Fault monitoring method and system for separate injection water distributor, electronic equipment and storage medium

Abstract

The invention discloses a fault monitoring method and system for a separate injection water distributor, electronic equipment and a storage medium, and relates to the technical field of oil field automation control. The method comprises the following steps: comprehensively monitoring multi-dimensional data such as pressure inside and outside an oil pipe, liquid flow and the like, and combining data threshold comparison and dynamic trend analysis to comprehensively evaluate the running state of the water distributor, and effectively judging whether a dropping-fishing core is stuck or not by utilizing a wireless communication state between a wireless positioning short section and an external pressure short section; the abnormal initial judgment result is subjected to matching and binary coding by means of a preset fault logic model, and fault information is uploaded to a ground system in a pressure-flow wave form through wave code signal conversion, so that the reliability and the operation and maintenance efficiency of a separate injection process are improved, various faults can be recognized in time, injection stop of a water injection well caused by fault expansion is avoided, and the injection efficiency is improved. The number of times of non-planned well repair operation is greatly reduced, the maintenance cost is reduced, and key technical support is provided for intelligent and fine management of the separated layer water injection process.

Description

TECHNICAL FIELD

[0001] The application relates to the technical field of oilfield automation control, in particular to a fault monitoring method and system of a separate injection water distributor, an electronic device and a storage medium. BACKGROUND

[0002] In the separate layer water injection process of oilfield development, the separate injection water distributor is the core equipment for regulating and controlling the water injection amount of each oil layer, and the stability of its operating state directly affects the water injection efficiency and the development effect of the oil reservoir. With the development of oilfield automation control technology, intelligent separate injection water distributors have been widely used in downhole operations, but they are long-term exposed to the complex downhole environment of high temperature, high pressure and high salinity, and are prone to faults due to problems such as sensor aging, mechanical part jamming, and wireless communication interference. If not discovered and handled in time, it may lead to serious consequences such as injection well stoppage, imbalance of formation liquid supply, and increase of non-planned workover operation frequency and maintenance cost.

[0003] After detecting the abnormality, the existing system often takes global shutdown or restart measures due to ambiguous fault type identification, resulting in forced interruption of normal modules and prolonging system recovery time. Therefore, there is an urgent need for a separate injection water distributor fault monitoring method that can integrate multi-dimensional data, accurately identify fault types, and reliably transmit fault information, to improve the intelligent and fine management level of the separate layer water injection process and ensure the long-term stable operation of the injection well. SUMMARY

[0004] The purpose of the present application is to provide a separate injection water distributor fault monitoring method and system, an electronic device and a storage medium to solve the problems raised in the background.

[0005] In a first aspect, an embodiment of the present application provides a separate injection water distributor fault monitoring method applied to a separate injection water distributor including a downhole working barrel and a fishing core, the downhole working barrel being connected with the oil pipe, the downhole working barrel being provided with a wireless positioning outer pressure short section, the fishing core being provided with a wireless positioning short section, the method comprising: collecting oil pipe internal pressure data, oil pipe external pressure data and oil pipe internal liquid flow data; comparing the pressure data and the flow data with the preset standard operating parameters respectively to determine whether the pressure data and the flow data are beyond the normal range; analyzing the data change trend after entering the stable working mode to determine whether there is an abnormal trend of continuous rise or fall; judging whether the fishing core is jammed based on the wireless communication state between the wireless positioning short section and the wireless positioning outer pressure short section; inputting the abnormal preliminary judgment result into a preset fault logic model, and outputting the corresponding fault type according to the model rule matching; binary encoding the determined fault type, and the wireless positioning short section sends the encoded fault information to the wireless positioning outer pressure short section in the wave code signal; the wireless positioning outer pressure short section receives the signal, and converts the wave code signal containing the fault information into a pressure-flow wave and sends it to the ground system.

[0006] In some implementations of the first aspect, the pressure data and the flow data are compared with preset standard operating parameters respectively to determine whether the pressure data and the flow data are out of a normal range, including: comparing the tubing internal pressure data with a preset internal pressure normal range, and if the tubing internal pressure data is out of the preset internal pressure normal range, marking as internal pressure single-point overrun; comparing the tubing liquid flow data with a reference flow range, and if the tubing liquid flow data is out of the reference flow range, marking as flow single-point overrun; comparing the tubing external pressure data with an external pressure normal range, and if the tubing external pressure data is out of the external pressure normal range, marking as external pressure single-point overrun.

[0007] In some implementations of the first aspect, the data trend after entering the stable working mode is analyzed to determine whether there is an abnormal trend of continuous rise or fall, including: continuously collecting M times of internal pressure data within a set first trend analysis period, and if N times of the internal pressure data are out of the standard range, determining that the internal pressure is continuously overrun; M and N are positive integers, and M is greater than N; continuously collecting P times of external pressure data within a set second trend analysis period, and if Q times of the external pressure data are out of the standard range, determining that the external pressure is continuously overrun; P and Q are positive integers, and P is greater than Q.

[0008] In some implementations of the first aspect, the fault logic model includes mapping rules of data overrun and fault type, mapping rules of trend abnormality and fault type, and mapping rules of communication state and stuck type, and the fault type includes pressure sensor fault, flow sensor fault, fishing core stuck fault, and wireless communication fault; the abnormal preliminary judgment result is input into a preset fault logic model, and a corresponding fault type is matched and output according to the model rules, including: if the abnormal preliminary judgment result is that the pressure data is out of the preset standard pressure range, the fault logic model matches and outputs the pressure sensor fault according to the mapping rules of data overrun and fault type; if the abnormal preliminary judgment result is that the flow data is out of the preset standard flow range, the fault logic model matches and outputs the flow sensor fault according to the mapping rules of data overrun and fault type; if the abnormal preliminary judgment result is that the wireless positioning nipple and the wireless positioning external pressure nipple are in communication interruption or the communication signal strength is continuously lower than a preset signal value, the fault logic model matches and outputs the fishing core stuck fault or the wireless communication fault according to the mapping rules of communication state and stuck type; if the abnormal preliminary judgment result is that the pressure data or the flow data has an abnormal trend of continuous rise or fall after entering the stable working mode, the fault logic model matches and outputs the corresponding sensor fault according to the mapping rules of trend abnormality and fault type.

