Communication control methods and systems for integrated oil extraction

Abstract

This application relates to the field of communication mechanism technology, providing a communication control method and system for integrated oil extraction. The method includes: deploying sensors at the oilfield site to collect key data in real time; encoding and timing-marking the data using edge computing devices, uploading it to a virtual layer communication control platform; evaluating the effective parameters of the communication link based on the sensor's response synchronization under the same physical event; performing timing analysis based on the effective parameters to obtain communication control deviations; compensating for synchronization constraints based on the deviations to obtain a communication strategy, and then adjusting and controlling the communication link. This application solves the technical problems of large link delays and high communication interruption rates caused by complex geological environments in traditional oil extraction communication mechanisms. It achieves the technical effect of ensuring the stability and response speed of the communication link by performing edge computing processing and synchronization evaluation on real-time collected data, thereby improving the synchronization accuracy of inter-well control signals.

Description

Technical Field

[0001] This application relates to the field of communication mechanism technology, specifically to a communication control method and system for integrated oil extraction. Background Technology

[0002] With the continuous development of oil extraction technology, especially the widespread application of thermal recovery technologies such as Steam Assisted Gravity Drainage (SAGD), communication and control in oilfield development are facing increasingly complex challenges. In SAGD technology, precise control of steam injection wells and production wells is crucial for improving extraction efficiency, reducing costs, and extending oilfield lifespan. Therefore, ensuring stable, real-time communication between downhole equipment and surface control systems has become one of the key technologies in oilfield development.

[0003] However, in actual oilfield environments, there are many unfavorable factors, such as complex geological structures, high temperature and high pressure conditions, and strong magnetic field interference. These factors not only affect the operating status of equipment but also pose a severe challenge to the stability of communication links. Traditional communication mechanisms often suffer from large link delays and frequent communication interruptions due to complex formation structures and large distances between wells, which in turn affect the stability and response speed of control. Summary of the Invention

[0004] This application provides a communication control method and system for integrated oil extraction, aiming to solve the technical problems of large link delay and high communication interruption rate caused by complex geological environments in traditional oil extraction communication mechanisms.

[0005] The first aspect disclosed in this application provides a communication control method for integrated oil extraction. The method includes: deploying multiple types of sensors, including steam injection wells and production wells, at the oilfield site to collect key data such as temperature, pressure, wellbore position, and steam injection rate in real time; using edge computing devices to uniformly encode and time-series label the collected data, uploading it to a communication control platform in a virtual layer; evaluating the effective parameters of the communication link based on the response synchronization of multiple sensors under the same physical event; performing time-series analysis based on the effective parameters of the communication link to obtain the communication control deviation; performing communication synchronization constraint compensation based on the communication control deviation to obtain a communication control strategy; and performing communication link adjustment control based on the communication control strategy.

[0006] Another aspect of this application discloses a communication control system for integrated oil extraction. The system includes: a data acquisition module: deploying multiple types of sensors, including steam injection wells and production wells, at the oilfield site to collect key data such as temperature, pressure, wellbore position, and steam injection rate in real time; a synchronization evaluation module: using edge computing devices to uniformly encode and time-series-mark the collected data, uploading it to a virtual layer communication control platform, and evaluating the effective parameters of the communication link based on the response synchronization of multiple sensors under the same physical event; a timing analysis module: performing timing analysis based on the effective parameters of the communication link to obtain communication control deviations; and an adjustment control module: compensating for communication synchronization constraints based on the communication control deviations to obtain a communication control strategy, and performing communication link adjustment control based on the communication control strategy.

[0007] One or more technical solutions provided in this application have at least the following technical effects or advantages: The aforementioned communication control method for integrated oil extraction first monitors key data such as temperature, pressure, wellbore position, and steam injection rate in real time by deploying multiple sensors on steam injection wells and production wells. Then, edge computing devices uniformly encode and time-series-label this collected data before uploading it to the communication control platform in the virtual layer. Next, the platform evaluates the effectiveness of the communication link based on the synchronization of responses from multiple sensors to the same physical event. Through time-series analysis, it identifies control deviations in the communication link and compensates for these deviations to ensure communication synchronization. Finally, an optimized communication control strategy is formulated, and the communication link is adjusted and optimized according to this strategy to guarantee communication stability and efficiency.

[0008] The above description is merely an overview of the technical solution of this application. In order to better understand the technical means of this application and to implement it in accordance with the contents of the specification, and to make the above and other objects, features and advantages of this application more obvious and understandable, specific embodiments of this application are given below. Attached Figure Description

[0009] To more clearly illustrate the technical solutions in the embodiments of the present invention, 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 the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0010] Figure 1 This is a flowchart illustrating a communication control method for integrated oil extraction in one embodiment.

[0011] Figure 2 This is a diagram of a communication control system architecture for integrated oil extraction in one embodiment.

[0012] Figure labeling: Data acquisition module 11, Synchronization evaluation module 12, Time series analysis module 13, Adjustment and control module 14. Detailed Implementation

[0013] This application provides a communication control method and system for integrated oil extraction, which solves the technical problems of high link delay and high communication interruption rate caused by complex geological environments in traditional oil extraction communication mechanisms.

[0014] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application.

