Inspection method, device and equipment for oil and gas exploitation system and storage medium

Abstract

The invention discloses an inspection method, device and equipment for an oil and gas exploitation system and a storage medium, and belongs to the technical field of oil and gas exploitation. The method comprises the steps that basic information associated with an inspection point is acquired, the inspection point comprises a to-be-inspected equipment assembly in the oil and gas exploitation system, and the basic information represents the association relationship between the inspection point and inspection equipment; generating first inspection information by using the basic information and the inspection task of the inspection point; performing conflict detection on the first inspection information, and optimizing the first inspection information based on a conflict detection result to obtain second inspection information; routing inspection is conducted on the routing inspection point based on the second routing inspection information, first routing inspection data and second routing inspection data are obtained, the first routing inspection data comprise routing inspection images collected by the image collection device, and the second routing inspection data comprise information collected by the device sensor; and generating an inspection result based on the first inspection data and the second inspection data. The method can improve the inspection accuracy and inspection efficiency of the oil and gas exploitation equipment in the oil and gas exploitation system.

Description

Technical Field

[0001] This application relates to the field of oil and gas extraction, and in particular to an inspection method, apparatus, equipment and storage medium for an oil and gas extraction system. Background Technology

[0002] In the oil and gas extraction process, the regular inspection of the parameters of the oil and gas extraction system plays a crucial role. During the inspection, the parameters of the oil and gas extraction equipment are checked according to designated inspection times and routes. This inspection allows for the timely detection and handling of any abnormalities, ensuring the stable operation of the oil and gas extraction system. For example, oil and gas extraction equipment may include multiple inspection points, which can include instruments, valves, and switches. By inspecting the parameters of these instruments and valves, it can be confirmed whether the equipment parameters of the oil and gas extraction system are within normal limits. Summary of the Invention

[0003] This application provides an inspection method, apparatus, equipment, and storage medium for an oil and gas extraction system, which improves the inspection efficiency and accuracy of the oil and gas extraction system. The technical solution is as follows.

[0004] Firstly, a method for inspecting an oil and gas extraction system is provided, the method comprising:

[0005] Acquire basic information associated with inspection points, where the inspection points include equipment components to be inspected in the oil and gas extraction system. The basic information represents the association between the inspection points and the inspection equipment, and the inspection equipment includes image acquisition equipment and equipment sensors.

[0006] First inspection information is generated using the basic information and the inspection tasks of the inspection points;

[0007] Conflict detection is performed on the first inspection information, and the first inspection information is optimized based on the result of the conflict detection to obtain the second inspection information;

[0008] Based on the second inspection information, the inspection point is inspected to obtain first inspection data and second inspection data. The first inspection data includes the inspection image of the inspection point acquired by the image acquisition device, and the second inspection data includes the information of the inspection point acquired by the device sensor.

[0009] The inspection results are generated based on the first inspection data and the second inspection data.

[0010] Secondly, an inspection device for an oil and gas extraction system is provided, the device comprising:

[0011] The acquisition module is used to acquire basic information associated with inspection points. The inspection points include equipment components to be inspected in the oil and gas extraction system. The basic information represents the association between the inspection points and the inspection equipment. The inspection equipment includes image acquisition equipment and equipment sensors.

[0012] The generation module is used to generate first inspection information using the basic information and the inspection tasks of the inspection points;

[0013] An optimization module is used to perform conflict detection on the first inspection information, and optimize the first inspection information based on the conflict detection results to obtain the second inspection information;

[0014] The inspection module is used to inspect the inspection points based on the second inspection information to obtain first inspection data and second inspection data. The first inspection data includes the inspection images of the inspection points acquired by the image acquisition device, and the second inspection data includes the information of the inspection points acquired by the device sensors.

[0015] The inspection module is also used to generate inspection results based on the first inspection data and the second inspection data.

[0016] In one possible implementation, the first inspection information includes the first inspection path and the first inspection time of the inspection point. The generation module is used to configure the first inspection time of the inspection point using the inspection task of the inspection point; and to generate the first inspection path based on the first inspection time and the basic information.

[0017] In one possible implementation, the conflict detection result includes a first conflict detection result. The optimization module is used to perform conflict detection on the first inspection time of the inspection point to obtain the first conflict detection result, which characterizes the conflict situation of the first inspection time of the inspection point. If the first conflict detection result indicates that there are conflicting inspection points with the same or overlapping first inspection times, the inspection equipment associated with the conflicting inspection point is obtained, and the inspection equipment associated with the conflicting inspection point is optimized to obtain the second inspection information.

[0018] In one possible implementation, the conflict detection result includes a second conflict detection result. The optimization module is used to perform conflict detection on the first inspection path to obtain the second conflict detection result. The second conflict detection result indicates the conflict situation of the first inspection path of the inspection point. If the second conflict detection result indicates that there are conflicting inspection points based on the first inspection path, the module obtains the backoff time of the conflicting inspection points, optimizes the inspection sequence of the inspection points based on the backoff time of the conflicting inspection points, and obtains the second inspection information. The backoff time is determined based on the inspection task.

[0019] In one possible implementation, the inspection module is configured to: determine multiple first inspection images of the inspection point acquired by the image acquisition device within a reference time period based on the second inspection information; determine a first reference element in the multiple first inspection images; calculate the element offset of the first reference element in the multiple first inspection images, wherein the first reference element is a screen element contained in the multiple first inspection images, and the element offset represents the amount of positional change of the first reference element relative to the image acquisition device within the reference time period; and determine the first inspection data based on the first inspection images if the element offset is less than or equal to an offset threshold.

[0020] In one possible implementation, the inspection module is configured to determine a second inspection image of the inspection point acquired by the image acquisition device based on the second inspection information; determine a second reference element in the second inspection image; calculate the edge blur of the second reference element, wherein the second reference element is a scene element contained in the second inspection image, and the edge blur represents the degree of blur of the edge of the second reference element; and determine the first inspection data based on the second inspection image if the edge blur is less than or equal to a blur threshold.

[0021] In one possible implementation, the acquisition module is further configured to acquire the acquisition area of ​​the image acquisition device and the device sensor, determine the identifier of the inspection point included in the acquisition area, and associate the inspection point with the image acquisition device and the device sensor based on the identifier of the inspection point to obtain the basic information of the inspection point.

[0022] In one possible implementation, the acquisition module is further configured to acquire the control status of the image acquisition device and the device sensor;

[0023] The generation module is also used to generate the first inspection information using the basic information, the inspection task of the inspection point, and the control state.

