A real-time oil well monitoring and early warning system and method based on satellite communication

Abstract

The present invention provides a real-time oil well monitoring and early warning system and method based on satellite communication, belonging to the technical field of oil well monitoring. The system includes a model construction module, a performance evaluation module, an optimization module, and a satellite early warning transmission module. By integrating sensor data, geographic information, and satellite communication data, an oil well monitoring vector is constructed. A comprehensive virtual model of the oil well is simulated based on the vector. The system compares the simulation results with real-time data, evaluates key performance indicators, analyzes deviations, optimizes model parameters, generates ground early warning data, and transmits it in real time via satellite communication. This ensures safe and efficient oil well operation, global coverage, and stability, adapts to remote locations of oil wells, and identifies potential risks under operating conditions.

Description

Technical Field

[0001] The present invention relates to the technical field of oil well monitoring, and in particular to a satellite communication-based real-time oil well monitoring and early warning system and method. Background Art

[0002] With the gradual decrease in global oil supply and the increase in extraction costs, traditional oil and gas exploration and production methods can no longer meet the energy needs of modern society. With the development of information technology and sensor technology, new technologies such as satellite communications, the Internet of Things, and data analysis have been introduced into the oil and gas industry. Current technologies use downhole equipment and sensors for monitoring, but they often cannot cover remote areas. Performance monitoring using sensor data usually lacks real-time and systematization. Monitoring and data transmission in remote areas are often limited by ground networks, affecting the timeliness of data collection and analysis and posing potential risks.

[0003] Therefore, the present invention provides a satellite communication-based oil well real-time monitoring and early warning system and method. Summary of the Invention

[0004] The present invention provides a real-time oil well monitoring and early warning system and method based on satellite communication. By integrating sensor data, geographic information and satellite communication data, an oil well monitoring vector is constructed. A comprehensive virtual model of the oil well is simulated based on the vector. The system compares the simulation results with real-time data, evaluates key performance indicators, analyzes deviations, optimizes model parameters, generates ground early warning data and sends it in real time via satellite communication. This ensures safe and efficient oil well operations, global coverage and stability, adapts to remote locations of oil wells, and identifies potential risks under operating conditions.

[0005] The present invention provides a satellite communication-based real-time oil well monitoring and early warning system, comprising:

[0006] Model building module: Determines oil well monitoring vectors based on sensor data, geographic information, and satellite communication data, and combines simulation to build a comprehensive virtual model of the oil well;

[0007] Performance evaluation module: simulates the operation status of the oil well according to the comprehensive virtual model to obtain the simulated operation status, and evaluates the key performance indicators of the oil well according to the simulated operation status to obtain the evaluation results;

[0008] Optimization module: compares the simulation running status with the real-time running status, checks the deviation of the virtual model, analyzes the deviation, and classifies the model parameters of the virtual model into optimization levels based on the deviation analysis results;

[0009] Satellite early warning transmission module: Generates oil well surface early warning data according to the evaluation results and optimization level, and sends the oil well surface early warning data in real time based on the cooperation mechanism of high-orbit satellites and low-orbit satellites in satellite communications.

[0010] The present invention provides a satellite communication-based oil well real-time monitoring and early warning system, including a model building module, comprising:

[0011] Decompose target units: clarify the business objectives of the oil well, break down each business objective into measurable sub-goals, and identify the influencing factors of each measurable sub-goal;

[0012] Vector Construction Unit: Maps acquired sensor data, geographic information, and satellite communication data to various influencing factors to form a preliminary monitoring vector. Performs an indicator analysis on business objectives and influencing factors to derive primary indicators. Performs a causal analysis between the primary indicators and various factors in the preliminary monitoring vector. Based on the causal analysis results, an oil well monitoring vector is constructed.

[0013] Model building unit: Use oil well monitoring vectors combined with simulation to build a comprehensive virtual model of the oil well.

[0014] The present invention provides a satellite communication-based real-time oil well monitoring and early warning system, including a model building unit, comprising:

[0015] Vector extraction block: decomposes the oil well monitoring vector, and constructs physical vector, fluid vector, thermal vector and supplementary vector according to the decomposition results;

[0016] Physical sub-model block: constructing a physical sub-model based on the physical vector and the field geological data of the oil well;

[0017] Fluid sub-model block: Supplements the fluid-related information of the fluid inside the oil well according to the fluid property database, and constructs a fluid sub-model by combining the fluid-related information and the fluid vector;

[0018] Thermal sub-model block: obtains data related to oil well monitoring and operating equipment, derives equipment performance, and constructs a thermal sub-model by combining equipment performance, fluid-related information, and thermal vectors;

[0019] Supplementary sub-model block: identifies missing points in the oil well monitoring vector based on the model output data of the physical sub-model, fluid sub-model, and thermal sub-model, determines specific model supplementation requirements based on the missing points, and constructs a supplementary sub-model based on the specific model supplementation requirements and the supplementary vector;

[0020] Comprehensive building block: Determine the model interval according to the input and output corresponding to each sub-model, integrate the relevant data and output of each sub-model interval, and merge all sub-models based on the integration results and simulation to build a comprehensive virtual model.

[0021] The present invention provides a satellite communication-based oil well real-time monitoring and early warning system, and a performance evaluation module, comprising:

[0022] Benchmark value unit: Based on the business objectives of the oil wells, the fluctuation of the historical production data corresponding to the business objectives is analyzed. Based on the fluctuation analysis results, the valid time periods of the historical production data are filtered to obtain time period screening results. The time period screening results are combined with the historical production data to preset the benchmark value of the measurable sub-objective for each time period;

[0023] State unit: simulates the operating state of the oil well based on the comprehensive virtual model, extracts key performance indicators (KPIs) corresponding to measurable sub-goals, and compares the simulation results of each KPI with the corresponding benchmark value to derive the simulated operating state of the oil well.

