An unmanned aerial vehicle automatic inspection system and method suitable for a wellbore environment

Abstract

The application discloses an unmanned aerial vehicle automatic inspection system and method suitable for a wellbore environment and relates to the technical field of wellbore inspection. The system comprises an unmanned aerial vehicle inspection unit, a data acquisition unit, a signal transmission unit, a data analysis and management platform and a power supply unit. The unmanned aerial vehicle inspection unit is equipped with a 360-degree panoramic high-definition camera and a high-power three-dimensional laser radar, and can realize centimeter-level crack observation in a narrow space of a wellbore. The data acquisition unit acquires the position, power and inspection image data of the unmanned aerial vehicle in real time. The signal transmission unit guarantees real-time return of high-definition video without lag, and the delay is less than or equal to 200 ms. The data analysis and management platform realizes data display, storage and personalized adjustment. The application solves the problems of low efficiency, insufficient data precision and poor visualization of traditional wellbore inspection, improves the inspection efficiency and data reliability through an automatic inspection process, and provides comprehensive technical support for wellbore safety monitoring.

Description

Technical Field

[0001] This invention relates to the field of wellbore inspection technology, and specifically to an unmanned aerial vehicle (UAV) automatic inspection system and method suitable for wellbore environments. Background Technology

[0002] As a critical infrastructure in mining, oil and gas extraction, the integrity of the inner wall of a well shaft directly affects production safety and operational efficiency. Over long-term use, defects such as cracks, corrosion, and spalling can easily develop on the inner wall of a well shaft. If these defects are not detected and addressed in a timely manner, they may lead to major safety accidents such as well shaft collapse and fluid leakage.

[0003] Traditional wellbore inspections mainly rely on manual inspections from the bottom or monitoring with fixed sensors, which has many limitations. Manual inspections require the construction of complex lifting equipment, have long operation cycles, and are costly. Furthermore, the dim lighting, lack of oxygen, and confined space inside the well pose a serious threat to the personal safety of inspection personnel. Fixed sensor monitoring can only cover specific points and cannot achieve dynamic observation of the entire wellbore area, which is prone to blind spots. In addition, sensor data needs to be collected manually at regular intervals, and cannot provide real-time feedback on the wellbore status.

[0004] Existing drone inspection technologies are mostly used in open spaces, such as power lines and roads, and are difficult to adapt directly to the confined environment of manholes. On the one hand, the cameras on ordinary drones have limited field of view, making it impossible to fully observe the inner walls of the manhole, and their resolution is insufficient to identify centimeter-level cracks. On the other hand, signals attenuate rapidly inside manholes, and existing signal transmission equipment cannot guarantee real-time transmission of high-definition video, easily resulting in stuttering and delays, leading to incomplete inspection data. In addition, there is a lack of a professional data analysis platform specifically for manhole environments, making it impossible to achieve visualized management and historical traceability of inspection data, and failing to meet the needs of engineers for a comprehensive assessment of the manhole's condition.

[0005] Therefore, developing an automatic inspection system and method for unmanned aerial vehicles (UAVs) that can adapt to the confined and dimly lit environment of well shafts, achieve high-precision all-round inspection, and ensure real-time data transmission and efficient management has become an urgent technical problem to be solved in the field of well shaft safety monitoring. Summary of the Invention

[0006] To address the problems of low efficiency, poor safety, insufficient data accuracy, unstable signal transmission, and lack of management platform in existing wellbore inspection technologies, this invention provides an unmanned aerial vehicle (UAV) automatic inspection system and method suitable for wellbore environments. This system enables precise identification of centimeter-level cracks on the inner wall of the wellbore, real-time transmission of high-definition video, and visualized management and historical traceability of inspection data, thereby improving the automation level and safety reliability of wellbore inspection.

[0007] To achieve the above objectives, the present invention provides the following technical solution: an automatic inspection system for unmanned aerial vehicles (UAVs) suitable for wellbore environments, characterized in that it includes a UAV inspection unit, a data acquisition unit, a signal transmission unit, a data analysis and management platform, and a power supply unit; the UAV inspection unit is used to achieve all-round observation of the inner wall of the wellbore, the data acquisition unit is used to acquire the UAV's operating status and inspection data, the signal transmission unit is used to ensure real-time data transmission, the data analysis and management platform is used for data display, analysis, and management, and the power supply unit is used to provide power support for each unit.

