CN111368905A

CN111368905A - Signal recovery method and device applied to oil and gas exploration and signal recovery equipment

Info

Publication number: CN111368905A
Application number: CN202010133522.4A
Authority: CN
Inventors: 周红
Original assignee: Individual
Current assignee: Dongying Nujin Petroleum Technology Co.,Ltd.
Priority date: 2020-03-02
Filing date: 2020-03-02
Publication date: 2020-07-03
Anticipated expiration: 2040-03-02
Also published as: CN111368905B; CN112200229A; CN112215274A

Abstract

The invention provides a signal recovery method, a signal recovery device and a signal recovery device applied to oil and gas exploration, which can acquire a first sensing signal sent by a sensor, determine a first environmental parameter at a first target position represented by a signal type corresponding to the first sensing signal and a second environmental parameter on a straight line path from the first target position to a second target position of the signal recovery device from a pre-stored environmental parameter set, determine an attenuation vector when the sensing signal sent from the first target position reaches the second target position, weight the attenuation vector based on the determined first generalization factor and second generalization factor to obtain a second weighting vector so as to realize one-by-one correction of a first feature vector of the first sensing signal, and obtain a second sensing signal based on the second feature vector obtained by one-by-one correction. Therefore, the attenuation condition of the sensing signal can be analyzed based on the environmental parameters in the drilling well so as to recover and trace the source of the sensing signal.

Description

Signal recovery method and device applied to oil and gas exploration and signal recovery equipment

Technical Field

The invention relates to the technical field of signal processing in oil and gas exploration engineering, in particular to a signal recovery method, a signal recovery device and signal recovery equipment applied to oil and gas exploration.

Background

In oil and gas exploration engineering, in order to ensure the safe production of the whole oil and gas exploration engineering, sensors are generally arranged in a drilling well and on drilling equipment so as to realize the safe monitoring of the whole oil and gas exploration and the drilling process. However, as the drilling depth increases, the sensing signals acquired by the sensors may be attenuated by different degrees, which may cause errors or even distortions of the sensing signals received by the signal monitoring device to occur in different degrees, thereby making it difficult to ensure the accuracy of safety monitoring.

Disclosure of Invention

In order to improve the problems, the invention provides a signal recovery method, a signal recovery device and signal recovery equipment applied to oil-gas exploration.

In a first aspect of the embodiments of the present invention, there is provided a signal recovery method applied to oil and gas exploration, applied to a signal recovery device, the method at least including:

the method comprises the steps of obtaining first sensing signals which are sent by at least one sensor and carry signal types and signal character strings, wherein the signal types correspond to the signal character strings one by one, the signal types are used for representing the installation positions of the sensor, the signal character strings are sensing data which are collected by the sensor at the corresponding installation positions, and the character arrangement modes and character types of the sensing data corresponding to different installation positions are different;

determining a first environmental parameter at a first target position represented by a signal category corresponding to the at least one sensor and a second environmental parameter on a straight line path from the first target position to a second target position of the signal recovery device from a prestored environmental parameter set, wherein the first target position and the second target position are both determined by taking a world coordinate system as a reference, the first target position and the second target position are both three-dimensional coordinates, the environmental parameter set is obtained by the signal recovery device periodically from an environmental data collection device, and the environmental parameter set is updated in the environmental data collection device and in the signal recovery device in real time;

determining attenuation vectors when the sensing signals sent from the first target position reach the second target position according to the first environmental parameters and the second environmental parameters, wherein the attenuation vectors are multidimensional vectors, each vector value in the attenuation vectors corresponds to a different attenuation factor, and the attenuation factors are determined according to parameter types in the first environmental parameters and the second environmental parameters;

determining a first generalization factor of the attenuation vector according to the signal category of the first sensing signal, and determining a second generalization factor of the attenuation vector according to the character arrangement mode and the character type in the signal character string of the first sensing signal, wherein the first generalization factor is used for representing a first weighting value of at least part of first target vector values in the attenuation vectors corresponding to different signal categories, and the second generalization factor is used for representing a second weighting value of at least part of second target vector values in the attenuation vectors corresponding to different signal categories;

weighting the attenuation vector for the first time based on the first generalization factor to obtain a first weighting vector, determining the similarity rate between the first weighting vector and the attenuation vector, determining an influence factor corresponding to the second generalization factor based on the similarity rate, weighting the first weighting vector for the second time based on the second generalization factor and the influence factor to obtain a second weighting vector, wherein the influence factor is used for representing the change situation of at least part of second target vector values corresponding to the second generalization factor after the first weighting;

performing feature extraction on the first sensing signals to obtain first feature vectors, modifying each feature vector value in the first feature vectors one by one on the basis of the second weighted vectors to obtain second feature vectors, and performing feature restoration on the second feature vectors according to extraction logic for performing feature extraction on the first sensing signals to obtain second sensing signals; the first feature vector is used for representing the signal category of the first sensing signal and the character arrangement mode, the character type and the feature distribution of character information of the signal character string of the first sensing signal.

In an alternative embodiment, the determining an attenuation vector of the sensor signal transmitted from the first target location when it arrives at the second target location based on the first environmental parameter and the second environmental parameter includes:

determining a first data capacity of the first environmental parameter and a second data capacity of the second environmental parameter, establishing a parameter classification thread through a preset parameter classification rule, segmenting the parameter classification thread based on a ratio of the first data capacity to the second data capacity to obtain a first parameter classification thread and a second parameter classification thread, and respectively allocating a first time slice resource and a second time slice resource to the first parameter classification thread and the second parameter classification thread; the first data capacity and the second data capacity are used for representing the size of a first environmental parameter and the size of a second environmental parameter, a preset parameter classification rule is obtained based on a storage format of a parameter class of the environmental parameter in the signal recovery device, the first parameter classification thread and the second parameter classification thread are continuous and mutually independent parameter classification threads, and the first time slice resource and the second time slice resource are used for representing memory resources of the signal recovery device, which are needed by the parameter classification when the first parameter classification thread and the second parameter classification thread start and end simultaneously;

