Method and apparatus for velocity measurement of a downhole tool string

Abstract

The application relates to the technical field of downhole tool testing, and provides a tool string speed measurement method and equipment. The method comprises the following steps: acquiring acceleration data of a tool string; acquiring instantaneous speed data of the tool string; performing integral calculation on the acceleration data based on stored error correction coefficients to obtain a calculation speed, and outputting the calculation speed as a measurement speed; performing estimation filtering on the instantaneous speed and the calculation speed to obtain new error correction coefficients, updating the stored error correction coefficients to the new error correction coefficients, and using the new error correction coefficients for next integral calculation. The method combines the data of an inertial sensor and a collar pulse signal, dynamically adjusts the error correction coefficients, and improves the speed measurement precision. Not only is continuous speed monitoring provided, but also the error correction coefficients are iteratively optimized, so that high reliability in long-term operation is ensured.

Description

Technical Field

[0001] This invention relates to the field of downhole tool testing technology, and more specifically to a method and device for measuring the speed of a tool string. Background Technology

[0002] Oil and gas wells are typically constructed with casing. Within the casing well, a multi-stage, clustered perforated tool string connected to a bridge plug is delivered via cable. This requires external force, either through pumping or a traction device, to propel the tool string to the target section. Insufficient thrust will prevent the tool string from advancing smoothly in the build-up and horizontal sections; excessive thrust can lead to a sudden increase in wellhead pumping pressure, increasing the risk of dynamic seal failure at the wellhead cable and potentially increasing the risk of the tool string falling into the well or becoming stuck downhole. Therefore, it is crucial to accurately monitor the downhole tool string speed during delivery to ensure the thrust adapts to the varying conditions of different formations within the oil and gas well.

[0003] Currently, most methods in the oil and gas well industry for monitoring the operational status of downhole tool strings indirectly determine the cable slack through surface or downhole load-bearing devices to guide thrust setting. However, these methods suffer from limitations such as low measurement accuracy of the load-bearing devices; furthermore, the increasing weight of the cable as it descends interferes with the device's measurements. Additionally, methods cannot identify situations like jamming or cable accumulation during the cable delivery process. Therefore, existing methods cannot accurately monitor the true speed of the downhole tool string.

[0004] US Patent Application No. US2012 / 046867 discloses a downhole velocity correction system and method. The system utilizes an accelerometer to acquire data and provides this data to a processor. The processor calculates the downhole velocity of a tool train based on the accelerometer data. The processor calculates the average tool velocity over the intervals between the collars. The downhole velocity of the tool train calculated by the processor using the accelerometer data is compared with the average tool velocity calculated by the processor based on time and casing couplings. The processor determines whether the average calculated downhole tool velocity is less than or greater than the velocity of the tool train calculated by the processor using the accelerometer data, determines a correction factor, and determines the corrected downhole tool velocity.

[0005] Chinese patent application CN 107941187 B discloses a downhole tool string multi-parameter recorder, which uses separate radial and axial data acquisition devices to generate two complete sets of measurement data during the downhole and outhole processes of the downhole tool string. However, it does not disclose how to monitor the actual speed of the downhole tool string.

[0006] The paper "Research on Downhole Engineering Parameter Measurement Technology" studied the measurement of downhole drilling engineering parameters. It used a measurement system composed of downhole sensors, signal conditioning circuits, single-chip computers, memory and high-energy batteries to measure drilling engineering parameters. However, the paper did not describe how to accurately monitor the actual speed of the downhole tool string.

[0007] In conclusion, accurately monitoring the true speed of the downhole tool string is a problem that needs to be solved. Summary of the Invention

[0008] In view of this, embodiments of this application provide a method and apparatus for measuring the speed of a tool string, which can accurately monitor the true speed of the downhole tool string.

[0009] The first aspect of this application provides a method for measuring the velocity of a downhole tool string, including:

[0010] Obtain the acceleration data of the tool string;

[0011] Obtain the instantaneous velocity data of the tool string;

[0012] The acceleration data is integrated based on the stored error correction coefficients to obtain the calculated velocity, and the calculated velocity is output as the measured velocity.

[0013] The instantaneous velocity and the calculated velocity are estimated and filtered to obtain new error correction coefficients. The stored error correction coefficients are then updated to the new error correction coefficients and used for the next integration calculation.

[0014] This application embodiment acquires acceleration and instantaneous velocity data and performs integral calculations based on stored error correction coefficients to accurately estimate the velocity of a toolchain in real time. This method combines data from inertial sensors and clamp pulse signals, dynamically adjusting the error correction coefficients to improve the accuracy of velocity measurement. This integrated approach not only provides continuous velocity monitoring but also ensures high reliability during long-term operation through iterative optimization of the error correction coefficients.

