A signal transmission monitoring control system and method in a drill pipe based on artificial intelligence

Abstract

The present application relates to the field of signal transmission monitoring, and in particular to a signal transmission monitoring control system and method in a drill pipe based on artificial intelligence, the method comprising: obtaining basic signal waves of different rock formations, and setting corresponding error response values ​​for the basic signal waves; obtaining real-time signal waves in the drill pipe, and using the basic signal waves to identify noise signals in the real-time signal waves to complete the monitoring of the real-time signal waves. The present application improves the recognition accuracy of noise signals.

Description

Technical Field

[0001] The present application relates to the field of signal transmission monitoring, and in particular to an artificial intelligence-based signal transmission monitoring control system and method within a drill pipe. Background Art

[0002] Drill pipe is a steel pipe with a threaded tail, which is used to connect the surface equipment of the drilling rig and the drilling and grinding equipment or bottom hole device at the bottom of the well. The purpose of the drill pipe is to transport drilling mud to the drill bit and raise, lower or rotate the bottom hole device together with the drill bit. The drill pipe must be able to withstand huge internal and external pressure, twisting, bending and vibration. During the operation of the drill pipe, it is necessary to accurately measure the trajectory of the drilling hole and transmit the data measured at the drill bit end to the hole mouth equipment.

[0003] Rock formations of different hardness exert different reaction forces on the drill bit, causing the vibration frequency of the drill bit to change. Rock formations of different hardness will also affect the flow characteristics of the drilling mud, such as flow rate and pressure, which in turn affects the transmission of signals in the drill pipe. The strong vibrations generated when the drill bit and drill pipe pass through hard rock formations may generate additional noise signals, which will be superimposed on useful signals and cause signal interference.

[0004] The Chinese patent application document with publication number CN115310496A discloses a signal denoising method, device, equipment and storage medium based on a neural network. The method includes: according to the data signal in a preset time period, based on a preset neural network model, determining the extended signal of the data signal; the extended signal includes at least two signal points before the preset time period and at least two signal points after the preset time period, at least two of the signal points before the preset time period have extreme value points, and at least two of the signal points after the preset time period have extreme value points; combining the data signal and the extended signal to obtain a target signal; performing collective empirical mode decomposition on the target signal, and denoising the decomposed target signal to obtain a denoised signal of the target signal; according to the denoised signal of the target signal, obtaining a denoised signal of the data signal.

[0005] From the above scheme, it can be seen that the neural network model can be used to identify the noise signal of the drill pipe. Due to the uncertainty of the training samples, the trained neural network will amplify the noise signal when identifying the noise signal, resulting in low accuracy of the neural network model in identifying the noise signal. Summary of the invention

[0006] In order to improve the accuracy of identifying noise signals, the present application provides an artificial intelligence-based signal transmission monitoring and control system and method within a drill pipe.

[0007] In the first aspect, the present application provides a method for monitoring and controlling signal transmission in a drill pipe based on artificial intelligence, which adopts the following technical solutions:

[0008] A method for monitoring and controlling signal transmission in a drill pipe based on artificial intelligence comprises the following steps:

[0009] Obtaining basic signal waves of different rock formations, and setting corresponding error response values ​​for the basic signal waves;

[0010] Acquire the real-time signal wave in the drill pipe, and use the basic signal wave to identify the noise signal in the real-time signal wave to complete the monitoring of the real-time signal wave;

[0011] Among them, the method of using the basic signal wave to identify the noise signal is:

[0012] The area enclosed by the basic signal wave and the real-time signal wave is taken as the distinguishing value, the basic signal wave slides in sequence along the time direction of the real-time signal wave to obtain multiple distinguishing values, and the distinguishing value sequence is constructed using the obtained distinguishing values;

[0013] The data points in the difference value sequence that are greater than the error response value are recorded as null value points, and the difference value sequence is divided into multiple subsequences using the null value points;

[0014] The eigenvalue of each subsequence is calculated. The eigenvalue is positively correlated with the ratio of the minimum value to the maximum value in the subsequence. The eigenvalues ​​of subsequences at the same position in multiple distinguishing value sequences are compared. The subsequence corresponding to the maximum value is taken as the optimal subsequence, and multiple optimal subsequences are obtained. In response to the time interval between two optimal subsequences on the time axis, the real-time signal wave corresponding to the time interval is taken as the noise signal.