[0024] In one possible implementation, the device further includes a processing module, which is configured to determine data processing parameters for inspection reference data, wherein the inspection reference data represents process data collected or generated during the inspection process, and the inspection reference data includes at least one of the inspection image or the information of the inspection point; the data processing parameters are used to determine at least one of the processing model, data volume, or computing power occupied by the processing data of the inspection reference data; acquire the usage status of the computing resources of the processors in the data processing device, wherein the data processing device includes multiple processors, and the processors are used to process the inspection reference data; allocate a corresponding processor for the inspection reference data from the multiple processors based on the usage status of the computing resources and the data processing parameters; process the inspection reference data based on the allocated processor to obtain a data processing result, wherein the data processing result includes at least one of the first inspection information, the second inspection information, the first inspection data, the second inspection data, or the inspection result.

[0025] Thirdly, embodiments of this application provide a computer device, which includes a processor and a memory. The memory stores at least one piece of program code, which is loaded and executed by the processor to enable the computer device to implement the inspection method of any of the oil and gas extraction systems described above.

[0026] Fourthly, a computer-readable storage medium is also provided, wherein at least one piece of program code is stored in the computer-readable storage medium, the at least one piece of program code being loaded and executed by a processor to enable a computer to implement the inspection method of any of the above-described oil and gas extraction systems.

[0027] Fifthly, a computer program or computer program product is also provided, wherein the computer program or computer program product stores at least one computer instruction, which is loaded and executed by a processor to enable the computer to implement any of the above-mentioned inspection methods for oil and gas extraction systems.

[0028] The technical solution provided in this application brings at least the following beneficial effects:

[0029] This application performs conflict detection on the first inspection information generated using basic information from inspection points and inspection tasks. Based on the conflict detection results, the first inspection information is optimized to obtain second inspection information. This effectively avoids conflicts in inspection time or inspection paths between different inspection points, improving the rationality and efficiency of the second inspection information. Furthermore, using the second inspection information to obtain inspection results can reduce inspection time, increase inspection efficiency, improve the accuracy and timeliness of inspection results, and lower inspection costs. Attached Figure Description

[0030] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0031] Figure 1 This is a schematic diagram of the implementation environment of an inspection method for an oil and gas extraction system provided in an embodiment of this application;

[0032] Figure 2 This is a flowchart of an inspection method for an oil and gas extraction system provided in an embodiment of this application;

[0033] Figure 3 This is a schematic diagram of the timing flow of a conflict detection provided in an embodiment of this application;

[0034] Figure 4 This is a timing diagram of preloading provided in an embodiment of this application;

[0035] Figure 5 This is a schematic diagram of a process for obtaining first inspection data provided in an embodiment of this application;

[0036] Figure 6 This is a schematic diagram of the structure of an inspection device for an oil and gas extraction system provided in an embodiment of this application;

[0037] Figure 7 This is a schematic diagram of the structure of a server provided in an embodiment of this application. Detailed Implementation

[0038] To make the objectives, technical solutions, and advantages of this application clearer, the embodiments of this application will be described in further detail below with reference to the accompanying drawings.

[0039] It should be noted that the terms "first," "second," etc., used in this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such terms can be used interchangeably where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0040] Figure 1 This is a schematic diagram illustrating the implementation environment of an inspection method for an oil and gas extraction system provided in this application embodiment, such as... Figure 1As shown, the implementation environment includes: oil and gas extraction equipment 101, inspection equipment 102, and server 103. The oil and gas extraction equipment 101 is used for producing and transporting extracted oil or natural gas. The inspection equipment 102 is used to inspect the equipment parameters of the oil and gas extraction equipment 101 to ensure its normal operation. The server 103 is communicatively connected to the inspection equipment 102. The inspection data from the inspection equipment 102 can be sent to the server 103, which can process the inspection data to obtain the inspection results.

[0041] Those skilled in the art should understand that the above-described oil and gas extraction system is merely an example. Other existing or future oil and gas extraction systems that are applicable to this application should also be included within the scope of protection of this application, and are hereby incorporated by reference.

[0042] This application provides an inspection method for an oil and gas extraction system, which can be applied to the above-mentioned... Figure 1 The implementation environment is shown. For example, the method can be implemented by... Figure 1 The oil and gas extraction equipment 101, inspection equipment 102, and server 103 interact and execute commands, or the server 103 can execute the commands. The following explanation uses execution by server 103 as an example. Figure 2 As shown, the method includes the following steps 201 to 205.

[0043] In step 201, basic information associated with inspection points is obtained. Inspection points include equipment components to be inspected in the oil and gas extraction system. Basic information represents the relationship between inspection points and inspection equipment. Inspection equipment includes image acquisition equipment and equipment sensors.

[0044] In the exemplary embodiments of this application, the oil and gas extraction system may include oil and gas extraction equipment, which refers to equipment used for producing and transporting oil and natural gas. Oil and gas extraction equipment may include, but is not limited to, drilling equipment, extraction equipment, water injection equipment, compression equipment, separation equipment, transportation pipelines, and storage equipment. The oil and gas extraction equipment may be equipped with multiple inspection points according to equipment type and inspection requirements. Inspection points refer to equipment components or parts of the oil and gas extraction equipment that require regular inspection and maintenance. For example, inspection points may include, but are not limited to, instrumentation equipment, valve equipment, and control equipment. Instrumentation equipment may include pressure gauges, thermometers, and electromagnetic flow meters; valve equipment may include shut-off valves, pressure regulating valves, and flow regulating valves; control equipment may include operating status control equipment, communication control equipment, and parameter control equipment, etc.

[0045] Inspection points for oil and gas extraction equipment can be equipped with corresponding inspection devices, which may include image acquisition devices and equipment sensors. The image acquisition devices can be installed around the inspection point to collect images or videos of the point; these devices may include cameras. The equipment sensors can be located inside the inspection point to collect information about the point; these sensors may include temperature sensors, pressure sensors, flow sensors, and vibration sensors, etc.

[0046] In one embodiment, the process of determining the basic information associated with inspection points may include: acquiring the acquisition area of ​​the image acquisition device and the device sensor, and determining the identifier of the inspection points included in the acquisition area; based on the identifier of the inspection points, associating the inspection points with the image acquisition device and the device sensor to obtain the basic information associated with the inspection points.

[0047] For example, relevant parameters of the image acquisition device and its sensor are obtained. These parameters may include, but are not limited to, the focal length, installation position, and rotation angle of the image acquisition device; the relevant parameters of the sensor may include, but are not limited to, the acquisition distance and installation position of the sensor. These parameters determine the first acquisition area corresponding to the image acquisition device and the second acquisition area corresponding to the sensor. Identifiers (ID1) of the inspection points included within the first and second acquisition areas are obtained, wherein there is a unique correspondence between the inspection point identifier and the inspection point.