[0015] In one embodiment, acquiring the instantaneous speed data of the toolchain includes:

[0016] Generate coupling pulse signal;

[0017] The pulse signal was identified and determined to be a coupling pulse signal;

[0018] When the signal is identified as a coupling pulse signal, the coupling pulse signal is accumulated.

[0019] The coupling serial number is determined based on the cumulative values;

[0020] Based on the coupling serial number, the pre-stored oil and gas well parameter table is searched to obtain the coupling length information;

[0021] The instantaneous velocity data is calculated based on the coupling length information.

[0022] This embodiment generates and identifies valid coupling pulse signals, accumulates the signals to determine the coupling sequence number, and finally retrieves instantaneous velocity data from a pre-stored oil and gas well parameter table. By utilizing a fixed downhole coupling as a reference point, the instantaneous velocity measurement becomes more accurate and reliable. This method reduces the accumulated error caused by relying solely on accelerometers, improving the overall accuracy of velocity measurement.

[0023] In one embodiment, generating the coupling pulse signal includes:

[0024] While the tool string is moving, it senses the coupling and generates a coupling pulse signal.

[0025] This application embodiment senses the coupling and generates a coupling pulse signal while the tool string is moving. This method utilizes existing downhole structural features (i.e., the coupling) as a reference point for velocity measurement. This not only reduces reliance on external equipment but also improves the system's robustness and adaptability. Furthermore, by generating a pulse signal through sensing the coupling, high-precision velocity measurement can be achieved without the need for additional complex equipment.

[0026] In one embodiment, identifying the pulse signal as a coupling pulse signal includes:

[0027] Waiting for the sudden edge of the pulse signal;

[0028] When a sudden change in the pulse signal is detected and its amplitude meets the preset value, the first peak recognition state is entered.

[0029] In the first peak identification state, if the second derivative of the pulse signal undergoes a sudden change, and the peak value of the sudden change satisfies the first preset peak value, then the second peak identification state is entered.

[0030] In the second peak identification state, if the second derivative of the pulse signal undergoes a sudden change, and the peak value of the sudden change satisfies the second preset peak value, then the third peak identification state is entered.

[0031] If the peak value identified in the first peak recognition state and the peak value identified in the third peak recognition state are both peaks or troughs, then the pulse signal is determined to be a coupling pulse signal.

[0032] This application employs a multi-stage state machine recognition algorithm, from waiting for the abrupt edge to detecting changes in the second derivative, ultimately confirming the valid coupling pulse signal. This method effectively eliminates interference signals, ensuring that only signals conforming to a specific pattern are identified as coupling pulses. This multi-level verification mechanism improves the accuracy of signal recognition, thereby guaranteeing the reliability of instantaneous velocity data.

[0033] In one embodiment, the step of estimating and filtering the instantaneous velocity and the calculated velocity to obtain new error correction coefficients includes:

[0034] Calculate the error between the instantaneous velocity and the calculated velocity;

[0035] The error propagation coefficient is adjusted according to the error propagation equation using the gradient descent method to minimize the error.

[0036] The error propagation coefficient corresponding to minimizing the error is used as the new error correction coefficient.

[0037] This application's embodiments minimize the error by calculating the error between the instantaneous velocity and the calculated velocity, and by adjusting the error propagation coefficient using the gradient descent method. This method iteratively optimizes the error correction coefficient, gradually reducing systematic errors in velocity measurement. This adaptive adjustment mechanism continuously improves the accuracy of velocity measurement over long-term operation, ensuring the stability and reliability of the system.

[0038] In one embodiment, after acquiring the acceleration data of the toolchain, the method further includes:

[0039] The acceleration data is filtered, and the normalized cutoff frequency of the filter is 0.25, with a stopband gain of less than 80dB.

[0040] This embodiment of the application filters the acceleration data, with a cutoff frequency normalization value of 0.25 and a stopband gain of less than 80dB. This filtering setting effectively removes high-frequency noise and retains low-frequency motion signals, thereby improving the quality of the acceleration data, ensuring the accuracy of the integral calculation speed, and contributing to improving the overall speed measurement accuracy.

[0041] A second aspect of this application provides a velocity measurement device for a downhole tool string, comprising:

[0042] The acceleration detection module is used to acquire acceleration data of the toolchain;

[0043] The data processing module is used to acquire the instantaneous speed data of the toolchain;

[0044] The acceleration data is integrated based on the stored error correction coefficients to obtain the calculated velocity, and the calculated velocity is output as the measured velocity.

