Method, device and system for safety management and control of high-risk operation of oil field

Abstract

The invention discloses a method, a device and a system for safety management and control of high-risk operation of an oil field. The method comprises the following steps: acquiring image information, acquired by an image acquisition module, of each monitoring position of an oil field operation area; processing the image, inputting the processed image into a pre-trained intelligent analysis and identification model for the high-risk action and behavior of the oil field operation, and identifying whether the preset high-risk action and behavior appear in the image; acquiring position information of field personnel in the oil field operation area, and determining a movement track of the field personnel according to the position information of the field personnel; and judging whether a preset early warning rule is met or not according to the movement track of the field personnel in the oil field operation area and the recognition result of the image on the high-risk action and behavior, and if yes, sending out early warning information according to a preset mode. According to the embodiment of the invention, the computer vision identification and the space positioning technology are combined, and remote and automatic safety management of the operation site in the oil field operation area is realized.

Description

Technical Field

[0001] The present invention relates to the technical field of security monitoring, and particularly to a method, device and system for safety control of high-risk operations in oil fields. Background Art

[0002] It is a consensus and development trend in the current energy industry to realize the digital and intelligent transformation and development of oil and gas field enterprises. To ensure the normal operation of oil and gas field stations, the daily operation and maintenance and monitoring of oil and gas production stations are inevitable. On the other hand, with the deep development of remote, deep and small fault block oil and gas fields, more and more new construction and expansion of oil production stations are carried out. How to ensure the efficient monitoring of high-risk operations in oil production plants with limited personnel has become an increasingly prominent safety management problem.

[0003] At present, the established oil production station monitoring systems in China mainly focus on manned operation. Employees conduct regular or irregular on-site inspections, which is a passive monitoring and management method and does not realize the active safety control function for the operations in the oil production station. In the actual implementation of the above management measures, in terms of the safety control of on-site operations, they still cannot fully meet the actual needs, which are mainly reflected in:

[0004] (1) There is a lack of effective supervision means for on-site operators to approach or enter unauthorized operation areas. Personnel safety accidents occur from time to time. Most of the reasons are that operators enter high-risk pressure areas without permission due to various subjective reasons, resulting in personnel safety accidents.

[0005] (2) There is a lack of intelligent early warning and prevention measures for the habitual violations and behaviors of on-site operators not following the regulations in high-risk operations. The violations of on-site operators are still discovered by people on-site or through remote video by the human eyes of monitoring personnel. Through on-site supervision or remote video supervision, omissions will occur due to the limitations of supervisors, and violations cannot be discovered in a timely and effective manner. In addition, this method is inefficient and extremely costly. Summary of the Invention

[0006] In view of the above problems, the present invention is proposed to provide a method, device and system for safety control of high-risk operations in oil fields that overcome the above problems or at least partially solve the above problems.

[0007] In a first aspect, an embodiment of the present invention provides a method for safety control of high-risk operations in oil fields, including:

[0008] Obtaining image information of each monitoring position in the oil field operation area collected by an image acquisition module;

[0009] Process the image, and input the processed image into an intelligent analysis and recognition model for high-risk actions and behaviors in oilfield operations that has been pre-trained to identify whether the preset high-risk actions and behaviors appear in the image;

[0010] Obtain the position information of on-site personnel in the oilfield operation area, and determine the movement trajectory of the on-site personnel according to the position information of the on-site personnel;

[0011] Judge whether it conforms to the preset warning rules according to the movement trajectory of the on-site personnel in the oilfield operation area and the recognition result of high-risk actions and behaviors in the image. If it conforms, send a warning message in a preset manner.

[0012] In one embodiment, collect image information at each monitoring position in the oilfield operation area, including:

[0013] Obtain the monitoring video data at each monitoring position in the oilfield operation area;

[0014] The processing of the image includes:

[0015] Convert the monitoring video data into image frame data and preprocess the image frame data;

[0016] The preprocessing includes one or more of the following:

[0017] Image grayscale, image enhancement, edge extraction, and binarization.

[0018] In one embodiment, obtaining the position information of on-site personnel in the oilfield operation area includes:

[0019] Locate the on-site personnel through the radio frequency device signal received by the radio frequency processing module connected by the LBS positioning system and the number of the radio frequency device corresponding to the radio frequency device signal;

[0020] The radio frequency device signal received by the radio frequency processing module is read from the radio frequency device carried by the on-site personnel by the radio frequency processing module; the number of each radio frequency device has a unique corresponding relationship with each on-site personnel.