[0008] Preferably, the UAV inspection unit includes the UAV itself, a 360° panoramic high-definition camera, a 3D LiDAR, and an illumination module; the 360° panoramic high-definition camera uses a high-definition sensor with at least 8 megapixels, a horizontal field of view of 0–360°, a vertical field of view of 0–90°, an image resolution ≥3840×2160, and can identify cracks at the cm level; the 3D LiDAR uses a radar head with 80W-160W points / s, a ranging accuracy of 1.5cm, and a scanning frequency ≥10Hz; the illumination module includes 4-6 high-power LED beads, each with a power ≥10W and an illuminance ≥5000 Hz. The lux drone inspection unit includes the drone itself, a 360° panoramic high-definition camera, a 3D LiDAR, and an illumination module. The 360° panoramic high-definition camera uses a high-definition sensor with over 8 megapixels, a horizontal field of view ≥180°, a vertical field of view ≥90°, an image resolution ≥3840×2160, and can identify cracks ≤1cm. The 3D LiDAR uses a radar head with 80W-160W points / s, a ranging accuracy ≤±5mm, and a scanning frequency ≥10Hz. The illumination module contains 4-6 high-power LED beads, each with a power ≥10W and a light intensity ≥5000lux.

[0009] Preferably, the data acquisition unit includes a lidar positioning and navigation module, an IMU inertial measurement unit (IMU), a power monitoring module, and a data storage module; the GPS positioning module uses lidar SLAM positioning with a positioning accuracy of 1.5cm and an update frequency of ≥10Hz; the IMU IMU includes a 3-axis accelerometer with a measurement range of ±16g and a 3-axis gyroscope with a measurement range of ±2000° / s; the power monitoring module has a measurement accuracy of ≤±0.01V and a remaining power of ≤±1%; the data storage module uses a high-speed SD card with a capacity of ≥256GB to store data associations. The location information and timestamp data acquisition unit includes a GPS positioning module, an IMU inertial measurement module, a power monitoring module, and a data storage module. The GPS positioning module adopts BeiDou / GPS dual-mode positioning with a positioning accuracy of ≤1m and an update frequency of ≥1Hz. The IMU inertial measurement module includes a 3-axis accelerometer with a measurement range of ±16g and a 3-axis gyroscope with a measurement range of ±2000° / s. The power monitoring module has a measurement accuracy of ≤±0.01V and a remaining power of ≤±1%. The data storage module uses a high-speed SD card with a capacity of ≥128GB to store data associated with location information and timestamps.

[0010] Preferably, the signal transmission unit includes an airborne transmission module for the UAV and a ground transmission base station; the airborne transmission module for the UAV uses 5.8GHz frequency band wireless transmission with a rate of ≥50Mbps and a latency of ≤200ms; the ground transmission base station is located near the wellhead, with a communication distance of ≥500m inside the well, and supports bidirectional communication.

[0011] Preferably, the data analysis and management platform is based on a B / S architecture, including a real-time monitoring module, a data recording module, a personalized adjustment module, and an anomaly warning module. The real-time monitoring module displays the drone's battery level and voltage, single-battery flight time of ≥15 minutes, location information, and multiple camera views. The data recording module generates historical data files by date and supports export in MP4, JPG, and CSV formats. The personalized adjustment module supports parameter customization and multi-user permission management. The anomaly warning module can automatically detect cracks and push warning information.

[0012] Preferably, the power supply unit includes a drone battery; the drone battery has a capacity of ≥8000mAh and a flight time of ≥15 minutes.

[0013] An automated inspection method for unmanned aerial vehicles (UAVs) suitable for wellbore environments includes a pre-inspection preparation stage, an automated inspection stage, a data processing and analysis stage, and a post-inspection maintenance stage. The pre-inspection preparation stage includes equipment inspection, parameter setting, and initial positioning. The automated inspection stage includes autonomous flight of the UAV, data acquisition, and real-time transmission. The data processing and analysis stage includes data processing, real-time display, and anomaly warning. The post-inspection maintenance stage includes equipment maintenance, data export, and maintenance plan development.

[0014] Preferably, the automatic inspection phase specifically includes:

[0015] S201, the UAV activates the lighting module and enters the well shaft according to the preset path; the IMU module compensates for the lidar data.

[0016] S202, the camera and lidar synchronously collect data, and the data acquisition unit associates the data with location and time information;

[0017] S203, the signal transmission unit transmits data to the platform, and inspection personnel can switch perspectives and control frequency recording / photography.

[0018] Preferably, the data processing and analysis stage specifically includes:

[0019] S301: The platform detects cracks using image recognition algorithms and determines the location of cracks by combining point cloud data. An early warning is triggered when the crack width is ≥1cm.

[0020] S302: The platform displays the drone's status and inspection results in real time and generates inspection logs.