[0048] For example, the first acquisition area may include one or more inspection points, and the image acquisition device (camera) can collect information from one or more inspection points. That is, the identifier (ID2) of the image acquisition device and the identifier (ID1) of the inspection point in the first acquisition area are associated. Similarly, the identifier (ID3) of the device sensor and the identifier (ID1) of the inspection point in the second acquisition area are associated. Using the identifier (ID1) of the inspection point, the identifier (ID2) of the image acquisition device and the identifier (ID3) of the device sensor associated with the inspection point can be determined, thus obtaining the basic information of the inspection point. By determining the basic information associated with the inspection point, the relationship between the inspection point, the image acquisition device, and the device sensor is established, which can provide assurance for the subsequent inspection process.

[0049] In step 202, the first inspection information is generated using the basic information and the inspection tasks of the inspection points.

[0050] In the exemplary embodiments of this application, the inspection task can be determined based on the inspection needs or inspection plan of oil and gas extraction equipment. For example, the inspection task may include, but is not limited to, inspection items, inspection time of inspection points, inspection frequency, and priority of inspection points. The inspection item can be an item or equipment that needs to be inspected. The first inspection information includes the first inspection path and the first inspection time of the inspection point. The process of generating the first inspection information using basic information and the inspection task of the inspection point may include: configuring the first inspection time of the inspection point using the inspection task of the inspection point; and generating the first inspection path based on the first inspection time and basic information.

[0051] For example, inspection points with fixed inspection times are determined based on the inspection task, and inspection points with relative inspection times are determined based on the inspection frequency of the inspection task. A corresponding first inspection time is configured for each inspection point based on its priority, inspection duration, fixed inspection time, and relative inspection time. The first inspection time can be a specific point in time or a time period. For example, the first inspection time can be the time when the inspection begins, or it can be a time period with both a start and end inspection time. This application does not limit the method of setting the first inspection time.

[0052] For example, the inspection time for inspection point A is 9:00 AM, and the inspection duration is 10 minutes; the inspection time for inspection point B is any time between 1:00 PM and 1:30 PM, and the inspection duration is 5 minutes; the inspection frequency for inspection point C is 4 times a day, and the inspection duration is 1 hour. The first inspection time for inspection point A is configured as 9:00 AM - 9:10 AM, the first inspection time for inspection point B is 1:20 PM - 1:25 PM, and the first inspection times for inspection point C are 0:00 AM - 1:00 PM, 6:00 AM - 7:00 AM, 12:00 PM - 1:00 PM, and 6:00 PM - 7:00 PM. It should be noted that the above-described first inspection times for the inspection points are illustrative examples, and the inspection times can be configured based on actual inspection conditions; this application does not impose any restrictions on this.

[0053] In one possible implementation, the basic information may further include the location information of inspection points, image acquisition devices, and device sensors. After determining the first inspection time for each inspection point, a first inspection path covering all inspection points can be determined based on the chronological order of the first inspection times and the location information in the basic information. The first inspection path may include the chronological order of the inspection points and the image acquisition devices and device sensors associated with each inspection point. First inspection information is obtained based on the first inspection times and the first inspection path.

[0054] In an exemplary embodiment of this application, before generating the first inspection information, the control status of the image acquisition device and the device sensors can also be obtained; the first inspection information is generated using the basic information, the inspection task of the inspection point, and the control status.

[0055] For example, the control state of the image acquisition device and its sensors can include a controlled state and a free state. The controlled state indicates that the image acquisition device and sensors are currently under the control of the operator, and in this state, they cannot perform inspection tasks. The free state indicates that the image acquisition device and sensors can perform inspection tasks. Therefore, the first inspection information is generated using basic information, the inspection tasks at the inspection points, and the image acquisition device and sensors in a free state. It should be noted that the process of generating the first inspection information using the image acquisition device and sensors in a free state is similar to the process described above, and will not be elaborated upon further here.

[0056] The exemplary embodiment of this application utilizes the inspection task of the inspection point to configure the first inspection time of the inspection point, which can improve the flexibility of configuring the first inspection time of the inspection point while meeting the inspection task. Generating the first inspection path using the first inspection time and basic information can improve the rationality of the inspection process, thereby improving inspection efficiency. Before generating the first inspection information, the control state of the image acquisition device and the device sensor can also be determined. Generating the first inspection information using the image acquisition device and device sensor in a free state can avoid the use of manually controlled image acquisition devices and device sensors during the inspection process, avoiding conflicts and interference caused by manual operation, helping to ensure the continuity and stability of the inspection process, and improving the accuracy and reliability of the inspection data.

[0057] In step 203, conflict detection is performed on the first inspection information, and the first inspection information is optimized based on the conflict detection results to obtain the second inspection information.

[0058] For example, after generating the first inspection information, conflict detection can be performed on at least one of the first inspection time or the first inspection path in the first inspection information. Conflict detection can include time conflict detection and path conflict detection. Time conflict detection is used to avoid using the same image acquisition device to acquire images of different inspection points or using the same device sensor to acquire data of different inspection points during the same inspection time. Path conflict detection is used to avoid multiple inspection tasks using the same image acquisition device or device sensor during the same inspection time. After obtaining the conflict detection result, if the conflict detection result indicates a conflict between the first inspection time or the first inspection path, the first inspection time or the first inspection path can be optimized based on the conflict detection result to obtain second inspection information. The second inspection information can include a second inspection time and a second inspection path. If the conflict detection result indicates that there is no conflict between the first inspection time or the first inspection path, the second inspection time can be the same as or different from the first inspection time; the second inspection path can be the same as or different from the first inspection path.

[0059] In one embodiment, the time conflict detection process may include: performing conflict detection on the first inspection time of the inspection point to obtain a first conflict detection result, the first conflict detection result representing the conflict situation of the first inspection time of the inspection point; if the first conflict detection result indicates that there are conflicting inspection points with the same or overlapping first inspection times, obtaining the inspection equipment associated with the conflicting inspection points, optimizing the inspection equipment associated with the conflicting inspection points, and obtaining second inspection information.