[0021] In one embodiment, the intelligent analysis and recognition model for high-risk actions and behaviors in oilfield operations is trained by the following method:

[0022] Extract the image data of the oilfield operation site;

[0023] Extract the features of high-risk actions and behaviors in the image data of the oilfield operation site to generate corresponding feature vectors;

[0024] Encode the types of high-risk actions and behaviors in the image data to obtain vectors of corresponding types;

[0025] Use the feature vectors of high-risk actions and behaviors in the image data and the vectors of the corresponding types as training sample data;

[0026] Use the training sample data to train a preset neural network model to obtain an intelligent analysis and recognition model for high-risk actions and behaviors in oilfield operations.

[0027] In one embodiment, according to the movement trajectories of on-site personnel in the oilfield operation area and the recognition results of high-risk actions and behaviors in the image, determine whether it meets the preset warning rules, including:

[0028] If it is determined according to the movement trajectories of on-site personnel in the oilfield operation area that the on-site personnel are located in a preset dangerous area; and a preset high-risk action or behavior is recognized in the image of the corresponding area, it is determined that a warning needs to be issued.

[0029] In one embodiment, issue a warning message in a preset manner, including:

[0030] According to the level of the warning message, use one or more of the following methods for warning:

[0031] Broadcast through the audio output terminal;

[0032] Display an alarm message on the monitoring terminal.

[0033] In one embodiment, the dangerous area includes: high-voltage area, flammable and explosive area, confined space;

[0034] The high-risk actions or behaviors include: not wearing safety protection equipment, working at heights in violation of regulations, and working in a non-permitted dangerous area.

[0035] In a second aspect, an embodiment of the present invention provides a device for safety control of high-risk oilfield operations, including:

[0036] A first acquisition module for acquiring image information of each monitoring position in the oilfield operation area;

[0037] An identification module for processing the image and inputting the processed image into an intelligent analysis and recognition model for high-risk actions and behaviors in oilfield operations obtained by pre-training to identify whether a preset high-risk action and behavior appear in the image;

[0038] A second acquisition module for acquiring the position information of on-site personnel in the oilfield operation area and determining the movement trajectory of the on-site personnel according to the position information of the on-site personnel;

[0039] An early warning module, configured to determine whether it meets a preset early warning rule according to the movement track of on-site personnel in the oilfield operation area and the recognition result of high-risk actions and behaviors in the image. If it meets, an early warning message is sent in a preset manner.

[0040] In a third aspect, an embodiment of the present invention provides a server, which includes: a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, it implements the method for safety control of high-risk oilfield operations as described above.

[0041] In a fourth aspect, an embodiment of the present invention provides a system for safety control of high-risk oilfield operations, including: an image acquisition module, a personnel positioning module, a radio frequency processing module, a radio frequency device, and a server; wherein:

[0042] The image acquisition module is configured to acquire image information of each monitoring position in the operation area.

[0043] The personnel positioning module is configured to locate the on-site personnel according to the radio frequency signals transmitted by the radio frequency devices carried by the on-site personnel in the oil production station operation area.

[0044] The radio frequency processing module is configured to receive the radio frequency signals transmitted by the radio frequency devices, communicate with the personnel positioning module, and send the radio frequency signals to the personnel positioning module.

[0045] The radio frequency device is configured to be installed on the on-site personnel and emit radio frequency signals.

[0046] The server is configured to obtain the image information of each monitoring position in the oilfield operation area acquired by the image acquisition module; process the image, input the processed image into an intelligent analysis and recognition model of high-risk actions and behaviors in oilfield operations obtained through pre-training, and identify whether there are preset high-risk actions and behaviors in the image; obtain the position information of on-site personnel in the oilfield operation area, and determine the movement track of the on-site personnel according to the position information of the on-site personnel; determine whether it meets a preset early warning rule according to the movement track of on-site personnel in the oilfield operation area and the recognition result of high-risk actions and behaviors in the image. If it meets, it is determined that an early warning message needs to be sent.

[0047] The early warning module is configured to send an early warning message in a preset manner according to the instruction of the server.