[0015] It should be noted that the terms “comprising” and “having”, and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or server that includes a series of steps or units is not necessarily limited to those steps or units that are explicitly listed, but may include other steps or modules that are not explicitly listed or that are inherent to such process, method, product, or device.

[0016] Example 1, as Figure 1 As shown, this application provides a communication control method for integrated oil extraction, the method comprising: Multiple types of sensors, including those for steam injection wells and production wells, are deployed at the oilfield site to collect key data such as temperature, pressure, wellbore position, and steam injection rate in real time.

[0017] In this embodiment, various types of sensors, such as temperature sensors, pressure sensors, displacement sensors, and flow sensors, are deployed in the oilfield for steam injection wells and production wells. Each sensor is installed at different depths and locations downhole to ensure accurate reflection of changes in various downhole parameters. Specifically, the temperature sensor is used to collect real-time temperature changes of steam and crude oil in the well, thereby determining the effectiveness of steam injection and its interaction with the oil layer; the pressure sensor is used to collect real-time pressure changes in the well, ensuring that the steam injection process does not exceed the tolerance range of the equipment or the oil layer, preventing safety accidents; the displacement sensor is used to collect real-time lateral and longitudinal offsets of the wellbore, determining the real-time position of the wellbore to avoid deviations from the designed trajectory, which could affect the uniform distribution of steam and the effective displacement of the oil layer; and the flow sensor is used to quantify the steam injection rate by collecting the flow rate of the injected steam, ensuring that the steam injection speed meets the predetermined production requirements and avoiding excessively fast or slow injection speeds that could affect the permeability of the oil layer or the steam utilization efficiency. Real-time collection of these data provides a reliable basis for subsequent data processing, analysis, and decision-making.

[0018] The collected data is uniformly encoded and time-series labeled using edge computing devices and uploaded to the communication control platform of the virtual layer. Based on the response synchronization of multiple sensors under the same physical event, the effective parameters of the communication link are evaluated.

[0019] In one embodiment, after receiving data from multiple sensors, the edge computing device first performs unified encoding and time-series marking on this data. Unified encoding uses the edge computing device's built-in protocol conversion middleware (based on the OPC UA standard) to convert the raw data from various sensors into a standard encoding format, such as JSON, and adds a unique device identifier to the data packet header for accurate identification and parsing during subsequent transmission and analysis. Time-series marking uses the edge computing device's built-in clock to automatically generate a timestamp (UTC time format) during data conversion. For example, when a steam injection well pressure sensor detects a pressure surge at 13:45:30.123456789, the timestamp field of the corresponding data packet will be marked as "2024-10-05T13:45:30.123456789Z". Time-series marking ensures that all data is arranged in the order of acquisition time, enabling synchronous data exchange between different sensors collected at the same time, ensuring data consistency and timeliness. Subsequently, the encoded and time-stamped data is uploaded to the communication control platform of the virtual layer. This platform collects synchronization data from multiple sensors, analyzes the synchronicity of sensor responses under the same physical event, and calculates multiple evaluation parameters. By integrating these evaluation parameters, the effective parameters of the communication link can be determined. These effective parameters will serve as the basis for subsequent adjustments to the communication link configuration and optimization of control strategies. In this way, the communication control platform can understand the status of the communication link in real time, ensuring that the stability and reliability of data transmission remain at their optimal levels throughout the oilfield extraction process.

[0020] Furthermore, this application provides methods for evaluating effective parameters of a communication link based on the response synchronization of multiple sensors under the same physical event, including: The first evaluation parameter is obtained by analyzing the alignment of the timestamps of the collected data; the second evaluation parameter is obtained by judging the consistency of the trend of physical quantities; the third evaluation parameter is obtained by detecting the data collection frequency and update stability; the first evaluation parameter, the second evaluation parameter and the third evaluation parameter are weighted and aggregated to obtain the effective parameters of the communication link.

[0021] Preferably, for data collected by each sensor, the alignment of multi-sensor data triggered by the same physical event (such as the opening of a steam injection valve) is analyzed. In this process, the median of the timestamp differences is calculated, and the ratio of this median to the maximum allowable time difference is subtracted from 1. The resulting difference is the alignment score, which is added to the first evaluation parameter to reflect the effectiveness of the communication link in time synchronization. To assess the consistency of physical quantity trends under the same physical event, the Pearson correlation coefficient is calculated for each pair of sensor data (such as temperature and pressure), and the average of the Pearson correlation coefficients of all sensor pairs is calculated. This average is the trend consistency score, which is added to the second evaluation parameter to reflect whether the data transmitted by the communication link conforms to physical laws. To assess the stability of data updates under the same physical event, a Fourier transform (FFT) is performed on the data stream of each sensor to extract the dominant frequency component. The standard deviation of frequency fluctuation is then calculated, and the ratio of this standard deviation to the dominant frequency component is subtracted from 1. The resulting difference is the stability score, which is added to the third evaluation parameter to reflect the frequency stability of data transmission in the communication link. After obtaining the first, second, and third evaluation parameters, in order to comprehensively evaluate the effectiveness of the communication link, the three evaluation parameters are weighted and aggregated using pre-configured weights to obtain the final effective parameters of the communication link. These effective parameters reflect the overall performance of the entire communication link and can comprehensively evaluate the stability, real-time performance, and reliability of the communication link, providing a basis for further optimizing the communication link and improving data transmission stability.