[0060] Taking image acquisition devices as an example, this explanation illustrates the process. Within an inspection area, one inspection point can be associated with multiple image acquisition devices, and multiple inspection points can also be associated with the same image acquisition device. After determining the first inspection time for each inspection point, a conflict detection algorithm can be used to detect the first inspection time of each inspection point, obtaining the first conflict detection result. This first conflict detection result includes the conflict status of the first inspection times between different inspection points. When the first conflict detection result indicates the existence of conflicting inspection points—that is, when the first inspection times of different inspection points are the same or overlap—the image acquisition devices associated with the conflicting inspection points are identified. The conflicting inspection points are then assigned to different image acquisition devices, optimizing the image acquisition devices used during the inspection process, thus obtaining the second inspection information.

[0061] For example, if the first inspection times of inspection points D and E are the same or overlap, then inspection points D and E can be identified as conflicting inspection points. Both inspection points D and E are associated with a first image acquisition device and a second image acquisition device; that is, either the first or second image acquisition device can collect data from inspection points D and E. Inspection points D and E can be assigned to different image acquisition devices. For example, the first image acquisition device collects data from inspection point D, and the second image acquisition device collects data from inspection point E.

[0062] An exemplary embodiment of this application detects conflicts in the first inspection time of inspection points to obtain conflicting inspection points, optimizes the inspection equipment associated with the conflicting inspection points, and obtains second inspection information. Using the second inspection information during the inspection process can effectively avoid time conflicts between different inspection points and improve the efficiency of subsequent inspections based on the second inspection information.

[0063] In another embodiment, the path conflict detection process may include: performing conflict detection on the first inspection path of the inspection point to obtain a second conflict detection result, the second conflict detection result indicating the conflict status of the first inspection path of the inspection point; if the second conflict detection result indicates that there are conflicting inspection points on the first inspection path, obtaining the backoff time of the conflicting inspection points, optimizing the inspection sequence of the inspection points based on the backoff time of the conflicting inspection points, and obtaining second inspection information, the backoff time being determined based on the inspection task.

[0064] Taking the image acquisition device as an example, the inspection path can include multiple inspection points. A conflict detection algorithm is used to perform conflict detection on the image acquisition devices associated with each inspection point in the first inspection path, resulting in a second conflict detection result. This second conflict detection result includes data collected by the same image acquisition device at the same time from multiple inspection points (conflicting inspection points), determining the backoff time for each conflicting inspection point. The backoff time is a random time interval used to delay execution for each conflicting inspection point. The inspection order of the conflicting inspection points is optimized based on the backoff time and the first inspection time; that is, the first inspection path is optimized to obtain a second inspection path. Conflict detection is then performed on each inspection point in the second path. If the conflict detection result indicates that no conflicting inspection points exist, the second inspection information can be obtained. It should be noted that the inspection time of the inspection points after adjusting the inspection order based on the backoff time meets the requirements of the inspection task.

[0065] The following explanation uses a camera as an example to illustrate the concept. Figure 3 This is a schematic diagram of the timing flow for conflict detection provided in an embodiment of this application. Figure 3As shown, inspection points T1 and T2 are both associated with camera 1. Conflict detection is performed on the first inspection path containing inspection points T1 and T2, identifying them as conflicting inspection points. The backoff time for each inspection point is determined. Based on the first inspection time and backoff time of inspection points T1 and T2, the inspection order of inspection points T1 and T2 is determined, and a second inspection path is established. Conflict detection is performed at each inspection point in the second inspection path. If the second inspection path meets the inspection requirements, the second inspection time and second inspection path for inspection points T1 and T2 are determined, thus obtaining the second inspection information.

[0066] An exemplary embodiment of this application detects conflicts on a first inspection path to obtain conflict inspection points, optimizes the inspection sequence of these points using the backoff time of the conflict inspection points, and obtains second inspection information. Using this second inspection information during the inspection process ensures that the same inspection device inspects the same inspection point at the same time, avoiding interruptions or delays in the inspection task due to path conflicts, ensuring the smooth progress of the inspection process, and improving inspection efficiency.

[0067] In step 204, the inspection points are inspected based on the second inspection information to obtain first inspection data and second inspection data. The first inspection data includes the inspection images of the inspection points collected by the image acquisition device, and the second inspection data includes the information of the inspection points collected by the device sensors.

[0068] After determining the second inspection information, the inspection equipment can be controlled to collect information of the inspection points based on the second inspection information. For example, the image acquisition equipment can be controlled to collect images of the inspection points to obtain the first inspection data; the sensor of the control equipment can be controlled to collect information of the inspection points to obtain the second inspection data.

[0069] Optionally, before controlling the image acquisition devices to acquire images of the inspection points, each image acquisition device can be preloaded based on the second inspection information. Taking a camera as an example, when the camera completes image acquisition of the inspection point, the acquired images are preloaded, i.e., a portion of the images are stored in a cache or memory. When processing the acquired images, the preloaded images can be processed directly, reducing image processing waiting time and improving data processing efficiency, especially in mining systems.

[0070] Figure 4 This is a timing diagram illustrating preloading provided in an embodiment of this application. For example... Figure 4 As shown, after cameras 1, 2 and 3 complete the image acquisition at the inspection point, they can preload the images acquired by each camera and then process the preloaded images.

[0071] In an exemplary embodiment of this application, the process of determining the first inspection data using an image acquisition device may include steps 2041 to 2043.

[0072] In step 2041, multiple first inspection images of the inspection points acquired by the image acquisition device within the reference time period are determined based on the second inspection information.

[0073] For example, during the inspection of inspection points, the image acquisition device can rotate to acquire inspection images of multiple inspection points. During this rotation, image shake may occur, or the device may jitter during image acquisition, resulting in unsatisfactory image quality. Therefore, in the process of acquiring images of inspection points based on second inspection information, a reference duration can be determined based on the second inspection time contained in the second inspection information. This reference duration can be a segment of time within the second inspection time. Within this reference duration, the image acquisition device acquires images of the inspection points to obtain the first inspection image, which can be a series of consecutive frames. For example, if the image acquisition device can acquire 24 images per second, and the reference duration is 3 seconds, the corresponding first inspection image would be 72 images.

[0074] In step 2042, a first reference element is determined in multiple first inspection images, and the element offset of the first reference element in multiple first inspection images is calculated. The first reference element is the image element contained in multiple first inspection images, and the element offset represents the change in position of the first reference element relative to the image acquisition device within a reference time period.

[0075] In an exemplary embodiment of this application, the first inspection image may include multiple screen elements, which may be device components included in the first inspection image. At least one first reference element is randomly determined from the multiple screen elements. Then, a reference coordinate system is constructed using the fixed point of the image acquisition device as the origin, and the coordinates of the first reference element in the reference coordinate system are determined respectively. In multiple consecutive first inspection images, the offset corresponding to the first reference element in the first inspection image is determined based on the coordinates of the first reference element. The offset corresponding to the first reference element can be determined based on the coordinates of the first element. For example, the element offset can be the change in position of the first reference element in the reference coordinate system within a reference time period.