[0015] The effect is that a distinction value sequence is constructed by calculating the distinction value, the distinction value sequence is divided into multiple subsequences to obtain an optimal subsequence, and noise signals are identified based on whether there is a time interval between the optimal subsequences, thereby improving the recognition accuracy of noise signals.

[0016] Preferably, the method for obtaining the basic signal waves of different rock formations is:

[0017] A signal wave database of the corresponding rock formation is constructed using multiple signal waves of each rock formation, the characteristic degree of each signal wave in the signal wave database is calculated, and the multiple characteristic degrees obtained are sorted to obtain a characteristic degree sequence; the characteristic degree sequence is divided into two sequences, one of the sequences is taken as the optimal sequence, and the signal wave corresponding to the maximum value in the optimal sequence is taken as the basic signal wave of the corresponding rock formation.

[0018] The effect is that by calculating the characteristic degree of the signal wave, a basic signal wave is obtained according to the characteristic degree, and the basic signal wave is an ideal signal wave for the corresponding rock formation, thereby improving the accuracy of calculating the distinction value.

[0019] Preferably, the expression of the characteristic degree is:

[0020] ;

[0021] In the formula, is the characteristic degree of the kth signal wave in the signal wave database, is the amplitude extreme value sequence corresponding to the kth signal wave in the signal wave database, is the amplitude extreme value sequence corresponding to the i-th signal wave in the signal wave database, is the time difference sequence corresponding to the kth signal wave in the signal wave database, is the time difference sequence corresponding to the i-th signal wave in the signal wave database, PPMCC is the Pearson correlation coefficient, ∑ is the summation symbol, and j is the total number of signal waves in the signal wave database.

[0022] The effect is that the characteristic degree of the signal wave can be accurately calculated through the above formula, and the accuracy of calculating the characteristic degree is improved by introducing two elements, the amplitude of the signal wave and the time difference sequence.

[0023] Preferably, the error response value is calculated as follows:

[0024] The difference value between the basic signal wave and each other signal wave in the signal wave database is calculated, and the maximum value among the difference values ​​is taken as the error response value of the basic signal wave.

[0025] Preferably, the characteristic degree sequence is divided into two sequences, and a method of taking one of the sequences as the optimal sequence is:

[0026] Calculate the split coefficient. The expression of the split coefficient is:

[0027] ;

[0028] In the formula, is the division coefficient, is the first part of the characteristic degree sequence, is the second part of the characteristic degree sequence, is the standard deviation function, is the hyperbolic tangent function;

[0029] When the split coefficient is the minimum value, the first part and the second part of the characteristic degree sequence are taken as two sequences;

[0030] The sequence with the larger mean value of characteristic degree is taken as the optimal sequence.

[0031] The effect is that the characteristic degree can be divided into two sequences through the division coefficient, which makes it easier to obtain the optimal sequence and improves the accuracy of obtaining the optimal sequence.

[0032] Preferably, the expression of the eigenvalue of the subsequence is:

[0033] ;

[0034] In the formula, Indicates The eigenvalues ​​of the subsequences, Indicates the number of data in the bth subsequence of the distinction value sequence corresponding to the basic signal wave, Represents the set of data numbers of the b-th subsequence in the distinguishing value sequence corresponding to each basic signal wave, , They respectively represent the maximum value and minimum value in the bth subsequence of the distinction value sequence corresponding to the basic signal wave.

[0035] Preferably, the expression of the eigenvalue of the subsequence is:

[0036] ;

[0037] In the formula, Indicates The eigenvalues ​​of the subsequences, , They respectively represent the maximum value and minimum value in the bth subsequence of the distinction value sequence corresponding to the basic signal wave.