[0024] Evaluation unit: classifies the simulation running status and evaluates key performance indicators based on the classification results.

[0025] The present invention provides a satellite communication-based real-time oil well monitoring and early warning system, including an evaluation unit, comprising:

[0026] Dynamic classification block: Set the dynamic classification formula for the simulation running status according to external influencing factors:

[0027] ,in, A Represents the simulation operation function; B Represents the operation function of external influencing factors; C Indicates the comprehensive classification value; Represents the frequency domain magnitude of the key performance indicators of the simulation run; Indicates the phase value of the key performance indicator within the segment screening result; The frequency domain amplitude representing the ambient temperature around the oil well; Indicates the phase value of the ambient temperature around the oil well; The frequency domain amplitude representing the equipment health index of the equipment corresponding to oil well monitoring and operation; Phase value indicating the health index of the device; The frequency domain amplitude representing the viscosity of the fluid in the oil well; Represents the phase value of fluid viscosity in the oil well; i represents the i-th importance factor; z represents the z-th influence factor; ; a, b, c as well as d Respectively represent the factors of influence of key performance indicators, ambient temperature, equipment health index and fluid viscosity on comprehensive classification; They represent the importance factors of key performance indicators, ambient temperature, equipment health index and fluid viscosity to the comprehensive classification; It represents the continuous influence function of all weights and amplitudes in each frequency domain;

[0028] Classification block: classifies the simulation running status according to the comprehensive classification value and obtains the classification result;

[0029] Dynamic reference value block:

[0030] ;in, Indicates dynamic reference value; D indicates preset reference value; Indicates the dynamic adjustment value of the benchmark value by external factors; Indicates the ambient temperature value around the oil well; Viscosity value of fluid in oil well; Equipment health index; Indicates the flow fluctuation value within the segment screening result; Indicates the geological characteristic index; a sensitivity index representing the frequency component correlation of the key performance indicator;

[0031] Adjustment block: ,in, 、 、 Represent the proportional gain, integral gain and differential gain respectively; Indicates the current classification result; Indicates the adjustment amount of the classification result;

[0032] according to The classification results are adjusted and the key performance indicators are evaluated based on the adjusted results.

[0033] The present invention provides a satellite communication-based oil well real-time monitoring and early warning system, including an optimization module, comprising:

[0034] State comparison unit: compares the simulated running state with the actual running state and obtains the deviation set of key performance indicators;

[0035] Grading unit: performs an impact assessment on the deviation set, and determines the factors causing the deviation based on the impact assessment results. Based on the factors causing the deviation, the model parameters to be optimized are marked, the model parameters with the marks to be optimized are optimized, and the model parameters are divided into optimization grades according to the number of marks to be optimized for the corresponding model parameters.

[0036] The present invention provides a real-time oil well monitoring and early warning system based on satellite communication, and a satellite early warning transmission module, comprising:

[0037] Trend determination unit: Generates a comparison trend between the virtual model output and the actual data based on the evaluation results of key performance indicators;

[0038] Warning trigger unit: Dynamically adjusts the warning threshold according to the optimization level, and generates ground warning data by combining the comparison trend and warning threshold;

[0039] Satellite mechanism unit: obtains current network performance data and generates current business requirements based on ground warning data, and generates a mechanism based on the current network performance data and current business requirements.

[0040] Path generation unit: sets different priorities for each transmission path from a high-orbit satellite to a low-orbit satellite based on the path parameters, combines the intelligent algorithm with the mechanism to generate the initial transmission path and potential transmission paths, monitors the real-time performance of each potential transmission path during the transmission process, and dynamically generates the optimal transmission path based on the real-time performance and the initial transmission path;

[0041] Satellite transmission unit: Introduces end-to-end encryption technology to encrypt the transmission data and ports separately, uses the corresponding high-orbit satellite to receive ground warning data according to the optimal transmission path, and forwards the ground data to the corresponding low-orbit satellite, which then forwards the ground warning data to the relevant management personnel's equipment end according to the optimal transmission path.

[0042] The present invention provides a satellite communication-based real-time oil well monitoring and early warning method, comprising:

[0043] Step 1: Determine the oil well monitoring vector based on sensor data, geographic information, and satellite communication data, and build a comprehensive virtual model of the oil well through simulation.

[0044] Step 2: simulating the operating state of the oil well according to the comprehensive virtual model, obtaining the simulated operating state, and evaluating the key performance indicators of the oil well according to the simulated operating state;

[0045] Step 3: Compare the simulation running state with the real-time running state, check the deviation of the virtual model, analyze the deviation, and optimize the model parameters of the virtual model based on the deviation analysis results;

[0046] Step 4: Generate oil well surface warning data based on the evaluation results and the optimization level, and send the oil well surface warning data in real time based on the cooperation mechanism of high-orbit satellites and low-orbit satellites in satellite communications.

[0047] Compared with the existing technology, the beneficial effects of this application are as follows: by integrating sensor data, geographic information and satellite communication data, an oil well monitoring vector is constructed, and a comprehensive virtual model of the oil well is simulated based on the vector. The system compares the simulation results with real-time data, evaluates key performance indicators, analyzes deviations, optimizes model parameters, generates ground early warning data and sends it in real time via satellite communication, ensuring safe and efficient oil well operations, ensuring global coverage and stability, adapting to the remote locations of oil wells, and identifying potential risks under operating conditions.

[0048] Other features and advantages of the present invention will be described in the following description, and in part will become apparent from the description, or will be understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the written description and the accompanying drawings.