mapping the first environmental parameter and the second environmental parameter to the first parameter classification thread and the second parameter classification thread respectively, starting the first parameter classification thread and the second parameter classification thread simultaneously based on the first time slice resource and the second time slice resource, and acquiring a first classification result and a second classification result output by the first parameter classification thread and the second parameter classification thread respectively; the first classification result comprises a plurality of first classification identifiers, each first classification identifier corresponds to at least one first parameter group in the first environment parameters, the second classification result comprises a plurality of second classification identifiers, and each second classification identifier corresponds to at least one second parameter in the second environment parameters;

determining at least part of first target identifications from a plurality of first classification identifications of the first classification result and determining at least part of second target identifications from the second classification result based on the at least part of first target identifications, wherein the first target identifications and the second target identifications are identifications corresponding to environmental parameters which have influence on transmission attenuation of sensing signals;

determining at least part of a first target parameter from the first environmental parameter based on the first target identifier and at least part of a second target parameter from the second environmental parameter based on the second target identifier; mapping at least part of first target parameters and at least part of second target parameters to a preset attenuation pairing list according to the relevance of the first target parameters and the second target parameters to determine a first attenuation influence array corresponding to at least part of the first target parameters and a second attenuation influence array corresponding to at least part of the second target parameters, wherein the attenuation pairing list comprises attenuation influence coefficients of different environmental parameters on the same sensing signal, and the attenuation influence coefficients are the average amplitude of signal attenuation representing the sensing signal in unit length;

determining a first interference weight of each first attenuation influence coefficient in the first attenuation influence array and a second interference weight of each second attenuation influence coefficient in the second attenuation influence array, sequencing the first interference weight and the second interference weight according to a descending order of the interference weights to obtain a first sequencing sequence, sequencing the first attenuation influence coefficient and the second attenuation influence coefficient according to the first sequencing sequence to obtain a second sequencing sequence, and obtaining the attenuation vector according to the second sequencing sequence, wherein the interference weights are used for representing attenuation superposition or attenuation cancellation generated when different attenuation influence coefficients attenuate a sensing signal.

In an alternative embodiment, the determining a first generalization factor for the attenuation vector according to the signal class of the first sensing signal comprises:

determining at least part of first target vector values from the attenuation vectors according to the signal category of the first sensing signals, wherein the matching degree between a vector dimension identifier corresponding to the first target vector values and a category identifier corresponding to the signal category of the first sensing signals is greater than a set value, the vector dimension identifiers and the category identifiers are stored in the signal recovery equipment in a binary code form, and the matching degree is obtained through the occupation ratio of binary numerical values of the vector dimension identifiers and the category identifiers on the same code bit and continuous same binary numerical value strings in the vector dimension identifiers and the category identifiers respectively;

determining a signal penetration rate corresponding to a signal class of the first sensing signal, wherein the signal penetration rate is used for representing the amplitude attenuation degree when the sensing signal passes through an obstacle, determining a correlation coefficient between each first target vector value of at least part of first target vector values and the signal penetration rate, the correlation coefficient is used for representing the correlation degree between each first target vector value and the signal penetration rate, assigning a first weighting value to each first target vector value according to the correlation coefficient, and determining the first generalization factor according to the first target vector value assigned with the first weighting value.

In an alternative embodiment, the determining the second generalization factor for the attenuation vector according to the arrangement of characters and the type of characters in the signal character string of the first sensing signal includes:

listing the graphic code containing the character arrangement mode and the character type stored in the signal recovery equipment;

determining a third eigenvector of the graphic code, wherein the third eigenvector is used for distinguishing the graphic code, and the graphic codes of different sensing signals are different;

and judging whether the vector dimension of the third feature vector is the same as the vector dimension of the attenuation vector, if so, determining a second weighted value of at least part of second target vector values in the attenuation vector according to the projection value of the third feature vector in the attenuation vector and determining a second generalization factor of the attenuation vector based on the second weighted value of at least part of the second target vector values, and if not, performing dimension increase and decrease on the third feature vector according to the vector dimension of the attenuation vector and executing a step similar to the step of determining the second weighted value of at least part of the second target vector values in the attenuation vector according to the projection value of the third feature vector in the attenuation vector.

In an alternative embodiment, the modifying each feature vector value in the first feature vector based on the second weighting vector to obtain a second feature vector includes:

extracting a correlation distribution sequence corresponding to the current magnitude value in the second weighting vector from the second weighting vector, obtaining a signal attenuation track corresponding to the current magnitude value included in the correlation distribution sequence, and generating a signal attenuation curve; the signal attenuation curve is used for representing the attenuation trend of the sensing signal, the current vector value is a vector value in the second weighting vector, and a set relation exists between the current vector value and each feature vector value in the first feature vector, and the set relation is used for representing that the current vector value is in attenuation correlation with the first feature vector;

mapping each characteristic vector value to the signal attenuation curve to obtain a characteristic node of each characteristic vector value in the signal attenuation curve, correcting the characteristic vector value corresponding to each characteristic node according to the position of each characteristic node in the signal attenuation curve to obtain a corrected vector value, and obtaining the second characteristic vector according to the corrected vector value.

In an alternative embodiment, the method further comprises: and storing the second sensing signal and the first sensing signal in an associated manner.

In an alternative embodiment, the data conversion protocol is generated by:

acquiring a first signal processing log generated by processing acquired sensing data in at least one sensor and determining first signal processing logic information corresponding to the first signal processing log, wherein the first signal processing log is stored in a storage area of the at least one sensor and is updated in real time;

acquiring a second signal processing log of a signal recovery device, and calculating the similarity between the first signal processing log and the second signal processing log according to the first signal processing logic information;

if the similarity between the first signal processing log and the second signal processing log is smaller than a preset similarity threshold, matching second signal processing logic information corresponding to the second signal processing log of a signal recovery device with the first signal processing logic information to obtain target logic information, wherein the target logic information is used for indicating a data conversion strategy between the signal recovery device and the at least one sensor, and the data conversion strategy is used for indicating the signal recovery device and the at least one sensor to perform parameter adjustment so as to realize data conversion;

splitting the target logic information into information sets, taking the information sets as a protocol framework, taking signal processing thread information of a first signal processing log in the at least one sensor as protocol content, and constructing a signal conversion protocol to obtain a first protocol;

adjusting the first protocol according to the second signal processing log to obtain a second protocol, namely adding the consideration of the first signal processing log, and adjusting the first protocol to obtain an adjustment result with high data conversion accuracy, namely the second protocol;

determining a first error rate of the second protocol relative to the information set, and matching a logic thread in the second protocol corresponding to the first error rate with the target logic information to obtain a matching result;

if the similarity between the first signal processing log and the second signal processing log is greater than or equal to the similarity threshold, determining a second error rate of the first protocol relative to the information set, and matching a logic thread in the first protocol corresponding to the second error rate with the target logic information to obtain a matching result;

and adding the first address of the signal recovery equipment and the second address of the at least one sensor to the protocol address corresponding to the second protocol according to the matching result to obtain the data conversion protocol.