[0022] Based on the effective parameters of the communication link, timing analysis is performed to obtain the communication control deviation.

[0023] In one embodiment, after acquiring valid parameters of the communication link, a complete data time-series chain is established based on the encoded and tagged time-series data uploaded by sensors to the communication control platform. Then, a moving time window is continuously slid across the data time-series chain, and the data within each window is analyzed to quantify the timing deviation in the communication link, thereby deriving a communication control deviation to reflect the gap between the actual communication link and the expected target. This deviation index provides a basis for subsequent communication control strategy optimization, ensuring that communication can be dynamically adjusted according to the link status, improving the stability and efficiency of the communication link, and thus ensuring the real-time performance and accuracy of data transmission during oilfield exploitation.

[0024] Furthermore, this application provides a method for obtaining communication control deviations by performing timing analysis based on the effective parameters of the communication link, including: Based on the unified encoding and timing markers, a data timing chain for the collected data is established; a moving time window is set, and the data timing chain is divided into windows based on the moving time window to obtain a window timing chain; based on the effective parameters of the communication link, the window timing chain is analyzed for deviation timing to obtain the communication control deviation.

[0025] Optionally, on the communication control platform, a complete data time-series chain is constructed based on sensor data with unified encoding and timing tags. This data time-series chain is a continuous data stream formed by arranging all data points of each sensor in chronological order, ensuring the timeliness and synchronization of the data. Subsequently, to more accurately analyze the temporal changes of the data, a moving time window is set. This moving time window can slide within the data time-series chain, and its length can be set according to specific business needs, such as 1 second, 10 seconds, or a longer time period. The moving time window then slides chronologically within the data time-series chain, and each time it slides, the data within the window is segmented, thus dividing the entire data time-series chain into multiple window time-series chains. This avoids excessive complexity and processing delays caused by processing the entire chain of data as a single unit. After each window time-series chain is generated, deviation analysis is performed on the time-series chain based on the effective parameters of the communication link. Specifically, for each window timing chain, the standard deviation of the sensor response time difference within the window is first calculated, then the standard deviation is divided by the tolerance standard deviation, and the calculated quotient is multiplied by the effective parameters of the communication link to obtain the time offset deviation. This time offset deviation will be used as the communication control deviation to reflect the gap between the actual data transmission process and the ideal transmission situation.

[0026] Based on the communication control deviation, communication synchronization constraint compensation is performed to obtain a communication control strategy, and communication link adjustment control is performed based on the communication control strategy.

[0027] In one embodiment, after obtaining the communication control deviation, a communication synchronization constraint compensation analysis is performed on the calculated communication control deviation based on the response relationship between the steam injection well and the production well. This determines a compensation chain for communication compensation, which defines how to compensate for timing deviations in each time window, ensuring that data is transmitted in the expected order. Subsequently, the adjustable parameters of the communication are analyzed based on the compensation chain to formulate an optimal communication control strategy. This strategy is adjusted according to the compensated link status to ensure that the communication link remains stable and efficient in different operating environments. For example, the communication control strategy may include optimizing the data transmission rate, adjusting the channel bandwidth, and setting the data transmission priority. Afterwards, according to the determined communication control strategy, corresponding adjustments to the communication link are executed, such as adjusting the communication bandwidth and optimizing the data transmission path, to ensure that the communication link operates stably in dynamically changing environments. Simultaneously, the communication link status is monitored in real time, the communication control strategy is updated based on new deviations, and further adjustments are made to the communication link to ensure that the entire system maintains optimal communication performance and data transmission efficiency throughout the oilfield extraction process.

[0028] Furthermore, this application provides a communication control strategy by compensating for communication synchronization constraints based on the aforementioned communication control deviation, including: Establish the target response relationship between the steam injection well and the production well; perform communication synchronization compensation on the communication control deviation according to the target response relationship to obtain a compensation chain; and perform communication adjustable parameter link search based on the compensation chain to obtain the communication control strategy.

[0029] Optionally, there is an interaction between the steam injection well and the production well. Typically, the injected steam affects parameters such as pressure and temperature in the production well. To ensure effective coordination between the steam injection well and the production well, it is first necessary to define their target response relationship. This target response relationship describes how the operation of the steam injection well (e.g., steam injection rate) affects the response of the production well (e.g., oil production rate, pressure changes) under different operating conditions. To accurately quantify this relationship, a regression model is built based on historical data to describe the functional relationship between the steam injection rate and the production well response. This model, based on physical laws (SAGD process mechanism) and historically collected data, uses the least squares method to continuously fit the model parameters until the fitting error meets the error threshold. Subsequently, based on the target response relationship, communication control deviations are analyzed to calculate a compensation amount. One or more compensation measures are then matched according to the calculated compensation amount. By arranging these compensation measures, a compensation chain is formed to ensure precise synchronization of communication between the steam injection well and the production well, so that the operation of the injection well can influence the response of the production well according to the predetermined target. Next, this compensation chain is used to match within the adjustable communication parameter library to identify key parameters that need adjustment, such as bandwidth allocation parameters, data transmission cycle parameters, and transmission priority. Based on these parameters, optimization is performed to determine multiple candidate parameter combinations. Then, these candidate parameter combinations are iterated through, and combined with the actual state of the current communication link and the target response relationship, the optimal candidate parameter combination is selected to construct a communication control strategy. This strategy minimizes communication delays and deviations, ensuring synchronized operation between steam injection wells and production wells, thereby improving the oilfield's production efficiency and stability.

