Embedded off-line intelligent in-well high-frequency pressure monitoring device

Abstract

The present disclosure relates to the technical field of pressure monitoring, and particularly relates to an embedded offline intelligent in-well high-frequency pressure monitoring device. The device comprises: a pressure monitoring module, which is in direct contact with the in-well fluid at the fracturing fracture opening, is used for in-situ collection of the pressure at the fracturing fracture opening, and obtains pressure data; a data processing module, which is used for obtaining the pressure data and determining the fracture characteristics corresponding to the pressure data, and generating parameter control instructions corresponding to the fracture characteristics; and a data transmission module, which is used for sending the parameter control instructions to a control center, so that the control center adjusts the fracturing wellhead parameters according to the parameter control instructions. The present disclosure adopting the above scheme can realize real-time and accurate monitoring of the pressure curve.

Description

Technical Field

[0001] This disclosure relates to the field of pressure monitoring technology, and in particular to an embedded offline intelligent in-well high-frequency pressure monitoring device. Background Technology

[0002] Hydraulic fracturing technology, by injecting high-pressure fluid into rock formations to create an artificial fracture network, effectively reduces the overall stiffness of the roof and promotes stratified collapse, and has become a key means of modifying rigid roof structures. In recent years, significant progress has been made in the prevention and control of rockbursts through a three-dimensional technical system of "surface horizontal well segmented fracturing + downhole regional fracturing + working face local fracturing." The pressure curve during fracturing carries real-time fracturing information and is a comprehensive reflection of complex events such as the competitive propagation of multiple fracture clusters, changes in perforation near-wellbore friction, changes in flow distribution (flow and intra-fracture filtration), fracturing conditions, and wellbore events. A clear understanding of the characteristics of the fracturing operation curve is crucial for identifying the state of the fracturing fractures. Therefore, how to achieve real-time and accurate monitoring of the pressure curve has become a key focus. Summary of the Invention

[0003] This disclosure aims to at least partially address one of the technical problems in the related art.

[0004] Therefore, the purpose of this disclosure is to propose an embedded offline intelligent in-well high-frequency pressure monitoring device to achieve real-time and accurate monitoring of pressure curves.

[0005] To achieve the above objectives, one embodiment of this disclosure proposes an embedded offline intelligent in-well high-frequency pressure monitoring device, comprising:

[0006] The pressure monitoring module is in direct contact with the fluid in the well at the fracture opening, and is used to collect pressure data in situ at the fracture opening.

[0007] The data processing module is used to acquire the pressure data, determine the crack characteristics corresponding to the pressure data, and generate parameter control instructions corresponding to the crack characteristics.

[0008] The data transmission module is used to send the parameter adjustment command to the control center, so that the control center can adjust the fracturing wellhead parameters according to the parameter adjustment command.

[0009] Optionally, the pressure monitoring module is used to collect pressure at the fracture opening in situ. When obtaining pressure data, it is specifically used for:

[0010] Pressure data is obtained by in-situ sampling of the pressure at the fracture opening using a preset sampling frequency, wherein the preset sampling frequency is not less than a sampling frequency threshold.

[0011] Optionally, the crack features include crack propagation events and the event types corresponding to the crack propagation events. When the data processing module determines the crack features corresponding to the pressure data, it is specifically used for:

[0012] Time-domain and frequency-domain information are extracted from the pressure data;

[0013] Feature recognition is performed on the time-domain information and the frequency-domain information to obtain the fracture propagation events in the fracturing process and the event types corresponding to the fracture propagation events.

[0014] Optionally, when the data processing module is used to decompose time-domain information and frequency-domain information from the pressure data, it is specifically used for:

[0015] Continuous wavelet transform is performed on the pressure data to decompose time-domain and frequency-domain information from the pressure data.

