Acoustic logging transducer control method and system with excitation waveform acquisition function

Abstract

The invention relates to the technical field of data analysis, in particular to an acoustic logging transducer control method and system with an excitation waveform collection function, and the method comprises the steps: collecting acoustic data information; acquiring standard data corresponding to each acquisition sequence data according to the same acquisition sequence data size of each group of sound wave data; according to the change trend and the fluctuation condition of the sound data corresponding to each collection sequence of each collection data, obtaining a noise probability parameter corresponding to each collection sequence data in combination with the fitting degree with the standard data; acquiring a proportional gain value according to the noise probability parameter corresponding to each sequence data acquired each time and the size of the corresponding data acquisition sequence; and adjusting the measurement data according to the proportional gain value corresponding to each piece of sequence data acquired each time. According to the embodiment of the invention, the accuracy and stability of measurement are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of data analysis, and in particular to a control method and system for an acoustic logging transducer with an excitation waveform acquisition function. Background Art

[0002] The principle of proportional control of an acoustic logging transducer is to control the size ratio of the output signal according to the size of the input signal. A transducer is a device that converts one form of energy into another form, and an acoustic logging transducer is a device that converts acoustic energy into an electrical signal. Proportional control is to control the size of the output signal by adjusting the proportional relationship between the input signal and the output signal. The characteristic of proportional control is fast response. When there is a deviation signal input, the output immediately changes proportionally with it. The greater the deviation, the stronger the output control action. When the proportional gain is larger, the voltage will be adjusted to the preset value faster, and the adjustment sensitivity is higher. An overly large proportional gain value will cause the amplitude of the output signal to be too large, which may cause the measurement system to be overloaded or distorted. An overly small proportional gain value will cause the amplitude of the output signal to be too small, which may make the measurement system less sensitive to changes in the input signal, affecting the accuracy and stability of the measurement. Summary of the Invention

[0003] The present invention provides a control method and system for an acoustic logging transducer with an excitation waveform acquisition function to solve existing problems.

[0004] The control method and system for an acoustic logging transducer with an excitation waveform acquisition function of the present invention adopt the following technical solutions:

[0005] An embodiment of the present invention provides a control method for an acoustic logging transducer with an excitation waveform acquisition function, and the method includes the following steps:

[0006] Collect acoustic data information;

[0007] Obtain the standard data corresponding to each acquisition sequence data according to the size of the same acquisition sequence data in each group of acoustic data;

[0008] Obtain the noise probability parameter corresponding to each acquisition sequence data according to the change trend and fluctuation of the sound data corresponding to each acquisition sequence in each data acquisition and the fitting degree with the standard data;

[0009] Obtain the proportional gain value according to the noise probability parameter corresponding to each sequence data in each acquisition and the size of the corresponding data acquisition sequence; adjust the measurement data according to the proportional gain value corresponding to each sequence data in each acquisition.

[0010] Further, obtaining the noise probability parameter corresponding to each acquisition sequence data according to the change trend and fluctuation of the sound data corresponding to each acquisition sequence in each acquisition, combined with the fitting degree with the standard data, includes the following specific methods:

[0011] Obtaining the fitting parameter of each acquisition corresponding to each acquisition sequence data according to the fitting degree of each acquisition corresponding to each acquisition sequence data and the standard data;

[0012] Obtaining the fluctuation coefficient of each acquisition corresponding to the same acquisition sequence data according to the change of each acquisition corresponding to the same acquisition sequence data;

[0013] Obtaining the noise probability parameter according to the fluctuation coefficient of each sequence data corresponding to each acquisition and the fitting parameter of each acquisition corresponding to each acquisition sequence data.

[0014] Further, obtaining the proportional gain value according to the noise probability parameter of each sequence data corresponding to each acquisition and the size of the corresponding data acquisition sequence, includes the following specific methods:

[0015]

[0016] In the formula, Prg k，l represents the proportional gain value of the first sequence data corresponding to the kth acquisition, U is a hyperparameter, Prm k，l represents the noise probability parameter of the first sequence data corresponding to the kth acquisition, T represents the acquisition data duration, D represents the acquisition data time interval, 1 represents the data acquisition sequence, and the proportional gain value of each acquisition corresponding to each sequence data is obtained according to this method.