In a second aspect of the embodiments of the present invention, there is provided a signal recovery apparatus for use in oil and gas exploration, including:

the device comprises an acquisition module, a processing module and a processing module, wherein the acquisition module is used for acquiring a first sensing signal which is sent by at least one sensor and carries a signal type and a signal character string, the signal type corresponds to the signal character string one by one, the signal type is used for representing the installation position of the sensor, the signal character string is sensing data which is acquired by the sensor at the corresponding installation position, and the character arrangement mode and the character type of the sensing data corresponding to different installation positions are different;

a parameter determining module, configured to determine, from a pre-stored set of environmental parameters, a first environmental parameter at a first target location represented by a signal category corresponding to the at least one sensor and a second environmental parameter on a straight-line path from the first target location to a second target location of the signal recovery device, where the first target location and the second target location are both determined with reference to a world coordinate system, the first target location and the second target location are both three-dimensional coordinates, the set of environmental parameters is periodically obtained by the signal recovery device from an environmental data collecting device, and the set of environmental parameters is updated in the environmental data collecting device and in the signal recovery device in real time;

a vector determination module, configured to determine, according to the first environmental parameter and the second environmental parameter, attenuation vectors when a sensing signal transmitted from the first target location reaches the second target location, where the attenuation vectors are multidimensional vectors, each vector value in the attenuation vectors corresponds to a different attenuation factor, and the attenuation factors are determined by a parameter category in the first environmental parameter and the second environmental parameter;

a generalization factor determination module, configured to determine a first generalization factor of the attenuation vector according to a signal category of the first sensing signal, and determine a second generalization factor of the attenuation vector according to a character arrangement manner and a character type in a signal string of the first sensing signal, where the first generalization factor is used to represent first weighted values of at least part of first target vector values in the attenuation vectors corresponding to different signal categories, and the second generalization factor is used to represent second weighted values of at least part of second target vector values in the attenuation vectors corresponding to different signal categories;

the weighting module is used for performing first weighting on the attenuation vector based on the first generalization factor to obtain a first weighting vector and determining the similarity rate between the first weighting vector and the attenuation vector, determining an influence factor corresponding to the second generalization factor based on the similarity rate, and performing second weighting on the first weighting vector based on the second generalization factor and the influence factor to obtain a second weighting vector, wherein the influence factor is used for representing the change situation of at least part of second target vector values corresponding to the second generalization factor after the first weighting;

the signal recovery module is used for performing feature extraction on the first sensing signals to obtain first feature vectors, correcting each feature vector value in the first feature vectors one by one on the basis of the second weighted vectors to obtain second feature vectors, and performing feature restoration on the second feature vectors according to extraction logic for performing feature extraction on the first sensing signals to obtain second sensing signals; the first feature vector is used for representing the signal category of the first sensing signal and the character arrangement mode, the character type and the feature distribution of character information of the signal character string of the first sensing signal.

In a third aspect of the embodiments of the present invention, there is provided a signal recovery apparatus, including: a processor and a memory and bus connected to the processor; the processor and the memory are communicated with each other through the bus; the processor is used for calling the computer program in the memory to execute the signal recovery method applied to the oil and gas exploration.

In a fourth aspect of embodiments of the present invention, there is provided a computer readable storage medium having stored thereon a program which, when executed by a processor, implements the signal recovery method as described above for use in oil and gas exploration.

The signal recovery method applied to oil and gas exploration provided by the embodiment of the invention, the device and the signal recovery equipment can acquire a first sensing signal sent by a sensor, determine a first environmental parameter at a first target position represented by a signal type corresponding to the first sensing signal and a second environmental parameter on a straight line path from the first target position to a second target position of the signal recovery equipment from a prestored environmental parameter set, determine an attenuation vector when the sensing signal sent from the first target position reaches the second target position, weight the attenuation vector based on the determined first generalization factor and the determined second generalization factor to obtain a second weighting vector so as to realize one-by-one correction of a first characteristic vector of the first sensing signal, and obtain a second sensing signal based on the second characteristic vector obtained through one-by-one correction. Therefore, the attenuation condition of the sensing signal can be analyzed based on the environmental parameters in the drilling well so as to recover and trace the source of the sensing signal.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present invention and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained from the drawings without inventive effort.

FIG. 1 is a flow chart of a signal recovery method for use in oil and gas exploration according to an embodiment of the present invention.

FIG. 2 is a functional block diagram of a signal recovery device for use in oil and gas exploration according to an embodiment of the present invention.

Fig. 3 is a schematic diagram of product modules of a signal recovery apparatus according to an embodiment of the present invention.

Icon:

20-signal recovery means; 201-an acquisition module; 202-a parameter determination module; 203-vector determination module; 204-a generalization factor determination module; 205-a weighting module; 206-a signal recovery module;

30-a signal recovery device; 301-a processor; 302-a memory; 303-bus.

Detailed Description

Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.

In order to better understand the technical solutions of the present invention, the following detailed descriptions of the technical solutions of the present invention are provided with the accompanying drawings and the specific embodiments, and it should be understood that the embodiments and the specific features of the embodiments of the present invention are detailed descriptions of the technical solutions of the present invention, and are not limitations of the technical solutions of the present invention, and the technical features of the embodiments and the embodiments of the present invention may be combined with each other without conflict.