[0049] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0051] Figure 1 1 is a schematic structural diagram of a satellite communication-based oil well real-time monitoring and early warning system provided by an embodiment of the present invention;

[0052] Figure 2 The present invention provides a flow chart of a method for real-time monitoring and early warning of oil wells based on satellite communication. DETAILED DESCRIPTION

[0053] The preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0054] Example 1:

[0055] The embodiment of the present invention provides a real-time monitoring and early warning system and method for oil wells based on satellite communication, such as Figure 1 Shown, including:

[0056] Model building module: Determines oil well monitoring vectors based on sensor data, geographic information, and satellite communication data, and combines simulation to build a comprehensive virtual model of the oil well;

[0057] Performance evaluation module: simulates the operation status of the oil well according to the comprehensive virtual model to obtain the simulated operation status, and evaluates the key performance indicators of the oil well according to the simulated operation status to obtain the evaluation results;

[0058] Optimization module: compares the simulation running status with the real-time running status, checks the deviation of the virtual model, analyzes the deviation, and classifies the model parameters of the virtual model into optimization levels based on the deviation analysis results;

[0059] Satellite early warning transmission module: Generates oil well surface early warning data according to the evaluation results and optimization level, and sends the oil well surface early warning data in real time based on the cooperation mechanism of high-orbit satellites and low-orbit satellites in satellite communications.

[0060] In this embodiment, the oil well monitoring vector is a comprehensive data set formed by integrating multiple data sources (including real-time monitoring, historical data, environmental parameters, etc.). The data set is used to support the comprehensive monitoring and evaluation of oil wells. For example, the oil well monitoring vector may include: pressure monitoring data, temperature monitoring data, fluid flow, equipment status information, and environmental condition parameters.

[0061] In this embodiment, the model interval is determined based on the inputs and outputs corresponding to the physical sub-model, fluid sub-model, thermal sub-model and supplementary sub-model, the relevant data and outputs of each sub-model interval are integrated, and all sub-models are merged based on the integration results combined with simulation to construct a comprehensive virtual model.

[0062] In this embodiment, by comparing the simulated operating state with the actual operating state, a deviation set of key performance indicators is obtained, an impact assessment is performed on the deviation set, factors causing the deviation are identified, and model parameters that need to be optimized are identified. Finally, the model parameters are divided into optimization levels according to the number of identifications to be optimized.

[0063] In this embodiment, the optimization level classification refers to the process of classifying the model parameters according to the number of identifications to be optimized and the importance of these parameters.

[0064] In this embodiment, key performance indicators are important data determined according to business objectives and used to measure the operating efficiency, production capacity and safety of oil wells, including: production, pressure, temperature, equipment status, energy consumption and safety performance indicators.

[0065] In this embodiment, the simulated operating state is the predicted operating condition of the oil well obtained through computer simulation based on the comprehensive virtual model. This state is the simulation result of a model constructed based on input parameters such as historical data, sensor readings, geographic information, etc. It should simulate the performance of an actual oil well under specific conditions, including: predicted production, predicted pressure and temperature distribution, expected service life of the equipment, and predicted energy consumption.

[0066] In this embodiment, the evaluation result refers to an evaluation of the key performance indicators of the oil well based on the simulated operating status, which is a comprehensive judgment of the current and future performance of the oil well, including: comparative analysis of the actual performance of the oil well and the simulation model, identification of performance deviations and potential problems, analysis of trends in performance degradation or improvement, and an overall evaluation of the operating efficiency and safety of the oil well.

[0067] In this embodiment, the coordination mechanism includes preliminary data collection, intelligent algorithm generation of transmission paths, real-time performance monitoring and secure transmission.

[0068] The working principle and beneficial effects of the above technical solution are: by integrating sensor data, geographic information and satellite communication data, an oil well monitoring vector is constructed, and a comprehensive virtual model of the oil well is simulated based on the vector. The system compares the simulation results with real-time data, evaluates key performance indicators, analyzes deviations, optimizes model parameters, generates ground early warning data and sends it in real time via satellite communication, ensuring safe and efficient oil well operations, ensuring global coverage and stability, adapting to the remote location of the oil well, and identifying potential risks under operating conditions.

[0069] Example 2:

[0070] The embodiment of the present invention provides a satellite communication-based real-time oil well monitoring and early warning system, wherein the model building module includes:

[0071] Decompose target units: clarify the business objectives of the oil well, break down each business objective into measurable sub-goals, and identify the influencing factors of each measurable sub-goal;

[0072] Vector Construction Unit: Maps acquired sensor data, geographic information, and satellite communication data to various influencing factors to form a preliminary monitoring vector. Performs an indicator analysis on business objectives and influencing factors to derive primary indicators. Performs a causal analysis between the primary indicators and various factors in the preliminary monitoring vector. Based on the causal analysis results, an oil well monitoring vector is constructed.

[0073] Model building unit: Use oil well monitoring vectors combined with simulation to build a comprehensive virtual model of the oil well.

[0074] In this embodiment, the business objectives refer to the overall goals that are expected to be achieved during the operation of the oil well, which are usually closely related to economic benefits, production capacity, and environmental protection, including: increasing production, reducing costs, improving energy efficiency, ensuring safety, and improving environmental impact.

[0075] In this embodiment, measurable sub-goals are specific, quantifiable goals set to achieve business objectives, typically with clear numerical standards. For example: 5% increase in daily oil production: Within one year, the target daily oil production will increase from 100 barrels to 105 barrels; 10% reduction in energy consumption: The energy required to produce one barrel of oil will be reduced; fewer than five equipment failures: The number of equipment failures per year will not exceed five.

[0076] In this embodiment, the decomposition process is the process of converting the overall business goal into actionable and measurable sub-goals. The process is to clarify the most important business goal (such as improving production efficiency), split the main goal into multiple specific measurable sub-goals (such as increasing daily oil production and reducing costs), and identify factors that affect each sub-goal, such as equipment age, fluid characteristics, environmental conditions, etc.

[0077] In this embodiment, the primary indicator is a specific performance parameter derived based on the business objective and its measurable sub-objectives when constructing the monitoring vector, and is used to evaluate the operating status of the oil well and the degree to which the objective is achieved, for example: daily oil production: the specific production quantity, energy consumption: the energy consumption per unit of oil produced.