[0017] Further, obtaining the fitting parameter of each acquisition corresponding to each acquisition sequence data according to the fitting degree of each acquisition corresponding to each acquisition sequence data and the standard data, includes the following specific methods:

[0018]

[0019] In the formula, Fit k，l represents the fitting parameter of the first acquisition sequence data corresponding to the kth acquisition, Std k，l represents the standard data of the lth acquisition sequence data corresponding to the kth acquisition, w k，l represents the sound data of the lth acquisition sequence data corresponding to the kth acquisition, T represents the acquisition data duration, D represents the acquisition data time interval, Std k，j represents the standard data of the jth acquisition sequence data corresponding to the kth acquisition, w k，j represents the sound data of the jth acquisition sequence data corresponding to the kth acquisition, and the fitting parameter of each acquisition corresponding to each acquisition sequence data is obtained according to this method.

[0020] Further, obtaining the fluctuation coefficient of the same sequence data corresponding to each acquisition according to the change of the same acquisition sequence data includes the following specific method:

[0021]

[0022] In the formula, Voc k，l represents the fluctuation coefficient of the l-th sequence data corresponding to the k-th acquisition, and w I，l represents the l-th sequence sound data corresponding to the i-th acquisition. represents the mean value of the l-th sequence sound data corresponding to each acquisition, and B represents the number of acquisition data. The fluctuation coefficient of the same sequence data corresponding to each acquisition is obtained according to this method.

[0023] Further, obtaining the noise probability parameter according to the fluctuation coefficient of each sequence data corresponding to each acquisition and the fitting parameter of each acquisition sequence data includes the following specific method:

[0024] Prm k，l = Fit k，l ×Voc k，l

[0025] In the formula, Prm k，l represents the noise probability parameter of the l-th sequence data corresponding to the k-th acquisition, Fit k，l represents the fitting parameter of the l-th acquisition sequence data corresponding to the k-th acquisition, and Voc k，l represents the fluctuation coefficient of the l-th sequence data corresponding to the k-th acquisition. The noise probability parameter of each sequence data corresponding to each acquisition is obtained according to this method.

[0026] Further, obtaining the standard data corresponding to each acquisition sequence data according to the size of the same acquisition sequence data in each group of acoustic wave data includes the following specific method:

[0027]

[0028] In the formula, Std k，l represents the standard data of the l-th acquisition sequence sound data corresponding to the k-th acquisition data, and w i，l represents the l-th acquisition sequence sound data corresponding to the i-th acquisition data, and B represents the number of acquisition data. The standard data of each acquisition sequence sound data corresponding to each acquisition data is obtained according to this method.

[0029] Further, collecting the acoustic wave data information includes the following specific method:

[0030] Each data collection lasts for T seconds. The acoustic wave emission device emits waves every T seconds according to the preset data collection duration. After the acoustic wave is emitted, the sensor collects all acoustic wave data within T seconds at a preset collection interval of D seconds, and converts the acoustic wave data into numbers. A total of B data collections are performed to obtain B sets of acoustic wave data information.

[0031] Further, the data between adjacent two collection sequences is adjusted with the proportional gain value corresponding to the data of the previous sequence until all data adjustment processes are completed, and the adjusted data is obtained.

[0032] An embodiment of the present invention provides an acoustic logging transducer control system with an excitation waveform collection function. The system includes a data collection module, a data calculation module, a data analysis module, and a data adjustment module, where:

[0033] The data collection module is used to collect acoustic wave data information;

[0034] The data calculation module is used to obtain the standard data corresponding to each collection sequence data according to the size of the same collection timing data of each group of acoustic wave data;

[0035] The data analysis module is used to obtain the noise probability parameter corresponding to each collection sequence data according to the change trend and fluctuation of the sound data corresponding to each collection sequence of each data collection and the fitting degree with the standard data;

[0036] The data adjustment module is used to obtain the proportional gain value according to the noise probability parameter of each sequence data corresponding to each collection and the size of the corresponding data collection sequence; and adjust the measurement data according to the proportional gain value of each sequence data corresponding to each collection.