[0045] The instantaneous velocity and the calculated velocity are estimated and filtered to obtain new error correction coefficients. The stored error correction coefficients are then updated to the new error correction coefficients and used for the next integration calculation.

[0046] In one embodiment, a magnetic induction device is further included, the magnetic induction device being used to generate a coupling pulse signal;

[0047] The data processing module is also used to identify the pulse signal and determine it as a coupling pulse signal;

[0048] When the signal is identified as a coupling pulse signal, the coupling pulse signal is accumulated.

[0049] The coupling serial number is determined based on the cumulative values;

[0050] Based on the coupling serial number, the pre-stored oil and gas well parameter table is searched to obtain the coupling length information;

[0051] The instantaneous velocity data is calculated based on the coupling length information.

[0052] In one embodiment, the data processing module is further configured to:

[0053] Calculate the error between the instantaneous velocity and the calculated velocity;

[0054] The error propagation coefficient is adjusted according to the error propagation equation using the gradient descent method to minimize the error.

[0055] The error propagation coefficient corresponding to minimizing the error is used as the new error correction coefficient.

[0056] In one embodiment, the system further includes a data storage module, which is connected to the data processing module.

[0057] The data storage module is used to store oil and gas well parameter tables.

[0058] The data storage module in this embodiment is used to store oil and gas well parameter tables. By pre-storing these parameters, the device can quickly access the required data after initialization, simplifying the operation process. Furthermore, the design of the data storage module ensures that data is not lost even in the event of a power outage, improving the system's reliability and portability.

[0059] In one embodiment, the system further includes a data acquisition module, the input of which is connected to the magnetic induction device and the output of which is connected to the data processing module.

[0060] The acquisition module is used to convert the clamp pulse signal generated by the magnetic induction device into a digital signal and send it to the data processing module.

[0061] In one embodiment, a communication module for communicating with the ground is also included. The communication module is connected to the data processing module. The acceleration detection module, the data processing module, the magnetic induction device, and the communication module are disposed within a housing located downhole.

[0062] The communication module in this embodiment is used to communicate with the surface, ensuring data exchange between the downhole equipment and the surface control system. This communication function not only supports real-time monitoring and remote control, but also facilitates data recording and analysis. Through a reliable communication connection, surface operators can obtain the status information of the downhole tool string in a timely manner, thereby making more accurate operational decisions and improving the safety and efficiency of operations.

[0063] A third aspect of this application provides a computer program product including a computer program that, when run, causes the method described in the first aspect of this application to be performed.

[0064] The first aspect of this application provides a method for measuring the velocity of a downhole tool string. This method involves acquiring acceleration data of the tool string; acquiring instantaneous velocity data of the tool string; integrating the acceleration data based on stored error correction coefficients to obtain a calculated velocity, and outputting the calculated velocity as the measured velocity; estimating and filtering the instantaneous velocity and the calculated velocity to obtain new error correction coefficients; updating the stored error correction coefficients with the new error correction coefficients; and using these new error correction coefficients for the next integration calculation. By combining data from an inertial sensor and coupling pulse signals, and dynamically adjusting the error correction coefficients, the accuracy of velocity measurement is improved. This integrated method not only provides continuous velocity monitoring but also ensures high reliability during long-term operation through iterative optimization of the error correction coefficients.

[0065] It is understood that the beneficial effects of the second and third aspects mentioned above can be found in the relevant descriptions in the first aspect mentioned above, and will not be repeated here. Attached Figure Description

[0066] To more clearly illustrate the technical solutions in the embodiments of this application, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0067] Figure 1 This is a schematic flowchart of a speed measurement method for a toolchain provided in an embodiment of this application;

[0068] Figure 2 This is a schematic flowchart of a speed measurement method for a toolchain provided in another embodiment of this application;

[0069] Figure 3 This is a schematic flowchart of a speed measurement method for a toolchain provided in another embodiment of this application;

[0070] Figure 4 This is a schematic flowchart of a speed measurement method for a toolchain provided in another embodiment of this application;

[0071] Figure 5 This is a schematic flowchart of a speed measurement method for a toolchain provided in another embodiment of this application;

[0072] Figure 6 This is a schematic diagram of the speed measuring device provided in the embodiments of this application. Detailed Implementation

[0073] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of this application. However, those skilled in the art will understand that this application may also be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods have been omitted so as not to obscure the description of this application with unnecessary detail.

[0074] It should be understood that, when used in this application specification and the appended claims, the term "comprising" indicates the presence of the described features, integrals, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or a collection thereof.