[0016] Optionally, the data processing module is used to perform feature recognition on the time-domain information and the frequency-domain information to obtain fracture propagation events during the fracturing process and the event types corresponding to the fracture propagation events, including:

[0017] Obtain a training database and use the training database to train the initial feature recognition model to obtain a trained feature recognition model;

[0018] The time-domain information and the frequency-domain information are input into the trained feature recognition model to obtain the crack propagation events during the fracturing process and the event types corresponding to the crack propagation events.

[0019] Optionally, when the data processing module generates the parameter adjustment instructions corresponding to the crack features, it is specifically used for:

[0020] Based on the correspondence between crack features and codes, generate the coding instructions corresponding to the crack features;

[0021] The parameter control instructions corresponding to the crack features are determined based on the encoded instructions.

[0022] Optionally, the data processing module is further configured to:

[0023] If the encoded instruction is not generated within the time threshold, a normal operation instruction is sent to the data transmission module. The normal operation instruction is used to indicate that the embedded offline intelligent in-well high-frequency pressure monitoring device is in normal working condition and that there is no need to adjust the fracturing wellhead parameters.

[0024] Optionally, the device further includes a device body, and the data transmission module includes a data transmitting unit and a data receiving unit; wherein,

[0025] The device body is installed inside the packer column. The pressure monitoring module, the data processing module, and the data transmission unit are all installed inside the device body. The data transmission unit is used to receive and transmit the parameter control command.

[0026] The data receiving unit is used to receive the parameter control command transmitted by the data transmitting unit and send the parameter control command to the control center.

[0027] Optionally, the device further includes a centralizer; wherein,

[0028] The centralizer is located at the head of the device body so that the device body fits tightly against the well wall.

[0029] Optionally, the device further includes a power module; wherein,

[0030] The power module is used to supply power to the pressure monitoring module, the data processing module, and the data transmission unit.

[0031] In summary, the embedded offline intelligent in-well high-frequency pressure monitoring device provided in this disclosure, by realizing real-time monitoring of fluid pressure at the fracture opening in the well and in-situ intelligent analysis of pressure data, generates parameter control commands and sends these commands to the control center, can provide hardware and theoretical basis for parameter control at the fracture wellhead, forming real-time monitoring and dynamic control during the fracturing process. This overcomes the limitations of existing technologies in achieving real-time monitoring and intelligent analysis of pressure at the fracture opening in both surface and downhole fracturing processes, as well as dynamic control of fracturing parameters.

[0032] Additional aspects and advantages of this disclosure will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of this disclosure. Attached Figure Description

[0033] The above and / or additional aspects and advantages of this disclosure will become apparent and readily understood from the following description of the embodiments taken in conjunction with the accompanying drawings, in which:

[0034] Figure 1 This is a schematic diagram of the structure of an embedded offline intelligent in-well high-frequency pressure monitoring device provided in an embodiment of the present disclosure;

[0035] Figure 2 A cross-sectional view of an embedded offline intelligent in-well high-frequency pressure monitoring device provided in an embodiment of this disclosure;

[0036] Figure 3A schematic diagram illustrating an application scenario of an embedded offline intelligent in-well high-frequency pressure monitoring device provided in one embodiment of this disclosure;

[0037] Figure 4 This is a front view of a centralizer provided in an embodiment of this disclosure. Detailed Implementation

[0038] Embodiments of this disclosure are described in detail below. Examples of these embodiments are illustrated in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain this disclosure, and should not be construed as limiting this disclosure.

[0039] It should be noted that while some technologies have been developed for bottomhole fracturing monitoring, these technologies suffer from drawbacks such as storage-based monitoring, the need for manual placement of equipment at the fracture site, and data processing lag. Furthermore, wellhead pressure monitoring equipment monitors pump inlet pressure at a frequency of 1Hz, meaning one pressure data point is collected per second. Since the lengths of surface fracturing wells and downhole pressure boreholes vary considerably, reaching hundreds of meters, the friction generated within the well has a highly complex impact on the fluid. Considering the challenges of hydrostatic pressure and frictional resistance along the flow path, it is difficult to quantitatively calculate the specific values, making it difficult to directly reflect the pressure at the fracture site. This results in a significant, even distorted, difference between the pressure monitored at the pump inlet and the pressure at the fracturing point within the well. Finally, no technology yet enables real-time monitoring, intelligent analysis, and dynamic control of bottomhole pressure.