[0048] In one embodiment, the image acquisition module is a camera set in the operation area; the personnel positioning module is an LBS positioning system.

[0049] The beneficial effects of the above technical solutions provided by the embodiments of the present invention at least include:

[0050] The above-mentioned method for safety control of high-risk oilfield operations provided by the embodiments of the present invention processes the obtained image information of each monitoring position in the oilfield operation area and inputs it into the intelligent analysis and recognition model of high-risk actions and behaviors in oilfield operations to identify whether there are preset high-risk actions and behaviors in the image. And according to the position information of the on-site personnel in the operation area, it is determined whether the on-site personnel are located in a high-risk area. Combining the results of image intelligent recognition and the geographical location information of the personnel, it is judged whether a warning needs to be issued according to the preset rules. If so, a warning message is sent in the pre-set manner. The embodiments of the present invention combine computer vision recognition and spatial positioning technology to realize remote and automated safety management of the operation site in the oilfield operation area. Through the all-round real-time monitoring of the image information and position information of the on-site operators in the station, it can be timely judged whether the on-site personnel have preset illegal behaviors and give real-time warnings for the illegal behaviors.

[0051] Other features and advantages of the present invention will be described in the following specification, and, in part, will be obvious from the specification, or will be understood by implementing the present invention. The objectives and other advantages of the present invention can be realized and obtained by the structures specifically pointed out in the written specification, claims, and drawings.

[0052] The technical solutions of the present invention will be further described in detail below through the drawings and embodiments. Description of the Drawings

[0053] The drawings are used to provide a further understanding of the present invention and constitute a part of the specification. They are used together with the embodiments of the present invention to explain the present invention and do not constitute a limitation to the present invention. In the drawings:

[0054] Figure 1 is a flowchart of the method for safety control of high-risk oilfield operations in the embodiments of the present invention;

[0055] Figure 2 is a structural block diagram of the device for safety control of high-risk oilfield operations in the embodiments of the present invention;

[0056] Figure 3 is a structural schematic diagram of the high-risk oilfield operation safety control system obtained based on computer vision and spatial positioning in the embodiments of the present invention. Detailed Embodiments

[0057] The exemplary embodiments of the present disclosure will be described in more detail below with reference to the drawings. Although the exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided so that the present disclosure can be more thoroughly understood and the scope of the present disclosure can be fully conveyed to those skilled in the art.

[0058] An embodiment of the present invention provides a method for safety control of high-risk oilfield operations. Referring to Figure 1 as shown, it includes:

[0059] S1. Obtain the image information of each monitoring position in the oilfield operation area collected by the image acquisition module;

[0060] S2. Process the image, and input the processed image into a pre-trained intelligent analysis and recognition model for high-risk actions and behaviors in oilfield operations to identify whether there are preset high-risk actions and behaviors in the image;

[0061] S3. Obtain the position information of on-site personnel in the oilfield operation area, and determine the movement trajectory of the on-site personnel according to the position information of the on-site personnel;

[0062] S4. According to the movement trajectory of on-site personnel in the oilfield operation area and the recognition result of high-risk actions and behaviors in the image, determine whether it conforms to the preset warning rules; if it conforms, execute the following step S5;

[0063] S5. Send a warning message in a preset manner.

[0064] For the method for safety control of high-risk oilfield operations provided by the embodiment of the present invention, after processing the obtained image information of each monitoring position in the oilfield operation area and inputting it into the intelligent analysis and recognition model for high-risk actions and behaviors in oilfield operations, it is identified whether there are preset high-risk actions and behaviors in the image, and according to the position information of on-site personnel in the operation area, it is determined whether the on-site personnel are located in a high-risk area. Combining the result of image intelligent recognition and the geographical location information of personnel, it is determined whether a warning needs to be issued according to the preset rules. If so, a warning message is sent in a preset manner. The embodiment of the present invention combines computer vision recognition and spatial positioning technology to realize remote and automated safety management of the operation site in the oilfield operation area. Through the all-round real-time monitoring of the image information and position information of on-site operators in the station, it can be timely determined whether the on-site personnel have preset violation behaviors and give real-time warnings for violation behaviors.

[0065] In the embodiment of the present invention, the above-mentioned dangerous areas may include, for example: high-voltage areas, flammable and explosive areas, confined spaces, etc.