[0078] In this embodiment, the preliminary monitoring vector is the result of mapping sensor data, geographic information, and satellite communication data to each influencing factor, providing basic data for subsequent monitoring. For example, the preliminary monitoring vector may include the following: pressure (fluid pressure downhole), temperature (ambient and fluid temperature), flow rate (fluid output from the well), and vibration (equipment operating status and health status).

[0079] In this embodiment, causal analysis is the process of identifying the relationship between primary indicators and influencing factors. The specific steps include: obtaining historical data, including the measurement values of primary indicators and influencing factors, using correlation analysis, regression analysis and other methods to quantitatively analyze the relationship between indicators, establishing a mathematical model to explain how each influencing factor affects the value of the primary indicator, and using new data to verify the accuracy of the model.

[0080] The working principle and beneficial effects of the above technical solution are as follows: by clarifying the business objectives of the oil well, breaking them down into measurable sub-goals, and then identifying the influencing factors of each sub-goal, combining sensor data, geographic information and satellite communication data, mapping each influencing factor, and constructing a preliminary monitoring vector. Through causal analysis, the primary indicators are associated with the monitoring vector, and finally a comprehensive virtual model is constructed to effectively monitor progress and ensure the achievement of business objectives. It realizes real-time monitoring of the operation status of the oil well, which helps to accurately identify operational problems and their causes.

[0081] Example 3:

[0082] An embodiment of the present invention provides a satellite communication-based real-time oil well monitoring and early warning system, wherein the model building unit includes:

[0083] Vector extraction block: decomposes the oil well monitoring vector, and constructs physical vector, fluid vector, thermal vector and supplementary vector according to the decomposition results;

[0084] Physical sub-model block: constructing a physical sub-model based on the physical vector and the field geological data of the oil well;

[0085] Fluid sub-model block: Supplements the fluid-related information of the fluid inside the oil well according to the fluid property database, and constructs a fluid sub-model by combining the fluid-related information and the fluid vector;

[0086] Thermal sub-model block: obtains data related to oil well monitoring and operating equipment, derives equipment performance, and constructs a thermal sub-model by combining equipment performance, fluid-related information, and thermal vectors;

[0087] Supplementary sub-model block: identifies missing points in the oil well monitoring vector based on the model output data of the physical sub-model, fluid sub-model, and thermal sub-model, determines specific model supplementation requirements based on the missing points, and constructs a supplementary sub-model based on the specific model supplementation requirements and the supplementary vector;

[0088] Comprehensive building block: Determine the model interval according to the input and output corresponding to each sub-model, integrate the relevant data and output of each sub-model interval, and merge all sub-models based on the integration results and simulation to build a comprehensive virtual model.

[0089] In this embodiment, the oil well monitoring vectors are decomposed into different categories, each category representing a different physical property of the oil well: physical vectors: including structural parameters of the oil well, such as well depth, well diameter, well wall thickness, etc.; fluid vectors: involving the dynamic characteristics of the fluid inside the oil well, such as flow rate, pressure, flow rate, etc.; thermal vectors: parameters related to temperature distribution and heat exchange inside and outside the oil well; supplementary vectors: other parameters that need to be monitored but are not covered by the first three categories, such as chemical composition, material fatigue, etc.

[0090] In this embodiment, the physical sub-model is constructed by combining physical vectors and field geological data (such as rock physical properties, sequence stratigraphic information, etc.), which describes the physical structure and geological environment of the oil well; the fluid sub-model uses a fluid property database (which may include information such as viscosity, density, and composition) to supplement the fluid vector, and combines this information to construct a fluid dynamics model; the thermal sub-model is constructed by combining equipment performance data (such as the thermal efficiency of the pump, the thermal insulation performance of the pipeline, etc.), fluid information and thermal vectors to describe the temperature distribution and heat exchange process of the oil well; the supplementary sub-model is to identify missing points in the monitoring vector based on the outputs of the physical sub-model, fluid sub-model and thermal sub-model. Missing points are defects in the data collection process or failures of the monitoring equipment.

[0091] In this embodiment, the model interval refers to the input and output range of each sub-model, which is the effective working interval or parameter space of the model.

[0092] In this embodiment, the merging process is to integrate the outputs of all sub-models together to ensure that they are consistent at the boundary conditions and interfaces, and involves the adjustment and optimization of parameters to ensure seamless integration of all sub-models.

[0093] The working principle and beneficial effects of the above technical solution are as follows: by decomposing the oil well monitoring vector, constructing the physical vector, fluid vector, thermal vector and supplementary vector, combining the field geological data of the oil well and the fluid property database, each sub-model is independently constructed and mutually verified. By integrating the output and input of the sub-model, a comprehensive virtual model is finally formed to provide comprehensive operation status assessment and prediction, support scientific decision-making, and optimize resource allocation and operational efficiency.

[0094] Example 4:

[0095] The embodiment of the present invention provides a satellite communication-based real-time oil well monitoring and early warning system, including a performance evaluation module, comprising:

[0096] Benchmark value unit: Based on the business objectives of the oil wells, the fluctuation of the historical production data corresponding to the business objectives is analyzed. Based on the fluctuation analysis results, the valid time periods of the historical production data are filtered to obtain time period screening results. The time period screening results are combined with the historical production data to preset the benchmark value of the measurable sub-objective for each time period;

[0097] State unit: simulates the operating state of the oil well based on the comprehensive virtual model, extracts key performance indicators (KPIs) corresponding to measurable sub-goals, and compares the simulation results of each KPI with the corresponding benchmark value to derive the simulated operating state of the oil well.

[0098] Evaluation unit: classifies the simulation running status and evaluates key performance indicators based on the classification results.

