An automatic picking method for downhole dynamic liquid level depth based on AIC model

Abstract

The application discloses an automatic picking method for downhole dynamic liquid level depth based on an AIC model, which comprises the following steps: sending infrasonic wave signals at a well mouth, collecting echo signals reflected by an oil well dynamic liquid level; performing analog-digital conversion, spectrum processing and signal separation on the echo signals to obtain a main frequency of the echo signals and a liquid level echo signal; determining an acoustic wave propagation speed in the oil well according to the main frequency and a preset casing length, so as to determine a time sequence length value; and determining the dynamic liquid level depth of the oil well based on the AIC model, according to the liquid level echo signal and the time sequence length value. Compared with the existing dynamic liquid level monitoring method, the method is more accurate and faster, can automatically identify the depth of the liquid level, provides an economic and effective method for calculating the acoustic speed and the dynamic liquid level depth in the oil production well, and has high practical value.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of oil well production, and particularly relates to an automatic picking method and device for downhole dynamic liquid level depth based on an AIC model, an electronic device and a computer readable storage medium. BACKGROUND

[0002] Real-time monitoring of the dynamic liquid level depth value of a production well is an important link in the production process. Currently, common dynamic liquid level measurement methods in China include the float method, pressure gauge detection method, optical fiber detection method, indicator diagram method and acoustic wave method. Among them, the float method has limited application scenarios and cannot be used in a wide range; the pressure gauge detection method is tedious to operate and has high maintenance costs in the later stage; the optical fiber detection method has high costs and is suitable for laboratory research, but is difficult to popularize; the indicator diagram method is complex to calculate, has poor robustness and low precision.

[0003] At present, most of the dynamic liquid level monitors of production wells in China are designed based on the acoustic wave method. Acoustic waves are mechanical waves that are often caused by acoustic vibrations and have two forms of transverse waves and longitudinal waves. The frequency of the acoustic waves that can be perceived by the human ear is between 20Hz-20kHz. The acoustic wave method is simple to operate, has low costs, is highly adaptable and has high stability. However, the dynamic liquid level monitor of the production well designed based on the acoustic wave method has problems of low safety, small measurement depth range, low measurement accuracy and poor real-time performance.

[0004] Therefore, it is necessary to propose an automatic picking method for downhole dynamic liquid level depth based on an AIC model to solve the technical problems of low safety, small measurement depth range, low measurement accuracy and poor real-time performance of the existing dynamic liquid level monitor of the production well. SUMMARY

[0005] The application provides an automatic picking method for downhole dynamic liquid level depth based on an AIC model to solve the problems of low safety, small measurement depth range, low measurement accuracy and poor real-time performance of the existing dynamic liquid level monitor of the production well designed based on the acoustic wave method.

[0006] The automatic picking method for downhole dynamic liquid level depth based on the AIC model provided by the application comprises the following steps:

[0007] Subsonic wave signals are sent at the wellhead, and echo signals reflected by the dynamic liquid level of the oil well are collected;

[0008] The echo signals are subjected to analog-to-digital conversion to obtain digital echo signals;

[0009] The digital echo signals are subjected to spectrum processing and signal separation to obtain the main frequency of the echo signals and liquid surface echo signals;

[0010] The acoustic wave propagation speed in the oil well is determined according to the main frequency and a preset casing length;

[0011] determining a time series length value according to the preset liquid level depth and the sound wave propagation speed;

[0012] determining the dynamic liquid level depth of the oil well according to the liquid level echo signal and the time series length value based on the AIC model.

[0013] Further, the digital echo signal is subjected to spectrum processing to obtain a main frequency of the echo signal, including:

[0014] The digital echo signal is subjected to Fourier transform to decompose the digital echo signal into signals of different frequency components, and the main frequency of the digital echo signal is determined.

[0015] Further, the digital echo signal is subjected to signal separation to obtain a liquid level echo signal of the echo signal, including:

[0016] The liquid level echo signal and the casing collar signal are separated from the signals of different frequency components by dynamically setting a passband of a filter.

[0017] Further, the sound wave propagation speed in the oil well is determined according to the main frequency and a preset casing length, including:

[0018] The sound wave propagation speed is calculated according to a formula v=2L0f0;

[0019] wherein L0 is the preset casing length, f0 is the main frequency of the echo signal, and v is the sound wave propagation speed.