[0009] In conjunction with the first aspect, in some implementations of the first aspect, the initial anomaly judgment result is a single-dimensional anomaly result. The initial anomaly judgment result is input into a preset fault logic model, and the corresponding fault type is matched and output according to the model rules. This also includes: when the initial anomaly judgment result is a single-point internal pressure exceeding the limit, the preset fault logic model matches and outputs an internal pressure sensor fault based on the mapping rules between data exceeding the range and fault types; when the initial anomaly judgment result is a single-point flow exceeding the limit, the preset fault logic model matches and outputs a flow sensor fault based on the mapping rules between data exceeding the range and fault types; when the initial anomaly judgment result is a single-point external pressure exceeding the limit, the preset fault logic model matches and outputs an external pressure sensor fault based on the mapping rules between data exceeding the range and fault types; when the initial anomaly judgment result is a continuous internal pressure exceeding the limit, the fault logic model matches and outputs an internal pressure sensor fault based on the mapping rules between trend anomalies and fault types; when the initial anomaly judgment result is a continuous external pressure exceeding the limit... When the limit is exceeded, the fault logic model matches and outputs an external pressure sensor fault based on the mapping rule between trend anomalies and fault types; it obtains communication signal strength, arrival confirmation signal, interaction frequency, and positioning deviation data from the wireless positioning sub-section, and obtains the arm extension feedback signal from the support arm assembly of the retrieval core; when the initial anomaly judgment result is that the support arm extension feedback signal is missing and the communication signal strength is continuously lower than the preset signal value, the fault logic model matches and outputs a retrieval core jamming fault based on the mapping rule between communication status and jamming type; when the initial anomaly judgment result is that the arrival confirmation signal is not received and the positioning deviation data exceeds the preset difference, the fault logic model matches and outputs a retrieval core deployment jamming fault based on the mapping rule between communication status and jamming type; when the initial anomaly judgment result is that the communication interaction interruption is greater than the preset time and the position deviation exceeds the threshold, the fault logic model matches and outputs a retrieval core jamming fault during operation based on the mapping rule between communication status and jamming type.

[0010] In conjunction with the first aspect, in some implementations of the first aspect, the initial anomaly judgment result is a multi-dimensional anomaly result. The initial anomaly judgment result is input into a preset fault logic model, and the corresponding fault type is matched and output according to the model rules. It also includes: for the multi-dimensional anomaly result, matching and outputting the corresponding fault type according to the layer-by-layer verification rules of the built-in logic tree of the preset fault logic model. The first layer of verification is to determine whether there are simultaneous single-point pressure over-limit and single-point flow over-limit. If so, it proceeds to the second layer of verification. The second layer of verification is to verify whether the changing trends of pressure data and flow data are consistent. If the trends are consistent and both show abnormal changes, it further verifies whether the wireless communication status is normal. The third layer of verification is that if the wireless communication status is normal, it is determined that the related data anomaly is caused by the formation fluid supply anomaly. If the wireless communication status is abnormal, the combined fault type of sensor fault and wireless communication fault is matched and output by combining the signal interaction success rate and positioning deviation data.

[0011] In conjunction with the first aspect, in some implementations of the first aspect, the determined fault type is binary encoded, including: setting a fault judgment code bit for 1 instruction transmission interval, where encoding 0 indicates no fault and encoding 1 indicates a fault exists; assigning a corresponding binary fault code to each known fault type, with a single fault code occupying 4 instruction transmission intervals; assigning a preset unknown fault code to unknown faults, with the unknown fault code occupying 4 instruction transmission intervals; if multiple faults exist, encoding them in the order of fault judgment code bit → first fault code → second fault code → ... → last fault code → end signal, with the end signal being a fixed code for 1 instruction transmission interval.

[0012] Secondly, one embodiment of this application provides a fault monitoring system for a water injection distribution device. The system includes: a downhole working cylinder connected to the tubing and placed in the downhole water injection zone; the downhole working cylinder includes a wireless positioning external pressure section; a retrieval core, separately installed inside the downhole working cylinder, which can be deployed and retrieved at a fixed point inside the tubing using a retrieval tool; the retrieval core includes a wireless positioning section; a sensor module for collecting pressure data inside the tubing, pressure data outside the tubing, and fluid flow data inside the tubing; a data processing module connected to the sensor module for comparing the pressure and flow data with preset standard operating parameters to determine whether they exceed the normal range, and analyzing the data change trend after entering a stable operating mode to determine whether there is an abnormal trend of continuous increase or decrease; and a jamming detection module. The system comprises the following modules: a fault detection module, integrated into the wireless positioning sub-section or the wireless positioning external pressure sub-section, used to determine whether the retrieval core is stuck based on the wireless communication status of the wireless positioning sub-section and the wireless positioning external pressure sub-section; a fault diagnosis module, connected to the data processing module and the stuck detection module, with a built-in preset fault logic model, used to match and output the corresponding fault type based on the initial anomaly judgment result; an encoding module, connected to the fault diagnosis module, used to perform binary encoding on the determined fault type; and a wavecode communication module, including a signal transmission unit and a signal conversion unit. The signal transmission unit, integrated into the wireless positioning sub-section, is used to embed the encoded fault information into the wavecode signal and transmit it. The signal conversion unit, integrated into the wireless positioning external pressure sub-section, is used to receive the wavecode signal and convert the wavecode signal containing the fault information into a signal, which is then transmitted to the ground system.

[0013] Thirdly, one embodiment of this application provides an electronic device, the electronic device comprising: a processor; a memory for storing processor-executable instructions; the processor being configured to perform the method mentioned in the first aspect above.

[0014] Fourthly, one embodiment of this application provides a computer-readable storage medium storing a computer program for performing the method mentioned in the first aspect above.

[0015] The fault monitoring method for the water distributor provided in this application comprehensively monitors multi-dimensional data such as pressure inside and outside the tubing and fluid flow rate, and combines data threshold comparison and dynamic trend analysis to comprehensively evaluate the operating status of the water distributor, significantly improving the accuracy of fault identification and early warning capability. Utilizing the wireless communication status between the wireless positioning sub and the external pressure sub, it can effectively determine whether the core is stuck. Furthermore, it uses a preset fault logic model to intelligently match and binary encode anomalies, and uploads the fault information to the surface system in the form of pressure-flow waves through wavecode signal conversion, establishing a reliable and efficient downhole-to-surface information transmission channel, improving the reliability and maintenance efficiency of the water injection process. This method can promptly identify multiple faults, preventing fault escalation that could lead to well shutdown, significantly reducing unplanned well workover operations, lowering maintenance costs, and providing key technical support for the intelligent and refined management of the stratified water injection process. Attached Figure Description

[0016] Figure 1 This is a schematic diagram of the structure of an intelligent water distribution device with positioning and retrieval wavecode, which is provided as another exemplary embodiment of this application.

[0017] Figure 2 A schematic diagram of the installation structure of the downhole working barrel and the core dropping / retrieval device, which is another exemplary embodiment of this application.

[0018] Figure 3 A schematic diagram of a downhole working cylinder structure provided as another exemplary embodiment of this application.

[0019] Figure 4 A schematic diagram of the core structure for launching and retrieving, provided as another exemplary embodiment of this application.

[0020] Figure 5 A schematic diagram of the interface structure between the retrieval core and the working cylinder, provided as another exemplary embodiment of this application.

[0021] Figure 6 A schematic diagram of the interface structure between the support arm assembly and the working cylinder, provided as another exemplary embodiment of this application.

[0022] Figure 7 A schematic diagram of a partial structure of a retrieval core provided as another exemplary embodiment of this application.