In order to solve the technical problems, embodiments of the present invention provide a signal recovery method, a signal recovery device, and a signal recovery apparatus for oil and gas exploration, which can analyze the attenuation of a sensing signal based on an environmental parameter in a drilling well after receiving the sensing signal sent by a sensor, thereby recovering and tracing the sensing signal, so as to reduce the error of the received sensing signal, improve the distortion of the sensing signal, and ensure the accuracy of safety monitoring during oil and gas exploration and the drilling process based on the sensing signal.

On the basis, please refer to fig. 1, which is a flowchart of a signal recovery method applied to oil and gas exploration according to an embodiment of the present invention. In this embodiment, the signal recovery device is in communication with at least one sensor, which may be located on the drilling device, on the exploration device, or at a particular location of the borehole, such as the 1/2 depth location of the explored borehole.

Further, the signal recovery device can also be communicated with the signal monitoring device and used for sending the recovered sensing signal to the signal monitoring device so that the signal monitoring device can accurately and safely monitor the oil and gas exploration process or the drilling process based on the recovered sensing signal. In this embodiment, the method may specifically include the following.

Step S21, acquiring a first sensing signal which is sent by at least one sensor and carries a signal type and a signal character string, wherein the signal type corresponds to the signal character string one by one, the signal type is used for representing the installation position of the sensor, the signal character string is sensing data which is acquired by the sensor at the corresponding installation position, and the character arrangement mode and the character type of the sensing data corresponding to different installation positions are different.

In this embodiment, the installation location may be many locations, for example, at the position of a drill pipe of the drilling equipment, at the pipe wall of a hydrocarbon pipeline, and at a set depth position (for example, 1/2 depth position) of an exploratory drilled well, the signal character string is encapsulated with the signal category in the form of a data packet, and it is understood that when the signal character string and the corresponding signal category are encapsulated into a corresponding first sensing signal, the first sensing signal is a digital signal.

Step S22, determining, from a pre-stored environment parameter set, a first environment parameter at a first target location represented by a signal category corresponding to the at least one sensor and a second environment parameter on a straight-line path from the first target location to a second target location of the signal recovery device, where the first target location and the second target location are both determined with reference to a world coordinate system, the first target location and the second target location are both three-dimensional coordinates, the environment parameter set is periodically acquired by the signal recovery device from an environment data collection device, and the environment parameter set is updated in the environment data collection device and in the signal recovery device in real time.

Step S23, determining, according to the first environmental parameter and the second environmental parameter, an attenuation vector when the sensing signal sent from the first target location reaches the second target location, where the attenuation vector is a multidimensional vector, each vector value in the attenuation vector corresponds to a different attenuation factor, and the attenuation factor is determined by a parameter category in the first environmental parameter and the second environmental parameter.

Step S24, determining a first generalization factor of the attenuation vector according to the signal category of the first sensing signal, and determining a second generalization factor of the attenuation vector according to the character arrangement manner and the character type in the signal string of the first sensing signal, where the first generalization factor is used to represent first weighting values of at least part of first target vector values in the attenuation vectors corresponding to different signal categories, and the second generalization factor is used to represent second weighting values of at least part of second target vector values in the attenuation vectors corresponding to different signal categories.

Step S25, performing first weighting on the attenuation vector based on the first generalization factor to obtain a first weighting vector, determining a similarity between the first weighting vector and the attenuation vector, determining an influence factor corresponding to the second generalization factor based on the similarity, performing second weighting on the first weighting vector based on the second generalization factor and the influence factor to obtain a second weighting vector, where the influence factor is used to characterize a variation of at least a portion of a second target vector value corresponding to the second generalization factor after the first weighting.

Step S26, performing feature extraction on the first sensing signal to obtain a first feature vector, modifying each feature vector value in the first feature vector one by one based on the second weighted vector to obtain a second feature vector, and performing feature restoration on the second feature vector according to an extraction logic for performing feature extraction on the first sensing signal to obtain a second sensing signal; the first feature vector is used for representing the signal category of the first sensing signal and the character arrangement mode, the character type and the feature distribution of character information of the signal character string of the first sensing signal.

In this embodiment, the second sensing signal is a signal obtained by recovering the first sensing signal, and the second sensing signal can also be understood as a signal on the sensor side. For example, the sensor acquires that the sensing data at the corresponding installation position is D, packages the sensing data D into the second sensing signal M2, and then sends the second sensing signal M2 to the signal recovery device, but due to attenuation in the signal transmission process, the sensing signal finally received by the signal recovery device is the first sensing signal M1.

By the method, the first environmental parameters and the second environmental parameters which cause the second sensing signal M2 to be attenuated into the first sensing signal M1 can be analyzed, and the second weighting vector which restores the first sensing signal M1 into the second sensing signal M2 is determined, so that the first sensing signal M1 can be accurately restored and traced.

Based on the above, it can be understood that, by obtaining a first sensing signal sent by a sensor and determining, from a set of pre-stored environmental parameters, a first environmental parameter at a first target position represented by a signal category corresponding to the first sensing signal and a second environmental parameter on a straight line path from the first target position to a second target position of a signal recovery device, an attenuation vector when the sensing signal sent from the first target position reaches the second target position is further determined, and then weighting the attenuation vector twice based on the determined first generalization factor and the determined second generalization factor to obtain a second weighting vector, so as to implement one-by-one modification of the first eigenvector of the first sensing signal, and thereby obtain a second sensing signal through reduction based on the second eigenvector obtained through one-by-one modification. Therefore, the attenuation condition of the sensing signal can be analyzed based on the environmental parameters in the drilling well so as to recover and trace the source of the sensing signal.

In practical application, the sensor is heterogeneous equipment relative to the signal recovery equipment, and after the sensor acquires the sensing data after the corresponding installation position, the sensor needs to encapsulate the sensing data into a sensing signal which can be received by the signal recovery equipment. In order to achieve the above purpose, the signal recovery device may implant a data conversion protocol into the sensor in advance, so that after the sensor collects the sensing data, the sensor can convert and encapsulate the sensing data into the sensing signal that the signal recovery device can receive and process according to the data conversion protocol.