[0037] The beneficial effect of the technical solution of the present invention is that the present invention improves the measurement accuracy and stability. An overly large proportional gain value will cause the amplitude of the output signal to be too large, which may cause the measurement system to be overloaded or distorted. An overly small proportional gain value will cause the amplitude of the output signal to be too small, which may make the measurement system less sensitive to changes in the input signal and affect the measurement accuracy and stability. This step controls the frequency band of the collected data to obtain sound information at different exploration depths, collects data multiple times and compares to obtain the noise level of the data, and adaptively adjusts the proportional gain according to the noise level and exploration depth, so that each data has a corresponding proportional gain parameter. The greater the noise probability and the shallower the exploration depth, the smaller the proportional gain of the data to reduce the data noise level and the possibility of over-saturation. The smaller the noise probability and the deeper the exploration depth, the greater the proportional gain of the data to improve the detail information and accurately reflect the characteristics of underground rocks. Description of the Drawings

[0038] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the accompanying drawings required for the description of the embodiments or the prior art. Obviously, the accompanying drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other accompanying drawings can be obtained based on these drawings.

[0039] Figure 1 It is a flowchart of the steps of a method for controlling an acoustic logging transducer with an excitation waveform acquisition function according to the present invention;

[0040] Figure 2 It is a block diagram of the structure of a control system for an acoustic logging transducer with an excitation waveform acquisition function according to the present invention. Detailed implementation manners

[0041] In order to further elaborate on the technical means and effects adopted by the present invention to achieve the intended invention purpose, the following, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation manners, structures, features, and effects of a method and system for controlling an acoustic logging transducer with an excitation waveform acquisition function according to the present invention. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. In addition, the specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0042] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those of ordinary skill in the technical field to which the present invention belongs.

[0043] The following specifically describes the specific solutions of a method and system for controlling an acoustic logging transducer with an excitation waveform acquisition function provided by the present invention in conjunction with the accompanying drawings.

[0044] Please refer to Figure 1 , which shows a flowchart of the steps of a method for controlling an acoustic logging transducer with an excitation waveform acquisition function provided by an embodiment of the present invention. The method includes the following steps:

[0045] Step S001: Collect acoustic data information.

[0046] It should be noted that the adjustment of the proportional gain of the acoustic logging transducer is based on the analysis and evaluation of the formation characteristics and wellbore conditions by the logging engineer. In practical applications, the adjustment of the proportional gain is carried out according to parameters such as the lithology, porosity, and permeability of the formation. Generally speaking, the data measured with a larger proportional gain has a larger amplitude and dynamic range, which can better reflect the subtle changes in the formation, but oversaturation may occur. While the data measured with a smaller proportional gain has a smaller amplitude and dynamic range, with a weaker response to subtle changes, but it can reduce the possibility of oversaturation. In an ideal state, the data measured by the proportional gain should be able to accurately reflect the characteristics of the formation, have an appropriate amplitude and dynamic range, and can clearly display the interfaces and changes of the formation. The adjustment of the proportional gain in the ideal state can maximize the resolution and accuracy of the logging data, thus better helping engineers with formation evaluation and oil and gas exploration work.

[0047] The depth that acoustic logging can detect is generally between several hundred meters and several kilometers, and the specific detection depth depends on the performance and design of the acoustic logging equipment. Generally speaking, the acoustic logging equipment can detect at different depths, and the method of detecting different depths is usually achieved by changing the receiving time of the sensor of the acoustic receiver, so that data at different depths can be obtained. In the present invention, it is necessary to preset an acquisition interval of D seconds, the duration of each data acquisition is T seconds, and the total number of data acquisitions is B times. In this embodiment, the acquisition interval is D = 0.001 seconds, the duration of each data acquisition is T = 1 second, and the total number of data acquisitions is B times for discussion, and in other embodiments, it depends on the specific implementation situation.