[0075] Furthermore, in the description of this application and the appended claims, the terms "first," "second," "third," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0076] References to "one embodiment" or "some embodiments" as described in this specification mean that one or more embodiments of this application include a specific feature, structure, or characteristic described in connection with that embodiment. Therefore, the phrases "in one embodiment," "in some embodiments," "in other embodiments," "in still other embodiments," etc., appearing in different parts of this specification do not necessarily refer to the same embodiment, but rather mean "one or more, but not all, embodiments," unless otherwise specifically emphasized. The terms "comprising," "including," "having," and variations thereof mean "including but not limited to," unless otherwise specifically emphasized.

[0077] Example 1

[0078] like Figure 1 As shown, the speed measurement method for the toolchain provided in this application embodiment includes the following steps S101 to S104:

[0079] Step S101: Obtain the acceleration data of the tool string.

[0080] In applications, the components for acquiring motion acceleration include an inertial accelerometer and a data acquisition and filtering circuit. After the acceleration is acquired, it is filtered to remove disturbances that occurred during the acquisition process.

[0081] In applications, the acquired acceleration data undergoes filtering to remove disturbances introduced during the acquisition process. A Butterworth digital filter can be used, with a cutoff frequency normalization value set to 0.25 and a stopband gain of less than 80dB. This effectively removes high-frequency noise, preserves low-frequency motion signals, and improves the quality of the acceleration data.

[0082] Step S102: Obtain the instantaneous velocity data of the tool string.

[0083] In application, when the tool string moves and passes the casing coupling, the magnetic induction device senses the presence of the coupling and generates a fixed-shape abrupt pulse signal. A state machine-based recognition algorithm identifies the coupling pulse signal. The recognition process includes waiting for the abrupt edge of the pulse signal, detecting changes in the second derivative, and finally confirming a valid coupling pulse signal. After identifying a coupling pulse signal, these pulse signals are accumulated. Based on the accumulated values, the coupling number of the current tool string is determined. According to the determined coupling number, the corresponding instantaneous velocity data is obtained by looking up the pre-stored oil and gas well parameter table in the equipment.

[0084] Step S103: Integrate the acceleration data based on the stored error correction coefficient to obtain the calculated velocity, and output the calculated velocity as the measured velocity.

[0085] In the application, the filtered acceleration data is fed into an integrator, and the tool string's velocity is calculated through integration. The integration process accumulates the acceleration data to obtain the velocity data. During the integration calculation, stored error correction coefficients are used to correct the acceleration data to reduce systematic errors. The calculated velocity data is then output as the measured velocity. This velocity data reflects the real-time motion of the tool string downhole.

[0086] Step S104: Estimate and filter the instantaneous velocity and the calculation velocity to obtain new error correction coefficients, update the stored error correction coefficients with the new error correction coefficients, and use them for the next integration calculation.

[0087] In this application, the error between the instantaneous velocity (obtained from the coupling pulse signal) and the calculated velocity (obtained by integrating acceleration data) is calculated. The error propagation coefficient is adjusted using the gradient descent method according to the error propagation equation to minimize the error. This process is an iterative optimization process, gradually reducing the error through multiple iterations. When the error is minimized, the corresponding error propagation coefficient is used as the new error correction coefficient. The new error correction coefficient overwrites the old one and is stored for the next integration calculation. This ensures that the latest and most accurate error correction coefficient is used in each velocity calculation, thereby improving the accuracy of velocity measurement.

[0088] This application embodiment acquires acceleration and instantaneous velocity data and performs integral calculations based on stored error correction coefficients to accurately estimate the velocity of a toolchain in real time. This method combines data from inertial sensors and clamp pulse signals, dynamically adjusting the error correction coefficients to improve the accuracy of velocity measurement. This integrated approach not only provides continuous velocity monitoring but also ensures high reliability during long-term operation through iterative optimization of the error correction coefficients.

[0089] In one embodiment, such as Figure 2 As shown, step S102 includes the following steps S201 and S205:

[0090] Step S201: Generate coupling pulse signal.

[0091] In applications, the magnetic induction device in the tool string detects the presence of the sleeve coupling as the tool string moves. This induction is based on the principle of electromagnetic induction; when the tool string passes the coupling, the magnetic induction device generates a sudden pulse signal of a fixed shape. This pulse signal has a specific shape and amplitude, which can be used to identify the position of the tool string. In this way, a identifiable signal is generated every time the tool string passes the coupling.

[0092] Step S202: Identify the pulse signal and determine it to be a coupling pulse signal.

[0093] Step S203: When the signal is determined to be a coupling pulse signal, the coupling pulse signal is accumulated.