[0020] Further, a time series length value is determined according to the preset liquid level depth and the sound wave propagation speed, including:

[0021] The time series length value is determined according to formulas T0=H0 / 2v and N=T0f0;

[0022] wherein N is the time series length value, H0 is the preset liquid level depth, v is the sound wave propagation speed, and f0 is the main frequency of the echo signal.

[0023] Further, the dynamic liquid level depth of the oil well is determined according to the liquid level echo signal, the sound wave propagation speed and the time series length value based on the AIC model, including:

[0024] The liquid level echo signal is substituted into a formula to determine a liquid level echo time t;

[0025] The dynamic liquid level depth H of the oil well is determined according to the liquid level echo time t and the sound wave propagation speed v through a formula H=vt / 2;

[0026] Wherein, k is the data sampling point in the window range, x(i) (i=1, 2, 3, …N) is the amplitude of the waveform data point in the window, var is the variance calculation function, CF is the characteristic function of the signal, and N is the length of the signal.

[0027] The application also provides an automatic picking device for downhole dynamic liquid level depth based on an AIC model, comprising:

[0028] A signal acquisition module is configured to send infrasonic wave signals at a wellhead and collect echo signals reflected by a dynamic liquid level of an oil well.

[0029] An analog-digital conversion module is configured to perform analog-digital conversion on the echo signals to obtain digital echo signals.

[0030] An extraction module is configured to perform spectrum processing and signal separation on the digital echo signals to obtain a main frequency of the echo signals and a liquid level echo signal.

[0031] A sound velocity calculation module is configured to determine a sound wave propagation speed in the oil well according to the main frequency and a preset casing length.

[0032] A time determination module is configured to determine a time sequence length value according to a preset liquid level depth and the sound wave propagation speed.

[0033] A liquid level depth calculation module is configured to determine a dynamic liquid level depth of the oil well based on an AIC model, according to the liquid level echo signal, the sound wave propagation speed, and the time sequence length value.

[0034] The application also provides an electronic device comprising a processor and a memory, wherein the memory stores a computer program, and the computer program is executed by the processor to implement the automatic picking method for downhole dynamic liquid level depth based on the AIC model.

[0035] The application also provides a computer readable storage medium storing a computer program, and the computer program is executed by a processor to implement the automatic picking method for downhole dynamic liquid level depth based on the AIC model.

[0036] Compared with the prior art, the beneficial effects of the present application include: the well down dynamic liquid level depth automatic picking method based on the AIC model provided by the present application, first, the echo signal reflected by the oil well dynamic liquid level after sending the infrasonic wave signal is collected, and the echo signal is subjected to digital-to-analog conversion, spectrum processing and signal separation to obtain the main frequency of the echo signal and the liquid level echo signal; second, the sound wave propagation speed and the time sequence length value are determined according to the main frequency, the preset casing length and the preset liquid level depth; finally, the oil well dynamic liquid level depth is obtained according to the liquid level echo signal, the sound wave propagation speed and the time sequence length value. Compared with the existing dynamic liquid level monitoring method, the method of the present application is more accurate and fast, and can automatically identify the depth of the liquid level; provides an economic and effective method for calculating the sound speed and dynamic liquid level depth in the oil production well, and has high practical value. BRIEF DESCRIPTION OF DRAWINGS

[0037] Figure 1 A waveform schematic diagram of the dynamic liquid level echo signal embodiment provided by the present application;

[0038] Figure 2 A flowchart of the well down dynamic liquid level depth automatic picking method based on the AIC model embodiment provided by the present application;

[0039] Figure 3 A schematic diagram of the dynamic liquid level depth embodiment obtained by the picking method of the present embodiment;

[0040] Figure 4 A structural schematic diagram of the well down dynamic liquid level depth automatic picking device based on the AIC model embodiment provided by the present application;

[0041] Figure 5 A structural schematic diagram of the electronic device embodiment provided by the present application. DETAILED DESCRIPTION

[0042] The preferred embodiments of the present application will be specifically described below in conjunction with the accompanying drawings, wherein the drawings form a part of the present application, and are used together with the embodiments of the present application to explain the principles of the present application, but are not used to limit the scope of the present application.

[0043] Before the embodiment description, the inventive concept of the present application is first described.

[0044] At present, the dynamic liquid level monitors of most oil production wells in China are designed based on the sound wave method. However, the oil production well dynamic liquid level monitors designed based on the sound wave method have the problems of low safety, small measurement depth range, low measurement accuracy and poor real-time performance.