[0030] Furthermore, this application provides a method for searching adjustable communication parameters based on the compensation chain to obtain the communication control strategy, including: Establish a communication adjustable parameter library, including channel bandwidth allocation parameters, data transmission cycle parameters, transmission priority, retransmission threshold, and channel switching; based on the communication adjustable parameter library, analyze the key parameters affecting communication deviation in the compensation chain; according to the key parameters, traverse the parameter space through constraint rules to search for candidate parameter combinations; combine the current communication link status and target response relationship to determine the optimal communication control strategy from the candidate parameter combinations.

[0031] Optionally, during the communication link optimization process, a communication adjustable parameter library is first established. This library includes channel bandwidth allocation parameters, data transmission cycle parameters, transmission priority, retransmission threshold, and channel switching. The channel bandwidth allocation parameter determines the maximum amount of data (i.e., bandwidth) that each channel can transmit. By setting different bandwidth parameters, different transmission requirements and environmental conditions can be accommodated. The data transmission cycle parameter determines the frequency of data transmission on the communication link. By setting different data transmission cycles, sudden situations or changes in equipment status can be addressed. Transmission priority defines which data should be transmitted first and which can be delayed when multiple data streams are transmitted, determining the data transmission order for different types of data. The retransmission threshold refers to how many retransmission attempts are allowed when data packet loss or communication errors occur. An excessively high retransmission threshold may lead to long delays, while an excessively low threshold may result in information loss. Channel switching controls when and how to switch from the current communication channel to another channel, thereby avoiding control delays or data loss due to communication instability. Subsequently, compensation measures for the communication link at different time periods are obtained from the compensation chain. Based on these measures, key parameters that significantly affect the deviation are identified from the adjustable communication parameter library. These key parameters are the main parameters adjusted by the compensation measures; for example, bandwidth optimization targets the channel bandwidth allocation parameter. Next, to ensure system stability and communication quality, constraints are set based on the actual equipment conditions. For example, bandwidth cannot exceed the physical channel capacity, the transmission period cannot be less than 1 / 10 of the low-frequency data period, and the proportion of high-priority data packets in the same channel cannot exceed 70%. These constraints ensure that the selected parameter combinations do not lead to excessive load or unstable communication during optimization. After determining the constraints, they are used to limit the parameter space. Random combinations of key parameters are then iterated through the parameter space. Each iteration yields key parameter values ​​that satisfy the constraints and serves as candidate parameter combinations for reference when selecting the optimal strategy in the next step. Then, the current communication link status and target response relationship are input into simulation software to simulate the current communication scenario. Candidate parameter combinations are then synchronized to the simulation scenario for adjustment, determining multiple simulation effect parameters, such as the current link's transmission rate, latency, signal strength, and data packet loss rate. Finally, by performing entropy calculations on these evaluation parameters, the optimal candidate parameter combination is determined to form the final communication control strategy, ensuring maximum performance of the communication link.

[0032] Furthermore, this application provides a method for determining the optimal communication control strategy from the candidate parameter combinations, including: The communication entropy is evaluated based on the multi-sensor time alignment error, physical quantity response trend offset, actual communication link delay, communication link packet loss rate, and data update frequency fluctuation to obtain the communication entropy; based on the communication entropy, the parameter combination with the highest risk tolerance is selected from the candidate parameter combinations to determine the optimal communication control strategy.

[0033] Optionally, after simulating the candidate parameter combinations, the effect parameters of this simulation adjustment will be obtained, including multi-sensor time alignment error, physical quantity response trend offset, actual communication link delay, communication link packet loss rate, and data update frequency fluctuation. Subsequently, based on these effect parameters, a comprehensive communication entropy index is calculated using the entropy formula. This communication entropy measures the overall uncertainty and risk of the communication link; the higher the communication entropy, the greater the uncertainty of the link, and the lower its stability and reliability. Then, based on the calculated communication entropy, risk tolerance conditions corresponding to the risk level are matched. Finally, based on the risk tolerance conditions, the parameter combination with the minimum fault tolerance and optimal response efficiency is selected as the optimal communication control strategy. This optimal communication control strategy will ensure real-time and stable data transmission under various communication environments and support efficient control and decision-making processes, thereby improving the efficiency and intelligent control capabilities of oilfield extraction.

[0034] Furthermore, this application provides a method for determining the optimal communication control strategy by selecting the parameter combination with the highest risk tolerance from the candidate parameter combinations based on the communication entropy, including: A risk tolerance model is established for each candidate parameter combination, including a preset communication mitigation adaptability threshold, response delay tolerance, and control stability scoring standard. The risk tolerance of each candidate parameter combination is evaluated using the risk tolerance model. The communication entropy is classified into levels, and the risk tolerance conditions corresponding to each level are determined. Based on the risk tolerance conditions, the parameter combination that meets the minimum fault tolerance required for the current communication entropy level and has the best response efficiency is selected from the candidate parameter combinations as the optimal communication control strategy.