[0066] The above-mentioned high-risk actions or behaviors may include, for example: not wearing safety protection equipment, climbing heights for operations in violation of regulations, and operating in unauthorized dangerous areas, etc.

[0067] The dangerous areas can be divided according to the actual scenario of the operation area, and are not limited to the above several areas.

[0068] High-risk actions or behaviors can also be artificially restricted according to actual operation specifications, fire protection requirements, relevant rules and regulations for work safety, etc.

[0069] In one embodiment, in the above step S1, the image information of each monitoring position in the oilfield operation area can be collected by obtaining the monitoring video data of each monitoring position in the oilfield operation area.

[0070] The above processing of the image is achieved by the following method:

[0071] The monitoring video data is converted into image frame data, and the following one or more preprocessings are performed on the image frame data:

[0072] Image grayscale, image enhancement, edge extraction, and binarization.

[0073] The monitoring video data is extracted to obtain the data frame by frame, which can refer to the prior art.

[0074] In order to make the recognition of the image more accurate, it is necessary to preprocess the image input into the model, such as performing operations of the above-mentioned image grayscale, image enhancement, edge extraction, and binarization. After the above processing, the image meets the requirements of the input data of the intelligent analysis and recognition model for high-risk actions and behaviors in oilfield operations, and its features are more easily recognized by the intelligent analysis and recognition model for high-risk actions and behaviors in oilfield operations.

[0075] In one embodiment, in the above step S3, the position information of the on-site personnel in the oilfield operation area is obtained, which can be specifically achieved by the following method:

[0076] The on-site personnel are located through the RF device signal received by the RF processing module communicatively connected to the LBS positioning system and the number of the RF device corresponding to the RF device signal.

[0077] Among them, the RF device signal received by the above RF processing module is read by the RF processing module from the RF device carried by the on-site personnel; the number of each RF device has a unique corresponding relationship with each on-site personnel.

[0078] The above RF device can be, for example, an RFID tag. Each on-site operator carries an RFID tag, and this tag can correspond uniquely to this operator. For example, the number of the tag corresponds uniquely to the personnel number of this operator. By reading the RFID tag, the position of the RFID tag can be obtained, and then the real-time position of this operator can be obtained.

[0079] The radio frequency processing module can be, for example, several terminals set at the station operation site, which are used to receive the signals of radio frequency devices carried by on-site personnel. It is communicatively connected to the LBS positioning system, calculates the position information of the active radio frequency card, and can obtain the movement trajectories of the personnel at the station operation site based on the position information and the radio frequency number (such as the card number).

[0080] In one embodiment, the intelligent analysis and recognition model for high-risk actions and behaviors in oilfield operations is trained through the following method:

[0081] Extract the image data of the oilfield operation site;

[0082] Extract the features of high-risk actions and behaviors from the image data of the oilfield operation site to generate corresponding feature vectors;

[0083] Encode the types of high-risk actions and behaviors in the image data to obtain vectors of corresponding types;

[0084] Use the feature vectors of high-risk actions and behaviors in the image data and the vectors of corresponding types as training sample data;

[0085] Use the training sample data to train a preset neural network model to obtain the intelligent analysis and recognition model for high-risk actions and behaviors in oilfield operations.

[0086] The training sample data set can be divided into a training set and a validation set. The model is trained through the training set, and through the validation set, the parameters of the model are adjusted in the way of gradient descent until the preset convergence condition is reached. The learning method of the neural network model can refer to the existing technology. The neural network model can be, for example, a Convolutional Neural Networks (CNN), a Recurrent Neural Network (RNN), etc.

[0087] In one embodiment, in step S4 above, according to the movement trajectories of the on-site personnel in the oilfield operation area and the recognition results of high-risk actions and behaviors in the images, it is judged whether it conforms to the preset warning rules, including:

[0088] If it is judged according to the movement trajectories of the on-site personnel in the oilfield operation area that the on-site personnel are located in a preset dangerous area; and preset high-risk actions or behaviors are recognized in the images of the corresponding area, it is determined that a warning needs to be issued.

[0089] In one embodiment, the warning information can be issued in a preset manner, including:

[0090] According to the level of the warning information, one or more of the following methods are used for warning:

[0091] Broadcast through the audio output terminal;

[0092] Display the alarm information on the monitoring terminal.