[0023] Figure 8 The diagram shown is a flowchart illustrating a fault monitoring method for a water distributor according to an embodiment of this application.

[0024] Figure 9 The diagram shown is a structural schematic of an electronic device provided in an exemplary embodiment of this application.

[0025] In the diagram: 1. Downhole working tube; 2. Drop-out core; 3. Downhole packer; 4. Surface system; 5. Wellhead Christmas tree; 6. Casing; 7. Surface blowout preventer; 8. Tubing; 1-1. Lower connector; 1-2. Water nozzle assembly; 1-3. Interface assembly; 1-4. Outer casing; 1-5. Wireless positioning external pressure sub; 2-1. Adjustment assembly; 2-2. Support arm assembly; 2-3. Motor drive section; 2-4. Wireless positioning sub; 2-5. Circuit power supply sub; 2-6. Centralizing sub; 2-7. Flow and pressure sub; 2-8. Retrieval head; 2-9. Support arm; 2-10. Anti-rotation key; 13-1. Support platform; 13-2. Anti-rotation slot; 13-3. Adjustment slot. Detailed Implementation

[0026] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0027] Exemplary device Combination Figures 1 to 7 The intelligent water distribution device with positioning and retrieval wavecode provided in this embodiment has a downhole working cylinder 1 connected vertically to the tubing string and permanently placed downhole. The retrieval core 2 is placed inside the downhole working cylinder 1. The tubing string sequentially connects the downhole working cylinder 1 and the packer 3, placing them inside the casing 6, with the upper end suspended at the wellhead. A Christmas tree 5 is installed at the wellhead for sealing. A blowout preventer 7 is threadedly installed above the Christmas tree 5 and can be disassembled and reassembled as needed. The surface system 4 is installed at the water inlet valve of the Christmas tree 5 via a flange.

[0028] The upper end of the downhole working tube 1 is a wireless positioning external pressure section 1-5. The wireless positioning external pressure section 1-5 includes an external pressure sensor, an external pressure circuit and power supply module, and a wireless communication module. The external pressure sensor can measure the external pressure of the tubing 8, and the wireless communication module can wirelessly exchange information with the launch and retrieval core 2 and store data.

[0029] The lower end is the lower connector 1-1, which provides an installation interface and water injection channel for the water nozzle assembly 1-2, and an installation interface for the interface assembly 1-3. It connects to the upper end via the outer protective tube 1-4, isolating the oil pipe from the inside and outside. The water nozzle assembly 1-2 adjusts the flow rate by adjusting the outlet area. The interface assembly 1-3 provides a support platform, anti-rotation position, and adjustment interface for the retrieval core 2, ultimately transmitting the driving force of the retrieval core 2 to the water nozzle assembly 1-2 via gears. The upper part of the interface assembly 1-3 is the support platform 13-1 for the support arm 2-9, and the middle part is the anti-rotation slot 13-2. The lower part is the interface adjustment slot 13-3 for the adjustment assembly.

[0030] The lower end of the retrieval core 2 is an adjustment assembly 2-1, which is connected to the motor drive unit 2-3 via a shaft and can rotate in both directions. The support arm assembly 2-2 includes a support arm 2-9 and an anti-rotation key 2-10. The support arm 2-9 can extend and retract, and the anti-rotation key 2-10 provides radial limit. The motor drive unit 2-3 internally includes the motor and its control components, and is externally sealed with a pressure-bearing housing. The wireless positioning sub-section 2-4 internally includes a wireless communication module, which can communicate wirelessly with the downhole working tube 1. The circuit power supply sub-section 2-5 includes a control circuit and a power supply battery, controlling each sub-section and component and providing power and data storage functions. The centering sub-section 2-6 ensures that the retrieval core is centered in the instrument and tubing channel, providing support for the flow meter and core to move up and down normally. The flow and pressure sub-section 2-7 includes an electromagnetic flow meter and an internal pressure sensor. The electromagnetic flow meter can measure the flow rate passing through the retrieval core 2, and the internal pressure sensor can measure the pressure inside the tubing 8 in real time and transmit the data to the data processing module. The retrieval head 2-8 is located at the upper end of the retrieval core 2 and is mainly used to provide an interface for retrieval and deployment instruments.

[0031] In a specific implementation process, the downhole working tube 1 and the drop-out core 2 are located in the downhole tool string. The tool string includes the downhole working tube 1, packer 3, tubing string, etc., and is connected and sealed by tubing 8. Each downhole working tube 1 is sealed with its own cavity by the packer 3. The fluid in the tubing 8 enters the formation through the holes on the casing 6 after passing through the sealed cavity of the downhole working tube 1. The wellhead Christmas tree controls various valves to allow the fluid to be injected into the downhole from the tubing 8. The surface equipment 4 controls the pressure of the injected fluid to form an orderly code pattern, and then transmits the data to the downhole. The external pressure sensor of the wireless positioning external pressure subsection 1-5 can measure the external pressure of the tubing 8. The flow and pressure subsection 2-7 includes an electromagnetic flowmeter and an internal pressure sensor. The electromagnetic flowmeter can measure the flow rate through the drop-out core 2, and the internal pressure sensor can measure the pressure inside the tubing 8 in real time and transmit the data to the data processing module. The data processing module compares pressure and flow data with preset standard operating parameters to determine if they exceed normal ranges and analyzes data change trends after entering stable operating mode to determine if there are any abnormal trends of continuous increase or decrease. The jamming detection module, integrated into the wireless positioning sub-section 2-4 or the wireless positioning external pressure sub-section 1-5, determines whether the retrieval core is jammed based on the wireless communication status between the two sub-sections. The fault diagnosis module has a built-in preset fault logic model to match and output the corresponding fault type based on the initial anomaly judgment result. The encoding module performs binary encoding on the determined fault type. The wavecode communication module includes a signal transmission unit and a signal conversion unit. The signal transmission unit, integrated into the wireless positioning sub-section, embeds the encoded fault information into the wavecode signal and transmits it. The signal conversion unit, integrated into the wireless positioning external pressure sub-section, receives the wavecode signal and converts the wavecode signal containing fault information into a pressure-flow wave, which is then transmitted to the ground system 4.

[0032] When retrieving the core 2, the retrieval tool is inserted from the surface blowout preventer 7 into the tubing and then downhole along the inner cavity of the tubing 8. The retrieval device uses the retrieval head 2-8 to grab the core 2 and retrieve it from the tubing 8. During the retrieval process, the support arm 2-9 retracts freely under the pulling force. Specifically, after opening, the support arm 2-9 springs outward under the force of a spring. When pulled, the tubing wall and the reducer compress the support arm 2-9, causing the spring to contract. However, when there is no reducer or tubing wall compression, the support arm 2-9 automatically opens again; that is, the support arm 2-9 only contracts and does not return to its original position.