[0035] Optionally, after obtaining candidate parameter combinations, a risk tolerance model is built for each combination. These models can be constructed based on deep neural networks and can predict the communication mitigation adaptability range, response delay tolerance, and control stability score of the candidate parameter combination based on the input candidate parameter combination and communication entropy. The construction process typically includes forward propagation, loss calculation, backpropagation, and parameter optimization. Furthermore, each risk tolerance model is associated with a set of preset thresholds, including preset communication mitigation adaptability thresholds, response delay tolerance, and control stability score criteria. The preset communication mitigation adaptability thresholds represent the range that can be automatically adapted to abnormal communication states; the response delay tolerance defines the acceptable upper limit of control response delay in practical applications; and the control stability score criteria represent stability under disturbances. Subsequently, the system uses a constructed risk tolerance model to evaluate the risk tolerance of the current candidate parameter combinations and their corresponding communication entropy. This predicts the communication mitigation adaptability range, response delay tolerance, and control stability score of the current candidate parameter combinations. The deviations of these scores are then calculated against corresponding thresholds, and weighted to obtain the risk tolerance of the current candidate parameter combinations. Next, the system matches the communication entropy of the current candidate parameter combinations with a risk level table. This risk level table is pre-defined based on the range of communication entropy values ​​and includes multiple communication entropy ranges, such as 0 to 0.3 for low risk and 0.3 to 0.6 for medium risk. Each risk level also corresponds to a risk tolerance range. By comparing the communication entropy, the risk tolerance range corresponding to the current communication entropy can be extracted from the risk level table and used as the risk tolerance condition. The same operation is performed for other candidate parameter combinations to obtain their corresponding risk levels and risk tolerance conditions. Then, the calculated risk tolerance of each candidate parameter combination is compared with the corresponding risk tolerance conditions. Candidate parameter combinations that do not meet the risk tolerance conditions are eliminated. Then, the candidate parameter combination with the minimum fault tolerance and the optimal response efficiency is extracted from the remaining candidate parameter combinations. In other words, the candidate parameter combination with the minimum tolerance and the minimum response delay under the premise of ensuring communication stability is extracted as the optimal communication control strategy and applied to communication link scheduling and control.

[0036] Furthermore, this application provides a communication control platform for uploading to the virtual layer, which also includes: A digital twin model is constructed to map the structural state of the steam injection well and the production well in real time, and the historical trajectory and operating trend of the downhole equipment are dynamically updated based on the collected data. The digital twin model is used to predict the trend of communication entropy changes based on historical communication status data, equipment operating status and environmental disturbance parameters. When the predicted communication entropy exceeds a preset threshold, the communication control platform performs parameter combination screening and preloads the corresponding communication control strategy in advance, so as to complete the link control strategy switch before the entropy value actually reaches the preset threshold.

[0037] Optionally, based on 3D wellbore structure data, sensor installation locations, and tubing structure parameters, a digital twin model of the steam injection well and the production well is established. The model includes static structural information such as wellbore morphology, depth distribution, steam injection and oil production nodes, sensor locations, and pipeline interface status. Data from various types of sensors, including temperature, pressure, wellbore position, and steam injection rate, are then mapped in real-time to their corresponding physical locations in the digital twin model. The historical trajectory and operational trends recorded in the model are updated to match the equipment operating status data of the digital twin model with the actual situation. Subsequently, based on the historical communication status data (i.e., the recorded historical trajectory and operational trends) bound to the digital twin model, combined with historical communication status data (communication delay records, packet loss rate changes, bandwidth, etc.) and environmental disturbance parameters (wellbore temperature gradient, steam injection fluctuations, etc.), a communication entropy prediction model is used to predict the communication entropy values ​​for several future time steps (e.g., the next 10 minutes, 30 minutes), forming a communication entropy change curve. This communication entropy prediction model is constructed based on a Long Short-Term Memory (LSTM) network, and the construction method is similar to that described above. The communication entropy change curve is then compared with a preset threshold. If any data in the curve exceeds the threshold, the communication control platform will perform the aforementioned parameter combination process (i.e., obtain candidate parameter combinations) before determining the corresponding communication control strategy. Once the communication control strategy is determined, it is not immediately loaded and used; instead, it is cached in the edge computing device. This way, when the communication entropy actually reaches the threshold, there is no need to recalculate; the pre-loaded communication control strategy is directly activated, achieving a delay-free switchover and effectively preventing communication interruptions or control failures caused by sudden changes in link state.

[0038] Furthermore, this application provides communication link adjustment control based on the aforementioned communication control strategy, and further includes: Monitor the communication response effect after the communication link is adjusted, including data transmission integrity, policy execution delay and communication entropy change trend; perform correlation analysis between the communication response effect and the communication control policy to form a policy execution feedback record; update the policy evaluation factor in the communication adjustable parameter library based on the feedback record, optimize the subsequent parameter selection criteria, and write the relevant data back to the digital twin model to correct the fitting bias and parameter weights in the communication entropy prediction model.