[0021] S303: After the inspection is completed, the historical data files are uploaded to the platform and stored in categories.

[0022] Preferably, in the pre-inspection preparation stage, the preset inspection path includes spiral and vertical types, and the flight speed can be adjusted within the range of 0.5-3m / s;

[0023] During the post-inspection maintenance phase, the inspection report includes wellbore condition assessment, fracture statistics, and early warning records. The maintenance records are entered into the platform to form a closed-loop management system.

[0024] Beneficial effects:

[0025] (1) High inspection accuracy: Through a 360° panoramic high-definition camera (8 million pixels or more) and a high-power three-dimensional laser radar (80W-160W points / S), the accuracy of centimeter-level (≤1cm) cracks on the inner wall of the well is achieved. The crack size is calculated by combining point cloud data, which solves the problem of insufficient accuracy of traditional inspection.

[0026] (2) Strong real-time performance: The signal transmission unit adopts 5.8GHz frequency band wireless transmission with a rate of ≥50Mbps and a delay of ≤200ms, ensuring that high-definition video is transmitted without lag. At the same time, the data analysis and management platform displays the drone status and inspection results in real time, which facilitates timely detection of anomalies.

[0027] (3) High degree of automation: After the inspection path and flight parameters are preset, the UAV can complete the well inspection autonomously without human intervention, reducing the risk of manual entry into the well. At the same time, the data collection, transmission, analysis and storage process is fully automated, improving inspection efficiency (the inspection time of a single well is shortened by more than 50%).

[0028] (4) Strong adaptability: The UAV is made of high pressure resistant and corrosion resistant materials, the lighting module improves the dim environment of the well, and the integrated design of the signal transmission unit makes it easy to carry down into the well, and is suitable for well environments with an inner diameter of ≥1.5m.

[0029] (5) Convenient management: The data analysis and management platform supports personalized parameter adjustment, historical data tracing and anomaly warning, generates standardized inspection reports, realizes systematic management of wellbore inspection data, and provides data support for wellbore maintenance.

[0030] The above description is merely an overview of the technical solutions of the embodiments of this application. In order to better understand the technical means of the embodiments of this application and to implement them in accordance with the contents of the specification, and to make the above and other objects, features and advantages of the embodiments of this application more apparent and understandable, specific implementation methods of this application are described below. Attached Figure Description

[0031] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0032] Figure 1 This is a block diagram of the overall structure of the UAV automatic inspection system in an embodiment of the present invention;

[0033] Figure 2 This is a schematic diagram of the structure of the UAV inspection unit in an embodiment of the present invention;

[0034] Figure 3 This is a functional block diagram of the data analysis and management platform in an embodiment of the present invention;

[0035] Figure 4 This is a flowchart of the automatic inspection method for unmanned aerial vehicles (UAVs) in an embodiment of the present invention. Detailed Implementation

[0036] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, 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, 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.

[0037] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains; the terminology used herein in the specification of the application is for the purpose of describing particular embodiments only and is not intended to limit the application; the terms “comprising” and “having”, and any variations thereof, in the specification, claims and drawings of this application are intended to cover non-exclusive inclusion.

[0038] The term "embodiment" as used herein means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of the phrase "embodiment" in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0039] Furthermore, the terms "first," "second," etc., in the specification and claims of this application or in the aforementioned drawings are used to distinguish different objects rather than to describe a specific order, and may explicitly or implicitly include one or more of the features.

[0040] In the description of this application, it should be noted that, unless otherwise expressly specified and limited, the terms "installation," "connection," and "joining" should be interpreted broadly. For example, "connection" or "joining" in mechanical structures can refer to a physical connection, such as a fixed connection, for example, a connection fixed by fasteners, such as a connection fixed by screws, bolts, or other fasteners; a physical connection can also be a detachable connection, such as a snap-fit ​​or interlocking connection; a physical connection can also be an integral connection, such as a connection formed by welding, bonding, or integral molding. Those skilled in the art can understand the specific meaning of the above terms in this application based on the specific circumstances.

[0041] To enable those skilled in the art to better understand the present application, the following will be combined with... Figures 1-4 The technical solutions in the embodiments of this application will be clearly and completely described.

[0042] Example 1

[0043] An automated drone inspection system suitable for mine shafts is developed to meet the inspection needs of vertical mine shafts (500m deep, 1.5m inner diameter). The specific configuration is as follows:

[0044] The drone inspection unit's main body is made of carbon fiber, weighs 1.5kg, and can withstand an air pressure of 0.1MPa inside the well shaft; the 360° panoramic high-definition camera uses a Hikvision DS-2CD6A20FWD-IZS model, with 8 megapixels, a resolution of 3840×2160, a horizontal field of view of 180°, and a vertical field of view of 90°, achieving 360° observation through stitching together four lenses; the 3D LiDAR uses RoboSense Airy.