[0048] Specifically, in order to implement a control method for an acoustic logging transducer with an excitation waveform acquisition function proposed in this embodiment, it is first necessary to acquire acoustic data information, and the specific process is as follows:

[0049] The duration of each data acquisition is T seconds. The acoustic emission device emits once every T seconds according to the preset data acquisition duration. After the acoustic wave is emitted, the sensor acquires all the acoustic data within T seconds according to the preset acquisition interval of D seconds, and converts the acoustic data into digital form. A total of B times of data are acquired to obtain B groups of acoustic data information.

[0050] Thus far, the acoustic data information is obtained through the above method.

[0051] Step S002: Obtain the standard data corresponding to each acquisition sequence data according to the size of the same acquisition timing data in each group of acoustic data.

[0052] It should be noted that after the acoustic wave is emitted, due to distance and different geological structures, the acoustic wave receiver sensor receives different acoustic wave information at different times, thus obtaining acoustic wave data at different depths of acoustic logging. Therefore, when collecting data each time, the acoustic wave data in the previous sequence of the acquisition timing mostly corresponds to the shallow layer information of acoustic logging because the sensor receives the reflected acoustic wave earlier. The subsequent acoustic wave data in the acquisition timing each time may correspond to the near-deep layer information of the acoustic side because the sensor receives the reflected acoustic wave for a longer time. However, the reflected acoustic wave may be affected by noise. Normal data usually has an obvious trend and variation, which can show the structure and properties of the formation. These data usually have a high signal-to-noise ratio and can clearly reflect the characteristics of underground rocks, such as velocity, density, etc. Noise data, on the other hand, usually shows random fluctuations or interference and lacks obvious trends and variations. These data usually have a low signal-to-noise ratio and cannot accurately reflect the characteristics of underground rocks, and water flow or heterogeneous terrain will make the trends and variations of the acoustic wave data received by the sensor more chaotic. Therefore, in this step, the ideal distribution of the acoustic wave data corresponding to different acquisition timings is obtained by comparing the changes in the acoustic wave data corresponding to different acquisition timings in each group of collected acoustic wave data.

[0053] Specifically, the specific method for obtaining the standard data corresponding to each acquisition sequence data according to the data size of the same acquisition sequence in each group of acoustic wave data is as follows:

[0054]

[0055] In the formula, Std k，l represents the standard data of the sound data corresponding to the first acquisition sequence for the k-th acquisition data, w i，l represents the sound data corresponding to the l-th acquisition sequence for the i-th acquisition data, B represents the number of acquisition data times, and the standard data of the sound data corresponding to each acquisition sequence for each acquisition data is obtained according to this method.

[0056] So far, the standard data of the sound data corresponding to each acquisition sequence for each acquisition data has been obtained through the above method.

[0057] Step S003: Obtain the noise probability parameter corresponding to each acquisition sequence data according to the change trend and fluctuation of the sound data corresponding to each acquisition sequence of each acquisition data in combination with the fitting degree with the standard data.

[0058] It should be noted that the standard data is obtained based on the average of multiple measurements, which means that the sound data is likely to fluctuate around the standard data, and the closer it is to the standard data, the greater the probability that the sound data is normal data. However, the heterogeneity and fluidity of the geology also need to be considered. Therefore, this step needs to obtain the noise probability parameter corresponding to each acquisition sequence data based on the change trend and fluctuation of the sound data corresponding to each acquisition sequence of each data acquisition and the degree of fit with the standard data.

[0059] Specifically, the fitting parameters of each acquisition sequence data corresponding to each acquisition are obtained according to the degree of fit between each acquisition sequence data and the standard data:

[0060]

[0061] Where, Fit k，l Std represents the fitting parameters of the kth acquisition corresponding to the lth acquisition sequence data. k，l represents the standard data of the kth acquisition corresponding to the lth acquisition sequence data, w k，l Indicates the sound data of the kth acquisition corresponding to the lth acquisition sequence data, T indicates the acquisition data duration, D indicates the acquisition data time interval, Std k，j Indicates the standard data of the kth acquisition corresponding to the jth acquisition sequence data, w k，j The k-th acquisition represents the sound data corresponding to the j-th acquisition sequence data, and the fitting parameters corresponding to each acquisition sequence data are obtained according to this method.