[0094] In the application, the system accumulates each valid coupling pulse signal it detects. This accumulation process can be accomplished by a counter, which increments by one for each detected valid coupling pulse signal. In addition to simple counting, the system can also record the specific timestamp and other relevant information for each pulse signal for subsequent analysis and processing.

[0095] Step S204: Determine the coupling serial number based on the accumulated values.

[0096] In application, the coupling number of the current tool string can be determined by accumulating the number of pulse signals. For example, if 10 pulse signals are accumulated, it can be inferred that the tool string has passed through 10 couplings. The coupling number corresponds to the specific location of the downhole tool string. Since the distance between each coupling is known, the exact location of the tool string downhole can be calculated using the coupling number.

[0097] Step S205: Based on the coupling serial number, search the pre-stored oil and gas well parameter table to obtain the coupling length information.

[0098] In the application, during the initialization phase, discrete data such as the coupling length of the oil and gas well is written and stored in the device. This data is stored in fixed-point format and is not lost after power failure. Based on the coupling sequence number determined in step S204, the pre-stored oil and gas well parameter table is retrieved. The parameter table contains the sequence number of each coupling and its corresponding coupling length information.

[0099] Step S206: Calculate instantaneous velocity data based on the coupling length information.

[0100] In application, the instantaneous velocity of the tool string when passing through a given coupling can be calculated using the coupling serial number and coupling length information from the parameter table. The instantaneous velocity can be calculated based on the time difference between couplings and the known distance.

[0101] This embodiment generates and identifies valid coupling pulse signals, accumulates the signals to determine the coupling sequence number, and finally retrieves instantaneous velocity data from a pre-stored oil and gas well parameter table. Utilizing a fixed coupling downhole as a reference point makes instantaneous velocity measurement more accurate and reliable. This method reduces accumulated errors caused by relying solely on accelerometers, improving the overall accuracy of velocity measurement. This method can promptly detect downhole jamming and cable accumulation during the cable delivery string process, safely monitoring the actual operating status of the downhole tool string. Based on perforation operation information, this method uses inertial acceleration data to directly calculate the real-time velocity of the current tool string downhole, offering advantages such as high measurement accuracy, intuitive results, and simple structure compared to traditional indirect measurement methods.

[0102] In one embodiment, step S201 includes: sensing the coupling while the tool string is in a moving state to generate a coupling pulse signal.

[0103] In application, couplings are made of metal and are used to connect two casing sections, thereby connecting all the casing in an oil and gas well. The couplings create a discontinuity between the casing sections in the oil and gas well. A magnetic induction device can sense and output a fixed-shape abrupt pulse signal, known as the coupling pulse signal.

[0104] This application embodiment senses the coupling and generates a coupling pulse signal while the tool string is moving. This method utilizes existing downhole structural features (i.e., the coupling) as a reference point for velocity measurement. This not only reduces reliance on external equipment but also improves the system's robustness and adaptability. Furthermore, by generating a pulse signal through sensing the coupling, high-precision velocity measurement can be achieved without the need for additional complex equipment.

[0105] In one embodiment, such as Figure 3 As shown, step S202 includes the following steps S301 and S305:

[0106] Step S301: Wait for the pulse signal to change abruptly.

[0107] In the application, the system is in a standby state, continuously monitoring the pulse signal. The pulse signal abruptly changes edge, that is, the change of the signal from low level to high level (rising edge) or from high level to low level (falling edge).

[0108] Step S302: When a sudden change in the pulse signal is detected and its amplitude meets the preset amplitude, the first peak recognition state is entered.

[0109] In the application, after detecting a sudden change edge, the amplitude of the sudden change edge is further checked to see if it meets a preset threshold requirement. This threshold is to ensure that the signal abrupt change is not caused by noise or other interference. If the amplitude of the sudden change edge meets the preset threshold, the system will enter the first peak recognition state. In this state, the system begins to search for the first significant peak of the pulse signal.

[0110] Step S303: In the first peak recognition state, if the second derivative of the pulse signal undergoes a sudden change and the peak value of the sudden change satisfies the first preset peak value, then enter the second peak recognition state.

[0111] In the application, during the first peak recognition state, the system performs second-order derivative processing on the pulse signal to capture inflection points and extreme points in the signal. Through second-order derivative processing, the system can detect local maxima or minima in the signal. If the detected abrupt peak meets a first preset peak threshold, the system will enter the second peak recognition state.

[0112] Step S304: In the second peak recognition state, if the second derivative of the pulse signal undergoes a sudden change, and the peak value of the sudden change satisfies the second preset peak value, then enter the third peak recognition state.