[0076] In step 2043, if the element offset is less than or equal to the offset threshold, the first inspection data is determined based on the first inspection image.

[0077] For example, after determining the element offset of the first reference element, the element offset can be compared with an offset threshold. When the element offset is less than or equal to the offset threshold, the image acquisition device can be considered to be in a stationary state. That is, the first inspection image acquired by the image acquisition device meets the requirements of the inspection task. Any image containing the device component to be inspected can be selected from the first inspection image. The instruments in the image are identified based on a target detection algorithm, and the data of the instruments is obtained, thus obtaining the first inspection data. When the element offset is greater than the offset threshold, the reference duration can be re-determined based on the second inspection time, and the first inspection image can be acquired again until the element offset of the first reference element in the first inspection image is less than or equal to the offset threshold. It should be noted that the offset threshold can be set based on the actual inspection task, and this application does not limit it in this regard. Furthermore, the method for determining the first inspection data is illustrative; other methods can also be used to determine the first inspection data.

[0078] An exemplary embodiment of this application calculates the element offset of a first reference element in a first inspection image. Based on the element offset and the offset threshold, a higher quality inspection image can be determined, avoiding the problem of poor quality of the first inspection image caused by jitter or shaking of the acquisition device. This can improve the accuracy and reliability of the first inspection data determined based on the first inspection image.

[0079] In an exemplary embodiment of this application, the process of determining the first inspection data using an image acquisition device may further include steps 2044 to 2046.

[0080] In step 2044, the second inspection image of the inspection point acquired by the image acquisition device is determined based on the second inspection information.

[0081] For example, the number of second inspection images can be one or multiple. The image acquisition device can be controlled to acquire images of the inspection points based on the second acquisition time in the second inspection information to obtain the second inspection image.

[0082] In step 2045, a second reference element is determined in the second inspection image, and the edge blur of the second reference element is calculated. The second reference element is the image element contained in the second inspection image, and the edge blur represents the degree of blur of the edge of the second reference element.

[0083] In the exemplary embodiments of this application, the process of determining the second reference element is similar to that of determining the first reference element, and can be found in the relevant description in step 2042, which will not be repeated here. After determining the second reference element, an edge detection algorithm can be used to calculate the edge blur of the second reference element, wherein the edge blur is used to characterize the degree of blur of the edge of the second reference element in the second inspection image.

[0084] The process of calculating the edge blur of the second reference element can be as follows: Convert the second inspection image to a grayscale image and perform denoising processing on the grayscale image to reduce noise interference. Then, use a gradient algorithm to calculate the gradient changes of the pixels in the edge region of the second reference element in the grayscale image. The gradient change can be the difference in gradient magnitude between the current pixel and its surrounding pixels. Analyze the gradient changes of the pixels in the edge region of the second reference element, for example, by calculating the mean or variance of the gradient changes, and use the calculation result as the edge blur of the second reference element. Taking the calculation of the variance of the gradient change as an example, the larger the variance, the more drastic the gradient change in the edge region, and the clearer the edge; conversely, the smaller the variance, the gentler the gradient change in the edge region, and the more blurred the edge. The reciprocal of the variance can be used as the edge blur of the second reference element.

[0085] In step 2046, if the edge ambiguity is less than or equal to the ambiguity threshold, the first inspection data is determined based on the second inspection image.

[0086] For example, a blur threshold is set based on the image processing requirements of the actual inspection process. The edge blur of the second reference element is compared with the blur threshold. If the edge blur is less than or equal to the blur threshold, the edge of the second inspection image is considered clear, and the image acquisition device is in good focus. If the edge blur is greater than the blur threshold, the edge of the second inspection image is considered blurry, and there may be a defocusing problem. The parameters of the image acquisition device need to be adjusted to re-acquire the second inspection image. After the edge blur of the second inspection image meets the requirements, the first inspection data can be determined based on the second inspection image. The process of determining the first inspection data based on the second inspection image is similar to the process of determining the first inspection data based on the first inspection image. Refer to the relevant description in step 2043, which will not be elaborated further here.

[0087] It should be noted that steps 2044 to 2046 can be executed simultaneously with steps 2041 to 2043, or they can be executed after steps 2041 to 2043; this application does not impose any restrictions on this. Furthermore, the above method for calculating edge ambiguity is illustrative; other methods can also be used to calculate edge ambiguity.

[0088] An exemplary embodiment of this application calculates the edge ambiguity of a second reference element in a second inspection image. Based on the edge ambiguity and ambiguity threshold, a higher quality second inspection image can be determined, which is beneficial for identifying instruments in the second inspection image and obtaining first inspection data, thereby improving the accuracy of the first inspection data.

[0089] The following explanation uses the example of the second inspection image being the same as the first inspection image. Figure 5 This is a schematic diagram of a process for obtaining first inspection data provided in an embodiment of this application. Figure 5 As shown, inspection images are acquired within different reference durations (reference duration 1, reference duration 2, and reference duration 3). Reference elements in the inspection images are determined, the element offset of the reference elements is detected, and then the edge ambiguity of the reference elements is detected. After the element offset detection and edge ambiguity detection meet the requirements of the inspection task, the inspection images can be processed to obtain the first inspection data.

[0090] In step 205, inspection results are generated based on the first inspection data and the second inspection data.

[0091] In an exemplary embodiment of this application, the device sensor can collect data from inspection points in real time to obtain sensor-collected data. After determining the first inspection data, the first acquisition time corresponding to the first inspection data can be obtained, where the first acquisition time can be a time within a reference duration. Based on the first acquisition time, the second inspection data is determined from the sensor-collected data, where the second inspection data corresponds to the second acquisition time of the device sensor, and the second acquisition time is the same as or close to the first acquisition time. The first inspection data and the second inspection data are compared. If the first inspection data and the second inspection data are the same, or if the difference between the first inspection data and the second inspection data is less than or equal to an error threshold, a normal inspection result for the inspection point can be generated; otherwise, an abnormal inspection result for the inspection point is generated, and the abnormal information in the inspection result is reported.

[0092] This application performs conflict detection on the first inspection information generated using basic information from inspection points and inspection tasks. Based on the conflict detection results, the first inspection information is optimized to obtain second inspection information. This effectively avoids conflicts in inspection time or inspection paths between different inspection points, improving the rationality and efficiency of the second inspection information. Furthermore, using the second inspection information to obtain inspection results can reduce inspection time, increase inspection efficiency, improve the accuracy and timeliness of inspection results, and lower inspection costs.