[0062] Furthermore, the specific method for obtaining the fluctuation coefficient of the same sequence data collected each time according to the change of the same sequence data collected each time is as follows:

[0063]

[0064] Where Voc k，l represents the fluctuation coefficient of the kth collection corresponding to the lth sequence data, w I，l Indicates that the first acquisition corresponds to the first sequence of sound data, It represents the mean value of the lth sequence of sound data collected each time, and B represents the number of times the data is collected. According to this method, the fluctuation coefficient of each sequence data collected each time is obtained.

[0065] Furthermore, the specific method for obtaining the noise probability parameter according to the fluctuation coefficient of each sequence data corresponding to each acquisition and the fitting parameter of each acquisition sequence data corresponding to each acquisition is as follows:

[0066] Prm k，l =Fit k，l ×Voc k，l

[0067] In the formula, Prm k，l represents the noise probability parameter corresponding to the l-th sequence data for the k-th acquisition, and Fit k，l represents the fitting parameter corresponding to the l-th acquisition sequence data for the k-th acquisition, and Voc k，l represents the fluctuation coefficient corresponding to the 1st sequence data for the k-th acquisition. The noise probability parameter corresponding to each sequence data for each acquisition is obtained by this method.

[0068] It should be noted that the larger the fitting parameter corresponding to the data, the greater the difference between the data and the standard data, and the greater the probability that the data is noise; the larger the fluctuation coefficient of the data, the greater the fluctuation degree of the acoustic wave data measured at the same depth, and the lower the signal-to-noise ratio of the data, and the greater the probability that it is noise data. Therefore, the obtained noise probability parameter is larger.

[0069] So far, the noise probability parameter corresponding to each sequence data for each acquisition is obtained by the above method.

[0070] Step S004: Obtain the proportional gain value according to the noise probability parameter corresponding to each sequence data for each acquisition and the size of the corresponding data acquisition sequence; adjust the measurement data according to the proportional gain value corresponding to each sequence data for each acquisition.

[0071] It should be noted that the proportional gain value can be obtained according to the noise probability parameter corresponding to each sequence data for each acquisition and the acquisition sequence. When the acquisition sequence of the data is larger, the proportional gain should be increased to increase the amplitude and dynamic range, because a larger acquisition sequence corresponds to a greater exploration depth of acoustic logging, and the data fluctuation is less obvious. The data fluctuation amplitude should be increased to retain the detailed information. For the data with a smaller acquisition sequence corresponding to a smaller exploration depth of acoustic logging, the proportional gain value should be reduced to reduce the noise influence and the possibility of over-saturation. At the same time, the larger the noise probability parameter of the data, the proportional gain should be reduced to improve the signal-to-noise ratio of the acquired data, and the smaller the noise probability parameter of the data, the proportional gain should be increased.

[0072] Specifically, the specific method for obtaining the proportional gain value according to the noise probability parameter corresponding to each sequence data for each acquisition and the size of the corresponding data acquisition sequence is as follows:

[0073]

[0074] In the formula, Prg k，l represents the proportional gain value corresponding to the 1st sequence data for the k-th acquisition, U is a hyperparameter, and Prm k，lIt represents the noise probability parameter corresponding to the l-th sequence of data for the k-th acquisition. T represents the acquisition duration of the data, D represents the acquisition time interval of the data, and l represents the data acquisition sequence. According to this method, the proportional gain value corresponding to each sequence of data for each acquisition is obtained.

[0075] It should be noted that U is a hyperparameter used to adjust the growth ratio and depends on the value range of the signal received by the measurement device. In this embodiment, U = 2.7 is discussed. In other embodiments, it depends on the specific implementation situation. In this step, the value range of the domain is greater than or equal to 0, so the value range of the range is also greater than or equal to 0. The purpose is to make the proportional gain parameter decrease as the noise probability parameter increases.

