calculation formula is: ; Formula 2; in: R2D represents the two-dimensional correlation coefficient; S[k] is the time difference sequence; ; s1 represents the starting time difference; s2 represents the termination time difference; ; t1 represents the start time of the calculation area; t2 represents the end time of the calculation area; Twin indicates the calculation window length; int represents rounding operation; ts represents the sampling time interval of each waveform.

[0035] like Figure 5 and 6 As shown in the figure, they represent the two-dimensional correlation coefficient contour map and one-dimensional correlation coefficient curve map obtained after the cross-correlation calculation of 8 discrete binary waves. The data involved in the calculation of the 8 waveforms are Figure 4 The waveform data in the parallelogram box in the figure, the solid line box and the dashed line box represent the current calculation window and the next calculation window after moving one time step at a given time difference, respectively.

[0036] Furthermore, the calculation formula of the S5 one-dimensional correlation coefficient R1D is: ; Formula 3.

[0037] Among them, R1D(S[k]) represents the one-dimensional correlation coefficient corresponding to the time difference value. During the calculation, each S[k] value is fixed, and the maximum value of the corresponding two-dimensional correlation coefficient within the range of m is calculated.

[0038] Further, S6 searches for the maximum value of the one-dimensional correlation coefficient, including: respectively setting the time difference search ranges of the longitudinal wave, the shear wave and the Stoneley wave, wherein the longitudinal wave time difference range is [DTC1, DTC2], the shear wave time difference range is [DTS1, DTS2], and the Stoneley wave time difference range is [DTST1, DTST2]; searching for the maximum value of the one-dimensional correlation coefficient within the time difference ranges corresponding to the longitudinal wave, the shear wave and the Stoneley wave, and selecting the time difference value corresponding to the local maximum value of the corresponding coefficient as the time difference value of the longitudinal wave, the shear wave and the Stoneley wave. The horizontal coordinate of the maximum value corresponds to the time difference values ​​of the three modes of waves propagating in the formation, namely, the longitudinal wave time difference, the shear wave time difference and the Stoneley wave time difference of the formation.

[0039] Furthermore, the setting of the time difference search range of the longitudinal wave, the shear wave and the Stoneley wave includes: generating the time difference search range of the longitudinal wave, the shear wave and the Stoneley wave based on the lithology parameters of the target formation.

[0040] Before logging, the lithology parameters of the target formation are obtained through geological surveys, core analysis or adjacent well data. These parameters include: rock type (such as sandstone, shale, carbonate rock, etc.), porosity range, rock density, mineral composition, formation pressure and temperature. According to the lithology parameters, combined with the principles of geophysics and experimental data, the propagation characteristics of P-waves, S-waves and Stoneley waves in the target formation are analyzed: Dense rock: The sound wave propagates faster and the time difference is smaller. Rocks with high porosity: The sound wave propagates slower and the time difference is larger. Rocks containing fluids: The time difference between S-waves and Stoneley waves will change due to the properties of the fluids (such as oil, gas, water).

[0041] According to the lithological parameters and the propagation characteristics of acoustic waves, reasonable time difference search ranges are set for P-waves, S-waves and Stoneley waves respectively: P-wave time difference search range: Set the P-wave time difference range according to the density and porosity of the target formation. S-wave time difference search range: Set the S-wave time difference range according to the rigidity and pore structure of the rock. Stoneley wave time difference search range: Set the Stoneley wave time difference range according to the formation fluid properties and pore pressure. Combined with historical data and logging results of neighboring wells, the time difference search range is further optimized to ensure that the search range covers the actual time difference value of the target formation, while reducing unnecessary calculations. During the logging process, the time difference values ​​of P-waves, S-waves and Stoneley waves are extracted in real time according to the set time difference search range to provide reliable data for oil and gas reservoir evaluation.

[0042] like Figure 7 As shown in the figure, the measured waveform data is processed by the downhole acoustic wave time difference real-time rapid extraction method to obtain the downhole formation time difference curve. The first track is the depth track and the second track is the time difference curve. Based on formula 3, the one-dimensional correlation coefficient curve about the time difference is obtained. By searching the one-dimensional curve, three maximum values ​​can be obtained. The horizontal coordinates of the maximum values ​​correspond to the time difference values ​​of the three mode waves propagating in the formation, namely the longitudinal wave time difference, the shear wave time difference and the Stoneley wave time difference of the formation.

[0043] Through the real-time and rapid extraction method of downhole acoustic wave time difference, the demand for downhole instruments to upload formation measurement information in real time during logging operations can be met, providing reliable data for real-time and rapid monitoring of downhole formation acoustic wave time difference data for deep oil and gas reservoir evaluation.

[0044] like Figure 8 As shown, a downhole acoustic wave time difference real-time rapid extraction device comprises: A single-transmitter-eight-receiver full-wave acoustic logging tool, comprising a transmitting transducer T and eight receiving transducers R1 to R8; The transmitting transducer T and the receiving transducers R1 to R8 are mounted on the metal core rod and arranged coaxially with the metal core rod; The receiving transducers R1 to R8 are all located on the same side of the transmitting transducer T, wherein the first receiving transducer R1 is at a distance L from the transmitting transducer T, which is used as the source distance; The spacing between receiving transducers R1 and R2 is S, and the spacing between all eight receiving transducers is S; that is, the spacing between two adjacent receiving transducers is S; The sound insulator is used to isolate the sound wave signal that propagates directly along the metal core rod to the receiving transducer, ensuring that the received sound wave signal comes from the formation.

[0045] This article uses specific examples to illustrate the principles and implementation methods of the present invention. The above examples are only used to help understand the method and core ideas of the present invention. At the same time, for those skilled in the art, according to the ideas of the present invention, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting the present invention.