[0033] When deploying the retrieval core 2, the deployer grabs the retrieval head 2-8 of the retrieval core 2 and enters the tubing through the surface blowout preventer 7. At this time, the support arm 2-9 is in the retracted state. After the retrieval core 2 passes through the downhole working tube 1 of the current layer, the retrieval core 2 is pulled up above the downhole working tube 1. At this time, the support arm 2-9 assembly 2-2 is squeezed by the diameter change of the downhole working tube lower connector 1-1 and opens. After continuing to lower, the support arm 2-9 encounters resistance at the support platform 13-1 and cannot be lowered further. Then the deployer releases the retrieval head 2-8. At this time, the retrieval core 2 has been deployed in place, and the deployer is then removed from the tubing 8. The retrieval core 2 communicates with the wireless positioning external pressure section 1-5 of the downhole working tube via the wireless positioning sub-section 2-4 to confirm that the core is in place. By rotating the adjustment assembly 2-1, the adjustment assembly 2-1 is engaged with the adjustment slot 13-3 in the interface assembly 1-3, and the locking key is engaged with the anti-rotation slot 13-2. If flow rate adjustment is required, continue rotating adjustment component 2-1, which will then drive water nozzle component 1-2 to adjust the flow rate.

[0034] Exemplary methods Figure 8 The diagram shown is a flowchart illustrating a fault monitoring method for a water distributor according to an embodiment of this application. Figure 8 As shown in the embodiment of this application, the fault monitoring method for the water distribution device is applied to a water distribution device including a downhole working tube and a retrieval core. The downhole working tube is connected to the tubing, and the downhole working tube is equipped with a wireless positioning external pressure short section. The retrieval core is equipped with a wireless positioning short section. The method includes the following steps.

[0035] Step 800: Collect pressure data inside the tubing, pressure data outside the tubing, and fluid flow data inside the tubing.

[0036] Real-time data acquisition using multi-dimensional sensors: After the water distribution unit is started, the internal pressure sensor of the flow and pressure sub-section collects the pressure data inside the oil pipe in real time, the electromagnetic flow meter collects the liquid flow data inside the oil pipe in real time, and the external pressure sensor of the wireless positioning external pressure sub-section collects the external pressure data outside the oil pipe in real time. Each sensor converts the collected pressure and flow data into electrical signals at preset intervals and transmits them to the microprocessor of the retrieval core. At the same time, the signals are cached in the short-term memory of the retrieval core to form a traceable sequence of operating data.

[0037] It should be understood that the preset interval can be 100 milliseconds, or it can be set to other values ​​according to the actual situation.

[0038] Step 801: Compare the pressure data and flow data with the preset standard operating parameters to determine whether the pressure data and flow data exceed the normal range.

[0039] Specifically, the pressure data inside the oil pipe is compared with the preset normal internal pressure range. If it exceeds the normal internal pressure range, it is marked as a single point of internal pressure exceeding the limit. The fluid flow data inside the oil pipe is compared with the reference flow range. If it exceeds the reference flow range, it is marked as a single point of flow exceeding the limit. The external pressure data of the oil pipe is compared with the normal external pressure range. If it exceeds the normal external pressure range, it is marked as a single point of external pressure exceeding the limit.

[0040] In one embodiment, after each receipt of sensor data (every 100 milliseconds), a single-point numerical comparison is immediately performed: the real-time internal pressure value of the internal pressure sensor (e.g., 10.8 MPa) is extracted and compared with the currently adapted normal internal pressure range (9.5-10.5 MPa). If it exceeds the range (10.8 MPa > 10.5 MPa), it is marked as "single-point internal pressure exceeding limit" and temporarily stored in the abnormal buffer area; simultaneously, the real-time flow rate value (e.g., 0.03 m³ / min) is compared with the normal flow rate range (0.035-0.04 m³ / min). If it is lower than the lower limit, it is marked as "single-point flow rate exceeding limit"; the real-time external pressure value (e.g., 2.5 MPa) is compared with the normal external pressure range (0.5-2 MPa). If it exceeds the upper limit, it is marked as "single-point external pressure exceeding limit". The numerical ranges in this embodiment are only for example, and other numerical ranges are also possible.

[0041] Step 802: Analyze the data change trend after entering the stable working mode to determine whether there is an abnormal trend of continuous rise or fall.

[0042] Specifically, within the first trend analysis period, internal pressure data is collected M times continuously. If N of these data exceed the standard range, it is determined that the internal pressure is continuously exceeding the limit. M and N are both positive integers, and M is greater than N. Within the second trend analysis period, external pressure data is collected P times continuously. If Q of these data exceed the standard range, it is determined that the external pressure is continuously exceeding the limit. P and Q are both positive integers, and P is greater than Q.

[0043] In one specific embodiment, the first trend analysis cycle is 5 data acquisition cycles, i.e., 500 milliseconds, continuously collecting 5 single-point data. If 3 or more of them exceed the standard range (e.g., internal pressure is 10.6MPa, 10.7MPa, and 10.8MPa for 3 consecutive times, all exceeding the 10.5MPa upper limit), it is judged as "internal pressure continuously exceeding the limit" and transferred from the "abnormal buffer area" to the "fault judgment area". If the single-point exceedance only occurs 1-2 times and the subsequent data returns to the normal range (e.g., internal pressure drops from 10.6MPa to 10.4MPa), it is judged as "instantaneous fluctuation", the abnormal mark is cleared, and unnecessary warnings are avoided.

[0044] In one specific embodiment, considering the more frequent external pressure fluctuations under high-risk well conditions (such as deep wells and high-pressure formations), it is necessary to improve the judgment sensitivity. The second trend analysis cycle is set to 4 data acquisition cycles (corresponding to a duration of 400 milliseconds), i.e., P=4; Q=2 is set (allowing fewer instances of exceeding the limit to trigger the judgment, avoiding delays in risk warnings), and the normal range of external pressure is 0.8-2.5MPa (dynamically adapted according to the deep well formation pressure). The external pressure sensor continuously collects 4 sets of data, namely 2.6MPa, 2.7MPa, 2.4MPa, and 2.8MPa. Among them, 3 sets of data at 2.6MPa, 2.7MPa, and 2.8MPa exceed the upper limit of the normal range (2.5MPa), with 3 instances of exceeding the limit > Q=2 instances, which is judged as "continuous external pressure exceeding the limit". For single-point exceeding data, further periodic trend analysis is performed to avoid misjudgments caused by instantaneous fluctuations.

[0045] Step 803: Based on the wireless communication status between the wireless positioning sub-section and the wireless positioning external pressure sub-section, determine whether the retrieval core is stuck.

[0046] Step 804: Input the initial anomaly judgment result into the preset fault logic model, match and output the corresponding fault type according to the model rules.

[0047] The fault logic model includes built-in mapping rules for data out of range and fault type, trend anomaly and fault type, and communication status and stagnation type.

[0048] For example, fault types include pressure sensor faults, flow sensor faults, retrieval core jamming faults, and wireless communication faults.