On the basis, the signal recovery device needs to implant a data conversion protocol in the sensor before acquiring the first sensing signal, and further, the signal recovery device may specifically generate the data conversion protocol in the following manner.

Step S31, obtaining a first signal processing log generated by processing the acquired sensing data in the at least one sensor, and determining first signal processing logic information corresponding to the first signal processing log, where the first signal processing log is stored in a storage area of the at least one sensor, and the first signal processing log is updated in real time.

Step S32, obtaining a second signal processing log of the signal recovery device, and calculating a similarity between the first signal processing log and the second signal processing log according to the first signal processing logic information.

Step S33, if the similarity between the first signal processing log and the second signal processing log is smaller than a preset similarity threshold, matching second signal processing logic information corresponding to the second signal processing log of the signal recovery device with the first signal processing logic information to obtain target logic information, where the target logic information is used to indicate a data conversion policy between the signal recovery device and the at least one sensor, and the data conversion policy is used to indicate the signal recovery device and the at least one sensor to perform parameter adjustment to implement data conversion.

Step S34, splitting the target logic information into information sets, and building a signal conversion protocol with the information sets as a protocol framework and the signal processing thread information of the first signal processing log in the at least one sensor as protocol content to obtain a first protocol.

Step S35, adjusting the first protocol according to the second signal processing log to obtain a second protocol, that is, adding the consideration of the first signal processing log, and adjusting the first protocol, so as to obtain an adjustment result with high data conversion accuracy, that is, the second protocol.

Step S36, determining a first error rate of the second protocol relative to the information set, and matching the logic thread in the second protocol corresponding to the first error rate with the target logic information to obtain a matching result.

Step S37, if the similarity between the first signal processing log and the second signal processing log is greater than or equal to the similarity threshold, determining a second error rate of the first protocol relative to the information set, and matching the logical thread in the first protocol corresponding to the second error rate with the target logical information to obtain a matching result.

Step S38, adding the first address of the signal recovery device and the second address of the at least one sensor to the protocol address corresponding to the second protocol according to the matching result to obtain the data conversion protocol.

In this embodiment, through steps S31 to S38, the data conversion protocol can be accurately determined, so that the signal recovery device can implant the data conversion protocol into the sensor, and it is ensured that after the sensor collects the sensing data, the sensing data can be converted and encapsulated into the sensing signal that can be received and processed by the signal recovery device according to the data conversion protocol.

In the present embodiment, the attenuation vector is the key to achieve the sensor signal recovery and tracing, so the accurate determination of the attenuation vector is an important factor to ensure the accuracy of the second sensor signal. For this purpose, in step S23, the determining, according to the first environmental parameter and the second environmental parameter, an attenuation vector when the sensing signal transmitted from the first target location reaches the second target location may specifically include the following.

Step S231, determining a first data capacity of the first environmental parameter and a second data capacity of the second environmental parameter, establishing a parameter classification thread according to a preset parameter classification rule, segmenting the parameter classification thread based on a ratio of the first data capacity to the second data capacity to obtain a first parameter classification thread and a second parameter classification thread, and allocating a first time slice resource and a second time slice resource to the first parameter classification thread and the second parameter classification thread respectively; the first data capacity and the second data capacity are used for representing the size of a first environment parameter and the size of a second environment parameter, a preset parameter classification rule is obtained based on a storage format of a parameter class of the environment parameter in the signal recovery device, the first parameter classification thread and the second parameter classification thread are continuous and mutually independent parameter classification threads, and the first time slice resource and the second time slice resource are used for representing memory resources of the signal recovery device, which are needed by the first parameter classification thread and the second parameter classification thread to start and end parameter classification simultaneously.

Step S232, mapping the first environmental parameter and the second environmental parameter to the first parameter classification thread and the second parameter classification thread, respectively, simultaneously starting the first parameter classification thread and the second parameter classification thread based on the first time slice resource and the second time slice resource, and obtaining a first classification result and a second classification result output by the first parameter classification thread and the second parameter classification thread, respectively; the first classification result includes a plurality of first classification identifiers, each first classification identifier corresponds to at least one first parameter group in the first environment parameters, the second classification result includes a plurality of second classification identifiers, and each second classification identifier corresponds to at least one second parameter in the second environment parameters.

Step S233, determining at least a part of a first target identifier from the plurality of first classification identifiers of the first classification result, and determining at least a part of a second target identifier from the second classification result based on the at least a part of the first target identifier, where the first target identifier and the second target identifier are identifiers corresponding to an environmental parameter that has an influence on transmission attenuation of the sensing signal.

Step S234, determining at least a part of first target parameters from the first environmental parameters based on the first target identifier and at least a part of second target parameters from the second environmental parameters based on the second target identifier; mapping at least part of the first target parameters and at least part of the second target parameters to a preset attenuation pairing list according to the relevance of the first target parameters and the second target parameters to determine a first attenuation influence array corresponding to at least part of the first target parameters and a second attenuation influence array corresponding to at least part of the second target parameters, wherein the attenuation pairing list comprises attenuation influence coefficients of different environmental parameters on the same sensing signal, and the attenuation influence coefficients are equal to the average amplitude representing the signal attenuation of the sensing signal in unit length.

Step S235, determining a first interference weight of each first attenuation influence coefficient in the first attenuation influence array and a second interference weight of each second attenuation influence coefficient in the second attenuation influence array, sorting the first interference weight and the second interference weight according to a descending order of the interference weights to obtain a first sorting sequence, sorting the first attenuation influence coefficient and the second attenuation influence coefficient according to the first sorting sequence to obtain a second sorting sequence, and obtaining the attenuation vector according to the second sorting sequence, where the interference weights are used to represent attenuation superposition or attenuation cancellation generated when different attenuation influence coefficients attenuate a sensing signal.

Through the content, the synchronism of parameter classification of the first environmental parameter and the second environmental parameter can be ensured, the attenuation vector is determined according to the first classification result and the second classification result obtained synchronously, attenuation superposition or attenuation offset generated when different attenuation influence coefficients attenuate the sensing signal can be considered when the attenuation vector is determined, and the accuracy of the attenuation vector is further ensured so as to ensure the accuracy of sensing signal recovery and tracing.