[0099] In this embodiment, fluctuation analysis refers to statistically analyzing the changing trends and fluctuation ranges in the historical production data of the oil wells to identify the stability and abnormal conditions of the data. The steps are: collecting historical production data of the oil wells, including key performance indicators such as production, pressure, and temperature, applying statistical methods (such as standard deviation, variance analysis, autocorrelation analysis, etc.) to evaluate the volatility of the data, using time series analysis methods (such as moving average, exponential smoothing, trend line analysis, etc.) to identify the long-term trend of the data, and identifying possible abnormal points or abnormal periods by comparing the volatility with the expected normal range.

[0100] In this embodiment, the time period screening results refer to selecting representative and reliable time periods from the historical production data based on the results of the fluctuation analysis. These time periods are considered to be periods when the oil well is operating stably and is not affected by external interference or equipment failures. The screened time periods should represent the performance of the oil well under normal operating conditions.

[0101] In this embodiment, the benchmark value is set based on the historical production data within the selected valid time period, representing the standard or average level that the key performance indicators of the oil well should reach during these time periods. The process of obtaining the benchmark value generally includes: aggregating the data within the selected time period, and calculating the average value, median or other statistics within each time period as the performance benchmark for that time period.

[0102] In this embodiment, the comparison process refers to comparing the simulation results of the integrated virtual model with preset benchmark values to evaluate the current operating status of the oil well. The process is: using the integrated virtual model to simulate the current or expected operating status of the oil well, extracting key performance indicators from the simulation results, comparing these indicators with corresponding benchmark values, identifying deviations, and judging whether the operating status of the oil well is normal, whether there is room for optimization, or whether measures need to be taken based on the size and direction of the deviation.

[0103] In this embodiment, the classification process is to set the classification formula of the simulation operation status through external influencing factors, including the frequency domain amplitude and phase information of key performance indicators and environmental conditions. The classification results are used to adjust the dynamic benchmark value, adjust the classification parameters, and finally evaluate the key performance indicators.

[0104] The working principle and beneficial effects of the above technical solution are as follows: by analyzing the fluctuations in the historical production data of the oil wells, determining the baseline value of each measurable sub-target, simulating the operating status of the oil wells based on the comprehensive virtual model, extracting key performance indicators, and comparing them with the corresponding baseline values to evaluate the current operating status of the oil wells. Finally, the simulation results are classified to make the business goals more realistic, improve the executableness of the indicators, achieve timely response to different operating conditions, and enhance the flexibility of oil well management.

[0105] Example 5:

[0106] An embodiment of the present invention provides a satellite communication-based real-time oil well monitoring and early warning system, including an evaluation unit, comprising:

[0107] Dynamic classification block: Set the dynamic classification formula for the simulation running status according to external influencing factors:

[0108] ,in, A Represents the simulation operation function; B Represents the operation function of external influencing factors; C Indicates the comprehensive classification value; Represents the frequency domain magnitude of the key performance indicators of the simulation run; Indicates the phase value of the key performance indicator within the segment screening result; The frequency domain amplitude representing the ambient temperature around the oil well; Indicates the phase value of the ambient temperature around the oil well; The frequency domain amplitude representing the equipment health index of the equipment corresponding to oil well monitoring and operation; Phase value indicating the health index of the device; The frequency domain amplitude representing the viscosity of the fluid in the oil well; Represents the phase value of fluid viscosity in the oil well; i represents the i-th importance factor; z represents the z-th influence factor; ; a, b, c as well as d Respectively represent the factors of influence of key performance indicators, ambient temperature, equipment health index and fluid viscosity on comprehensive classification; They represent the importance factors of key performance indicators, ambient temperature, equipment health index and fluid viscosity to the comprehensive classification; It represents the continuous influence function of all weights and amplitudes in each frequency domain;

[0109] Classification block: classifies the simulation running status according to the comprehensive classification value and obtains the classification result;

[0110] Dynamic reference value block:

[0111] ;in, Indicates dynamic reference value; D indicates preset reference value; Indicates the dynamic adjustment value of the benchmark value by external factors; Indicates the ambient temperature value around the oil well; Viscosity value of fluid in oil well; Equipment health index; Indicates the flow fluctuation value within the segment screening result; Indicates the geological characteristic index; a sensitivity index representing the frequency component correlation of the key performance indicator;

[0112] Adjustment block: ,in, 、 、 Represent the proportional gain, integral gain and differential gain respectively; Indicates the current classification result; Indicates the adjustment amount of the classification result;

[0113] according to The classification results are adjusted and the key performance indicators are evaluated based on the adjusted results.

[0114] In this embodiment, z Can be a, b, c, d Any one of a, b, c, d It can be any number, depending on the impact of key performance indicators, ambient temperature, equipment health index, and fluid viscosity on the overall classification.

[0115] In this embodiment, .

[0116] In this embodiment, the classification result refers to dividing the simulation operation status into different categories or levels according to the comprehensive classification value, and calculating a comprehensive classification value using the frequency domain amplitude and phase value of the key performance indicators of the simulation operation status and external influencing factors (such as ambient temperature, equipment health index, fluid viscosity, etc.). Taking into account the changes in external influencing factors, the simulation operation status is dynamically classified to reflect the real-time operating status and the influence of external conditions. According to preset rules or thresholds, the comprehensive classification value is converted into a specific classification result, such as normal operation, warning, maintenance required, etc.

[0117] In this embodiment, the process of adjusting the classification results refers to applying control logic (such as PID control) to adjust the operating parameters of the oil well based on the current classification results to optimize performance. According to the current classification results, control parameters such as proportional gain (P), integral gain (I), and differential gain (D) are used to adjust the operation of the oil well. Based on the output of the control logic, actual operational adjustments are implemented, such as changing the pump speed, adjusting the valve opening, etc. The actual operating status after adjustment is monitored and compared with the expected status. The difference is input into the control logic as feedback to form a closed-loop control.

[0118] In this embodiment, the evaluation of key performance indicators refers to monitoring and analyzing key operating parameters of the oil well to determine whether its performance meets the expected goals.