[0045] Compared with the sound wave (20Hz-20kHz) that can be sensed by human ears, the frequency of infrasound is usually low, and the sound wave with the frequency of 0-20Hz is generally referred to as infrasound. Infrasound has the advantages of long propagation distance and strong penetration. In the downhole echo signal, infrasound often becomes the main component of the coupling echo signal and the liquid surface echo signal due to the advantages of small attenuation and long propagation distance.

[0046] As shown in Figure 1 , the liquid surface echo signal generally includes a detonation wave, a coupling echo and a liquid surface echo. As can be seen from the curve of Figure 1 , the amplitude of the detonation wave is much larger than that of other places. In theory, since the length of each section of the oil pipe is equal, the coupling echo signal presents a periodic characteristic, which also provides a reliable solution for the extraction of the downhole sound velocity.

[0047] With the increase of the propagation distance, the amplitude of the signal gradually decreases, but the liquid surface echo is larger than the amplitude of the adjacent signal and has a low frequency. Due to the complex downhole working conditions, the signal is affected by environmental noise and has many burrs, and the characteristic recognition of the signal is difficult.

[0048] In addition, it can be found that with the increase of the depth, the relatively high-frequency signal gradually attenuates in the propagation process, the low-frequency infrasound has strong penetration and long propagation distance, and can reach the position of the liquid surface and generate the liquid surface echo signal. After a large amount of analysis and verification, the frequency of the coupling echo and the liquid surface echo is less than 20Hz. This also proves the advantages of the long propagation distance and strong penetration of infrasound, and it is reasonable to use infrasound as a sound source for monitoring the depth of the oil well liquid level.

[0049] The present application is based on the advantages of long propagation distance and strong penetration of infrasound, uses an electrically controlled piston type acoustic emission method to excite infrasound, so that the structure of the wellhead acoustic emission device is simple and stable, the safety factor is high, and the long-distance detection of acoustic waves can be realized; a simple mechanical structure, a lower-cost embedded design and a programming technology are used to realize a low-cost system architecture; automatic data acquisition and transmission are realized; a more powerful signal processing algorithm model is used to improve the accuracy of the calculation of various parameters of the downhole liquid level; in addition, the calculation results are stored and displayed in real time, and the problem of poor real-time performance of the system is solved.

[0050] An automatic picking method for the downhole liquid level depth based on an AIC model is provided, as shown in Figure 2 , the method comprises the following steps.

[0051] Step S101: sending an infrasound signal at the wellhead, and collecting a reflected echo signal after the oil well liquid level;

[0052] Step S102: performing analog-to-digital conversion on the echo signal to obtain a digital echo signal;

[0053] Step S103: performing spectrum processing and signal separation on the digital echo signal to obtain a main frequency of the echo signal and a liquid surface echo signal;

[0054] Step S104: determining a sound wave propagation speed in the oil well according to the main frequency and a preset casing length;

[0055] Step S105: determining a time sequence length value according to a preset liquid surface depth and the sound wave propagation speed;

[0056] Step S106: determining the liquid surface depth of the oil well based on an AIC model, according to the liquid surface echo signal, the sound wave propagation speed and the time sequence length value.

[0057] The method provided by the embodiment can automatically pick up the liquid surface depth of the oil well based on the AIC model. First, the echo signal reflected by the liquid surface of the oil well is collected after a subsonic wave signal is sent, and the echo signal is subjected to digital-to-analog conversion, spectrum processing and signal separation to obtain the main frequency of the echo signal and the liquid surface echo signal. Then, the sound wave propagation speed and the time sequence length value are determined according to the main frequency, the preset casing length and the preset liquid surface depth. Finally, the liquid surface depth of the oil well is obtained according to the liquid surface echo signal, the sound wave propagation speed and the time sequence length value. Compared with the existing liquid surface monitoring method, the method provided by the embodiment is more accurate and faster, and can automatically identify the depth of the liquid surface. The method provides an economic and effective method for calculating the sound speed and the liquid surface depth in the oil well, and has high practical value.

[0058] As a specific embodiment, first, a liquid surface echo instrument is installed at the wellhead of the oil well to collect the echo signal of the downhole reflecting surface in real time, and a subsonic wave signal is excited and sent to the inside of the wellbore. The echo signal of the downhole reflecting surface is subjected to A / D conversion, and the hexadecimal digital signal is sent to the host computer software through the RS232 serial port.