In a specific implementation, in order to accurately determine the first generalization factor of the attenuation vector, on the basis of step S23, in step S24, the determining the first generalization factor of the attenuation vector according to the signal class of the first sensing signal may specifically include the following.

Step S2411, determining at least a part of first target vector values from the attenuation vectors according to the signal category of the first sensing signal, where a matching degree between a vector dimension identifier corresponding to the first target vector value and a category identifier corresponding to the signal category of the first sensing signal is greater than a set value, the vector dimension identifier and the category identifier are stored in the signal recovery device in the form of binary codes, and the matching degree is obtained by the occupation ratio of binary values of the vector dimension identifier and the category identifier on the same code bit and a continuous same binary value string in the vector dimension identifier and the category identifier, respectively.

Step S2412, determining a signal penetration rate corresponding to a signal class of the first sensing signal, where the signal penetration rate is used to characterize an amplitude attenuation degree of the sensing signal when passing through an obstacle, determining a correlation coefficient between each first target vector value of at least a part of the first target vector values and the signal penetration rate, where the correlation coefficient is used to characterize the correlation degree between each first target vector value and the signal penetration rate, assigning a first weighting value to each first target vector value according to the correlation coefficient, and determining the first generalization factor according to the first target vector value to which the first weighting value is assigned.

It is understood that based on steps S2411-S2412, the first generalization factor of the attenuation vector can be accurately determined.

On the basis of the above, in step S24, the determining the second generalization factor of the attenuation vector according to the character arrangement and the character type in the signal string of the first sensing signal may specifically include the following.

Step S2421, listing the graphic code stored in the signal recovery device and containing the character arrangement mode and the character type.

Step S2422, determining a third feature vector of the graphic code, wherein the third feature vector is used for distinguishing the graphic code, and the graphic codes of different sensing signals are different.

Step S2423, determining whether the vector dimension of the third feature vector is the same as the vector dimension of the attenuation vector, if so, determining a second weighting value of at least a part of the second target vector values in the attenuation vector according to the projection value of the third feature vector in the attenuation vector and determining a second generalization factor of the attenuation vector based on the second weighting value of at least a part of the second target vector values, and if not, performing dimension increase and decrease on the third feature vector according to the vector dimension of the attenuation vector and performing a step similar to the step of determining the second weighting value of at least a part of the second target vector values in the attenuation vector according to the projection value of the third feature vector in the attenuation vector.

Through the steps, the characteristic recognition can be carried out on the graphic code, and the second generalization factor can be accurately determined.

In step S26, the modifying each feature vector value in the first feature vector one by one based on the second weighting vector to obtain a second feature vector may specifically include the following contents.

Step S2611, extracting a correlation distribution sequence corresponding to a current vector value in a second weighting vector from the second weighting vector, obtaining a signal attenuation trajectory corresponding to the current vector value included in the correlation distribution sequence, and generating a signal attenuation curve; the signal attenuation curve is used for representing the attenuation trend of the sensing signal, the current direction quantity value is a vector value in the second weighting vector and has a set relation with each feature vector value in the first feature vector, and the set relation is used for representing that the current direction quantity value is in attenuation relation with the first feature vector.

Step S2612, mapping each feature vector value to the signal attenuation curve to obtain a feature node of each feature vector value in the signal attenuation curve, correcting the feature vector value corresponding to each feature node according to the position of each feature node in the signal attenuation curve to obtain a corrected vector value, and obtaining the second feature vector according to the corrected vector value.

It is understood that based on steps S2611-S2612, each eigenvector value can be modified based on the signal attenuation curve, so as to recover the first eigenvector as a second eigenvector corresponding to the second sensing signal before the first sensing signal is attenuated.

Optionally, on the basis of the steps S21-S26, the method may further include the following: and storing the second sensing signal and the first sensing signal in an associated manner. In this embodiment, the vector value in the second eigenvector of the second sensing signal and the first eigenvector value of the first sensing signal may be in one-to-one correspondence and stored, so that when the first sensing signal and the second sensing signal sent by the same sensor and stored in association reach a certain number, big data statistics and analysis may be directly performed according to the association storage result, thereby directly determining the attenuation relationship between the first sensing signal and the second sensing signal, and thus directly determining the sensing signal before attenuation corresponding to the latest received sensing signal according to the attenuation relationship.

In an alternative embodiment, in step S26, the performing feature restoration on the second feature vector according to the extraction logic that performs feature extraction on the first sensing signal to obtain a second sensing signal may specifically include the following.

Step S2621, listing the logical nodes of the extracted logic, and establishing a first logical topology, where the first logical topology is a multi-node topology structure, each logical node corresponds to one feature extraction behavior, each feature extraction behavior corresponds to one behavior priority, the multiple logical nodes are arranged according to the order of the behavior priorities, and two adjacent logical nodes are connected by a directed connection line.

Step S2622, rearranging the plurality of logic nodes according to a sequence of priorities from low to high, performing reverse processing on the direction of the directional connecting line to obtain a second logic topology, generating target logic for restoring the second feature vector into a second sensing signal according to the second logic topology, and restoring the second feature vector based on the target extraction logic to obtain the second sensing signal.

It can be understood that through the above steps, the logic node from which the logic is extracted can be analyzed, and the first logic topology is inverted to obtain the second logic topology, so that the second feature vector can be accurately subjected to feature restoration based on the second logic topology, and thus the second sensing signal is obtained, and the accuracy of the second sensing signal is ensured.

On the basis of the above, please refer to fig. 3, which is a block diagram of a signal recovery device 20 for oil and gas exploration according to an embodiment of the present invention, the signal recovery device 20 for oil and gas exploration may include the following modules.