[0119] The working principle and beneficial effects of the above technical solution are: the classification formula of the simulation operation status is set by external influencing factors, including the frequency domain amplitude and phase information of key performance indicators and environmental conditions. The classification results are used to adjust the dynamic baseline value, adjust the classification parameters, and finally evaluate the key performance indicators to ensure the flexibility and adaptability of the oil well monitoring system and the timeliness of the early warning mechanism.

[0120] Example 6:

[0121] The embodiment of the present invention provides a satellite communication-based real-time oil well monitoring and early warning system, including an optimization module, comprising:

[0122] State comparison unit: compares the simulated running state with the actual running state and obtains the deviation set of key performance indicators;

[0123] Grading unit: performs an impact assessment on the deviation set, and determines the factors causing the deviation based on the impact assessment results. Based on the factors causing the deviation, the model parameters to be optimized are marked, the model parameters with the marks to be optimized are optimized, and the model parameters are divided into optimization grades according to the number of marks to be optimized for the corresponding model parameters.

[0124] In this embodiment, the comparison process involves comparing the simulated operating status of the oil well with the actual operating status, collecting data from the simulation model and the field monitoring system, comparing the key performance indicators calculated in the simulation model with the same indicators measured in actual operation, determining the differences between the simulated and actual indicators, and compiling these differences into a deviation set.

[0125] In this embodiment, the deviation set refers to the collection of all key performance indicator deviations obtained from the above comparison process, which is used to further analyze and identify problems in the operating status. For example, the deviation set is the flow indicator: the flow predicted by the simulation model is 10% higher than the actual measured value; the pressure indicator: the bottom hole pressure predicted by the simulation model differs from the actual measured value by 5%; the temperature indicator: the oil well temperature predicted by the simulation model differs from the actual measured value by 2%.

[0126] In this embodiment, the impact assessment result refers to the result obtained after analyzing the deviation set, determining which deviations are important and their possible impact on the operation of the oil well, evaluating the impact of each deviation on the operation of the oil well, and determining the potential factors that cause these deviations. For example, flow indicator deviation: this deviation is considered important because the flow rate is directly related to the production efficiency and revenue of the oil well. This deviation is caused by the performance of the oil well pump not meeting the preset parameters of the model. Therefore, this problem is marked as a high-priority problem that needs to be optimized.

[0127] In this embodiment, the parameters to be optimized are model parameters found to be associated with significant deviations during the impact assessment process. These parameters are marked as requiring optimization to improve the accuracy of the simulation model or the actual operating status of the oil well.

[0128] In this embodiment, the optimization process refers to the process of adjusting the model parameters marked as to be optimized, including modifying the model parameters to reduce the deviation, re-running the simulation model after adjusting the parameters to verify the improvement, and applying these optimizations to actual operations if the simulation results are satisfactory.

[0129] In this embodiment, the deviation-inducing factors refer to those that cause differences between the simulation model and the actual operating state, including equipment failure, operation error, environmental change, or model inaccuracy.

[0130] The working principle and beneficial effects of the above technical solution are: by comparing the simulated operating status with the actual operating status, the deviation set of key performance indicators is obtained, the impact of the deviation set is evaluated, the factors causing the deviation are identified, and the model parameters that need to be optimized are marked. Finally, the model parameters are divided into optimization levels according to the number of identifications to be optimized, to achieve dynamic response and optimization, and improve the accuracy and efficiency of oil well operations.

[0131] Example 7:

[0132] An embodiment of the present invention provides a satellite communication-based real-time oil well monitoring and early warning system, including a satellite early warning transmission module, comprising:

[0133] Trend determination unit: Generates a comparison trend between the virtual model output and the actual data based on the evaluation results of key performance indicators;

[0134] Warning trigger unit: Dynamically adjusts the warning threshold according to the optimization level, and generates ground warning data by combining the comparison trend and warning threshold;

[0135] Satellite mechanism unit: obtains current network performance data and generates current business requirements based on ground warning data, and generates a mechanism based on the current network performance data and current business requirements.

[0136] Path generation unit: sets different priorities for each transmission path from a high-orbit satellite to a low-orbit satellite based on the path parameters, combines the intelligent algorithm with the mechanism to generate the initial transmission path and potential transmission paths, monitors the real-time performance of each potential transmission path during the transmission process, and dynamically generates the optimal transmission path based on the real-time performance and the initial transmission path;

[0137] Satellite transmission unit: Introduces end-to-end encryption technology to encrypt the transmission data and ports separately, uses the corresponding high-orbit satellite to receive ground warning data according to the optimal transmission path, and forwards the ground data to the corresponding low-orbit satellite, which then forwards the ground warning data to the relevant management personnel's equipment end according to the optimal transmission path.

[0138] In this embodiment, the comparative trend is determined by comparing the output of the virtual model and the changing trend of the actual collected data over time. For example, assume that one of the key performance indicators is the daily production of the oil well. The virtual model predicts that the oil well should produce 1,000 barrels of oil per day. However, the actual data shows that the production has decreased by 50 barrels per day in the past week. This downward trend in production, if compared with the stable production predicted by the model, may indicate that the production efficiency of the oil well is declining, which may be due to equipment wear or degradation of reservoir performance.

[0139] In this embodiment, dynamic adjustment refers to the process of automatically adjusting system parameters based on real-time data and changing conditions. In an early warning system, this typically involves adjusting warning thresholds based on the latest monitoring data and analysis results. For example, in the aforementioned scenario of declining oil well production, the early warning trigger unit might adjust the production decline threshold from 30 barrels per day to 20 barrels per day based on recent trends and the optimization level. This means that if daily production drops by more than 20 barrels compared to the previous day, the system will trigger an alert.

[0140] In this embodiment, the current network performance data refers to the network status monitored in real time in the satellite communication system, including: delay, bandwidth, packet loss rate and signal strength.