[0040] The present disclosure will now be described in detail with reference to specific embodiments.

[0041] Figure 1 This is a schematic diagram of the structure of an embedded offline intelligent in-well high-frequency pressure monitoring device provided in an embodiment of this disclosure. Figure 1 As shown, the embedded offline intelligent in-well high-frequency pressure monitoring device includes:

[0042] The pressure monitoring module is in direct contact with the fluid in the well at the fracture opening, and is used to collect pressure data in situ at the fracture opening.

[0043] The data processing module is used to acquire pressure data, determine the crack characteristics corresponding to the pressure data, and generate parameter control instructions corresponding to the crack characteristics.

[0044] The data transmission module is used to send parameter control commands to the control center, so that the control center can adjust the parameters at the fracturing wellhead according to the parameter control commands.

[0045] According to some embodiments, the pressure monitoring module may employ a pressure sensor, the end face of which directly contacts the fluid in the well at the fracture opening, thereby enabling in-situ acquisition of pressure at the fracture opening.

[0046] In some embodiments, the data processing module may employ an integrated microprocessor to enable real-time processing of offline pressure data and generation of parameter control instructions.

[0047] In some embodiments, fracturing wellhead parameters include, but are not limited to, parameters such as wellhead displacement.

[0048] It should be noted that the device provided in this embodiment, by realizing real-time monitoring of fluid pressure at the fracture opening in the well and in-situ intelligent analysis of pressure data, generates parameter control commands and sends these commands to the control center. This provides hardware and theoretical basis for parameter control at the fracture wellhead, enabling real-time monitoring and dynamic control during the fracturing process. It overcomes the limitations of existing technologies in achieving real-time monitoring and intelligent analysis of pressure at the fracture opening in both surface and downhole fracturing processes, as well as dynamic control of fracturing parameters.

[0049] Optionally, the pressure monitoring module is used to collect pressure at the fracture opening in situ. When obtaining pressure data, it is specifically used for:

[0050] Pressure data is obtained by in-situ sampling of the pressure at the fracture opening using a preset sampling frequency, wherein the preset sampling frequency is not less than the sampling frequency threshold.

[0051] In some embodiments, the sampling frequency threshold is not specifically a fixed threshold. The sampling frequency threshold can be determined, for example, based on the actual application scenario.

[0052] In some embodiments, the pressure sensor may be a high-frequency piezoresistive sensor, thereby enabling real-time monitoring of high-frequency pressure at the crack opening.

[0053] For example, the pressure range of a high-frequency piezoresistive sensor can be 0-100MPa, and the sampling frequency can be ≥100Hz; the pressure range of a high-frequency piezoresistive sensor can also be 0-50MPa, and the sampling frequency can be no less than 20 data points per second, or 1 data point per 0.05 seconds.

[0054] Optionally, the crack characteristics include crack propagation events and the event types corresponding to the crack propagation events. When the data processing module determines the crack characteristics corresponding to the pressure data, it is specifically used for:

[0055] Time-domain and frequency-domain information is extracted from the pressure data;

[0056] By performing feature recognition on time-domain and frequency-domain information, the fracture propagation events and their corresponding event types during the fracturing process can be obtained.

[0057] According to some embodiments, the data processing module can perform continuous wavelet transform on the pressure data to decompose time-domain and frequency-domain information from the pressure data. Therefore, the accuracy and reliability of acquiring time-domain and frequency-domain information can be improved.

[0058] For example, crack propagation events and event types during fracturing can be identified by judging the characteristics of time-domain and frequency-domain information, such as multi-crack competitive propagation events and dominant single main crack propagation events.