[0059] The RS232 serial port state of the echo instrument and the power-on working state of the echo instrument are detected. The serial port is opened to accept and collect data, and the data is written into a file in real time for storage.

[0060] The subsonic wave is excited by using an electrically controlled piston type acoustic emission method, so that the wellhead acoustic emission device has a simple and stable structure, a high safety factor and can realize long-distance detection of acoustic waves, which has certain engineering significance for the development of subsonic wave detection technology. The system is developed by using low-cost embedded hardware and software to complete automatic collection and transmission of data.

[0061] As a preferred embodiment, the spectrum processing on the digital echo signal to obtain the main frequency of the echo signal comprises:

[0062] performing Fourier transform on the digital echo signal to decompose the digital echo signal into signals of different frequency components and determine a main frequency of the digital echo signal.

[0063] As a preferred embodiment, performing signal separation on the digital echo signal to obtain a liquid surface echo signal of the echo signal comprises:

[0064] Separating the liquid surface echo signal and the collar echo signal from the signals of different frequency components by dynamically setting a passband of a filter.

[0065] As a specific embodiment, performing Fourier transform on the collected downhole echo signal (time domain signal) to extract the liquid surface echo with a band-pass filter (0 to 10 Hz) and extract the collar echo with a band-pass filter (10 to 20 Hz).

[0066] A periodic signal can be expanded by Fourier expansion formula, and the specific formula is:

[0067]

[0068]

[0069] After expansion, it can be decomposed into the superposition of a direct current component, a fundamental wave component and other high harmonic components, and such decomposition is conducive to analyzing different frequency components in the signal to obtain the frequency spectrum of the original signal and thus separate the signals of different frequency components. Through Fourier transform, the main frequency f0 of the collected signal can be obtained.

[0070] The passband of the band-pass filter is dynamically set in the program, and the liquid surface wave can be set at 0 to 10 Hz in the initialization process. The passband of the filter can be adjusted according to the actual downhole condition to obtain the original signal of the liquid surface wave. For example, when the actual well depth of the oil production well is 1000 to 2500 meters, the passband of the band-pass filter can be set at 5 to 15 Hz. When the well depth is 500 to 1000 meters, the passband of the band-pass filter can be set at 0 to 10 Hz. When the well depth exceeds 2500 meters, the passband of the band-pass filter can be set at 0 to 20 Hz. At the same time, the passband of the collar wave is set at 10 to 20 Hz in the program, and the original signal of the collar wave is obtained after filtering.

[0071] As a preferred embodiment, determining the sound wave propagation speed in the oil well according to the main frequency and a preset casing length comprises:

[0072] The sound wave propagation speed is calculated according to the formula v = 2L0f0.

[0073] Wherein, L0 is the preset casing length, f0 is the main frequency of the echo signal, and v is the sound wave propagation speed.

[0074] In the actual downhole echo signal acquisition process, the data quantity is large, which will inevitably affect the accuracy of subsequent AIC model processing and the time delay of liquid level depth calculation. The preset liquid level depth H0 is added to effectively process the original acquisition signal, so as to reduce the calculation amount of data processing and improve the accuracy of the AIC model. The appropriate data length is selected to make the liquid level echo located in the effective range.

[0075] As a preferred embodiment, the time sequence length value is determined according to the preset liquid level depth and the sound wave propagation speed, comprising:

[0076] The time sequence length value is determined according to the formula T0=H0 / 2v and N=T0f0;

[0077] Wherein, N is the time sequence length value, H0 is the preset liquid level depth, v is the sound wave propagation speed, and f0 is the main frequency of the echo signal.

[0078] As a preferred embodiment, based on the AIC model, the liquid level depth of the oil well is determined according to the liquid level echo signal, the sound wave propagation speed and the time sequence length value, comprising:

[0079] The liquid level echo signal of 0 to 10 Hz is processed by the AIC model,

[0080] The formula is substituted The liquid level echo time t is determined by processing;

[0081] The liquid level depth H of the oil well is determined by the formula H=vt / 2 according to the liquid level echo time t and the sound wave propagation speed v;

[0082] Wherein, k is the data sampling point in the window range, x(i)(i=1, 2, 3,…N) is the amplitude of the waveform data point in the window, var is the variance calculation function, CF is the characteristic function of the signal, and N is the length of the signal.