[0141] In this embodiment, the current business demand refers to the data transmission and monitoring tasks required for the oil well and its related operations at a specific moment, including: data type: the information that needs to be transmitted (such as real-time monitoring data, early warning reports, etc.); timeliness requirement: the urgency of data transmission, determining how quickly the data needs to arrive (for example, real-time warnings should be sent as soon as possible); data volume: the size and content of the data that needs to be transmitted within a specific time.

[0142] In this embodiment, the mechanism basis refers to the strategies and processes formulated for data transmission in the context of current network performance data and business needs, including: priority strategy: planning data transmission strategies based on business needs and network conditions; fault tolerance and backup: setting up emergency mechanisms to prevent data loss or transmission failure.

[0143] In this embodiment, the initial transmission path refers to the preferred transmission path generated based on an optimization algorithm after evaluating current network performance and service requirements, and is generally the optimal communication path, for example, a data transmission line from a high-orbit satellite to a low-orbit satellite.

[0144] In this embodiment, potential transmission paths refer to other possible transmission paths evaluated in the process of generating the initial transmission path. Although these paths can be used for data transmission, they may not be the optimal choice. Potential paths can be used as alternative solutions and switched when problems occur with the initial path.

[0145] In this embodiment, real-time performance refers to the real-time monitoring and evaluation of metrics such as transmission rate, latency, and packet loss rate during data transmission. Real-time performance is a key indicator for ensuring data transmission quality, for example, monitoring the stability and speed of traffic during actual communication.

[0146] In this embodiment, the optimal transmission path is a path dynamically generated by an intelligent algorithm based on real-time network performance data and business needs. This path is considered to be the most efficient option based on network conditions and needs, with the lowest latency, optimal bandwidth and lowest packet loss rate, while meeting real-time performance requirements.

[0147] In this embodiment, the early warning mechanism refers to a series of actions initiated by the system when it detects that a key performance indicator exceeds a predetermined threshold. The purpose is to notify relevant personnel and take measures to prevent the problem from worsening. For example, if the daily production continues to decline, once the system detects that the production decline exceeds the dynamically adjusted early warning threshold, the early warning mechanism will be triggered, including generating a detailed ground early warning data and immediately sending it to the mobile device of the oilfield operations manager via satellite communication. After receiving the ground early warning data, the manager can quickly investigate the cause of the production decline and take necessary maintenance measures or adjust the production plan.

[0148] The working principle and beneficial effects of the above technical solution are: by analyzing key performance indicators, generating comparative trends between virtual model output and actual data, identifying potential abnormal conditions, dynamically adjusting warning thresholds based on optimization levels, generating ground warning data, combining network performance data with business needs, generating the optimal communication mechanism foundation, and carrying out end-to-end encryption to ensure that ground warning data is securely transmitted to the management personnel's equipment end, ensuring safe real-time data monitoring and transmission in remote areas, overcoming the limitations of traditional communication methods, and improving the flexibility and adaptability of the system.

[0149] Example 8:

[0150] The embodiment of the present invention provides a real-time monitoring and early warning method for oil wells based on satellite communication. Figure 2 Shown, including:

[0151] Step 1: Determine the oil well monitoring vector based on sensor data, geographic information, and satellite communication data, and build a comprehensive virtual model of the oil well through simulation.

[0152] Step 2: simulating the operating state of the oil well according to the comprehensive virtual model, obtaining the simulated operating state, and evaluating the key performance indicators of the oil well according to the simulated operating state;

[0153] Step 3: Compare the simulation running state with the real-time running state, check the deviation of the virtual model, analyze the deviation, and optimize the model parameters of the virtual model based on the deviation analysis results;

[0154] Step 4: Generate oil well surface warning data based on the evaluation results and the optimization level, and send the oil well surface warning data in real time based on the cooperation mechanism of high-orbit satellites and low-orbit satellites in satellite communications.

[0155] The working principle and beneficial effects of the above technical solution are: by integrating sensor data, geographic information and satellite communication data, an oil well monitoring vector is constructed, and a comprehensive virtual model of the oil well is simulated based on the vector. The system compares the simulation results with real-time data, evaluates key performance indicators, analyzes deviations, optimizes model parameters, generates ground early warning data and sends it in real time via satellite communication, ensuring safe and efficient oil well operations, ensuring global coverage and stability, adapting to the remote location of the oil well, and identifying potential risks under operating conditions.