[0038] In the second aspect, the present application provides an artificial intelligence-based signal transmission monitoring and control system in a drill pipe, which adopts the following technical solutions:

[0039] A drill rod internal signal transmission monitoring and control system based on artificial intelligence comprises: a processor and a memory, wherein the memory stores computer program instructions, and when the computer program instructions are executed by the processor, the above-mentioned drill rod internal signal transmission monitoring and control method based on artificial intelligence is implemented.

[0040] The effect is that the above-mentioned artificial intelligence-based signal transmission monitoring and control method in the drill pipe is generated into a computer program and stored in the memory so as to be loaded and executed by the processor, thereby making a system based on the memory and the processor for easy use.

[0041] This application has the following technical effects:

[0042] By obtaining the basic signal wave and the error response value, the distinction value is calculated using the basic signal wave and the real-time signal wave to construct a distinction value sequence, the distinction value sequence is divided into multiple subsequences, the characteristic values ​​of the subsequences are calculated to obtain the optimal subsequence, and whether there is a noise signal in the real-time signal wave is determined based on whether there is a time interval between the optimal subsequences, thereby completing the recognition of the noise signal and improving the recognition accuracy of the noise signal. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] By reading the detailed description below with reference to the accompanying drawings, the above and other purposes, features and advantages of the exemplary embodiments of the present application will become easily understood. In the accompanying drawings, several embodiments of the present application are shown in an exemplary and non-restrictive manner, and the same or corresponding numbers represent the same or corresponding parts.

[0044] Figure 1 It is a method flow chart of an artificial intelligence-based signal transmission monitoring control system and method in a drill pipe according to an embodiment of the present application.

[0045] Figure 2 This is a structural block diagram of an artificial intelligence-based signal transmission monitoring and control system in a drill pipe according to an embodiment of the present application. DETAILED DESCRIPTION

[0046] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present application.

[0047] It should be understood that when the terms "first", "second", etc. are used in the claims, specification and drawings of the present application, they are only used to distinguish different objects, rather than to describe a specific order. The terms "include" and "comprise" used in the specification and claims of the present application indicate the presence of the described features, wholes, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components and / or their collections.

[0048] The present application embodiment discloses a signal transmission monitoring and control method in a drill pipe based on artificial intelligence, referring to Figure 1 , including steps S1-S2, which are as follows:

[0049] S1: Obtain basic signal waves of different rock formations and set corresponding error response values ​​for the basic signal waves.

[0050] S11: constructing a signal wave database of the corresponding rock formation using the multiple signal waves of each rock formation.

[0051] Different rock formations have different hardnesses and different reaction forces on the drill bit, which can cause different frequencies and amplitudes of vibrations generated by the drill bit and drill rod when they are working, affecting the stability of the signal wave. In addition, the strong vibrations generated when drilling hard rock formations will produce additional noise signal waves, which are superimposed on useful signal waves and cause signal interference. Therefore, multiple signal waves are collected by conducting experiments on rock formations with different hardnesses to construct a signal wave database. It should be noted that a rock formation with a certain hardness corresponds to a signal wave database, and a signal wave database contains multiple signal waves.

[0052] S12: Calculate the characteristic degree of each signal wave in the signal wave database, and sort the obtained multiple characteristic degrees to obtain a characteristic degree sequence.

[0053] In one embodiment, the expression of the characteristic degree is:

[0054] ;

[0055] In the formula, The signal wave database The characteristic degree of a signal wave, The signal wave database The amplitude extreme value sequence corresponding to the signal wave is The signal wave database The amplitude extreme value sequence corresponding to the signal wave is The signal wave database The time difference sequence corresponding to the signal wave is The signal wave database The time difference sequence corresponding to the signal waves, PPMCC is the Pearson correlation coefficient, ∑ is the summation symbol, and j is the total number of signal waves in the signal wave database. It should be noted that It can also be understood as The peak value corresponding to the signal wave is is the time interval between two adjacent peaks; The signal wave database The peak value of the signal wave, is the time interval between two adjacent peaks. The greater the characteristic degree of the signal wave, the more similar the signal wave is to other signal waves, the more representative it is, and the closest to the ideal rock formation signal wave.

[0056] The characteristic degree of each signal wave in the signal wave database is calculated, and the characteristic degrees of multiple signal waves are sorted in ascending order to obtain a characteristic degree sequence.