[0049] Step 805: The determined fault type is binary encoded, and the wireless positioning sub-section embeds the encoded fault information into the wavecode signal and sends it to the wireless positioning external pressure sub-section.

[0050] Specifically, a fault judgment code can be set for one instruction transmission interval, with 0 indicating no fault and 1 indicating a fault. A corresponding binary fault code is assigned to each known fault type, with a single fault code occupying four instruction transmission intervals. A preset unknown fault code is assigned to unknown faults, with the unknown fault code occupying four instruction transmission intervals. If multiple faults exist, they are encoded in the following order: fault judgment code → first fault code → second fault code → ... → last fault code → end signal. The end signal is a fixed code for one instruction transmission interval.

[0051] For example, an internal pressure sensor fault corresponds to binary fault code 0001; a flow sensor fault corresponds to binary fault code 0010; a stuck core in the retrieval module corresponds to binary fault code 0011; and an unknown fault code is 1110. The above encoding is for illustrative purposes only. In actual implementation, the number of encoding bits, sequence format, and fault correspondences need to be adaptively adjusted according to the number of fault types in the injection and distribution system, communication protocol specifications, and surface system decoding requirements to meet the requirements of efficient transmission and accurate interpretation of downhole fault information.

[0052] For example, the encoding sequence is as follows: fault judgment code bit → first fault code → second fault code → … → last fault code → end signal: the first bit is the fault judgment code bit: "1"; known fault codes are arranged sequentially: the first fault code "0001" (internal pressure sensor fault), the second fault code "0011" (retrieval core stuck fault); an unknown fault code "1110" is inserted; and an end signal "1111" is added at the end. The final encoding sequence is: 1→0001→0011→1110→1111.

[0053] Step 806: The wireless positioning external pressure sub-section receives the signal and converts the wavecode signal containing fault information into a pressure-flow wave, which is then sent to the ground system.

[0054] After receiving the wavecode signal containing fault information from the wireless positioning sub-sub ...

[0055] Before transmission, the wireless positioning external pressure sub-section first uses the CRC cyclic redundancy check algorithm to verify the signal. If an error is found, it re-receives the fault information sent by the retrieval core until a correct signal is received. After confirming that the signal is correct, the pressure-flow wave is then transmitted back to the ground system, thereby achieving real-time and accurate reporting of fault information and ensuring that the ground system can promptly obtain the fault status of the water distribution unit.

[0056] The fault monitoring method for the water distributor provided in this application comprehensively monitors multi-dimensional data such as pressure inside and outside the tubing and fluid flow rate, and combines data threshold comparison and dynamic trend analysis to comprehensively evaluate the operating status of the water distributor, significantly improving the accuracy of fault identification and early warning capability. Utilizing the wireless communication status between the wireless positioning sub and the external pressure sub, it can effectively determine whether the core is stuck. Furthermore, it uses a preset fault logic model to intelligently match and binary encode anomalies, and uploads the fault information to the surface system in the form of pressure-flow waves through wavecode signal conversion, establishing a reliable and efficient downhole-to-surface information transmission channel, improving the reliability and maintenance efficiency of the water injection process. This method can promptly identify multiple faults, preventing fault escalation that could lead to well shutdown, significantly reducing unplanned well workover operations, lowering maintenance costs, and providing key technical support for the intelligent and refined management of the stratified water injection process.

[0057] In some embodiments, the initial anomaly judgment result is input into a preset fault logic model, and the corresponding fault type is matched and output according to the model rules, including the following four situations.

[0058] 1. If the initial judgment result of the abnormality is that the pressure data exceeds the preset standard pressure range, the fault logic model will match and output the pressure sensor fault according to the mapping rule between the data exceeding the range and the fault type.

[0059] 2. If the initial anomaly assessment result is that the flow data exceeds the preset standard flow range, the fault logic model will match and output a flow sensor fault based on the mapping rule between data exceeding the range and fault type.

[0060] 3. If the initial anomaly assessment result is that the communication between the wireless positioning short section and the wireless positioning external pressure short section is interrupted or the communication signal strength is continuously lower than the preset signal value, the fault logic model will match and output the core jamming fault or wireless communication fault according to the mapping rules between communication status and jamming type.

[0061] 4. If the initial judgment of the anomaly is that the pressure data or flow data shows an abnormal trend of continuous increase or continuous decrease after entering the stable working mode, the fault logic model will match and output the corresponding sensor fault according to the mapping rule between the trend anomaly and the fault type.

[0062] For example, during the actual operation of a downhole water distribution system, the system periodically collects data on tubing pressure, tubing external pressure, and tubing flow rate once per second. At a certain moment, the system detects that the tubing external pressure reading remains above the upper limit of the preset standard pressure range for 30 seconds (e.g., the preset upper limit is 40 MPa, but the actual detected value remains within the range of 42-45 MPa). After the initial anomaly judgment result is generated, it is input into the preset fault logic model. The model's built-in rule base contains "mapping rules between data out of range and fault types." The system matches these rules and determines that the current anomaly matches the characteristics of "pressure sensor failure," and then outputs the fault type.

[0063] Subsequently, the fault logic model continues to run. If the system detects that the flow data suddenly drops from the normal value (e.g., 50 m³ / d) to below the standard range within 5 sampling periods (e.g., the preset flow lower limit is 30 m³ / d, but the actual value drops to 20-25 m³ / d), then according to the same mapping rule, the model matches and outputs "flow sensor fault".

[0064] Another common scenario is that the communication signal strength between the downhole wireless positioning sub and the wireless positioning external pressure sub remains below the preset threshold of -90dBm for 10 consecutive sampling periods, or that communication is completely interrupted for 3 consecutive periods. The fault logic model determines whether a "deployment core jamming fault" or a "wireless communication module fault" has occurred based on the preset "mapping rules between communication status and jamming type," and outputs the corresponding fault type.

[0065] Furthermore, once the water distributor enters a stable operating mode, if the model detects an abnormal trend in pressure or flow data within 60 seconds (e.g., pressure continuously decreasing at a rate of 0.5 MPa per minute, or flow continuously increasing at a rate of 5 m³ / d per hour), even if the instantaneous value has not yet exceeded the threshold range, the trend analysis rule will be triggered. Based on the "mapping rule between trend anomalies and fault types," the model can predict sensor drift or failure risks in advance and output fault types such as "pressure sensor drift fault" or "flow sensor anomaly," achieving early identification and warning of faults.

[0066] The fault monitoring method for water distributors provided in this application, by constructing a preset fault logic model, can automatically and accurately map and match the initial judgment results of anomalies with specific fault types, significantly reducing the uncertainty and lag of manual judgment and greatly improving the accuracy and reliability of fault diagnosis. This method not only focuses on whether the data exceeds the threshold, but also continuously monitors the data trend after entering a stable state, thereby identifying potential drift-type faults and realizing the transformation from "post-event alarm" to "pre-event warning," effectively preventing the escalation of faults and ensuring the continuity and stability of the water distribution process.