[0045] Model, point cloud density 172W points / s, ranging accuracy 2cm, scanning frequency 10Hz; the lighting module uses 4 15W LED beads, with a light intensity of 6000 lux and a color temperature of 5000K, evenly distributed around the circumference of the UAV body.

[0046] The data acquisition unit's lidar positioning and navigation module uses a Beidou positioning module with a positioning accuracy of 0.5m and an update frequency of 1Hz; the IMU inertial measurement module uses the MPU6250 model, with an accelerometer measurement range of ±16g and a gyroscope measurement range of ±2000° / s; the power monitoring module uses an INA219 current and voltage sensor with a measurement accuracy of ±0.01V and ±1%; and the data storage module uses a Samsung 128GB high-speed SD card (UHS-I U3 level) that supports 4K@30fps video recording.

[0047] Example 2

[0048] Automatic inspection method for mine shafts using unmanned aerial vehicles

[0049] Based on the system of Embodiment 1, this embodiment provides an automatic inspection method for mine shafts using unmanned aerial vehicles (UAVs), the specific steps of which are as follows:

[0050] Inspection preparation stage

[0051] S101: Inspect all components of the drone to ensure that the camera lens is clean, the lidar is unobstructed, the lighting module is at normal brightness, the battery is at 90% charge, and the signal transmission is free from interference.

[0052] S102: Input wellbore parameters (depth 500m, inner diameter 1.5m, material is concrete) on the platform, set the inspection path, flight speed 0.5m / s, and add wellbore depth markings (mark once every 10m);

[0053] S103: Place the UAV at the wellhead takeoff point, use lidar to locate and calibrate the initial position (116.3000°E, 39.9000°N, 50.0m altitude), and record the initial data on the platform.

[0054] Automatic inspection phase

[0055] S201: The platform sends a takeoff command, the UAV activates its lighting module (6000 lux), descends along a spiral path, and the IMU module compensates for GPS data to ensure continuous position information;

[0056] S202: The camera captures real-time images of the inner wall of the wellbore, and the lidar collects point cloud data. The data acquisition unit associates the images, point clouds, and location (116.3000°E, 39.9000°N, altitude 40.0m) and time (2024-05-20 10:00:00) to form a data stream.

[0057] S203: The signal transmission unit transmits the data stream to the ground base station and then forwards it to the platform with a delay of 150ms, ensuring smooth video playback; inspection personnel switch the camera's side view and send a photo-taking command, storing high-definition images on the SD card.

[0058] Data processing and analysis stage

[0059] S301: The platform detects images using the YOLOv8 algorithm and identifies a 1.2cm wide crack at a depth of 450m. Combining this with point cloud data, the crack is calculated to be 50cm long and 3cm deep, triggering an audible and visual warning.

[0060] S302: The platform displays the current status of the drone (70% battery, location: 116.3000°E, 39.9000°N, altitude -450.0m), marks the location of the crack, and generates an inspection log;

[0061] S303: Inspection completed (10:30:00). The SD card will upload historical data (including 180 minutes of video and 50 pictures) to the platform and store it under the name "2024-05-20_Mine Shaft Inspection".

[0062] Post-inspection maintenance phase

[0063] S401: The drone returned to the wellhead, was inspected and found to be undamaged, and the battery with 15% charge was replaced;

[0064] S402: The platform exported an inspection report showing that the overall condition of the wellbore is good, with only one crack at 450m.

[0065] S403: Develop a maintenance plan, arrange personnel to repair the crack at 450m with epoxy resin, and enter the maintenance record into the platform.

[0066] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. An unmanned aerial vehicle (UAV) automatic inspection system suitable for well shaft environments, characterized in that: It includes a drone inspection unit, a data acquisition unit, a signal transmission unit, a data analysis and management platform, and a power supply unit. The drone inspection unit is used to achieve all-round observation of the inner wall of the well shaft. The data acquisition unit is used to acquire the drone's operating status and inspection data. The signal transmission unit is used to ensure real-time data transmission. The data analysis and management platform is used for data display, analysis, and management. The power supply unit is used to provide power support for each unit.