[0057] S13: Divide the characteristic degree sequence into two sequences, take one of the sequences as the optimal sequence, and take the signal wave corresponding to the maximum value in the optimal sequence as the basic signal wave of the corresponding rock formation.

[0058] Calculate the split coefficient. The expression of the split coefficient is: ; In the formula, is the division coefficient, is the first part of the characteristic degree sequence, is the second part of the characteristic degree sequence, is the standard deviation function, is a hyperbolic tangent function; when the split coefficient is the minimum value, the first part and the second part of the characteristic degree sequence are taken as two sequences; the sequence with a larger characteristic degree mean is taken as the optimal sequence.

[0059] Exemplarily, the characteristic degree sequence is ( , , …, , …, ), when the first part is ( , , …, ), the second part is ( , …, ) when the value of the division coefficient is the smallest, then calculate ( , , …, )、( , …, ) The mean of the characteristic degree of the two sequences. If the sequence ( , , …, ) has a greater mean characteristic degree than ( , …, ), then ( , , …, ) as the optimal sequence. , , …, It is sorted in order from small to large, so The value of is the largest, then The corresponding signal wave serves as the basic signal wave of the corresponding rock formation, and one rock formation corresponds to one basic signal wave.

[0060] S14: Setting a corresponding error response value for the basic signal wave.

[0061] In one embodiment, the difference values ​​between the basic signal wave and each other signal wave in the signal wave database are calculated, and the maximum value among the difference values ​​is used as the error response value of the basic signal wave.

[0062] The area enclosed by the basic signal wave and any other signal wave is taken as the difference value. The expression of the difference value is: ; Among them, z is the difference between the basic signal wave and other signal waves, is the mapping function of the basic signal wave, is the mapping function of other signal waves in the signal wave database. The larger the difference value, the greater the difference between the two signal waves. Multiple difference values ​​are obtained by calculation, and the maximum value among the difference values ​​is taken as the error response value.

[0063] In one embodiment, the error response value may also be manually set according to actual conditions.

[0064] S2: Acquire the real-time signal wave in the drill pipe, and use the basic signal wave to identify the noise signal in the real-time signal wave to complete the monitoring of the real-time signal wave.

[0065] S21: Construct a sequence of distinguishing values.

[0066] The real-time signal wave in the drill pipe is obtained. At this time, the area enclosed by the basic signal wave and the real-time signal wave is used as the distinction value. The basic signal wave slides in sequence along the time direction of the real-time signal wave to obtain multiple distinction values, and the obtained distinction values ​​are used to construct a distinction value sequence.

[0067] Exemplarily, the real-time signal wave is placed in a two-dimensional coordinate system, where the horizontal coordinate of the coordinate system is time and the vertical coordinate is amplitude. When the basic signal wave is in the initial position, the difference value is calculated once, and then the basic signal wave slides along the horizontal coordinate direction for one time scale, and the difference value at this time is calculated. The basic signal wave slides along the horizontal coordinate direction for multiple time scales, and finally multiple difference values ​​are obtained, and the difference value sequence is constructed using the obtained multiple difference values. It can be understood that one basic signal wave corresponds to one difference value sequence, and one difference value corresponds to one time scale.

[0068] S22: Divide the distinguishing value sequence into multiple subsequences.

[0069] The data points in the difference value sequence that are greater than the error response value are recorded as null value points, and the difference value sequence is divided into multiple subsequences using the null value points. The first item of the first subsequence is the difference value or null value point at the initial moment, and the last item is the null value point. The first item of the last subsequence is the null value point, and the last item is the null value point or difference value. The first item and the last item of the subsequence in the middle are both null value points.

[0070] Exemplarily, the difference value sequence corresponding to one basic signal wave is ( , , , , , , , , , ), where the data points represent Time has come The difference value of the moment, where , , is a null value point, then the subsequence is ( , , , )and( , , , , ).

[0071] S23: Calculate the eigenvalue of each subsequence.

[0072] Calculate the eigenvalue of each subsequence, which is positively correlated with the ratio of the minimum value to the maximum value in the subsequence.