[0067] In some embodiments, when the initial anomaly judgment result is a single-dimensional anomaly result, the initial anomaly judgment result is input into a preset fault logic model, and the corresponding fault type is matched and output according to the model rules. The following situations may also be included.

[0068] 1. When the initial judgment result of the abnormality is that the internal pressure exceeds the limit at a single point, the internal pressure sensor fault is matched and output according to the mapping rule between the data exceeding the range and the fault type.

[0069] 2. When the initial anomaly judgment result is that the flow rate exceeds the limit at a single point, the flow sensor fault is matched and output based on the mapping rule between data exceeding the range and fault type.

[0070] 3. When the initial judgment result of the abnormality is that the external pressure exceeds the limit at a single point, the external pressure sensor fault is matched and output according to the mapping rule between the data exceeding the range and the fault type.

[0071] 4. When the initial judgment result of the abnormality is that the internal pressure continues to exceed the limit, the fault logic model matches and outputs the internal pressure sensor fault according to the mapping rule between the abnormal trend and the fault type.

[0072] 5. When the initial judgment result of the abnormality is that the external pressure continues to exceed the limit, the fault logic model matches and outputs the external pressure sensor fault according to the mapping rule between the abnormal trend and the fault type.

[0073] After obtaining communication signal strength, arrival confirmation signal, interaction frequency, and positioning deviation data from the wireless positioning segment, and obtaining the tension feedback signal from the support arm assembly of the retrieval core, the initial anomaly judgment result is input into the preset fault logic model. The corresponding fault type is matched and output according to the model rules, and may also include the following situations.

[0074] 1. When the initial judgment of the anomaly is that the support arm tension feedback signal is missing and the communication signal strength is continuously lower than the preset signal value, the fault logic model matches and outputs the core jamming fault according to the mapping rule between communication status and jamming type.

[0075] During the deployment phase: The support arm extension feedback signal is missing, and the communication signal strength is consistently less than -80dBm (-85dBm), which is determined to be an anomaly of "support arm signal missing + weak communication signal". Based on the mapping rule between communication status and jamming type, the fault logic model matches and outputs the deployment core jamming fault.

[0076] 2. When the initial judgment result of the abnormality is that no confirmation signal has been received and the positioning deviation data exceeds the preset difference, the fault logic model matches and outputs the core deployment jamming fault according to the mapping rule between communication status and jamming type.

[0077] Specifically, during the deployment phase, if no confirmation signal is received and the positioning deviation is 15mm > the preset difference of 10mm, it is judged as an "abnormality of missing positioning signal + positioning deviation exceeding the limit". Based on the mapping rules between communication status and jamming type, the fault logic model matches and outputs a deployment jamming fault of the deployment core.

[0078] 3. When the initial judgment result of the anomaly is that the communication interaction interruption is greater than the preset time and the position deviation exceeds the threshold, the fault logic model matches and outputs the jamming fault during the core deployment and retrieval process according to the mapping rule between communication status and jamming type.

[0079] Working phase: Communication interruption for 12 seconds > preset time 10 seconds, and position deviation of 18mm > threshold 10mm, is judged as "communication interruption timeout + position deviation exceeding limit" abnormality.

[0080] The fault monitoring method for the water distributor provided in this application, through a preset fault logic model, can accurately distinguish and locate specific faults in internal pressure, external pressure, or flow sensors based on abnormal characteristics such as "single-point over-limit" or "continuous over-limit," effectively avoiding the problem of fault type confusion in traditional methods and greatly improving the accuracy and efficiency of sensor-level fault diagnosis. It also enhances the comprehensive judgment capability for mechanical faults such as core jamming during dispensing, ensuring continuous and stable operation of the dispensing process.

[0081] In some embodiments, when the initial anomaly judgment result is a multi-dimensional anomaly result, the initial anomaly judgment result is input into a preset fault logic model, and the corresponding fault type is matched and output according to the model rules, including the following steps.

[0082] For multi-dimensional abnormal results, the corresponding fault type is matched and output according to the layer-by-layer verification rules of the built-in logic tree of the preset fault logic model.

[0083] Specifically, the first layer of verification determines whether both single-point pressure and single-point flow exceedances exist simultaneously. If so, the process proceeds to the second layer of verification. The second layer of verification checks whether the trends of pressure and flow data are consistent. If the trends are consistent and both show abnormal changes, the wireless communication status is further verified. The third layer of verification determines that the abnormality in the associated data is caused by an abnormality in the formation fluid supply if the wireless communication status is normal. If the wireless communication status is abnormal, the combined fault type of sensor failure and wireless communication failure is matched and output based on the signal interaction success rate and positioning deviation data.

[0084] For example, during the stable operation phase of a water injection well's water distribution device, the preset normal range of internal pressure in the downhole working cylinder is 9.5-10.5 MPa, the normal range of flow rate is 0.035-0.04 m³ / min, the communication signal strength threshold is -80 dBm, the signal interaction success rate threshold is 90%, and the positioning deviation threshold is 10 mm.

[0085] The internal pressure sensor collected values ​​of 10.6MPa, 10.7MPa, 10.8MPa, 10.9MPa, and 11.0MPa for 5 consecutive cycles (500ms) (all exceeding the upper limit of 10.5MPa, marked as "Pressure Single Point Exceeds Limit"); the electromagnetic flowmeter collected values ​​of 0.025m³ / min, 0.024m³ / min, 0.023m³ / min, 0.022m³ / min, and 0.021m³ / min (all below the lower limit of 0.035m³ / min, marked as "Flow Single Point Exceeds Limit"); the wireless positioning sub-section feedback communication signal strength was -85dBm (<-80dBm), the signal interaction success rate was 75% (<90%), and the positioning deviation was 12mm (>10mm).

[0086] The fault logic model is verified layer by layer, including: First-level verification: The microprocessor identifies that both "single-point pressure over-limit" and "single-point flow over-limit" exist simultaneously, and then proceeds to the second-level verification.

[0087] Second layer verification: Trend analysis revealed that the internal pressure continued to rise (amount 0.4 MPa) and the flow rate continued to fall (amount 0.004 m³ / min), with consistent and abnormal trends, further verifying the wireless communication status.

[0088] The third layer of verification confirms abnormal wireless communication status (weak signal, low interaction success rate, positioning deviation exceeding the threshold). Combining this with the logic tree rule "multi-dimensional data anomaly + communication anomaly → sensor and communication combined failure," it outputs "internal pressure-flow sensor associated data anomaly + wireless communication failure." By constructing a three-level progressive fault diagnosis logic tree, accurate identification and classification of complex downhole working conditions are achieved.

[0089] Exemplary electronic devices Below, for reference Figure 9 This describes an electronic device according to embodiments of the present application. Figure 9 The diagram shown is a structural schematic of an electronic device provided in an exemplary embodiment of this application.

[0090] like Figure 9 As shown, the electronic device 900 includes one or more processors 901 and memory 902.