2. The UAV automatic inspection system suitable for wellbore environments according to claim 1, characterized in that: The UAV inspection unit includes the UAV itself, a 360° panoramic high-definition camera, a 3D LiDAR, and an illumination module. The 360° panoramic high-definition camera uses a high-definition sensor with over 8 megapixels, a horizontal field of view of 0–360°, a vertical field of view of 0–90°, and an image resolution of ≥3840×2160, capable of identifying cracks at the cm level. The 3D LiDAR uses a radar head with 80W-160W points / s, a ranging accuracy of 1.5cm, and a scanning frequency of ≥10Hz. The illumination module contains 4-6 high-power LED beads, each with a power of ≥10W and a light intensity of ≥5000 lux.

3. The unmanned aerial vehicle (UAV) automatic inspection system suitable for well shaft environments according to claim 1, characterized in that: The data acquisition unit includes a lidar positioning and navigation module, an IMU inertial measurement module, a power monitoring module, and a data storage module; The GPS positioning module uses LiDAR SLAM positioning, with a positioning accuracy of 1.5cm and an update frequency of ≥10Hz; The IMU inertial measurement module includes a 3-axis accelerometer with a measurement range of ±16g and a 3-axis gyroscope with a measurement range of ±2000° / s. The power monitoring module has a measurement accuracy of ≤±0.01V and a remaining power of ≤±1%. The data storage module uses a high-speed SD card with a capacity of ≥256GB to store data-related location information and timestamps.

4. The unmanned aerial vehicle (UAV) automatic inspection system suitable for well shaft environments according to claim 1, characterized in that: The signal transmission unit includes an airborne transmission module for the UAV and a ground transmission base station; The UAV onboard transmission module uses 5.8GHz frequency band wireless transmission with a speed of ≥50Mbps and a latency of ≤200ms; The ground transmission base station is located near the wellhead, with a communication distance of ≥500m inside the well, and supports two-way communication.

5. The unmanned aerial vehicle (UAV) automatic inspection system suitable for well shaft environments according to claim 1, characterized in that: The data analysis and management platform is based on a B / S architecture and includes a real-time monitoring module, a data recording module, a personalized adjustment module, and an anomaly warning module. The real-time monitoring module displays the drone's battery level and voltage, single battery life of ≥15 minutes, location information, and multiple camera views. The data recording module generates historical data files by date and supports exporting in MP4, JPG, and CSV formats. The personalized adjustment module supports parameter customization and multi-user permission management; the anomaly warning module can automatically detect cracks and push warning information.

6. The UAV automatic inspection system suitable for wellbore environments according to claim 1, characterized in that: The power supply unit includes a drone battery; The drone has a battery capacity of ≥8000mAh and a flight time of ≥15 minutes.

7. An automated inspection method for unmanned aerial vehicles (UAVs) suitable for wellbore environments, based on the system described in any one of claims 1-6, characterized in that, The inspection process includes a pre-inspection preparation phase, an automated inspection phase, a data processing and analysis phase, and a post-inspection maintenance phase. The pre-inspection preparation phase includes equipment inspection, parameter setting, and initial positioning. The automated inspection phase includes autonomous flight of the UAV, data acquisition, and real-time transmission. The data processing and analysis phase includes data processing, real-time display, and anomaly warning. The post-inspection maintenance phase includes equipment maintenance, data export, and maintenance plan development.

8. The automatic inspection method for unmanned aerial vehicles (UAVs) suitable for wellbore environments according to claim 7, characterized in that: The automatic inspection phase specifically includes: S201, the UAV activates the lighting module and enters the well shaft according to the preset path; the IMU module compensates for the lidar data. S202, the camera and lidar synchronously collect data, and the data acquisition unit associates the data with location and time information; S203, the signal transmission unit transmits data to the platform, and inspection personnel can switch perspectives and control frequency recording / photography.

9. The automatic inspection method for unmanned aerial vehicles (UAVs) suitable for wellbore environments according to claim 7, characterized in that: The data processing and analysis stage specifically includes: S301: The platform detects cracks using image recognition algorithms and determines the location of cracks by combining point cloud data. An early warning is triggered when the crack width is ≥1cm. S302: The platform displays the drone's status and inspection results in real time and generates inspection logs. S303: After the inspection is completed, the historical data files are uploaded to the platform and stored in categories.

10. The automatic inspection method for unmanned aerial vehicles (UAVs) suitable for wellbore environments according to claim 7, characterized in that: In the pre-inspection preparation stage, the preset inspection path includes spiral and vertical types, and the flight speed can be adjusted within the range of 0.5-3m / s; During the post-inspection maintenance phase, the inspection report includes wellbore condition assessment, fracture statistics, and early warning records. The maintenance records are entered into the platform to form a closed-loop management system.

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