[0113] In the application, during the second peak recognition state, the system continues to perform second-order derivative processing on the pulse signal to further refine the signal characteristics. Through second-order derivative processing, the system can more accurately locate feature points in the signal. If the detected abrupt peak meets the second preset peak threshold, the system will enter the third peak recognition state.

[0114] Step S305: If the peak value identified in the first peak recognition state and the peak value identified in the third peak recognition state are both peaks or troughs, then the pulse signal is determined to be a coupling pulse signal.

[0115] In the application, during the third peak identification state, the peak value from the first peak identification state is compared with the currently identified peak value. If both peaks are either peaks or both are troughs, then it can be confirmed that this is a coupling pulse signal. This matching mechanism eliminates interference from non-coupling pulse signals.

[0116] This application embodiment employs a multi-stage state machine recognition algorithm, from waiting for the abrupt edge to detecting changes in the second derivative, ultimately confirming the valid coupling pulse signal. This method effectively eliminates interference signals, ensuring that only signals conforming to a specific pattern are identified as coupling pulses. This multi-level verification mechanism improves the accuracy of signal recognition, thereby guaranteeing the reliability of instantaneous velocity data.

[0117] In one embodiment, the instantaneous velocity and the calculated velocity are estimated and filtered to obtain new error correction coefficients, such as... Figure 4 As shown, the steps include S401 to S403 as follows:

[0118] Step S401: Calculate the error between the instantaneous velocity and the calculated velocity.

[0119] In applications, the instantaneous speed is compared with the calculated speed, and the difference between the two is calculated. This difference is the error, representing the deviation between the current calculated speed and the actual speed.

[0120] Step S402: Use the gradient descent method to adjust the error propagation coefficient according to the error propagation equation to minimize the error.

[0121] In applications, the error propagation equation describes how errors propagate in a system and can be used to predict the trend of error changes.

[0122] In applications, gradient descent is used to find local minima of a function. In this process, the gradient (i.e., rate of change) of the current error with respect to the error propagation coefficients is calculated according to the error propagation equation. Gradient descent is then used to progressively adjust the error propagation coefficients, gradually reducing the error after each iteration. The error propagation coefficients are updated in the opposite direction of the error function's gradient until a coefficient value that minimizes the error is found. Through this iterative process, the error is recalculated after each adjustment, and the error propagation coefficients are continuously adjusted until the error converges to a relatively small range.

[0123] Step S403: Use the error propagation coefficient corresponding to minimizing the error as the new error correction coefficient.

[0124] In applications, after the gradient descent method iterates a certain number of times, if the error no longer decreases significantly or reaches a preset threshold, the error can be considered minimized. At this point, the current error propagation coefficient is stored as the new error correction coefficient, replacing the old one. The latest error correction coefficient will be used in the next integration calculation, thereby improving the accuracy of speed measurement. Each effective recognition of the coupling pulse signal triggers this process, continuously optimizing the error correction coefficient and ensuring the long-term stability and accuracy of speed measurement.

[0125] This application's embodiments minimize the error by calculating the error between the instantaneous velocity and the calculated velocity, and by adjusting the error propagation coefficient using the gradient descent method. This method iteratively optimizes the error correction coefficient, gradually reducing systematic errors in velocity measurement. This adaptive adjustment mechanism continuously improves the accuracy of velocity measurement over long-term operation, ensuring the stability and reliability of the system.

[0126] In one embodiment, after acquiring the acceleration data of the toolchain, the method further includes:

[0127] The acceleration data is filtered, with a normalized cutoff frequency of 0.25 and a stopband gain of less than 80dB.

[0128] This embodiment of the application filters the acceleration data, with a cutoff frequency normalization value of 0.25 and a stopband gain of less than 80dB. This filtering setting effectively removes high-frequency noise and retains low-frequency motion signals, thereby improving the quality of the acceleration data, ensuring the accuracy of the integral calculation speed, and contributing to improving the overall speed measurement accuracy.

[0129] In one embodiment, such as Figure 5 As shown, the velocity measurement of the downhole tool string may also include the following steps:

[0130] Step S1: The coupling pulse signal is captured and identified.

[0131] Step S2: Based on the identification results, obtain the instantaneous velocity from the oil and gas well parameter table.

[0132] Step S3: Sample and acquire acceleration data, and then filter the acceleration data.

[0133] Step S4: Filter the acceleration data.

[0134] Step S5: Integrate the filtered acceleration data based on the stored error correction coefficients to obtain the calculated velocity, which is then output as the real-time velocity.

[0135] Step S6: Estimate and filter the instantaneous velocity and calculation speed to obtain new error correction coefficients, update the stored error correction coefficients with the new error correction coefficients, and use them for the next integration calculation.