[0091] The processor 901 may be a central processing unit (CPU) or other form of processing unit with data processing capabilities and / or instruction execution capabilities, and may control other components in the electronic device 900 to perform desired functions.

[0092] The memory 902 may include one or more computer program products, which may include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. The volatile memory may include, for example, random access memory (RAM) and / or cache memory. The non-volatile memory may include, for example, read-only memory (ROM), hard disk, flash memory, etc. One or more computer program instructions may be stored on the computer-readable storage medium, and the processor 901 may execute the program instructions to implement the fault monitoring method of the water distribution device in the various embodiments of this application described above, and / or other desired functions. Various contents such as tubing pressure data, tubing external pressure data, and tubing fluid flow rate data may also be stored in the computer-readable storage medium.

[0093] In one example, the electronic device 900 may also include an input device 903 and an output device 904, which are interconnected via a bus system and / or other forms of connection mechanism (not shown).

[0094] The input device 903 may include, for example, a keyboard, a mouse, etc.

[0095] The output device 904 can output various information to the outside, including pressure-flow waves, etc. The output device 904 may include, for example, a display, a communication network, and remote output devices connected thereto, etc.

[0096] Of course, for the sake of simplicity, Figure 9 Only some of the components of the electronic device 900 relevant to this application are shown in this illustration; components such as buses, input / output interfaces, etc., are omitted. In addition, the electronic device 900 may include any other suitable components depending on the specific application.

[0097] In addition to the methods and devices described above, embodiments of this application may also be computer program products, which include computer program instructions that, when executed by a processor, cause the processor to perform the steps in the fault monitoring method for a water distributor according to various embodiments of this application as described in the "Exemplary Methods" section of this specification.

[0098] The computer program product can be written in any combination of one or more programming languages ​​to perform the operations of the embodiments of this application. The programming languages ​​include object-oriented programming languages ​​such as Java and C++, as well as conventional procedural programming languages ​​such as C or similar languages. The program code can be executed entirely on the user's computing device, partially on the user's computing device, as a standalone software package, partially on the user's computing device and partially on a remote computing device, or entirely on a remote computing device or server.

[0099] Furthermore, embodiments of this application may also be computer-readable storage media storing computer program instructions thereon, which, when executed by a processor, cause the processor to perform the steps in the fault monitoring method for a water distributor according to various embodiments of this application described in the "Exemplary Methods" section above.

[0100] The computer-readable storage medium may be any combination of one or more readable media. A readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may be, for example, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of readable storage media (a non-exhaustive list) include: an electrical connection having one or more wires, a portable disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof.

[0101] The basic principles of this application have been described above with reference to specific embodiments. However, it should be noted that the advantages, benefits, and effects mentioned in this application are merely examples and not limitations, and should not be considered as essential features of each embodiment of this application. Furthermore, the specific details disclosed above are for illustrative and facilitative purposes only, and are not limitations. These details do not limit the application to the necessity of employing the aforementioned specific details for implementation.

[0102] The block diagrams of devices, apparatuses, devices, and systems involved in this application are merely illustrative examples and are not intended to require or imply that they must be connected, arranged, or configured in the manner shown in the block diagrams. As those skilled in the art will recognize, these devices, apparatuses, devices, and systems can be connected, arranged, and configured in any manner. Words such as “comprising,” “including,” “having,” etc., are open-ended terms meaning “including but not limited to,” and are used interchangeably with them. The terms “or” and “and” as used herein refer to the terms “and / or,” and are used interchangeably with them unless the context clearly indicates otherwise. The term “such as” as used herein refers to the phrase “such as but not limited to,” and is used interchangeably with it.

[0103] It should also be noted that in the apparatus, equipment, and methods of this application, the components or steps can be disassembled and / or recombined. These disassemblies and / or recombinations should be considered as equivalent solutions of this application.

[0104] The above description of the disclosed aspects is provided to enable any person skilled in the art to make or use this application. Various modifications to these aspects will be readily apparent to those skilled in the art, and the general principles defined herein can be applied to other aspects without departing from the scope of this application. Therefore, this application is not intended to be limited to the aspects shown herein, but rather to be carried out within the widest scope consistent with the principles and novel features of the invention herein.

[0105] The above description has been given for illustrative and descriptive purposes. Furthermore, this description is not intended to limit the embodiments of this application to the forms of the invention herein. Although numerous exemplary aspects and embodiments have been discussed above, those skilled in the art will recognize certain variations, modifications, alterations, additions, and sub-combinations thereof.

Claims

1. A fault monitoring method for a water injection and distribution device, applied to a water injection and distribution device including a downhole working barrel and a retrieval core, wherein the downhole working barrel is connected to the tubing, the downhole working barrel is equipped with a wireless positioning external pressure short section, and the retrieval core is equipped with a wireless positioning short section, characterized in that... The method includes: Collect pressure data inside the tubing, pressure data outside the tubing, and fluid flow data inside the tubing; The pressure data and flow data are compared with preset standard operating parameters to determine whether the pressure data and flow data exceed the normal range; Analyze the data change trends after entering a stable working mode to determine whether there are any abnormal trends of continuous rise or fall; Based on the wireless communication status between the wireless positioning section and the wireless positioning external pressure section, determine whether the retrieval core is stuck; Input the initial anomaly judgment result into the preset fault logic model, match and output the corresponding fault type according to the model rules; The determined fault type is binary encoded, and the wireless positioning sub-section embeds the encoded fault information into the wavecode signal and sends it to the wireless positioning external pressure sub-section. The wireless positioning external pressure section receives the signal and converts the wavecode signal containing fault information into a pressure-flow wave, which is then sent to the ground system.

2. The fault monitoring method according to claim 1, characterized in that, The step of comparing the pressure data and flow rate data with preset standard operating parameters to determine whether the pressure data and flow rate data exceed the normal range includes: The pressure data inside the oil pipe is compared with the preset normal internal pressure range. If it exceeds the normal internal pressure range, it is marked as a single point of internal pressure exceeding the limit. The flow rate data of the liquid in the oil pipe is compared with the reference flow rate range. If it exceeds the reference flow rate range, it is marked as a single point of flow rate exceeding the limit. Compare the external pressure data of the oil pipe with the normal external pressure range. If it exceeds the normal external pressure range, mark it as a single point of external pressure exceeding the limit.

3. The fault monitoring method according to claim 1, characterized in that, The analysis of data changes after entering a stable operating mode, and the determination of whether there are any abnormal trends of continuous increase or decrease, includes: Within the first trend analysis period, internal pressure data is collected M times consecutively. If N of these data exceed the standard range, it is determined that the internal pressure is continuously exceeding the limit. M and N are both positive integers, with M being greater than N. Within the set second trend analysis period, external pressure data is collected P times continuously. If Q of these data exceed the standard range, it is determined that the external pressure is continuously exceeding the limit. P and Q are both positive integers, with P being greater than Q.