[0093] In the embodiment of the present invention, different high-risk actions and behaviors that occur and different high-risk areas where they are located can be defined with warning levels according to the severity of the consequences of the identified high-risk actions and behaviors, and / or the importance of the high-risk areas where the operators are located.

[0094] According to different warning levels, corresponding warning methods can be adopted. For example, various methods such as using audio, alarm lights, or displaying real-time warning information on the monitoring terminal can be used, and corresponding methods are adopted according to the urgency of the behavior results.

[0095] The embodiment of the present invention can also store and display image information, display the location information and movement trajectories of the personnel in the operation area, etc. through the APP, and provide corresponding alarm information (such as identifying high-risk behaviors and actions and marking the real-time location of the operator), and provide corresponding functions on the mobile terminal.

[0096] Based on the same inventive concept, the embodiment of the present invention also provides a device for safety control of high-risk oilfield operations, a server, and a system for safety control of high-risk oilfield operations. Since the principles of solving the problems of these devices, servers, and systems for safety control of high-risk oilfield operations are similar to those of the foregoing method, the implementation of these devices, servers, and systems can refer to the implementation of the foregoing method, and the repeated parts will not be described again.

[0097] A device for safety control of high-risk oilfield operations provided by the embodiment of the present invention, referring to Figure 2 as shown, includes:

[0098] The first acquisition module 21 is used to acquire image information of each monitoring position in the oilfield operation area;

[0099] The recognition module 22 is used to process the image and input the processed image into a pre-trained intelligent analysis and recognition model for high-risk actions and behaviors in oilfield operations to recognize whether the preset high-risk actions and behaviors appear in the image;

[0100] The second acquisition module 23 is used to acquire the location information of the on-site personnel in the oilfield operation area and determine the movement trajectory of the on-site personnel according to the location information of the on-site personnel;

[0101] The warning module 24 is used to judge whether it conforms to the preset warning rules according to the movement trajectory of the on-site personnel in the oilfield operation area and the recognition result of high-risk actions and behaviors in the image. If it conforms, warning information is sent out in a preset manner.

[0102] A server provided by an embodiment of the present invention includes: a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the program, it implements the method for safety control of high-risk oilfield operations as described above.

[0103] A system for safety control of high-risk oilfield operations provided by an embodiment of the present invention includes: an image acquisition module, a personnel positioning module, a radio frequency processing module, a radio frequency device, and a server; wherein:

[0104] The image acquisition module is used to acquire image information of each monitoring position in the operation area.

[0105] The personnel positioning module is used to position the on-site personnel according to the radio frequency signals emitted by the radio frequency devices carried by the on-site personnel in the oil production station operation area.

[0106] The radio frequency processing module is used to receive the radio frequency signals emitted by the radio frequency device, communicate with the personnel positioning module, and send the radio frequency signals to the personnel positioning module.

[0107] The radio frequency device is used to be installed on the on-site personnel and emit radio frequency signals.

[0108] The server is used to obtain the image information of each monitoring position in the oilfield operation area collected by the image acquisition module; process the images, input the processed images into a pre-trained intelligent analysis and recognition model for high-risk actions and behaviors in oilfield operations to identify whether there are preset high-risk actions and behaviors in the images; obtain the position information of the on-site personnel in the oilfield operation area, determine the movement trajectory of the on-site personnel according to the position information of the on-site personnel; judge whether it conforms to the preset warning rules according to the movement trajectory of the on-site personnel in the oilfield operation area and the recognition result of high-risk actions and behaviors in the images. If it conforms, it is determined that a warning message needs to be sent.

[0109] The warning module is used to send a warning message in a preset manner according to the instruction of the server.

[0110] In one embodiment, the image acquisition module is a camera set in the operation area;

[0111] The personnel positioning module is an LBS positioning system.

[0112] Taking a specific example of a system as an example, referring to Figure 3 As shown, in this example, a high-risk oilfield operation safety control system based on computer vision and spatial positioning includes the following combined parts:

[0113] An image acquisition module, an image processing module, an LBS-RFID personnel positioning module, an alarm module, a radio frequency processing module, and a storage, display, and mobile APP module. Among them:

[0114] Image acquisition module: It acquires image information of each monitoring position in the operation area.