[0083] The non-stationary signal of the AIC model is divided into several independent stationary parts, each part establishes an AIC model and is processed by autoregression, and the two statistical time periods before and after the sound wave are determined by the autoregression process. The division limit of the two time periods is the liquid level echo time t of the wave.

[0084] As shown in Figure 3 , it is a schematic diagram of the liquid level depth obtained by the method of the embodiment. Figure 3

[0085] The embodiment also provides an automatic picking device 400 for downhole liquid level depth based on the AIC model, and a structural block diagram thereof is shown in Figure 4 , comprising:

[0086] ​The signal acquisition module 401 is configured to send an infrasound wave signal at a well mouth and collect an echo signal reflected by a liquid level in the oil well.

[0087] The digital-analog conversion module 402 is configured to perform analog-digital conversion on the echo signal to obtain a digital echo signal.

[0088] The extraction module 403 is configured to perform spectrum processing and signal separation on the digital echo signal to obtain a main frequency of the echo signal and a liquid level echo signal.

[0089] The sound velocity calculation module 404 is configured to determine a sound wave propagation speed in the oil well according to the main frequency and a preset casing length.

[0090] The time determination module 405 is configured to determine a time sequence length value according to a preset liquid level depth and the sound wave propagation speed.

[0091] The liquid level depth calculation module 406 is configured to determine a liquid level depth of the oil well based on an AIC model, according to the liquid level echo signal, the sound wave propagation speed and the time sequence length value.

[0092] As shown in Figure 5 The electronic device 500 can be a mobile terminal, a desktop computer, a notebook computer, a palm computer, a server or the like. The electronic device 500 includes a processor 501, a memory 502 and a display 503.

[0093] The memory 502 can be an internal storage unit of the computer device, for example, a hard disk or a memory of the computer device. The memory 502 can also be an external storage device of the computer device, for example, a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card or the like. Further, the memory 502 can include both the internal storage unit and the external storage device. The memory 502 is configured to store application software and various data installed in the computer device, for example, program codes. The memory 502 can also be configured to temporarily store data that has been output or will be output. In an embodiment, the memory 502 stores a program 504 of a method for automatically picking up a downhole liquid level depth based on an AIC model. The program 504 can be executed by the processor 501, so that the method for automatically picking up a downhole liquid level depth based on an AIC model is realized.

[0094] The processor 501 may be a central processing unit (CPU), a microprocessor, or other data processing chip in some embodiments, for running program codes stored in the memory 502 or processing data, such as executing an AIC model-based automatic picking of downhole dynamic liquid level depth method.

[0095] The display 503 may be an LED display, a liquid crystal display, a touch liquid crystal display, an OLED (Organic Light-Emitting Diode) touch, or the like in some embodiments. The display 503 is used to display information of the computer device and to display a visualized user interface. The components 501-503 of the computer device communicate with each other through a system bus.

[0096] The embodiment also provides a computer readable storage medium having a computer program stored thereon, and the computer program is executed by a processor to implement the AIC model-based automatic picking of downhole dynamic liquid level depth method according to any of the above technical solutions.

[0097] The computer readable storage medium and the computer device according to the above embodiments of the present application can be implemented according to the content described in the AIC model-based automatic picking of downhole dynamic liquid level depth method, and have similar beneficial effects to the AIC model-based automatic picking of downhole dynamic liquid level depth method, which will not be described here.

[0098] The present application provides a simple and stable acoustic wave transmitter with high safety based on the advantages of infrasound wave propagation distance and strong penetration, realizes long-distance detection of acoustic waves, and has certain engineering significance for the development of infrasound detection technology; the system is developed by using low-cost embedded hardware and software to complete automatic data acquisition and transmission, and the downhole sound velocity and liquid surface echo position are accurately calculated through powerful signal processing algorithms; the real-time parameter display and data backup of the upper computer also provide basis for the analysis of formation liquid supply capacity and the formulation of oilfield work system in the later stage. It has great engineering significance and market promotion value for oil well detection.

[0099] The above description is only a preferred embodiment of the present application, but the protection scope of the present application is not limited thereto, and any person skilled in the art can easily think of changes or replacements within the technical range disclosed by the present application, which should be covered within the protection scope of the present application.