[0073] In one embodiment, the expression of the characteristic value of the subsequence is:

[0074] ;

[0075] In the formula, Indicates The eigenvalues ​​of the subsequences, Indicates the number of data in the bth subsequence of the distinction value sequence corresponding to the basic signal wave, Represents the set of data numbers of the b-th subsequence in the distinguishing value sequence corresponding to each basic signal wave, , They respectively represent the maximum value and minimum value in the bth subsequence of the distinction value sequence corresponding to the basic signal wave.

[0076] In one embodiment, the expression of the characteristic value of the subsequence is:

[0077] ;

[0078] In the formula, Indicates The eigenvalues ​​of the subsequences, , They respectively represent the maximum value and minimum value in the bth subsequence of the distinction value sequence corresponding to the basic signal wave.

[0079] In one embodiment, the expression of the characteristic value of the subsequence is:

[0080] ;

[0081] In the formula, Indicates The eigenvalues ​​of the subsequences, , They represent the maximum and minimum values ​​in the bth subsequence of the distinction value sequence corresponding to the basic signal wave, respectively. Represents the logarithmic function with base e.

[0082] S24: Obtain the optimal subsequence and identify the noise signal.

[0083] The characteristic values ​​of subsequences at the same position in multiple distinguishing value sequences are compared, and the subsequence corresponding to the maximum value is taken as the optimal subsequence to obtain multiple optimal subsequences. In response to the existence of a time interval between two optimal subsequences on the time axis, the real-time signal wave corresponding to the time interval is taken as the noise signal.

[0084] Exemplarily, a subsequence of a distinction value sequence corresponding to a basic signal wave is ( , …, )and( , …, ); The subsequence of the difference value corresponding to the other basic signal wave is ( , …, )and( , …, );in,( , …, )and( , …, ) is the optimal subsequence, then there is a time interval between the two optimal subsequences, the time interval is time, then it will The real-time signal wave corresponding to the moment is used as the noise signal to complete the identification of the noise signal and the monitoring of the real-time signal.

[0085] An embodiment of the present application also discloses an artificial intelligence-based signal transmission monitoring and control system inside a drill rod, comprising a processor and a memory, wherein the memory stores computer program instructions. When the computer program instructions are executed by the processor, an artificial intelligence-based signal transmission monitoring and control method inside a drill rod according to the present application is implemented.

[0086] The above system also includes other components well known to those skilled in the art, such as a communication bus and a communication interface, and their configuration and functions are known in the art, so they will not be described in detail here.

[0087] In the present application, the aforementioned memory may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, apparatus, or device. For example, a computer-readable storage medium may be any appropriate magnetic storage medium or magneto-optical storage medium, such as a resistive random access memory RRAM (Resistive Random Access Memory), a dynamic random access memory DRAM (Dynamic Random Access Memory), a static random access memory SRAM (Static Random Access Memory), an enhanced dynamic random access memory EDRAM (Enhanced Dynamic Random Access Memory), a high bandwidth memory HBM (High Bandwidth Memory), a hybrid memory cube HMC (Hybrid Memory Cube), etc., or any other medium that can be used to store the required information and can be accessed by an application, a module, or both. Any such computer storage medium may be part of a device or accessible or connectable to a device.

[0088] Although this specification has shown and described a plurality of embodiments of the present application, it is obvious to those skilled in the art that such embodiments are provided by way of example only. Those skilled in the art will think of many changes, modifications and alternatives without departing from the thought and spirit of the present application. It should be understood that in the process of practicing the present application, various alternatives to the embodiments of the present application described herein may be adopted.

[0089] The above are all preferred embodiments of the present application, and the protection scope of the present application is not limited thereto. Therefore, any equivalent changes made according to the structure, shape, and principle of the present application should be included in the protection scope of the present application.