[0115] Image processing module: First, it preprocesses the input image, which is used to perform preprocessing operations on the image information acquired by the image acquisition module. The preprocessing operations include one or more of image grayscale conversion, image enhancement, edge extraction, and binarization. Subsequently, it uses a convolutional neural network model to identify the personnel in the input image and determines whether the personnel is wearing safety protection equipment and whether they are performing high-risk operations.

[0116] Lbs-Rfid personnel positioning module: It is used to obtain the position information of on-site personnel in the oil production station operation area. According to the radio frequency device carried by the employee, it obtains the movement trajectory of the employee, and based on the position information and lbs positioning, it determines whether the employee is in a dangerous area such as a high-voltage area, a flammable and explosive area, or a confined space.

[0117] Alarm module: It generates the alarm into a common language and broadcasts it on each audio output terminal within the system and at the operation area site.

[0118] Radio frequency processing module: It is set at several terminals at the station operation site and is used to receive the signals of the radio frequency devices carried by employees. It is communicatively connected to the lbs positioning system, calculates the position information of the active radio frequency card, and obtains the movement trajectory of the personnel at the station operation site based on the position information and the radio frequency card number.

[0119] Storage, display, and mobile APP module: It is used to store and display the image information, position information, movement trajectory, and alarm information, and provides corresponding functions on the mobile side.

[0120] The user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties. And the collection, use, and processing of relevant data need to comply with the relevant laws, regulations, and standards of relevant countries and regions, and corresponding operation entrances are provided for users to choose to authorize or refuse.

[0121] Those skilled in the art should understand that the embodiments of the present invention can be provided as a method, a system, or a computer program product. Therefore, the present invention can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present invention can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk memory and optical memory, etc.) that contain computer-usable program code.

[0122] The present invention is described with reference to the flowcharts and / or block diagrams of methods, apparatuses (systems), and computer program products according to embodiments of the present invention. It should be understood that each flow and / or block in the flowchart and / or block diagram, as well as the combination of flows and / or blocks in the flowchart and / or block diagram, can be realized by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing devices generate means for realizing the functions specified in Figure 1 one flow or multiple flows and / or blocks Figure 1 one block or multiple blocks.

[0123] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing devices to work in a specific manner, so that the instructions stored in the computer-readable memory generate a manufactured article including instruction means, and the instruction means realizes the functions specified in Figure 1 one flow or multiple flows and / or blocks Figure 1 one block or multiple blocks.

[0124] These computer program instructions can also be loaded onto a computer or other programmable data processing devices, so that a series of operation steps are executed on the computer or other programmable devices to generate a computer-implemented process. Thus, the instructions executed on the computer or other programmable devices provide steps for realizing the functions specified in Figure 1 one flow or multiple flows and / or blocks Figure 1 one block or multiple blocks.

[0125] Obviously, those skilled in the art can make various modifications and variations to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalent technologies, the present invention is also intended to include these modifications and variations.

Claims

1. A method for safety control of high-risk operations in oilfields, characterized in that, Including: Obtaining image information of each monitoring location in the oilfield operation area collected by the image acquisition module; Processing the image, and inputting the processed image into an intelligent analysis and recognition model for high-risk actions and behaviors in oilfield operations that has been pre-trained, to identify whether preset high-risk actions and behaviors appear in the image; Obtaining the location information of on-site personnel in the oilfield operation area, and determining the movement trajectory of the on-site personnel according to the location information of the on-site personnel; Judging whether it conforms to a preset warning rule according to the movement trajectory of the on-site personnel in the oilfield operation area and the recognition result of high-risk actions and behaviors in the image. If it conforms, warning information is sent out in a preset manner.

2. The method according to claim 1, characterized in that, Collecting image information of each monitoring location in the oilfield operation area, including: Obtaining the monitoring video data of each monitoring location in the oilfield operation area; The processing of the image includes: Converting the monitoring video data into image frame data, and preprocessing the image frame data; The preprocessing includes one or more of the following: Image grayscale, image enhancement, edge extraction, and binarization.