[0059] In some embodiments, the data processing module can obtain a training database and use the training database to train an initial feature recognition model to obtain a trained feature recognition model; input time domain information and frequency domain information into the trained feature recognition model to obtain the fracture propagation events and the event types corresponding to the fracture propagation events during the fracturing process.

[0060] For example, a training database can be pre-established by labeling the dataset. The intelligent model can automatically learn the features of relevant events. If the model's recognition accuracy is greater than 95%, the model is considered basically reliable. The trained feature recognition model can be integrated into the data processing module using an embedded method, thereby realizing real-time analysis of pressure data and real-time identification of hydraulic fracturing events.

[0061] According to some embodiments, the data processing module can generate coded instructions corresponding to crack features based on the correspondence between crack features and codes; and determine parameter control instructions corresponding to crack features based on the coded instructions.

[0062] In some embodiments, the correspondence between crack features and codes can be stored in a coding database, and the correspondence stored in the coding database can be as shown in the following formula:

[0063]

[0064] In Equation (1) and Equation (2), the first column is the code corresponding to the crack feature, and the second column is the crack feature.

[0065] As shown in equations (1) and (2), the fracture characteristics also include the fracturing fluctuation rate characteristics, which can be set by setting a pressure fluctuation threshold. If the threshold is exceeded, a corresponding instruction will be generated.

[0066] As shown in equation (2), the coding database also stores the normal operation instruction "N". If no coding instruction is generated within the specified time threshold, the data processing module can send the normal operation instruction "N" to the data transmission module. This normal operation instruction indicates that the embedded offline intelligent in-well high-frequency pressure monitoring device is in normal working condition and that no adjustment to the fracturing wellhead parameters is required. This time threshold is not a fixed threshold; it can be adjusted according to the actual application scenario. For example, the time threshold could be 2 minutes.

[0067] It should be noted that the data processing module collects pressure data monitored by the pressure monitoring module, performs real-time analysis and storage, and obtains the crack characteristics corresponding to the pressure data. Then, the pre-identified crack propagation events are encoded, and the encoded instructions are simple byte instructions. This allows for real-time data processing through lightweight algorithms, reducing reliance on ground servers, enabling offline intelligent data analysis, and improving the convenience of subsequent data transmission.

[0068] The models, databases, and embedded hardware used in the data processing module can be configured according to the actual situation.

[0069] Optionally, Figure 2 This is a cross-sectional view of an embedded offline intelligent in-well high-frequency pressure monitoring device provided in an embodiment of this disclosure. Figure 2 As shown, the embedded offline intelligent in-well high-frequency pressure monitoring device also includes a device body 1, and a data transmission module including a data transmitting unit 6 and a data receiving unit 7; wherein,

[0070] The pressure monitoring module 3, the data processing module 5, and the data transmission unit 6 are all located inside the device body 1.

[0071] It should be noted that the purpose of setting up device body 1 is to protect the internal module. The shape, length and size of device body 1 can be set according to the wellbore. The key parameter of device body 1 is that the diameter of device body 1 is smaller than the diameter of the wellbore. Its shape, length and size can be adjusted according to actual needs and there are no restrictions on them.

[0072] In some embodiments, Figure 3 This diagram illustrates an application scenario of an embedded offline intelligent in-well high-frequency pressure monitoring device provided in one embodiment of this disclosure. Figure 3As shown, the application scenario involves the device body 1 being installed inside the packer string during fracturing to monitor the fluid pressure within the string during the fracture propagation process of the fracturing cluster. The string between the two packers constitutes the packer string, with the tail end of device body 1 directly connected to the head of the fracturing string. It, along with the string nozzle and the fracturing cluster position, is located within the packer string inside the fracturing well. Therefore, the pressure monitoring module 3 can monitor and collect the fluid pressure within the packer string, thereby obtaining the pressure data at the fracture opening.

[0073] The connection between the tail end of the device body 1 and the head of the fracturing string includes, but is not limited to, threaded connection, etc., and can be set according to the actual situation.