[0093] In an exemplary embodiment of this application, the oil and gas extraction system may include a large number of inspection points, and a large amount of inspection process data, i.e., inspection reference data, may be generated during the inspection process. Therefore, the inspection reference data needs to be processed, and the processing may include steps S1 to S4.

[0094] In step S1, the data processing parameters of the inspection reference data are determined. The inspection reference data represents the process data collected or generated during the inspection process. The inspection reference data includes at least one of the inspection images or inspection point information. The data processing parameters are used to determine at least one of the processing model, data volume, or computing power occupied by the processing data of the inspection reference data.

[0095] For example, during the inspection process, the inspection reference data includes at least one of inspection images or inspection point information. Specifically, an image acquisition device collects information from the inspection points to obtain inspection images; or a device sensor collects information from the inspection points to obtain inspection point information. After determining the inspection reference data, the corresponding data processing parameters can be obtained.

[0096] Taking the inspection reference data as an example, the process is as follows: After obtaining the inspection image, different processing models can be used to process it. These models may include a reference element detection model, an offset calculation model, and an element recognition model. Specifically, the reference element detection model is used to determine reference elements in the inspection image; the offset calculation model is used to calculate the element offset of the reference elements based on the inspection image; and the element recognition model is used to identify the instruments in the inspection image and obtain their readings, i.e., the first inspection data. The processing parameters, such as the processing model used in the inspection image processing, the number of inspection images, and the computing power required to process them, are determined.

[0097] In step S2, the usage status of the computing resources of the processor in the data processing device is obtained. The data processing device includes multiple processors, which are used to process inspection reference data.

[0098] In an exemplary embodiment of this application, a data processing device is used to process inspection reference data. The number of data processing devices can be one or more. For example, a data processing device may include a server. Each data processing device may include multiple processors, wherein the processors may include, but are not limited to, a graphics processing unit (GPU) and a central processing unit (CPU). The usage status of the processor computing resources may include, but is not limited to, GPU utilization, CPU utilization, data task processing time, and the length of the data task queue. Optionally, the memory usage status of the data processing device can also be obtained.

[0099] In step S3, based on the usage status of computing resources and data processing parameters, a corresponding processor is allocated from multiple processors to the inspection reference data.

[0100] In the first embodiment, the data processing device is taken as a server, and the number of servers is one. Processors with low utilization, short data task processing time, and short data task queue lengths can be selected based on the usage status of processor computing resources. That is, the selected processors have low load and sufficient remaining computing power, and the corresponding processors can be configured based on the data processing parameters of the inspection reference data. Optionally, the processing priority of the inspection reference data can also be determined, the processing order of the inspection reference data can be determined based on the priority, and the corresponding processors can be configured sequentially based on the processing order.

[0101] In the second embodiment, the data processing device is used as the server, and there are multiple servers. The inspection reference data is the inspection image. Based on the data processing parameters of the inspection image, the Internet Protocol Address (IP address) of the image acquisition device that acquired the inspection image can be determined. The IP address of the image acquisition device is preprocessed according to the requirements of a hash function. The preprocessing may include, but is not limited to, data padding and data grouping, so that the preprocessed IP address conforms to the input format of the hash function. The hash function is used to calculate a fixed-length hash value on the preprocessed IP address. The hash value can correspond one-to-one with the IP address to distinguish different image acquisition device IP addresses.

[0102] A server is allocated from multiple servers based on its hash value. The allocation process is as follows: the server's computing resource usage status is determined based on the usage status of each processor within the server, and an initial weight is assigned to each server based on this usage status. After acquiring the inspection image, a server can be selected from multiple servers using the data processing parameters corresponding to the inspection image. For example, the server's cycle period is calculated based on its initial weight, and the number of times each server appears within the cycle period is proportional to its initial weight. After acquiring the inspection image, a server is selected according to the order of the cycle periods. Optionally, after determining the server to process the inspection image, a processor for processing the inspection image can also be selected from multiple processors on the server using the same or similar method. By allocating servers for inspection reference data, it can be ensured that inspection reference data from the same IP address is processed by the same server, improving the consistency and continuity of the data processing process.

[0103] In step S4, the inspection reference data is processed based on the assigned processor to obtain data processing results. The data processing results include at least one of the following: first inspection information, second inspection information, first inspection data, second inspection data, or inspection results.

[0104] In an exemplary embodiment of this application, the inspection reference data is processed based on an assigned processor. The processing includes, but is not limited to, image processing and data analysis, resulting in a processed data result. For example, the inspection reference data may be a first inspection image. By using the processor to perform image processing on the first inspection image, the readings of the instruments in the first inspection image can be obtained, i.e., the data processing result. It should be noted that the data processing process described in this application is illustrative and can be determined based on the actual situation of the inspection process; this application does not impose any limitations on this process.

[0105] Optionally, during data processing, the server's data processing progress can be monitored in real time, and the allocated servers can be adjusted as necessary. After obtaining the data processing results, the server's weight can be updated using the server's data processing time and current computing resource usage. For example, if the server's data processing time is short, the server's weight increases; conversely, if the data processing time is long, the server's weight decreases.

[0106] In the exemplary embodiment of this application, during the inspection process, a corresponding data processing device or processor is configured for the inspection reference data based on the data processing parameters of the inspection reference data and the usage status of the computing resources of the processor in the data processing device. This can effectively avoid overload or idle situations of the data processing device or processor, and improve the resource utilization of the data processing device and the processing efficiency of the reference inspection data.

[0107] This application also provides an inspection device for an oil and gas extraction system. Figure 6 This is a schematic diagram of the structure of an inspection device for an oil and gas extraction system provided in an embodiment of this application, as shown below. Figure 6 As shown, the device includes:

[0108] The acquisition module 601 is used to acquire basic information associated with inspection points. Inspection points include equipment components to be inspected in the oil and gas extraction system. Basic information represents the association between inspection points and inspection equipment. Inspection equipment includes image acquisition equipment and equipment sensors.

[0109] The generation module 602 is used to generate the first inspection information using basic information and the inspection tasks of the inspection points;

[0110] The optimization module 603 is used to perform conflict detection on the first inspection information and optimize the first inspection information based on the conflict detection results to obtain the second inspection information.

[0111] The inspection module 604 is used to inspect the inspection points based on the second inspection information to obtain the first inspection data and the second inspection data. The first inspection data includes the inspection images of the inspection points collected by the image acquisition device, and the second inspection data includes the information of the inspection points collected by the device sensors.