3. The method according to claim 1, characterized in that, Obtaining the location information of on-site personnel in the oilfield operation area, including: Locating on-site personnel through the radio frequency device signal received by the radio frequency processing module communicatively connected to the LBS positioning system and the number of the radio frequency device corresponding to the radio frequency device signal; The radio frequency device signal received by the radio frequency processing module is read by the radio frequency processing module from the radio frequency device carried by on-site personnel; the number of each radio frequency device has a unique corresponding relationship with each on-site personnel.

4. The method according to claim 1, characterized in that, The intelligent analysis and recognition model for high-risk actions and behaviors in oilfield operations is trained by the following method: Extracting image data of the oilfield operation site; Extracting features of high-risk actions and behaviors in the image data of the oilfield operation site to generate corresponding feature vectors; Encoding the types of high-risk actions and behaviors in the image data to obtain vectors of corresponding types; Taking the feature vectors of high-risk actions and behaviors in the image data and the vectors of corresponding types as training sample data; Using the training sample data to train a preset neural network model to obtain the intelligent analysis and recognition model for high-risk actions and behaviors in oilfield operations.

5. The method according to claim 1, characterized in that, Judging whether it conforms to a preset warning rule according to the movement trajectory of the on-site personnel in the oilfield operation area and the recognition result of high-risk actions and behaviors in the image, including: If it is judged according to the movement trajectory of the on-site personnel in the oilfield operation area that the on-site personnel are located in a preset dangerous area; and preset high-risk actions or behaviors are recognized in the image of the corresponding area, it is determined that a warning is required.

6. The method according to claim 1, characterized in that, Sending out warning information in a preset manner, including: According to the level of the warning information, warning is carried out in one or more of the following ways: Broadcasting through the audio output terminal; Displaying alarm information on the monitoring terminal.

7. The method according to claim 1, characterized in that, The dangerous area includes: high-voltage area, flammable and explosive area, confined space; The high-risk actions or behaviors include: not wearing safety protection equipment, working at height in violation of regulations, and working in a non-permitted dangerous area.

8. A device for safety control of high-risk operations in oilfields, characterized in that, Including: The first acquisition module is used to acquire the image information of each monitoring position in the oilfield operation area; The recognition module is used to process the image, input the processed image into the intelligent analysis and recognition model of high-risk actions and behaviors in oilfield operations obtained through pre-training, and recognize whether there are preset high-risk actions and behaviors in the image; The second acquisition module is used to acquire the position information of on-site personnel in the oilfield operation area, and determine the movement trajectory of the on-site personnel according to the position information of the on-site personnel; The warning module is used to judge whether it conforms to the preset warning rules according to the movement trajectory of the on-site personnel in the oilfield operation area and the recognition result of high-risk actions and behaviors in the image. If it conforms, warning information is sent out in a preset manner.

9. A server, characterized in that, It includes: A memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the program, it implements the method for safety control of high-risk oilfield operations described in any one of claims 1-6.

10. A system for safety control of high-risk operations in oil fields, characterized in that, It includes: An image acquisition module, a personnel positioning module, a radio frequency processing module, a radio frequency device, and a server; wherein: The image acquisition module is used to acquire the image information of each monitoring position in the operation area; The personnel positioning module is used to position the on-site personnel according to the radio frequency signals emitted by the radio frequency devices carried by the on-site personnel in the oil production station operation area; The radio frequency processing module is used to receive the radio frequency signals emitted by the radio frequency device and communicate with the personnel positioning module, and send the radio frequency signals to the personnel positioning module; The radio frequency device is used to be installed on the on-site personnel and emit radio frequency signals; The server is used to acquire the image information of each monitoring position in the oilfield operation area collected by the image acquisition module; process the image, input the processed image into the intelligent analysis and recognition model of high-risk actions and behaviors in oilfield operations obtained through pre-training, and recognize whether there are preset high-risk actions and behaviors in the image; acquire the position information of on-site personnel in the oilfield operation area, and determine the movement trajectory of the on-site personnel according to the position information of the on-site personnel; judge whether it conforms to the preset warning rules according to the movement trajectory of the on-site personnel in the oilfield operation area and the recognition result of high-risk actions and behaviors in the image. If it conforms, it is determined that warning information needs to be sent out; The warning module is used to send out warning information in a preset manner according to the instruction of the server.

11. The system according to claim 1, characterized in that, The image acquisition module is a camera set in the operation area; The personnel positioning module is an LBS positioning system.

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