Claims

1. A method for real-time rapid extraction of downhole acoustic wave time difference, characterized in that: The following steps are involved: S1, collecting acoustic waveform data at different formation depths through a downhole acoustic wave time difference real-time rapid extraction device; S2, performing bandpass filtering on the acoustic waveform data; S3, performing waveform discrete binarization processing on the filtered waveform data; S4, using cross-correlation calculation based on wave arrival time and time difference window to obtain two-dimensional correlation coefficients under different wave arrival time and time difference windows for the waveform data processed by waveform discrete binarization; S5. According to the two-dimensional correlation coefficient, obtain the one-dimensional correlation coefficient corresponding to different time differences; S6. Search for the maximum value of the one-dimensional correlation coefficient to obtain the time difference values ​​corresponding to the longitudinal wave, transverse wave and Stoneley wave.

2. A downhole acoustic wave time difference real-time rapid extraction method according to claim 1, characterized in that: S2 bandpass filter preprocessing, including: Set the operating frequency range of the transmitting transducer [f1, f2]; Transforming the time domain acoustic wave signal of the receiving transducer into a frequency domain signal; Perform bandpass filtering within the set frequency range [f1, f2] to retain the signals within the frequency range and filter out the interference signals outside the range; Perform an inverse transform on the frequency domain signal after bandpass filtering and convert it back to the time domain signal.

3. A downhole acoustic wave time difference real-time rapid extraction method according to claim 2, characterized in that: S3 waveform discrete binarization preprocessing, including: Set the positive threshold PosThrehold and the negative threshold NegThrehold; ； in: Wave represents the waveform after bandpass filtering; SWave represents the waveform after discrete binarization; i represents the serial number of the receiving transducer; j represents the number of sampling points of the waveform; Compare the actual sound wave signal amplitude with the set positive and negative thresholds; When the amplitude of the acoustic wave signal is greater than the positive threshold, the signal amplitude is set to +1; When the amplitude of the sound wave signal is less than the negative threshold, the signal amplitude is set to -1; When the amplitude of the sound wave signal does not meet the above two conditions, the signal amplitude is set to 0.

4. A downhole acoustic wave time difference real-time rapid extraction method according to claim 3, characterized in that: The setting of the positive threshold PosThrehold and the negative threshold NegThrehold takes into account the minimum signal amplitude of the background noise, and the steps include: Analyze the amplitude distribution of background noise and determine the minimum signal amplitude of background noise; Based on the minimum signal amplitude of the background noise, the positive threshold PosThrehold and the negative threshold NegThrehold are set.

5. A downhole acoustic wave time difference real-time rapid extraction method according to claim 1, characterized in that: The S4 cross-correlation calculation includes the following steps: At different depth points, the time difference range [s1, s2] and arrival time range [t1, t2] are given; The outer loop traverses the time difference variable s, and the inner loop traverses to the time variable t, and a time window is determined under a set of (s, t) loop variables; In each determined time window, a two-dimensional cross-correlation calculation is performed on the received waveform data to obtain a two-dimensional correlation coefficient in the time window; The above process is repeated until all possible combinations of time difference and arrival time variable values ​​are traversed to complete the cross-correlation calculation process.

6. A downhole acoustic wave time difference real-time rapid extraction method according to claim 5, characterized in that: The cross-correlation calculation formula is: ； in: R2D represents the two-dimensional correlation coefficient; S[k] is the time difference sequence; ； s1 represents the starting time difference; s2 represents the termination time difference; ； t1 represents the start time of the calculation area; t2 represents the end time of the calculation area; Twin indicates the calculation window length; int represents rounding operation; ts represents the sampling time interval of each waveform.

7. A downhole acoustic wave time difference real-time rapid extraction method according to claim 6, characterized in that: The calculation formula of S5 one-dimensional correlation coefficient R1D is: ； Among them, R1D(S[k]) represents the one-dimensional correlation coefficient corresponding to the time difference value. During the calculation, each S[k] value is fixed, and the maximum value of the corresponding two-dimensional correlation coefficient within the range of m is calculated.

8. A downhole acoustic wave time difference real-time rapid extraction method according to claim 1, characterized in that: S6 searches for the maximum value of the one-dimensional correlation coefficient including: Set the time difference search range for longitudinal waves, shear waves and Stoneley waves respectively; The maximum value of the one-dimensional correlation coefficient is searched within the time difference range corresponding to the longitudinal wave, the transverse wave and the Stoneley wave, and the time difference value corresponding to the local maximum value of the corresponding coefficient is selected as the time difference value of the longitudinal wave, the transverse wave and the Stoneley wave.

9. A method for real-time rapid extraction of downhole acoustic wave time difference according to claim 8, characterized in that: The settings for the time difference search range for longitudinal waves, shear waves and Stoneley waves include: Based on the lithology parameters of the target formation, the time difference search range of the P-wave, S-wave and Stoneley wave is generated.

10. A downhole acoustic wave time difference real-time rapid extraction device used in the downhole acoustic wave time difference real-time rapid extraction method according to any one of claims 1 to 9, characterized in that: include: A full-wave acoustic logging tool includes a transmitting transducer and a number of receiving transducers; The transmitting transducer and a plurality of receiving transducers are mounted on the metal core rod and arranged coaxially with the metal core rod; A plurality of receiving transducers are located on the same side of the transmitting transducer, wherein the distance between the first receiving transducer and the transmitting transducer is L; The distance between two adjacent receiving transducers is S; The sound insulator is used to isolate the sound wave signal that is directly transmitted along the metal core rod to the receiving transducer. The sound insulator is installed on the metal rod between the first receiving transducer and the transmitting transducer.

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