[0074] According to some embodiments, the data transmission unit 6 is used to receive and transmit parameter control commands.

[0075] In some embodiments, the data transmitting unit 6 may be, for example, an electromagnetic transmitter. The electromagnetic transmitter may employ 1-10kHz low-frequency electromagnetic wave modulation technology to send the electromagnetic signal corresponding to the parameter control command to the data receiving unit 7 at the wellhead, with a communication distance ≥500 meters. Figure 3 As shown.

[0076] According to some embodiments, the data receiving unit 7 is used to receive parameter control instructions transmitted by the data transmitting unit and send the parameter control instructions to the control center.

[0077] In some embodiments, the data receiving unit 7 may be located at the wellhead, on the ground, or in a remote control center.

[0078] In some embodiments, the data receiving unit 7 may be, for example, an electromagnetic receiver. The electromagnetic receiver can receive electromagnetic signals transmitted downhole, decode them to obtain parameter control instructions, and forward these instructions to the control center so that the control center can adjust the fracturing wellhead parameters according to the instructions, such as... Figure 3 As shown.

[0079] When the control center receives a parameter adjustment command, it can also display the corresponding fracturing crack propagation event in real time.

[0080] It should be noted that, as Figure 3As shown, the transmission distance between the data receiving unit 7 and the data transmitting unit 6 is usually far, and there are unstable fluids such as fracturing fluid in the well. It is not possible to wirelessly transmit large amounts of data in real time. Therefore, the simple byte instruction is pre-released in the data processing module 5, as shown in Equations (1) and (2). The instruction byte number is 1, so the wireless real-time transmission instruction can be realized by electromagnetic method. This ensures the real-time acquisition and analysis of pressure data at the fracturing opening, and at the same time ensures that the ground or remote control center can receive the data analysis results in real time. This avoids the error of indirect measurement and also avoids the wireless transmission problem caused by large amounts of data.

[0081] Optionally, such as Figure 2 As shown, the device body 1 also includes a centralizer 2; wherein,

[0082] The centralizer 2 is located at the head of the device body 1 so that the device body 1 fits tightly against the well wall.

[0083] In some embodiments, when the straightener 2 is disposed at the head of the device body 1, it can be connected to the head of the device body 1.

[0084] in, Figure 4 This is a front view of a centralizer provided in an embodiment of this disclosure. Figure 4 As shown, the centralizer 2 adopts a spring support structure, which can ensure that the device body 1 fits tightly against the well wall, avoid displacement caused by downhole vibration, and ensure the stability of the device body 1 in the curved wellbore. In addition, the centralizer 2 is hollow in the center, which exposes the end face of the pressure monitoring module 3, allowing the end face of the pressure monitoring module 3 to directly contact the fluid in the packer string.

[0085] Among them, such as Figure 2 and Figure 3 As shown, the centralizer 2 is installed at the head of the fracturing tubing string to stabilize the device body 1 inside the packer tubing string, ensuring the stable delivery of the device body 1 and avoiding equipment bending accidents caused by wellbore bending.

[0086] The dimensions of the centralizer 2 can be designed to match the dimensions of the tubing in the well.

[0087] Optionally, such as Figure 2 As shown, the device body 1 also includes a power supply module 4; wherein,

[0088] The power supply module 4 is used to supply power to multiple modules within the device body 1, including but not limited to the pressure monitoring module 3, the data processing module 5, and the data transmission unit 6.

[0089] In some embodiments, the battery capacity and size of the power module 4 are set according to actual conditions. For example, the power module 4 needs to provide enough power to allow the device body 1 to operate continuously for a period of not less than the duration of one well fracturing cycle. For example, the power module 4 can use a high-temperature resistant and explosion-proof lithium battery pack to support the device body 1 to operate continuously downhole for ≥72 hours.