[0136] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0137] Example 2

[0138] like Figure 6 As shown in the illustration, this application also provides a velocity measurement device for a downhole tool string, comprising:

[0139] Acceleration detection module 101 is used to acquire acceleration data of the tool string;

[0140] Data processing module 102 is used to acquire instantaneous speed data of the tool string;

[0141] The acceleration data is integrated based on the stored error correction coefficients to obtain the calculated velocity, and the calculated velocity is output as the measured velocity.

[0142] The instantaneous velocity and the computational velocity are estimated and filtered to obtain new error correction coefficients. The stored error correction coefficients are then updated to the new error correction coefficients and used for the next integration calculation.

[0143] In applications, the data processing unit can be an embedded processor or other intelligent processor, including high-temperature resistant dedicated programmable logic devices or general-purpose processors that support floating-point accumulation operations.

[0144] The embodiments of this application use a simplified electronic circuit structure, which improves the shock resistance of the perforation, reduces the size, and is reusable, thereby reducing the cost of each use and the overall cost of use. This is economically beneficial for long-term use and maintenance.

[0145] In one embodiment, a magnetic induction device 103 is also included, which is used to generate a coupling pulse signal;

[0146] The data processing module 102 is also used to identify the pulse signal and determine it as a coupling pulse signal;

[0147] When the signal is identified as a coupling pulse signal, the coupling pulse signal is accumulated.

[0148] The coupling serial number is determined based on the cumulative values;

[0149] Based on the coupling serial number, the instantaneous velocity data is obtained by searching the pre-stored oil and gas well parameter table.

[0150] In one embodiment, the data processing module 102 is further configured to:

[0151] Calculate the error between the instantaneous velocity and the calculated velocity;

[0152] The error propagation coefficient is adjusted according to the error propagation equation using the gradient descent method to minimize the error.

[0153] The error propagation coefficient corresponding to minimizing the error is used as the new error correction coefficient.

[0154] In one embodiment, a data storage module 104 is also included, which is connected to the data processing module;

[0155] The data storage module is used to store oil and gas well parameter tables.

[0156] In the application, the external Flash is communicated using the SPI protocol. The oil and gas well parameters are stored in fixed-point format, and the first address of the Flash stores the number of bytes required to store the oil and gas well parameters.

[0157] The data storage module in this embodiment stores oil and gas well parameter tables. By pre-storing these parameters, the device can quickly access the required data after initialization, simplifying the operation process. Furthermore, the design of the data storage module ensures that data is not lost even in the event of a power outage, improving the system's reliability and portability. Oil and gas well parameters for the same well only need to be initialized once and then permanently stored internally, simplifying the operation process and improving operational portability.

[0158] In one embodiment, it further includes a data acquisition module 105, the input end of which is connected to the magnetic induction device 103, and the output end of which is connected to the data processing module 102.

[0159] The acquisition module 105 converts the coupling pulse signal generated by the magnetic induction device 103 into a digital signal and sends it to the data processing module 102. The magnetic induction device 103 is connected to the acquisition module 105 and sends the signal to the data processing unit via an ADC for coupling pulse signal capture and identification.

[0160] In one embodiment, a communication module 106 for communicating with the ground is also included. The communication module 106 is connected to the data processing module 102. The acceleration detection module 101, the data processing module 102, the magnetic induction device 103 and the communication module 106 are disposed inside the housing 100, which is located underground.

[0161] In application, the housing 100 is a metal housing used to provide mechanical protection for the internal modules and to withstand the fluid pressure downhole in oil and gas wells.

[0162] In one embodiment, a power management module 107 is also included for providing a stable voltage power supply to the device.

[0163] The communication module in this embodiment is used to communicate with the surface, ensuring data exchange between the downhole equipment and the surface control system. This communication function not only supports real-time monitoring and remote control, but also facilitates data recording and analysis. Through a reliable communication connection, surface operators can obtain the status information of the downhole tool string in a timely manner, thereby making more accurate operational decisions and improving the safety and efficiency of operations.

[0164] A third aspect of this application provides a computer program product including a computer program that, when run, causes the method described in the first aspect of this application to be performed.

[0165] This application provides a computer program product, including a computer program, which, when run on an electronic device, enables the electronic device to perform the steps described in the various method embodiments above.

[0166] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0167] The above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.