[0039] Optionally, after the communication control strategy is implemented, in order to continuously optimize communication performance and enhance adaptability, the communication control platform will monitor the response effect after link adjustment, and obtain data transmission integrity (the ratio of effective data packets per minute to the total number of data packets), strategy execution latency (the time difference between the issuance of the strategy activation command and the actual completion of link parameter adjustment), and communication entropy change trend. Subsequently, a mapping table is established for the adjustment behavior of each communication link, clarifying the current application's communication control strategy, and associating strategy parameters with monitoring results to form strategy-effect pairs. These strategy-effect pairs will form a strategy execution feedback record. Then, the actual effect results in the feedback record are compared with the original evaluation factors (such as application success rate, entropy improvement, and average latency response) of each parameter combination in the adjustable communication parameter library, and dynamically updated according to time-weighted averaging or a sliding window method. In future parameter combination screening processes, parameter combinations with high evaluation factors and stable historical performance will be prioritized to improve strategy adaptation success rate and response efficiency. Simultaneously, evaluation factor thresholds can be set to automatically eliminate combinations with multiple historical application failures or large effect fluctuations, reducing the parameter space and improving screening efficiency. Then, the key elements (entropy changes, response effects, and strategy parameters) in the strategy feedback records are structured and encoded, marked by time and link location to form a feedback data sequence. This feedback sequence is then written back into the corresponding digital twin model of the downhole equipment and fused with information such as historical operating trajectories and equipment status. Finally, feedback data is introduced into the communication entropy prediction model. By comparing the difference between the predicted entropy and the actual entropy, residual training optimization is performed to improve the model's prediction accuracy. Furthermore, based on the actual impact of different parameter combinations on entropy changes, the weights of the model's input features are adjusted, thereby achieving dynamic optimization of the communication entropy prediction model. This forms a closed-loop control of prediction-execution-feedback-correction, improving the model's scenario adaptability and predictive foresight.

[0040] In summary, the embodiments of this application have at least the following technical effects: This application first deploys multiple types of sensors, including steam injection wells and production wells, in the oilfield to collect key data such as temperature, pressure, wellbore position, and steam injection rate in real time. Then, edge computing devices are used to uniformly encode and time-track the collected data, which is then uploaded to the communication control platform of the virtual layer. Based on the synchronicity of responses from multiple sensors under the same physical event, the effective parameters of the communication link are evaluated. Next, time-tracking analysis is performed based on the effective parameters of the communication link to obtain the communication control deviation. Communication synchronization constraint compensation is then performed based on the communication control deviation to obtain a communication control strategy, and the communication link is adjusted and controlled according to the communication control strategy. These technical effects collectively solve the technical problems of large link delays and high communication interruption rates caused by complex geological environments in traditional oil extraction communication mechanisms. By performing edge computing processing and synchronization evaluation on real-time collected data, the stability and response speed of the communication link are ensured, thereby improving the synchronization accuracy of inter-well control signals.

[0041] Example 2, based on the same inventive concept as the communication control method for integrated oil extraction in the foregoing examples, such as... Figure 2 As shown, this application provides a communication control system for integrated oil extraction. The system includes: a data acquisition module 11, which deploys multiple types of sensors, including steam injection wells and production wells, at the oilfield site to collect key data such as temperature, pressure, wellbore position, and steam injection rate in real time; a synchronization evaluation module 12, which uses edge computing devices to uniformly encode and time-series label the collected data and uploads it to the communication control platform of the virtual layer, evaluating the effective parameters of the communication link based on the response synchronization of multiple sensors under the same physical event; a timing analysis module 13, which performs timing analysis based on the effective parameters of the communication link to obtain the communication control deviation; and an adjustment control module 14, which performs communication synchronization constraint compensation based on the communication control deviation to obtain a communication control strategy, and performs communication link adjustment control based on the communication control strategy.

[0042] Furthermore, the synchronization evaluation module 12 is also used to perform the following method: The first evaluation parameter is obtained by analyzing the alignment of the timestamps of the collected data; the second evaluation parameter is obtained by judging the consistency of the trend of physical quantities; the third evaluation parameter is obtained by detecting the data collection frequency and update stability; the first evaluation parameter, the second evaluation parameter and the third evaluation parameter are weighted and aggregated to obtain the effective parameters of the communication link.

[0043] Furthermore, the synchronization evaluation module 12 is also used to perform the following method: A digital twin model is constructed to map the structural state of the steam injection well and the production well in real time, and the historical trajectory and operating trend of the downhole equipment are dynamically updated based on the collected data. The digital twin model is used to predict the trend of communication entropy changes based on historical communication status data, equipment operating status and environmental disturbance parameters. When the predicted communication entropy exceeds a preset threshold, the communication control platform performs parameter combination screening and preloads the corresponding communication control strategy in advance, so as to complete the link control strategy switch before the entropy value actually reaches the preset threshold.

[0044] Furthermore, the timing parsing module 13 is also used to perform the following method: Based on the unified encoding and timing markers, a data timing chain for the collected data is established; a moving time window is set, and the data timing chain is divided into windows based on the moving time window to obtain a window timing chain; based on the effective parameters of the communication link, the window timing chain is analyzed for deviation timing to obtain the communication control deviation.