Claims

1. A method for automatically picking up downhole dynamic fluid level depth based on the AIC model, characterized in that, include: The infrasound signal is sent at the wellhead, and the echo signal after being reflected by the dynamic fluid surface of the oil well is collected. The echo signal is converted from analog to digital to obtain a digital echo signal; The digital echo signal is subjected to spectrum processing and signal separation to obtain the main frequency of the echo signal and the liquid surface echo signal; The digital echo signal is subjected to spectral processing to obtain the dominant frequency of the echo signal, including: Perform a Fourier transform on the digital echo signal to decompose it into signals with different frequency components, and determine the dominant frequency of the digital echo signal. The digital echo signal is subjected to signal separation to obtain the liquid surface echo signal of the echo signal, including: By dynamically setting the passband of the filter, the liquid surface echo signal and the coupling signal are separated from the signals of different frequency components; The propagation speed of sound waves in the oil well is determined based on the dominant frequency and the preset casing length. Determining the time series length value based on the preset liquid level depth and the sound wave propagation speed includes: According to the formula = / 2 and = Determine the length of the time series; in, This represents the length of the time series. To preset the liquid level depth, For the speed of sound wave propagation, The dominant frequency of the echo signal; Based on the AIC model, the dynamic fluid level depth of the oil well is determined according to the fluid surface echo signal and the time series length value, including: Substitute the liquid surface echo signal into the formula Determine the liquid surface echo time t; Based on the liquid surface echo time t and the sound wave propagation speed Through the formula H= t / 2, determine the dynamic fluid level depth H of the oil well; Where k represents the number of data sampling points within the window range. var is the amplitude of the waveform data points within the window, CF is the variance calculation function, N is the characteristic function of the signal, and N is the length of the signal.

2. The method for automatically picking up downhole dynamic fluid level depth based on the AIC model according to claim 1, characterized in that, Determining the sound wave propagation velocity in the oil well based on the dominant frequency and the preset casing length includes: According to the formula Calculate the speed of sound propagation; in, For the preset sleeve length, The dominant frequency of the echo signal. This refers to the speed of sound wave propagation.

3. An automatic downhole dynamic fluid level depth acquisition device based on the AIC model, characterized in that, include: The signal acquisition module is used to send infrasound signals through the wellhead and collect the echo signals reflected by the dynamic fluid surface of the oil well. A digital-to-analog converter module is used to perform analog-to-digital conversion on the echo signal to obtain a digital echo signal; The extraction module is used to perform spectrum processing and signal separation on the digital echo signal to obtain the main frequency of the echo signal and the liquid surface echo signal; The digital echo signal is subjected to spectral processing to obtain the dominant frequency of the echo signal, including: Perform a Fourier transform on the digital echo signal to decompose it into signals with different frequency components, and determine the dominant frequency of the digital echo signal. The digital echo signal is subjected to signal separation to obtain the liquid surface echo signal of the echo signal, including: By dynamically setting the passband of the filter, the liquid surface echo signal and the coupling signal are separated from the signals of different frequency components; The sound velocity calculation module is used to determine the sound wave propagation velocity in the oil well based on the dominant frequency and the preset casing length. The time determination module is used to determine the time series length value based on the preset liquid level depth and the sound wave propagation speed, including: According to the formula = / 2 and = Determine the length of the time series; in, This represents the length of the time series. To preset the liquid level depth, For the speed of sound wave propagation, The dominant frequency of the echo signal; The fluid level depth calculation module is used to determine the dynamic fluid level depth of the oil well based on the AIC model, according to the fluid level echo signal, the sound wave propagation velocity, and the time series length value, including: Substitute the liquid surface echo signal into the formula Determine the liquid surface echo time t; Based on the liquid surface echo time t and the sound wave propagation speed Through the formula H= t / 2, determine the dynamic fluid level depth H of the oil well; Where k represents the number of data sampling points within the window range. var is the amplitude of the waveform data points within the window, CF is the variance calculation function, N is the characteristic function of the signal, and N is the length of the signal.

4. An electronic device, characterized in that, It includes a processor and a memory, wherein the memory stores a computer program, and when the computer program is executed by the processor, it implements the automatic downhole dynamic fluid level depth picking method based on the AIC model as described in any one of claims 1-2.

5. A computer-readable storage medium, characterized in that, It stores a computer program, which, when executed by a processor, implements the automatic downhole dynamic fluid level depth picking method based on the AIC model as described in any one of claims 1-2.

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