[0112] The inspection module 604 is also used to generate inspection results based on the first inspection data and the second inspection data.

[0113] In one possible implementation, the first inspection information includes the first inspection path and the first inspection time of the inspection point. The generation module 602 is used to configure the first inspection time of the inspection point using the inspection task of the inspection point; and to generate the first inspection path based on the first inspection time and basic information.

[0114] In one possible implementation, the conflict detection result includes a first conflict detection result. An optimization module 603 is used to perform conflict detection on the first inspection time of the inspection point to obtain the first conflict detection result, which represents the conflict situation of the first inspection time of the inspection point. If the first conflict detection result shows that there are conflicting inspection points with the same or overlapping first inspection times, the inspection equipment associated with the conflicting inspection points is obtained, and the inspection equipment associated with the conflicting inspection points is optimized to obtain the second inspection information.

[0115] In one possible implementation, the conflict detection result includes a second conflict detection result. The optimization module 603 is used to perform conflict detection on the first inspection path to obtain the second conflict detection result. The second conflict detection result indicates the conflict status of the first inspection path of the inspection point. If the second conflict detection result indicates that there are conflicting inspection points based on the first inspection path, the backoff time of the conflicting inspection points is obtained. The inspection sequence of the inspection points is optimized based on the backoff time of the conflicting inspection points to obtain the second inspection information. The backoff time is determined based on the inspection task.

[0116] In one possible implementation, the inspection module 604 is used to determine multiple first inspection images of inspection points acquired by the image acquisition device within a reference time period based on the second inspection information; determine a first reference element in the multiple first inspection images; calculate the element offset of the first reference element in the multiple first inspection images; the first reference element is a screen element contained in the multiple first inspection images; the element offset represents the change in position of the first reference element relative to the image acquisition device within the reference time period; and determine first inspection data based on the first inspection images if the element offset is less than or equal to an offset threshold.

[0117] In one possible implementation, the inspection module 604 is used to determine a second inspection image of the inspection points acquired by the image acquisition device based on the second inspection information; determine a second reference element in the second inspection image; calculate the edge ambiguity of the second reference element, where the second reference element is a picture element contained in the second inspection image, and the edge ambiguity characterizes the degree of ambiguity of the edge of the second reference element; and determine first inspection data based on the second inspection image when the edge ambiguity is less than or equal to the ambiguity threshold.

[0118] In one possible implementation, the acquisition module 601 is further configured to acquire the acquisition area of ​​the image acquisition device and the device sensor, determine the identifier of the inspection point included in the acquisition area, and associate the inspection point with the image acquisition device and the device sensor based on the identifier of the inspection point to obtain the basic information of the inspection point.

[0119] In one possible implementation, the acquisition module 601 is also used to acquire the control status of the image acquisition device and the device sensors;

[0120] The generation module 602 is also used to generate the first inspection information using basic information, the inspection tasks of the inspection points, and the control status.

[0121] In one possible implementation, the device further includes a processing module (not shown in the figure). The processing module is used to determine the data processing parameters of the inspection reference data, which represents process data collected or generated during the inspection process. The inspection reference data includes at least one of inspection images or inspection point information. The data processing parameters are used to determine at least one of the processing model, data volume, or computing power occupied by the processing data of the inspection reference data. The processing module also acquires the usage status of the computing resources of the processors in the data processing device, which includes multiple processors for processing the inspection reference data. Based on the usage status of the computing resources and the data processing parameters, the processing module allocates a corresponding processor to the inspection reference data from the multiple processors. Based on the allocated processor, the processing module processes the inspection reference data to obtain a data processing result, which includes at least one of first inspection information, second inspection information, first inspection data, second inspection data, or inspection result.

[0122] This application performs conflict detection on the first inspection information generated using basic information of inspection points and inspection tasks. Based on the conflict detection results, the first inspection information is optimized to obtain second inspection information. This effectively avoids conflicts in inspection time or inspection paths between different inspection points, improving the rationality and efficiency of the second inspection information. Furthermore, using the second inspection information to obtain inspection results can reduce inspection time, improve inspection efficiency, and enhance the accuracy and timeliness of inspection results, thereby reducing inspection costs. In addition, configuring corresponding data processing devices or processors for the inspection reference data based on the data processing parameters and the computing resource usage status of the processor in the data processing equipment can effectively avoid overload or idle conditions of the data processing devices or processors, improving the resource utilization of the data processing equipment and the processing efficiency of the reference inspection data.

[0123] It should be understood that the above-described apparatus is only illustrated by the division of the functional modules described above when implementing its functions. In practical applications, the functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. In addition, the apparatus and method embodiments provided in the above embodiments belong to the same concept, and their specific implementation process can be found in the method embodiments, which will not be repeated here.

[0124] Figure 7This is a schematic diagram of a server structure provided in an embodiment of this application. The server 1300 can vary significantly due to different configurations or performance. It may include one or more processors 1301 and one or more memories 1302. Each memory 1302 stores at least one line of program code, which is loaded and executed by the processors 1301 to implement the inspection method for the oil and gas extraction system provided in the various method embodiments described above. Of course, the server 1300 may also have wired or wireless network interfaces, a keyboard, and input / output interfaces for input and output. The server 1300 may also include other components for implementing device functions, which will not be elaborated upon here.

[0125] In an exemplary embodiment, a computer-readable storage medium is also provided, which stores at least one piece of program code, which is loaded and executed by a processor to enable a computer to implement any of the above-described inspection methods for oil and gas extraction systems.

[0126] Optionally, the aforementioned computer-readable storage medium may be a read-only memory (ROM), a random access memory (RAM), a compact disc read-only memory (CD-ROM), magnetic tape, floppy disk, and optical data storage device, etc.

[0127] In an exemplary embodiment, a computer program or computer program product is also provided, which stores at least one computer instruction, which is loaded and executed by a processor to enable the computer to implement any of the above-described inspection methods for oil and gas extraction systems.

[0128] It should be noted that all information (including but not limited to user device information, user personal information, etc.), data (including but not limited to data used for analysis, stored data, displayed data, etc.), and signals involved in this application have been authorized by the user or fully authorized by all parties, and the collection, use, and processing of related data must comply with the relevant laws, regulations, and standards of the relevant countries and regions. For example, the basic information, first inspection information, second inspection information, first inspection data, second inspection data, and inspection results involved in this application were all obtained with full authorization.

[0129] It should be understood that "multiple" as used in this article refers to two or more. "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, or B alone. The character " / " generally indicates that the preceding and following related objects have an "or" relationship.