Claims

1. A signal transmission monitoring and control method in a drill pipe based on artificial intelligence, characterized in that: Includes steps: Obtaining basic signal waves of different rock formations, and setting corresponding error response values ​​for the basic signal waves; Acquire the real-time signal wave in the drill pipe, and use the basic signal wave to identify the noise signal in the real-time signal wave to complete the monitoring of the real-time signal wave; The method to obtain the basic signal waves of different rock formations is: Using multiple signal waves of each rock layer to construct a signal wave database of the corresponding rock layer, calculating the characteristic degree of each signal wave in the signal wave database, and sorting the obtained multiple characteristic degrees to obtain a characteristic degree sequence; The characteristic degree sequence is divided into two sequences, one of which is taken as the optimal sequence, and the signal wave corresponding to the maximum value in the optimal sequence is taken as the basic signal wave of the corresponding rock formation; The error response value is calculated as: Calculate the difference between the basic signal wave and each other signal wave in the signal wave database, and take the maximum value of the difference values ​​as the error response value of the basic signal wave; Among them, the method of using the basic signal wave to identify the noise signal is: The area enclosed by the basic signal wave and the real-time signal wave is taken as the distinguishing value, the basic signal wave slides in sequence along the time direction of the real-time signal wave to obtain multiple distinguishing values, and the distinguishing value sequence is constructed using the obtained distinguishing values; The data points in the difference value sequence that are greater than the error response value are recorded as null value points, and the difference value sequence is divided into multiple subsequences using the null value points; The eigenvalue of each subsequence is calculated. The eigenvalue is positively correlated with the ratio of the minimum value to the maximum value in the subsequence. The eigenvalues ​​of subsequences at the same position in multiple distinguishing value sequences are compared. The subsequence corresponding to the maximum value is taken as the optimal subsequence, and multiple optimal subsequences are obtained. In response to the time interval between two optimal subsequences on the time axis, the real-time signal wave corresponding to the time interval is taken as the noise signal.

2. The method for monitoring and controlling signal transmission in a drill pipe based on artificial intelligence according to claim 1, characterized in that: The expression of characteristic degree is: ； In the formula, The signal wave database The characteristic degree of a signal wave, The signal wave database The amplitude extreme value sequence corresponding to the signal wave is The signal wave database The amplitude extreme value sequence corresponding to the signal wave is The signal wave database The time difference sequence corresponding to the signal wave is The signal wave database The time difference sequence corresponding to the signal waves, PPMCC is the Pearson correlation coefficient, ∑ is the summation symbol, and j is the total number of signal waves in the signal wave database.

3. The method for monitoring and controlling signal transmission in a drill pipe based on artificial intelligence according to claim 1, characterized in that: The method of dividing the characteristic degree sequence into two sequences and taking one of the sequences as the optimal sequence is: Calculate the split coefficient. The expression of the split coefficient is: ； In the formula, is the division coefficient, is the first part of the characteristic degree sequence, is the second part of the characteristic degree sequence, is the standard deviation function, is the hyperbolic tangent function; When the split coefficient is the minimum value, the first part and the second part of the characteristic degree sequence are taken as two sequences; The sequence with the larger mean value of characteristic degree is taken as the optimal sequence.

4. The method for monitoring and controlling signal transmission in a drill pipe based on artificial intelligence according to claim 1, characterized in that: The expression of the eigenvalue of the subsequence is: ； In the formula, Indicates The eigenvalues ​​of the subsequences, Indicates the number of data in the bth subsequence of the distinction value sequence corresponding to the basic signal wave, Represents the set of data numbers of the b-th subsequence in the distinguishing value sequence corresponding to each basic signal wave, , They respectively represent the maximum value and minimum value in the bth subsequence of the distinction value sequence corresponding to the basic signal wave.

5. The method for monitoring and controlling signal transmission in a drill pipe based on artificial intelligence according to claim 1, characterized in that: The expression of the eigenvalue of the subsequence is: ； In the formula, Indicates The eigenvalues ​​of the subsequences, , They respectively represent the maximum value and minimum value in the bth subsequence of the distinction value sequence corresponding to the basic signal wave.

6. An artificial intelligence-based signal transmission monitoring and control system in a drill pipe, characterized in that: include: A processor and a memory, wherein the memory stores computer program instructions, and when the computer program instructions are executed by the processor, an artificial intelligence-based signal transmission monitoring and control method in a drill pipe is implemented according to any one of claims 1 to 5.

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