4. The fault monitoring method according to claim 1, characterized in that, The fault logic model has built-in mapping rules for data out of range and fault type, trend anomaly and fault type, and communication status and jamming type. The fault types include pressure sensor fault, flow sensor fault, core jamming fault, and wireless communication fault. The step of inputting the initial anomaly judgment result into a preset fault logic model, matching and outputting the corresponding fault type according to the model rules, includes: If the initial anomaly assessment result is that the pressure data exceeds the preset standard pressure range, the fault logic model will match and output a pressure sensor fault according to the mapping rule between the data exceeding the range and the fault type. If the initial anomaly judgment result is that the traffic data exceeds the preset standard traffic range, the fault logic model matches and outputs a traffic sensor fault according to the mapping rule between the data exceeding the range and the fault type. If the initial judgment result of the anomaly is that the communication between the wireless positioning section and the wireless positioning external pressure section is interrupted or the communication signal strength is continuously lower than the preset signal value, the fault logic model will match and output the core jamming fault or wireless communication fault according to the mapping rule between the communication status and the jamming type. If the initial anomaly assessment result is that the pressure data or flow data shows an abnormal trend of continuous increase or continuous decrease after entering the stable working mode, the fault logic model matches and outputs the corresponding sensor fault according to the mapping rule between the trend anomaly and the fault type.

5. The fault monitoring method according to claim 1, characterized in that, The initial anomaly assessment result is a single-dimensional anomaly result. The step of inputting the initial anomaly assessment result into a preset fault logic model, matching and outputting the corresponding fault type according to model rules, further includes: When the initial abnormality judgment result is that the internal pressure exceeds the limit at a single point, the preset fault logic model matches and outputs an internal pressure sensor fault according to the mapping rule between the data exceeding the range and the fault type. When the initial abnormality judgment result is that the flow rate exceeds the limit at a single point, the preset fault logic model matches and outputs a flow sensor fault according to the mapping rule between the data exceeding the range and the fault type. When the initial abnormality judgment result is that the external pressure single point exceeds the limit, according to the mapping rule between the data out of range and the fault type, the preset fault logic model matches and outputs an external pressure sensor fault. When the initial judgment result of the anomaly is that the internal pressure continues to exceed the limit, the fault logic model matches and outputs an internal pressure sensor fault according to the mapping rule between the trend anomaly and the fault type. When the initial judgment result of the anomaly is that the external pressure continues to exceed the limit, the fault logic model matches and outputs an external pressure sensor fault according to the mapping rule between the trend anomaly and the fault type. The communication signal strength, arrival confirmation signal, interaction frequency, and positioning deviation data are obtained from the wireless positioning segment, and the arm extension feedback signal is obtained from the support arm assembly of the retrieval core. When the initial abnormality judgment result is that the support arm extension feedback signal is missing and the communication signal strength is continuously lower than the preset signal value, the fault logic model matches and outputs the core jamming fault according to the mapping rule between the communication status and the jamming type. When the initial abnormality judgment result is that no confirmation signal has been received and the positioning deviation data exceeds the preset difference, the fault logic model matches and outputs a core deployment jamming fault according to the mapping rule between the communication status and the jamming type. When the initial judgment result of the anomaly is that the communication interaction interruption is greater than the preset time and the position deviation exceeds the threshold, the fault logic model matches and outputs the jamming fault during the core deployment and retrieval process according to the mapping rule between the communication status and the jamming type.

6. The fault monitoring method according to claim 1, characterized in that, The initial anomaly assessment result is a multi-dimensional anomaly result. The step of inputting the initial anomaly assessment result into a preset fault logic model, matching and outputting the corresponding fault type according to the model rules, further includes: For the aforementioned multi-dimensional anomaly results, the corresponding fault type is matched and output according to the layer-by-layer verification rules of the built-in logic tree of the preset fault logic model, wherein, The first layer of verification determines whether both pressure and flow exceed the limit at a single point exist simultaneously. If so, it proceeds to the second layer of verification. The second layer of verification is to check whether the changing trends of pressure data and flow data are consistent. If the trends are consistent and both show abnormal changes, the wireless communication status is further verified to be normal. The third layer of verification is as follows: if the wireless communication status is normal, it is determined that the abnormality of the associated data is caused by the abnormality of the formation fluid supply; if the wireless communication status is abnormal, the combined fault type of sensor failure and wireless communication failure is matched and output by combining the signal interaction success rate and positioning deviation data.

7. The fault monitoring method according to any one of claims 1 to 6, characterized in that, The process of binary encoding the determined fault type includes: Set a fault detection code bit for a 1 instruction transmission interval, where 0 indicates no fault and 1 indicates a fault exists; Assign a corresponding binary fault code to each known fault type, with each fault code occupying a 4 instruction transmission interval; A preset unknown fault code is assigned to an unknown fault, and the unknown fault code occupies 4 instruction sending intervals; If multiple faults exist, they are encoded in the following order: fault judgment code bit → first fault code → second fault code → ... → last fault code → end signal. The end signal is a fixed code for one instruction transmission interval.

8. A fault monitoring system for a water distributor, characterized in that, include: A downhole working tube, connected to the tubing and placed in the downhole water injection zone, the downhole working tube including a wireless positioning external pressure short section; The retrieval core is separately installed inside the downhole working tube. It can be deployed and retrieved at a fixed point inside the tubing using a retrieval tool. The retrieval core includes a wireless positioning section. The sensor module is used to collect pressure data inside the tubing, pressure data outside the tubing, and fluid flow data inside the tubing. The data processing module, connected to the sensor module, is used to compare the pressure data and flow data with preset standard operating parameters to determine whether they exceed the normal range, and to analyze the data change trend after entering the stable working mode to determine whether there is an abnormal trend of continuous increase or decrease. A jamming detection module, integrated into the wireless positioning sub-section or the wireless positioning external pressure sub-section, is used to determine whether the retrieval core is jammed based on the wireless communication status of the wireless positioning sub-section and the wireless positioning external pressure sub-section. The fault diagnosis module is connected to the data processing module and the jamming judgment module. The fault diagnosis module has a built-in preset fault logic model, which is used to match and output the corresponding fault type according to the initial abnormal judgment result. The encoding module, connected to the fault diagnosis module, is used to perform binary encoding on the determined fault type; The wavecode communication module includes a signal transmitting unit and a signal conversion unit. The signal transmitting unit is integrated with the wireless positioning sub-section and is used to embed the encoded fault information into the wavecode signal and transmit it. The signal conversion unit is integrated with the wireless positioning external pressure sub-section and is used to receive the wavecode signal and convert the wavecode signal containing the fault information into a pressure-flow wave, which is then transmitted to the ground system.

9. An electronic device, comprising: processor; as well as A memory that stores computer program instructions, which, when executed by a processor, cause the processor to perform the steps of the method as described in any one of claims 1 to 7.

10. A computer-readable storage medium storing computer program instructions that, when executed by a processor, cause the processor to perform the steps of the method as claimed in any one of claims 1 to 7.

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