An obtaining module 201, configured to obtain a first sensing signal that is sent by at least one sensor and carries a signal category and a signal character string, where the signal category corresponds to the signal character string one to one, the signal category is used to characterize an installation position of the sensor, the signal character string is sensing data acquired by the sensor at the corresponding installation position, and the sensing data corresponding to different installation positions have different character arrangement modes and different character types;

a parameter determining module 202, configured to determine, from a pre-stored environment parameter set, a first environment parameter at a first target location represented by a signal category corresponding to the at least one sensor and a second environment parameter on a straight-line path from the first target location to a second target location of the signal recovery device, where the first target location and the second target location are both determined with reference to a world coordinate system, the first target location and the second target location are both three-dimensional coordinates, the environment parameter set is periodically obtained by the signal recovery device from an environment data collecting device, and the environment parameter set is updated in the environment data collecting device and in the signal recovery device in real time;

a vector determining module 203, configured to determine, according to the first environmental parameter and the second environmental parameter, an attenuation vector when the sensing signal sent from the first target location reaches the second target location, where the attenuation vector is a multidimensional vector, each vector value in the attenuation vector corresponds to a different attenuation factor, and the attenuation factor is determined by a parameter category in the first environmental parameter and the second environmental parameter;

a generalization factor determination module 204, configured to determine a first generalization factor of the attenuation vector according to the signal category of the first sensing signal, and determine a second generalization factor of the attenuation vector according to a character arrangement manner and a character type in a character string of the signal of the first sensing signal, where the first generalization factor is used to characterize first weighting values of at least part of first target vector values in the attenuation vectors corresponding to different signal categories, and the second generalization factor is used to characterize second weighting values of at least part of second target vector values in the attenuation vectors corresponding to different signal categories;

a weighting module 205, configured to perform first weighting on the attenuation vector based on the first generalization factor to obtain a first weighting vector, determine a similarity between the first weighting vector and the attenuation vector, determine an influence factor corresponding to the second generalization factor based on the similarity, perform second weighting on the first weighting vector based on the second generalization factor and the influence factor to obtain a second weighting vector, where the influence factor is used to characterize a change of at least a portion of second target vector values corresponding to the second generalization factor after the first weighting;

a signal recovery module 206, configured to perform feature extraction on the first sensing signal to obtain a first feature vector, modify each feature vector value in the first feature vector one by one based on the second weighting vector to obtain a second feature vector, and perform feature restoration on the second feature vector according to an extraction logic for performing feature extraction on the first sensing signal to obtain a second sensing signal; the first feature vector is used for representing the signal category of the first sensing signal and the character arrangement mode, the character type and the feature distribution of character information of the signal character string of the first sensing signal.

Embodiments of the present invention also provide a computer-readable storage medium, on which a program is stored, which when executed by a processor implements the signal recovery method applied to oil and gas exploration.

The embodiment of the invention also provides a processor, which is used for running the program, wherein the program executes the signal recovery method applied to the oil and gas exploration during running.

In this embodiment, as shown in fig. 3, the signal recovery apparatus 300 includes at least one processor 301, and a memory 302 and a bus 303 connected to the processor 301. The processor 301 and the memory 302 are communicated with each other through a bus 303. The processor 301 is operable to invoke program instructions in the memory 302 to perform the signal recovery method described above as applied to a hydrocarbon survey.

In summary, the embodiment of the invention provides a signal recovery method applied to oil and gas exploration, the device and the signal recovery equipment can acquire a first sensing signal sent by a sensor, determine a first environmental parameter at a first target position represented by a signal type corresponding to the first sensing signal and a second environmental parameter on a straight line path from the first target position to a second target position of the signal recovery equipment from a prestored environmental parameter set, determine an attenuation vector when the sensing signal sent from the first target position reaches the second target position, weight the attenuation vector based on the determined first generalization factor and the determined second generalization factor to obtain a second weighting vector so as to realize one-by-one correction of a first feature vector of the first sensing signal, and obtain a second sensing signal based on the one-by-one corrected second feature vector. Therefore, the attenuation condition of the sensing signal can be analyzed based on the environmental parameters in the drilling well so as to realize the recovery and tracing of the sensing signal.

The present application is described with reference to flowchart illustrations and/or block diagrams of methods, cloud signal recovery devices (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing cloud signal recovery apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing cloud signal recovery apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

In a typical configuration, a cloud signal recovery device includes one or more processors (CPUs), memory, and a bus. The cloud signal recovery apparatus may further include an input/output interface, a network interface, and the like.

The memory may include volatile memory in a computer readable medium, Random Access Memory (RAM) and/or nonvolatile memory such as Read Only Memory (ROM) or flash memory (flash RAM), and the memory includes at least one memory chip. The memory is an example of a computer-readable medium.

Computer-readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), random access memory with other feature weights (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, read only disk read only memory (CD-ROM), Digital Versatile Disk (DVD) or other optical storage, magnetic cassettes, magnetic tape storage or other magnetic storage cloud signal recovery devices, or any other non-transmission medium that can be used to store information that can be matched by a computing cloud signal recovery device. As defined herein, a computer readable medium does not include a transitory computer readable medium such as a modulated data signal or a carrier wave.

It is also to be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or cloud signal recovery apparatus that comprises a list of elements does not include only those elements but also other elements not expressly listed or inherent to such process, method, article, or cloud signal recovery apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of additional like elements in the process, method, article of manufacture, or cloud signal recovery device comprising the element.

As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.

The above are merely examples of the present application and are not intended to limit the present application. Various modifications and changes may occur to those skilled in the art. Any modification, equivalent replacement, improvement or the like made within the spirit and principle of the present application shall be included within the scope of the claims of the present application.