[0090] Optionally, such as Figure 2 As shown, pressure monitoring module 3 is the first module at the head of device body 1, with its pressure acquisition end face exposed inside the packer column, directly contacting the liquid inside the packer column, thus allowing direct acquisition of the liquid pressure inside the column. Power module 4 is the second module at the head of device body 1, facilitating power supply to multiple modules within device body 1. Data processing module 5 is the third module at the head of device body 1, and data transmission unit 6 is the fourth module at the head of device body 1, facilitating subsequent analysis of pressure data and transmission of commands.

[0091] In some embodiments, the assembly order of the internal modules of the device body 1 does not specifically refer to the fixed order described above, and the assembly order can be adjusted according to the actual application scenario.

[0092] Furthermore, the different modules are interconnected. Battery module 4 provides power to pressure monitoring module 3, data processing module 5, and data transmission unit 6. Pressure monitoring module 3 collects pressure data and transmits it to data processing module 5. Data processing module 5 stores and analyzes the pressure data, generates corresponding instructions based on the analysis results, and transmits the instructions to data transmission unit 6. Data transmission unit 6 then sends the instructions to data receiving unit 7. The logical interconnections can be configured according to actual conditions.

[0093] In summary, the embedded offline intelligent in-well high-frequency pressure monitoring device provided in this disclosure provides hardware and theoretical basis for parameter control at the fracturing wellhead by enabling real-time monitoring of fluid pressure at the fracturing inlet, in-situ intelligent analysis of pressure data, generating parameter control commands, and sending these commands to the control center. This allows for real-time monitoring and dynamic control during the fracturing process. It overcomes the limitations of existing technologies in achieving real-time monitoring and intelligent analysis of pressure at the fracturing inlet during both surface and downhole fracturing, as well as dynamic control of fracturing parameters.

[0094] The collection, storage, use, processing, transmission, provision, and disclosure of user personal information involved in this disclosure all comply with the provisions of relevant laws and regulations and do not violate public order and good morals.

[0095] It should be noted that personal information collected from users should be used for legitimate and reasonable purposes and should not be shared or sold outside of these legitimate uses. Furthermore, such collection / sharing should only be conducted after receiving the user's informed consent, including but not limited to notifying the user to read the user agreement / user notice and sign an agreement / authorization that includes authorization of relevant user information before the user uses the function. In addition, any necessary steps must be taken to protect and safeguard access to such personal information data and ensure that others with access to personal information data comply with their privacy policies and procedures.

[0096] This disclosure is intended to provide implementation schemes for users to selectively prevent the use or access to their personal information data. Specifically, this disclosure is intended to provide hardware and / or software to prevent or block access to such personal information data. Once personal information data is no longer needed, risks can be minimized by restricting data collection and deleting data. Furthermore, where applicable, such personal information is de-identified to protect user privacy.

[0097] The acquisition, transmission, storage, use, and processing of data in this disclosed technical solution all comply with the relevant provisions of national laws and regulations.

[0098] It should be noted that in the embodiments disclosed herein, certain software, components, models, and other existing solutions in the industry may be mentioned. These should be considered as exemplary and are intended only to illustrate the feasibility of implementing the technical solution of this application. However, they do not mean that the applicant has used or necessarily used such solutions.

[0099] In the foregoing descriptions of the embodiments, the terms "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of this disclosure. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0100] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this disclosure, "a plurality of" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0101] Any process or method description in the flowchart or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or more executable instructions for implementing custom logic functions or processes, and the scope of preferred embodiments of this disclosure includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order depending on the functions involved, as will be understood by those skilled in the art to which embodiments of this disclosure pertain.

[0102] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-included system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of computer-readable media include: an electrical connection having one or more wires (electronic device), a portable computer disk drive (magnetic device), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Furthermore, computer-readable media can even be paper or other suitable media on which programs can be printed, because programs can be obtained electronically, for example, by optically scanning the paper or other media, followed by editing, interpreting, or otherwise processing as necessary, and then stored in computer memory.