[0076] Furthermore, the specific method for adjusting the measurement data according to the proportional gain value corresponding to each sequence of data for each acquisition is as follows:

[0077] The data between two adjacent acquisition sequences is adjusted with the proportional gain value corresponding to the previous sequence of data until all data adjustment processes are completed, and the adjusted data is obtained.

[0078] Please refer to Figure 2 , which shows the structural block diagram of an acoustic logging transducer control system with an excitation waveform acquisition function provided by an embodiment of the present invention. The system includes the following modules:

[0079] A data acquisition module, a data calculation module, a data analysis module, and a data adjustment module.

[0080] The present invention improves the measurement accuracy and stability. An overly large proportional gain value will cause the amplitude of the output signal to be too large, which may cause the measurement system to be overloaded or distorted. An overly small proportional gain value will cause the amplitude of the output signal to be too small, which may make the measurement system less sensitive to changes in the input signal and affect the measurement accuracy and stability. This step controls the frequency band of the acquired data to obtain sound information at different exploration depths, acquires the data multiple times and compares them to obtain the noise level of the data, and adaptively adjusts the proportional gain according to the noise level and exploration depth, so that each data has a corresponding proportional gain parameter. The greater the noise probability and the shallower the exploration depth, the smaller the proportional gain of the data to reduce the data noise level and the possibility of over-saturation. The smaller the noise probability and the deeper the exploration depth, the greater the proportional gain of the data to improve the detail information and accurately reflect the characteristics of underground rocks.

[0081] The above are only the preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A control method for an acoustic logging transducer with an excitation waveform acquisition function, characterized in that The method includes the following steps: Collect acoustic wave data information; Obtain the standard data corresponding to each acquisition sequence data according to the same acquisition sequence data size of each group of acoustic wave data; Obtain the noise probability parameter corresponding to each acquisition sequence data according to the change trend and fluctuation of the sound data corresponding to each acquisition sequence in each data acquisition and the fitting degree with the standard data; Obtain the proportional gain value according to the noise probability parameter corresponding to each sequence data in each acquisition and the corresponding data acquisition sequence size; adjust the measurement data according to the proportional gain value corresponding to each sequence data in each acquisition.

2. The acoustic logging transducer control method with an excitation waveform acquisition function according to claim 1, wherein, The method of obtaining the noise probability parameter corresponding to each acquisition sequence data according to the change trend and fluctuation of the sound data corresponding to each acquisition sequence in each data acquisition and the fitting degree with the standard data includes the following specific method: Obtain the fitting parameter corresponding to each acquisition sequence data in each acquisition according to the fitting degree of each acquisition sequence data corresponding to each acquisition with the standard data; Obtain the fluctuation coefficient of the same acquisition sequence data in each acquisition according to the change of the same acquisition sequence data in each acquisition; Obtain the noise probability parameter according to the fluctuation coefficient of each sequence data corresponding to each acquisition and the fitting parameter of each acquisition sequence data corresponding to each acquisition.

3. The acoustic logging transducer control method with an excitation waveform acquisition function according to claim 1, characterized in that, The method of obtaining the proportional gain value according to the noise probability parameter corresponding to each sequence data in each acquisition and the corresponding data acquisition sequence size includes the following specific method: where Prg k,l represents the proportional gain value of the k-th acquisition corresponding to the l-th sequence data, U is a hyperparameter, and Prm k,l represents the noise probability parameter of the k-th acquisition corresponding to the l-th sequence data, T represents the acquisition data duration, D represents the acquisition data time interval, and l represents the data acquisition sequence. According to this method, the proportional gain value of each acquisition corresponding to each sequence data is obtained.

4. The acoustic logging transducer control method with an excitation waveform acquisition function according to claim 2, characterized in that, The method of obtaining the fitting parameter corresponding to each acquisition sequence data in each acquisition according to the fitting degree of each acquisition sequence data corresponding to each acquisition with the standard data includes the following specific method: where, Fit k，l represents the fitting parameter corresponding to the data of the first acquisition sequence for the k-th acquisition, Std k，l represents the standard data corresponding to the data of the first acquisition sequence for the k-th acquisition, w k，l represents the sound data corresponding to the data of the l-th acquisition sequence for the k-th acquisition, T represents the duration of the acquired data, D represents the time interval of the acquired data, Std k，j represents the standard data corresponding to the data of the j-th acquisition sequence for the k-th acquisition, w k，j represents the sound data corresponding to the data of the j-th acquisition sequence for the k-th acquisition, and the fitting parameter corresponding to the data of each acquisition sequence for each acquisition is obtained according to this method.