[0045] Furthermore, the adjustment control module 14 is also used to perform the following method: Establish the target response relationship between the steam injection well and the production well; perform communication synchronization compensation on the communication control deviation according to the target response relationship to obtain a compensation chain; and perform communication adjustable parameter link search based on the compensation chain to obtain the communication control strategy.

[0046] Furthermore, the adjustment control module 14 is also used to perform the following method: Establish a communication adjustable parameter library, including channel bandwidth allocation parameters, data transmission cycle parameters, transmission priority, retransmission threshold, and channel switching; based on the communication adjustable parameter library, analyze the key parameters affecting communication deviation in the compensation chain; according to the key parameters, traverse the parameter space through constraint rules to search for candidate parameter combinations; combine the current communication link status and target response relationship to determine the optimal communication control strategy from the candidate parameter combinations.

[0047] Furthermore, the adjustment control module 14 is also used to perform the following method: The communication entropy is evaluated based on the multi-sensor time alignment error, physical quantity response trend offset, actual communication link delay, communication link packet loss rate, and data update frequency fluctuation to obtain the communication entropy; based on the communication entropy, the parameter combination with the highest risk tolerance is selected from the candidate parameter combinations to determine the optimal communication control strategy.

[0048] Furthermore, the adjustment control module 14 is also used to perform the following method: A risk tolerance model is established for each candidate parameter combination, including a preset communication mitigation adaptability threshold, response delay tolerance, and control stability scoring standard. The risk tolerance of each candidate parameter combination is evaluated using the risk tolerance model. The communication entropy is classified into levels, and the risk tolerance conditions corresponding to each level are determined. Based on the risk tolerance conditions, the parameter combination that meets the minimum fault tolerance required for the current communication entropy level and has the best response efficiency is selected from the candidate parameter combinations as the optimal communication control strategy.

[0049] Furthermore, the adjustment control module 14 is also used to perform the following method: Monitor the communication response effect after the communication link is adjusted, including data transmission integrity, policy execution delay and communication entropy change trend; perform correlation analysis between the communication response effect and the communication control policy to form a policy execution feedback record; update the policy evaluation factor in the communication adjustable parameter library based on the feedback record, optimize the subsequent parameter selection criteria, and write the relevant data back to the digital twin model to correct the fitting bias and parameter weights in the communication entropy prediction model.

[0050] It should be noted that the order of the embodiments described above is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. Furthermore, the above description focuses on specific embodiments of this specification. The processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired results. In some implementations, multitasking and parallel processing are possible or may be advantageous.

[0051] The above description is only a preferred embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

[0052] This specification and accompanying drawings are merely illustrative examples of this application and are intended to cover any and all modifications, variations, combinations, or equivalents within the scope of this application. Clearly, those skilled in the art can make various alterations and modifications to this application without departing from its scope. Therefore, if such modifications and modifications fall within the scope of this application and its equivalents, this application intends to include such modifications and modifications.

Claims

1. A communication control method for integrated oil extraction, characterized in that, include: Multiple types of sensors, including those for steam injection wells and production wells, are deployed at the oilfield site to collect key data such as temperature, pressure, well track position, and steam injection rate in real time. The collected data is uniformly encoded and time-series labeled using edge computing devices and uploaded to the communication control platform of the virtual layer. Based on the response synchronization of multiple sensors under the same physical event, the effective parameters of the communication link are evaluated. Based on the effective parameters of the communication link, the encoded and tagged timing data uploaded by the sensor to the communication control platform is subjected to timing analysis to quantify the timing deviation in the communication link and obtain the communication control deviation. Based on the communication control deviation, communication synchronization constraint compensation is performed to obtain a communication control strategy, and communication link adjustment control is performed based on the communication control strategy. Based on the synchronization of responses from multiple sensors to the same physical event, the effective parameters of the communication link are evaluated, including: Analyze the alignment of timestamps in the collected data to obtain the first evaluation parameter; Determine the consistency of the physical quantity trend to obtain the second evaluation parameter; The frequency of data acquisition and the stability of data updates are used to obtain a third evaluation parameter. The first evaluation parameter, the second evaluation parameter, and the third evaluation parameter are weighted and aggregated to obtain the effective parameters of the communication link. Based on the communication control deviation, communication synchronization constraint compensation is performed to obtain a communication control strategy, including: Establish the target response relationship between the steam injection well and the production well, wherein the target response relationship is based on a regression model built from historical data to describe the functional relationship between the steam injection rate and the production well response; Based on the target response relationship, communication synchronization compensation is performed on the communication control deviation to obtain a compensation chain, wherein the compensation chain is used to describe how to compensate for the timing deviation in each time window; Based on the compensation chain, the communication adjustable parameters are searched to obtain the communication control strategy.

2. The communication control method for integrated oil extraction according to claim 1, characterized in that, Obtain communication control deviations, including: Based on the unified coding and timing mark, a data timing chain of the collected data is established, wherein the data timing chain is a continuous data stream formed by arranging all data points of each sensor in chronological order; A moving time window is set up, which slides in the data time sequence chain in chronological order. Each time the moving time window is used, the data time sequence chain is divided into windows based on the moving time window to obtain the window time sequence chain. Based on the effective parameters of the communication link, the window timing chain is analyzed for deviation timing to obtain the communication control deviation.