[0103] It should be understood that various parts of this disclosure can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented using software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0104] Those skilled in the art will understand that all or part of the steps of the methods described in the above embodiments can be implemented by a program instructing related hardware, and the program can be stored in a computer-readable storage medium. When executed, the program includes one or a combination of the steps of the method embodiments.

[0105] Furthermore, the functional units in the various embodiments of this disclosure can be integrated into a processing module, or each unit can exist physically separately, or two or more units can be integrated into a module. The integrated module can be implemented in hardware or as a software functional module. If the integrated module is implemented as a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium.

[0106] The storage medium mentioned above can be a read-only memory, a disk, or an optical disk, etc. Although embodiments of the present disclosure have been shown and described above, it is to be understood that the above embodiments are exemplary and should not be construed as limiting the present disclosure. Those skilled in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of the present disclosure.

Claims

1. An embedded offline intelligent in-well high-frequency pressure monitoring device, characterized in that, include: The pressure monitoring module is in direct contact with the fluid in the well at the fracture opening, and is used to collect pressure data in situ at the fracture opening. The data processing module is used to acquire the pressure data, determine the crack characteristics corresponding to the pressure data, and generate parameter control instructions corresponding to the crack characteristics. The data transmission module is used to send the parameter adjustment command to the control center, so that the control center can adjust the fracturing wellhead parameters according to the parameter adjustment command; The pressure monitoring module is used to collect pressure at the fracture opening in situ. When obtaining pressure data, it is specifically used for: Pressure data is obtained by in-situ sampling of the pressure at the fracture opening using a preset sampling frequency, wherein the preset sampling frequency is not less than a sampling frequency threshold. The crack features include crack propagation events and the event types corresponding to the crack propagation events. When determining the crack features corresponding to the pressure data, the data processing module is specifically used for: Time-domain and frequency-domain information are extracted from the pressure data; By performing feature recognition on the time-domain information and the frequency-domain information, the fracture propagation events during the fracturing process and the event types corresponding to the fracture propagation events are obtained. The data processing module is used to perform feature recognition on the time-domain information and the frequency-domain information to obtain fracture propagation events during the fracturing process and the event types corresponding to the fracture propagation events, including: Obtain a training database and use the training database to train the initial feature recognition model to obtain a trained feature recognition model; The time-domain information and the frequency-domain information are input into the trained feature recognition model to obtain the fracture propagation events during the fracturing process and the event types corresponding to the fracture propagation events; When the data processing module generates parameter adjustment instructions corresponding to the crack features, it is specifically used for: Based on the correspondence between crack features and codes, generate the coding instructions corresponding to the crack features; The parameter control instruction corresponding to the crack feature is determined according to the encoded instruction; The device further includes a device body, and the data transmission module includes a data transmitting unit and a data receiving unit; wherein... The device body is installed inside the packer column. The pressure monitoring module, the data processing module, and the data transmission unit are all installed inside the device body. The data transmission unit is used to receive and transmit the parameter control command. The data receiving unit is used to receive the parameter control command transmitted by the data transmitting unit and send the parameter control command to the control center.

2. The apparatus according to claim 1, characterized in that, When the data processing module is used to decompose time-domain information and frequency-domain information from the pressure data, it is specifically used for: Continuous wavelet transform is performed on the pressure data to decompose time-domain and frequency-domain information from the pressure data.

3. The apparatus according to claim 1, characterized in that, The data processing module is also used for: If the encoded instruction is not generated within the time threshold, a normal operation instruction is sent to the data transmission module. The normal operation instruction is used to indicate that the embedded offline intelligent in-well high-frequency pressure monitoring device is in normal working condition and that there is no need to adjust the fracturing wellhead parameters.

4. The apparatus according to claim 1, characterized in that, The device also includes a central stabilizer; wherein... The centralizer is located at the head of the device body so that the device body fits tightly against the well wall.

5. The apparatus according to claim 1, characterized in that, The device also includes a power module; wherein... The power module is used to supply power to the pressure monitoring module, the data processing module, and the data transmission unit.

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