5. The control method of an acoustic logging transducer with an excitation waveform acquisition function according to claim 2, wherein, The method of obtaining the fluctuation coefficient of the same acquisition sequence data in each acquisition according to the change of the same acquisition sequence data in each acquisition includes the following specific method: Where, Voc k，l represents the fluctuation coefficient of the k-th acquisition corresponding to the first sequence of data, w I，l represents the first sequence of sound data corresponding to the I-th acquisition, represents the mean value of the first sequence of sound data corresponding to each acquisition, B represents the number of data acquisitions, and the fluctuation coefficient of each acquisition corresponding to each sequence of data is obtained according to this method.

6. The method for controlling an acoustic logging transducer with an excitation waveform acquisition function according to claim 2, wherein, The method of obtaining the noise probability parameter according to the fluctuation coefficient of each sequence data corresponding to each acquisition and the fitting parameter of each acquisition sequence data corresponding to each acquisition includes the following specific method: Prm k，l = Fit k，l × Voc k，l In the formula, Prm k，l represents the noise probability parameter corresponding to the l-th sequence data for the k-th acquisition, Fit k，l represents the fitting parameter corresponding to the l-th acquisition sequence data for the k-th acquisition, Voc k，l represents the fluctuation coefficient corresponding to the 1st sequence data for the k-th acquisition. The noise probability parameter corresponding to each sequence data for each acquisition is obtained by this method.

7. The control method of an acoustic logging transducer with an excitation waveform acquisition function according to claim 1, characterized in that The method of obtaining the standard data corresponding to each acquisition sequence data according to the same acquisition sequence data size of each group of acoustic wave data includes the following specific method: Wherein, Std k,l represents the standard data of the sound data corresponding to the l-th acquisition sequence for the k-th data acquisition, w i,l represents the sound data corresponding to the l-th acquisition sequence for the i-th data acquisition, B represents the number of data acquisitions, and the standard data of the sound data corresponding to each acquisition sequence for each data acquisition is obtained according to this method.

8. The acoustic logging transducer control method with an excitation waveform acquisition function according to claim 1, characterized in that, The method of collecting acoustic wave data information includes the following specific method: The duration of each data acquisition is T seconds. The acoustic wave transmitting device emits once every T seconds according to the preset data acquisition duration. After the acoustic wave is emitted, the sensor collects all acoustic wave data within T seconds at a preset acquisition interval of D seconds and converts the acoustic wave data into digital. A total of B times of data are collected to obtain B groups of acoustic wave data information.

9. The acoustic logging transducer control method with an excitation waveform acquisition function according to claim 1, characterized in that The method of adjusting the measurement data according to the proportional gain value corresponding to each sequence data in each acquisition includes the following specific method: Adjust the data between two adjacent acquisition sequences with the proportional gain value corresponding to the previous sequence data until all data adjustment processing is completed to obtain the adjusted data.

10. An acoustic logging transducer control system with an excitation waveform acquisition function, characterized in that, The system includes the following modules: A data acquisition module for collecting acoustic wave data information; A data calculation module for obtaining the standard data corresponding to each acquisition sequence data according to the same acquisition time sequence data size of each group of acoustic wave data; A data analysis module, which is used to obtain the noise probability parameter corresponding to each acquisition sequence data according to the change trend and fluctuation of the sound data corresponding to each acquisition sequence in each data acquisition and in combination with the fitting degree with the standard data; A data adjustment module, which is used to obtain the proportional gain value according to the noise probability parameter corresponding to each sequence data in each acquisition and the size of the corresponding data acquisition sequence; and adjust the measurement data according to the proportional gain value corresponding to each sequence data in each acquisition.

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