3. The communication control method for integrated oil extraction according to claim 1, characterized in that, Based on the compensation chain, a communication adjustable parameter search is performed to obtain the communication control strategy, including: Establish a library of adjustable communication parameters, including channel bandwidth allocation parameters, data transmission cycle parameters, transmission priority, retransmission threshold, and channel switching. Based on the aforementioned adjustable communication parameter library, the key parameters affecting communication deviation are analyzed in the compensation chain. Based on the key parameters, the parameter space is traversed through constraint rules to search for candidate parameter combinations; The optimal communication control strategy is determined from the candidate parameter combinations by combining the current communication link status and the target response relationship.

4. The communication control method for integrated oil extraction according to claim 3, characterized in that, Determining the optimal communication control strategy from the candidate parameter combinations includes: The communication entropy is obtained by evaluating the communication entropy index based on the multi-sensor time alignment error, physical quantity response trend offset, actual communication link delay, communication link packet loss rate, and data update frequency fluctuation. The optimal communication control strategy is determined by selecting the parameter combination with the highest risk tolerance from the candidate parameter combinations based on the communication entropy.

5. The communication control method for integrated oil extraction according to claim 4, characterized in that, Based on the communication entropy, the optimal communication control strategy is determined by selecting the parameter combination with the highest risk tolerance from the candidate parameter combinations, including: A risk tolerance model is established for each candidate parameter combination, including a preset communication mitigation adaptive threshold, response delay tolerance, and control stability scoring criteria. The risk tolerance of each candidate parameter combination is evaluated using the aforementioned risk tolerance model. Based on the communication entropy, a level classification is performed, and the risk tolerance conditions corresponding to each level are determined. Based on the risk tolerance condition, the optimal communication control strategy is selected from the candidate parameter combinations that meet the minimum fault tolerance requirement and have the best response efficiency for the current communication entropy level.

6. The communication control method for integrated oil extraction according to claim 4, characterized in that, The communication control platform uploaded to the virtual layer also includes: Construct a digital twin model to map the structural status of steam injection wells and production wells in real time, and dynamically update the historical trajectory and operating trend of downhole equipment based on the collected data; The digital twin model is used to predict the trend of communication entropy changes based on historical communication status data, equipment operating status, and environmental disturbance parameters. When the predicted communication entropy exceeds a preset threshold, the communication control platform performs parameter combination filtering and preloads the corresponding communication control strategy in advance, so as to complete the link control strategy switching before the entropy value actually reaches the preset threshold.

7. The communication control method for integrated oil extraction according to claim 6, characterized in that, According to the communication control strategy, communication link adjustment control is performed, followed by: Monitor the communication response effect after the communication link is adjusted, including data transmission integrity, policy execution delay and communication entropy change trend; The communication response effect is correlated with the communication control strategy to form a strategy execution feedback record; Based on the feedback record, the strategy evaluation factor in the adjustable communication parameter library is updated, the subsequent parameter selection criteria are optimized, and the relevant data is written back to the digital twin model to correct the fitting bias and parameter weights in the communication entropy prediction model.

8. A communication control system for integrated oil extraction, characterized in that, The system is used to execute the communication control method for integrated oil extraction as described in any one of claims 1-7, including: Data acquisition module: Multiple types of sensors, including those for steam injection wells and production wells, are deployed in the oilfield to collect key data such as temperature, pressure, well track position, and steam injection rate in real time; Synchronization evaluation module: The collected data is uniformly encoded and time-series labeled using edge computing devices and uploaded to the communication control platform of the virtual layer. Based on the response synchronization of multiple sensors under the same physical event, the effective parameters of the communication link are evaluated. Timing analysis module: Based on the effective parameters of the communication link, performs timing analysis on the encoded and tagged timing data uploaded by the sensor to the communication control platform, quantifies the timing deviation in the communication link, and obtains the communication control deviation; Adjustment control module: performs communication synchronization constraint compensation based on the communication control deviation, obtains communication control strategy, and performs communication link adjustment control based on the communication control strategy; The synchronicity evaluation module is also used to perform the following methods: Analyze the alignment of timestamps in the collected data to obtain the first evaluation parameter; Determine the consistency of the physical quantity trend to obtain the second evaluation parameter; The frequency of data acquisition and the stability of data updates are used to obtain a third evaluation parameter. The first evaluation parameter, the second evaluation parameter, and the third evaluation parameter are weighted and aggregated to obtain the effective parameters of the communication link. The adjustment control module is also used to perform the following methods: Establish the target response relationship between the steam injection well and the production well, wherein the target response relationship is based on a regression model built from historical data to describe the functional relationship between the steam injection rate and the production well response; Based on the target response relationship, communication synchronization compensation is performed on the communication control deviation to obtain a compensation chain, wherein the compensation chain is used to describe how to compensate for the timing deviation in each time window; Based on the compensation chain, the communication adjustable parameters are searched to obtain the communication control strategy.

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