Claims

1. A method for measuring the velocity of a downhole tool string, characterized in that, include: Obtain the acceleration data of the tool string; Obtain the instantaneous velocity data of the tool string; The acceleration data is integrated based on the stored error correction coefficients to obtain the calculated velocity, and the calculated velocity is output as the measured velocity. The instantaneous velocity and the calculated velocity are estimated and filtered to obtain new error correction coefficients. The stored error correction coefficients are then updated to the new error correction coefficients and used for the next integration calculation.

2. The method for measuring the velocity of a downhole tool string according to claim 1, characterized in that, The acquisition of instantaneous speed data of the tool string includes: Generate coupling pulse signal; The pulse signal was identified and determined to be a coupling pulse signal; When the signal is identified as a coupling pulse signal, the coupling pulse signal is accumulated. The coupling serial number is determined based on the cumulative values; Based on the coupling serial number, the pre-stored oil and gas well parameter table is searched to obtain the coupling length information; The instantaneous velocity data is calculated based on the coupling length information.

3. The method for measuring the velocity of a downhole tool string according to claim 2, characterized in that, The generation of the coupling pulse signal includes: While the tool string is moving, it senses the coupling and generates a coupling pulse signal.

4. The method for measuring the velocity of a downhole tool string according to claim 2, characterized in that, The process of identifying the pulse signal and determining it to be a coupling pulse signal includes: Waiting for the sudden edge of the pulse signal; When a sudden change in the pulse signal is detected and its amplitude meets the preset value, the first peak recognition state is entered. In the first peak identification state, if the second derivative of the pulse signal undergoes a sudden change, and the peak value of the sudden change satisfies the first preset peak value, then the second peak identification state is entered. In the second peak identification state, if the second derivative of the pulse signal undergoes a sudden change, and the peak value of the sudden change satisfies the second preset peak value, then the third peak identification state is entered. If the peak value identified in the first peak recognition state and the peak value identified in the third peak recognition state are both peaks or troughs, then the pulse signal is determined to be a coupling pulse signal.

5. The method for measuring the velocity of a downhole tool string according to claim 1, characterized in that, The estimation and filtering of the instantaneous velocity and the calculated velocity to obtain new error correction coefficients includes: Calculate the error between the instantaneous velocity and the calculated velocity; The error propagation coefficient is adjusted according to the error propagation equation using the gradient descent method to minimize the error. The error propagation coefficient corresponding to minimizing the error is used as the new error correction coefficient.

6. The method for measuring the velocity of a downhole tool string according to claim 1, characterized in that, After obtaining the acceleration data of the toolchain, the process further includes: The acceleration data is filtered, and the normalized cutoff frequency of the filter is 0.25, with a stopband gain of less than 80dB.

7. A speed measuring device for a downhole tool string, characterized in that, include: The acceleration detection module is used to acquire acceleration data of the toolchain; The data processing module is used to acquire the instantaneous speed data of the toolchain; The acceleration data is integrated based on the stored error correction coefficients to obtain the calculated velocity, and the calculated velocity is output as the measured velocity. The instantaneous velocity and the calculated velocity are estimated and filtered to obtain new error correction coefficients. The stored error correction coefficients are then updated to the new error correction coefficients and used for the next integration calculation.

8. The downhole tool string velocity measuring device according to claim 7, characterized in that, It also includes a magnetic induction device for generating coupling pulse signals; The data processing module is also used to identify the pulse signal and determine it as a coupling pulse signal; When the signal is identified as a coupling pulse signal, the coupling pulse signal is accumulated. The coupling serial number is determined based on the cumulative values; Based on the coupling serial number, the pre-stored oil and gas well parameter table is searched to obtain the coupling length information; The instantaneous velocity data is calculated based on the coupling length information.

9. The downhole tool string velocity measuring device according to claim 8, characterized in that, The data processing module is also used for: Calculate the error between the instantaneous velocity and the calculated velocity; The error propagation coefficient is adjusted according to the error propagation equation using the gradient descent method to minimize the error. The error propagation coefficient corresponding to minimizing the error is used as the new error correction coefficient.

10. The downhole tool string velocity measuring device according to claim 8, characterized in that, It also includes a data storage module, which is connected to the data processing module; The data storage module is used to store oil and gas well parameter tables.

11. The downhole tool string velocity measuring device according to claim 8, characterized in that, It also includes a data acquisition module, the input end of which is connected to the magnetic induction device, and the output end of which is connected to the data processing module; The acquisition module is used to convert the clamp pulse signal generated by the magnetic induction device into a digital signal and send it to the data processing module.

12. The downhole tool string velocity measuring device according to claim 8, characterized in that, It also includes a communication module for communicating with the ground, the communication module being connected to the data processing module, the acceleration detection module, the data processing module, the magnetic induction device and the communication module being disposed inside a housing, the housing being disposed downhole.

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