Claims

1. A method for signal recovery for use in oil and gas exploration, the method comprising at least:

acquiring a first sensing signal which is sent by at least one sensor and carries a signal type and a signal character string, wherein the signal type corresponds to the signal character string one by one, the signal type is used for representing the installation position of the sensor, the signal character string is sensing data which is acquired by the sensor at the corresponding installation position, and the character arrangement mode and the character type of the sensing data corresponding to different installation positions are different;

2. The method of claim 1, wherein determining an attenuation vector for the sensor signal transmitted from the first target location to reach the second target location based on the first environmental parameter and the second environmental parameter comprises:

determining at least part of a first target parameter from the first environmental parameter based on the first target identifier and at least part of a second target parameter from the second environmental parameter based on the second target identifier; mapping at least part of first target parameters and at least part of second target parameters to a preset attenuation pairing list according to the relevance of the first target parameters and the second target parameters to determine a first attenuation influence array corresponding to at least part of the first target parameters and a second attenuation influence array corresponding to at least part of the second target parameters, wherein the attenuation pairing list comprises attenuation influence coefficients of different environmental parameters on the same sensing signal, and the attenuation influence coefficients are the same as the average amplitude representing the signal attenuation of the sensing signal in unit length;

determining a first interference weight of each first attenuation influence coefficient in the first attenuation influence array and a second interference weight of each second attenuation influence coefficient in the second attenuation influence array, sequencing the first interference weight and the second interference weight according to a descending order of the interference weights to obtain a first sequencing sequence, sequencing the first attenuation influence coefficient and the second attenuation influence coefficient according to the first sequencing sequence to obtain a second sequencing sequence, and obtaining the attenuation vector according to the second sequencing sequence, wherein the interference weights are used for representing attenuation superposition or attenuation cancellation generated when different attenuation influence coefficients attenuate the sensing signal.

3. The method of claim 1, wherein determining a first generalization factor for the attenuation vector from a signal class of the first sensing signal comprises:

determining at least part of first target vector values from the attenuation vectors according to the signal category of the first sensing signals, wherein the matching degree between the vector dimension identifications corresponding to the first target vector values and the category identifications corresponding to the signal category of the first sensing signals is greater than a set value, the vector dimension identifications and the category identifications are stored in the signal recovery equipment in a binary code mode, and the matching degree is obtained through the occupation ratio of binary values of the vector dimension identifications and the category identifications on the same code bit and continuous same binary value strings in the vector dimension identifications and the category identifications respectively;

the method comprises the steps of determining a signal penetration rate corresponding to a signal class of the first sensing signal, wherein the signal penetration rate is used for representing the amplitude attenuation degree when the sensing signal passes through an obstacle, determining a correlation coefficient between each first target vector value of at least part of first target vector values and the signal penetration rate, wherein the correlation coefficient is used for representing the correlation degree between each first target vector value and the signal penetration rate, assigning a first weighting value to each first target vector value according to the correlation coefficient, and determining the first generalization factor according to the first target vector value assigned with the first weighting value.

4. The method of claim 3, wherein determining the second generalization factor for the attenuation vector based on an arrangement of characters and a type of character in the signal string of the first sensed signal comprises:

5. The method of claim 1, wherein the modifying each eigenvector value in the first eigenvector one by one based on the second weighted vector to obtain a second eigenvector comprises:

extracting a correlation distribution sequence corresponding to a current vector value in a second weighting vector from the second weighting vector, obtaining a signal attenuation track corresponding to the current vector value included in the correlation distribution sequence and generating a signal attenuation curve; the signal attenuation curve is used for representing the attenuation trend of the sensing signal, the current direction quantity value is a vector value in the second weighting vector and has a set relation with each feature vector value in the first feature vector, and the set relation is used for representing that the current direction quantity value is in attenuation relation with the first feature vector;

6. The method according to any one of claims 1-5, further comprising: and storing the second sensing signal and the first sensing signal in an associated manner.

7. The method of claim 6, wherein the data conversion protocol is generated by:

acquiring a first signal processing log generated by processing acquired sensing data in at least one sensor and determining first signal processing logic information corresponding to the first signal processing log, wherein the first signal processing log is stored in a storage area of the at least one sensor, and the first signal processing log is updated in real time;

acquiring a second signal processing log of the signal recovery device, and calculating the similarity between the first signal processing log and the second signal processing log according to the first signal processing logic information;

splitting the target logic information into information sets, taking the information sets as a protocol framework, taking signal processing thread information of a first signal processing log in the at least one sensor as protocol content, and building a signal conversion protocol to obtain a first protocol;

8. A signal recovery device for use in oil and gas exploration, comprising:

a parameter determining module, configured to determine, from a pre-stored environment parameter set, a first environment parameter at a first target location represented by a signal category corresponding to the at least one sensor and a second environment parameter on a straight-line path from the first target location to a second target location of the signal recovery device, where the first target location and the second target location are both determined with reference to a world coordinate system, the first target location and the second target location are both three-dimensional coordinates, the environment parameter set is obtained by the signal recovery device periodically from an environment data collecting device, and the environment parameter set is updated in the environment data collecting device and in the signal recovery device in real time;

a vector determination module, configured to determine, according to the first environmental parameter and the second environmental parameter, an attenuation vector when a sensing signal sent from the first target location reaches the second target location, where the attenuation vector is a multidimensional vector, each vector value in the attenuation vector corresponds to a different attenuation factor, and the attenuation factor is determined by a parameter category in the first environmental parameter and the second environmental parameter;

a generalization factor determination module, configured to determine a first generalization factor of the attenuation vector according to a signal category of the first sensing signal, and determine a second generalization factor of the attenuation vector according to a character arrangement manner and a character type in a signal string of the first sensing signal, where the first generalization factor is used to characterize first weighted values of at least part of first target vector values in the attenuation vectors corresponding to different signal categories, and the second generalization factor is used to characterize second weighted values of at least part of second target vector values in the attenuation vectors corresponding to different signal categories;

the weighting module is used for carrying out first weighting on the attenuation vector based on the first generalization factor to obtain a first weighting vector and determining the similarity rate between the first weighting vector and the attenuation vector, determining an influence factor corresponding to the second generalization factor based on the similarity rate, carrying out second weighting on the first weighting vector based on the second generalization factor and the influence factor to obtain a second weighting vector, wherein the influence factor is used for representing the change situation of at least part of second target vector values corresponding to the second generalization factor after the first weighting;

9. A signal recovery apparatus, comprising: a processor and a memory and bus connected to the processor; the processor and the memory are communicated with each other through the bus; the processor is used to call the computer program in the memory to execute the signal recovery method applied to oil and gas exploration according to any one of the above claims 1-7.

10. A computer-readable storage medium, characterized in that it has a program stored thereon, which when executed by a processor, implements a signal recovery method for use in oil and gas exploration according to any one of the preceding claims 1 to 7.