[0130] The above description is merely an exemplary embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, improvements, etc., made within the principles of this application should be included within the protection scope of this application.

Claims

1. A method for inspecting an oil and gas extraction system, characterized in that, The method includes: Acquire basic information associated with inspection points, where the inspection points include equipment components to be inspected in the oil and gas extraction system. The basic information represents the association between the inspection points and the inspection equipment, and the inspection equipment includes image acquisition equipment and equipment sensors. First inspection information is generated using the basic information and the inspection tasks of the inspection points; Conflict detection is performed on the first inspection information, and the first inspection information is optimized based on the result of the conflict detection to obtain the second inspection information; Based on the second inspection information, the inspection point is inspected to obtain first inspection data and second inspection data. The first inspection data includes the inspection image of the inspection point acquired by the image acquisition device, and the second inspection data includes the information of the inspection point acquired by the device sensor. The inspection results are generated based on the first inspection data and the second inspection data.

2. The method according to claim 1, characterized in that, The first inspection information includes the first inspection path and the first inspection time of the inspection point. Generating the first inspection information using the basic information and the inspection task of the inspection point includes: Configure the first inspection time of the inspection point using the inspection task of the inspection point; The first inspection path is generated based on the first inspection time and the basic information.

3. The method according to claim 2, characterized in that, The conflict detection result includes a first conflict detection result. The process of performing conflict detection on the first inspection information and optimizing the first inspection information based on the conflict detection result to obtain second inspection information includes: Conflict detection is performed on the first inspection time of the inspection point to obtain the first conflict detection result, which represents the conflict situation of the first inspection time of the inspection point. If the first conflict detection result indicates the existence of conflicting inspection points with the same or overlapping first inspection times, the inspection equipment associated with the conflicting inspection points is obtained, and the inspection equipment associated with the conflicting inspection points is optimized to obtain the second inspection information.

4. The method according to claim 2, characterized in that, The conflict detection result includes a second conflict detection result. The process of performing conflict detection on the first inspection information and optimizing the first inspection information based on the conflict detection result to obtain the second inspection information includes: Conflict detection is performed on the first inspection path to obtain the second conflict detection result. The second conflict detection result shows the conflict situation of the first inspection path at the inspection point. If the second conflict detection result indicates that there are conflict inspection points based on the first inspection path, the backoff time of the conflict inspection point is obtained, and the inspection sequence of the inspection points is optimized based on the backoff time of the conflict inspection point to obtain the second inspection information. The backoff time is determined based on the inspection task.

5. The method according to claim 1, characterized in that, The step of inspecting the inspection points based on the second inspection information to obtain the first inspection data includes: Based on the second inspection information, multiple first inspection images of the inspection points acquired by the image acquisition device within a reference time period are determined; A first reference element is determined in the plurality of first inspection images, and the element offset of the first reference element in the plurality of first inspection images is calculated. The first reference element is a screen element contained in the plurality of first inspection images, and the element offset represents the amount of position change of the first reference element relative to the image acquisition device within the reference time period. If the element offset is less than or equal to the offset threshold, the first inspection data is determined based on the first inspection image.

6. The method according to claim 1, characterized in that, The step of inspecting the inspection points based on the second inspection information to obtain the first inspection data includes: Based on the second inspection information, the second inspection image of the inspection point acquired by the image acquisition device is determined; In the second inspection image, a second reference element is determined, and the edge blur of the second reference element is calculated. The second reference element is the image element contained in the second inspection image, and the edge blur represents the degree of blur of the edge of the second reference element. If the edge blurriness is less than or equal to the blurriness threshold, the first inspection data is determined based on the second inspection image.

7. The method according to any one of claims 1 to 6, characterized in that, Before obtaining the basic information associated with the inspection points, the process also includes: Obtain the acquisition area of ​​the image acquisition device and the sensor of the device, and determine the identifiers of the inspection points included in the acquisition area; Based on the identifier of the inspection point, the inspection point is associated with the image acquisition device and the device sensor to obtain the basic information of the inspection point.

8. The method according to any one of claims 1 to 6, characterized in that, Before generating the first inspection information using the basic information and the inspection tasks of the inspection points, the process also includes: Obtain the control status of the image acquisition device and the device sensors; The process of generating first inspection information using the basic information and the inspection tasks of the inspection points includes: The first inspection information is generated using the basic information, the inspection tasks of the inspection points, and the control status.

9. The method according to any one of claims 1 to 6, characterized in that, The method further includes: The data processing parameters for the inspection reference data are determined. The inspection reference data represents the process data collected or generated during the inspection process. The inspection reference data includes at least one of the inspection image or the information of the inspection point. The data processing parameters are used to determine at least one of the processing model, data volume or computing power occupied by the processing data of the inspection reference data. The usage status of the computing resources of the processor in the data processing device is obtained. The data processing device includes multiple processors, which are used to process the inspection reference data. Based on the usage status of the computing resources and the data processing parameters, a corresponding processor is allocated from the plurality of processors to the inspection reference data; The inspection reference data is processed by the assigned processor to obtain a data processing result, which includes at least one of the first inspection information, the second inspection information, the first inspection data, the second inspection data, or the inspection result.

10. An inspection device for an oil and gas extraction system, characterized in that, The device includes: The acquisition module is used to acquire basic information associated with inspection points. The inspection points include equipment components to be inspected in the oil and gas extraction system. The basic information represents the association between the inspection points and the inspection equipment. The inspection equipment includes image acquisition equipment and equipment sensors. The generation module is used to generate first inspection information using the basic information and the inspection tasks of the inspection points; An optimization module is used to perform conflict detection on the first inspection information, and optimize the first inspection information based on the conflict detection results to obtain the second inspection information; The inspection module is used to inspect the inspection points based on the second inspection information to obtain first inspection data and second inspection data. The first inspection data includes the inspection images of the inspection points acquired by the image acquisition device, and the second inspection data includes the information of the inspection points acquired by the device sensors. The inspection module is also used to generate inspection results based on the first inspection data and the second inspection data.

11. A computer device, characterized in that, The computer device includes a processor and a memory, the memory storing at least one piece of program code, which is loaded and executed by the processor to enable the computer device to implement the inspection method of the oil and gas extraction system as described in any one of claims 1 to 9.

12. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores at least one piece of program code, which is loaded and executed by a processor to enable the computer to implement the inspection method for the oil and gas extraction system as described in any one of claims 1 to 9.

13. A computer program product, characterized in that, The computer program product stores at least one computer instruction, which is loaded and executed by a processor to enable the computer to implement the inspection method of the oil and gas extraction system as described in any one of claims 1 to 9.

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