[0156] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A real-time monitoring and early warning system for oil wells based on satellite communication, characterized in that: include: Model building module: Determines oil well monitoring vectors based on sensor data, geographic information, and satellite communication data, and combines simulation to build a comprehensive virtual model of the oil well; Performance evaluation module: simulates the operation status of the oil well according to the comprehensive virtual model to obtain the simulated operation status, and evaluates the key performance indicators of the oil well according to the simulated operation status to obtain the evaluation results; Optimization module: compares the simulation running status with the real-time running status, checks the deviation of the virtual model, analyzes the deviation, and classifies the model parameters of the virtual model into optimization levels based on the deviation analysis results; Satellite early warning transmission module: generates oil well surface early warning data based on the evaluation results and optimization level, and transmits the oil well surface early warning data in real time based on the cooperation mechanism of high-orbit satellites and low-orbit satellites in satellite communications; Among them, the performance evaluation module includes: Benchmark value unit: Based on the business objectives of the oil wells, the fluctuation of the historical production data corresponding to the business objectives is analyzed. Based on the fluctuation analysis results, the valid time periods of the historical production data are filtered to obtain time period screening results. The time period screening results are combined with the historical production data to preset the benchmark value of the measurable sub-objective for each time period; State unit: simulates the operating state of the oil well based on the comprehensive virtual model, extracts key performance indicators (KPIs) corresponding to measurable sub-goals, and compares the simulation results of each KPI with the corresponding benchmark value to derive the simulated operating state of the oil well. Evaluation unit: classifying the simulation running status and evaluating key performance indicators based on the classification results; The assessment units include: Dynamic classification block: Set the dynamic classification formula for the simulation running status according to external influencing factors: ,in, A Represents the simulation operation function; B Represents the operation function of external influencing factors; C Indicates the comprehensive classification value; Represents the frequency domain magnitude of the key performance indicators of the simulation run; Indicates the phase value of the key performance indicator within the segment screening result; The frequency domain amplitude representing the ambient temperature around the oil well; Indicates the phase value of the ambient temperature around the oil well; The frequency domain amplitude representing the equipment health index of the equipment corresponding to oil well monitoring and operation; Phase value indicating the health index of the device; The frequency domain amplitude representing the viscosity of the fluid in the oil well; represents the phase value of the fluid viscosity in the oil well; i represents the i-th importance factor; z represents the z-th influence factor; ; a, b, c as well as d Respectively represent the factors of influence of key performance indicators, ambient temperature, equipment health index and fluid viscosity on comprehensive classification; They represent the importance factors of key performance indicators, ambient temperature, equipment health index, and fluid viscosity to the comprehensive classification; represents the continuous influence function of all weights and amplitudes in each frequency domain; Classification block: classifies the simulation running status according to the comprehensive classification value and obtains the classification result; Dynamic reference value block: ;in, Indicates dynamic reference value; D indicates preset reference value; Indicates the dynamic adjustment value of the benchmark value by external factors; Indicates the ambient temperature value around the oil well; Viscosity value of fluid in oil well; Equipment health index; Indicates the flow fluctuation value within the segment screening result; Indicates the geological characteristic index; a sensitivity index representing the frequency component correlation of the key performance indicator; Adjustment block: ,in, 、 、 Represent the proportional gain, integral gain and differential gain respectively; Indicates the current classification result; Indicates the adjustment amount of the classification result; according to The classification results are adjusted and the key performance indicators are evaluated based on the adjusted results.

2. The satellite communication-based real-time oil well monitoring and early warning system according to claim 1, characterized in that: Model building modules, including: Decompose target units: clarify the business objectives of the oil well, break down each business objective into measurable sub-goals, and identify the influencing factors of each measurable sub-goal; Vector Construction Unit: Maps acquired sensor data, geographic information, and satellite communication data to various influencing factors to form a preliminary monitoring vector. Performs an indicator analysis on business objectives and influencing factors to derive primary indicators. Performs a causal analysis between the primary indicators and various factors in the preliminary monitoring vector. Based on the causal analysis results, an oil well monitoring vector is constructed. Model building unit: Use oil well monitoring vectors combined with simulation to build a comprehensive virtual model of the oil well.

3. The satellite communication-based real-time oil well monitoring and early warning system according to claim 2, characterized in that: Model building unit, including: Vector extraction block: decomposes the oil well monitoring vector, and constructs physical vector, fluid vector, thermal vector and supplementary vector according to the decomposition results; Physical sub-model block: constructing a physical sub-model based on the physical vector and the field geological data of the oil well; Fluid sub-model block: Supplements the fluid-related information of the fluid inside the oil well according to the fluid property database, and constructs a fluid sub-model by combining the fluid-related information and the fluid vector; Thermal sub-model block: obtains data related to oil well monitoring and operating equipment, derives equipment performance, and constructs a thermal sub-model by combining equipment performance, fluid-related information, and thermal vectors; Supplementary sub-model block: identifies missing points in the oil well monitoring vector based on the model output data of the physical sub-model, fluid sub-model, and thermal sub-model, determines specific model supplementation requirements based on the missing points, and constructs a supplementary sub-model based on the specific model supplementation requirements and the supplementary vector; Comprehensive building block: Determine the model interval according to the input and output corresponding to each sub-model, integrate the relevant data and output of each sub-model interval, and merge all sub-models based on the integration results and simulation to build a comprehensive virtual model.

4. The satellite communication-based real-time oil well monitoring and early warning system according to claim 1, characterized in that: Optimization modules, including: State comparison unit: compares the simulated running state with the actual running state and obtains the deviation set of key performance indicators; Grading unit: performs an impact assessment on the deviation set, and determines the factors causing the deviation based on the impact assessment results. Based on the factors causing the deviation, the model parameters to be optimized are marked, the model parameters with the marks to be optimized are optimized, and the model parameters are divided into optimization grades according to the number of marks to be optimized for the corresponding model parameters.

5. The satellite communication-based real-time oil well monitoring and early warning system according to claim 1, characterized in that: Satellite early warning transmission module, including: Trend determination unit: Generates a comparison trend between the virtual model output and the actual data based on the evaluation results of key performance indicators; Warning trigger unit: Dynamically adjusts the warning threshold according to the optimization level, and generates ground warning data by combining the comparison trend and warning threshold; Satellite mechanism unit: obtains current network performance data and generates current business requirements based on ground warning data, and generates a mechanism based on the current network performance data and current business requirements. Path generation unit: sets different priorities for each transmission path from a high-orbit satellite to a low-orbit satellite based on the path parameters, combines the intelligent algorithm with the mechanism to generate the initial transmission path and potential transmission paths, monitors the real-time performance of each potential transmission path during the transmission process, and dynamically generates the optimal transmission path based on the real-time performance and the initial transmission path; Satellite transmission unit: Introduces end-to-end encryption technology to encrypt the transmission data and ports separately, uses the corresponding high-orbit satellite to receive ground warning data according to the optimal transmission path, and forwards the ground data to the corresponding low-orbit satellite, which then forwards the ground warning data to the relevant management personnel's equipment end according to the optimal transmission path.

6. A real-time monitoring and early warning method for oil wells based on satellite communication, characterized in that: include: Step 1: Determine the oil well monitoring vector based on sensor data, geographic information, and satellite communication data, and build a comprehensive virtual model of the oil well through simulation. Step 2: simulating the operating state of the oil well according to the comprehensive virtual model, obtaining the simulated operating state, and evaluating the key performance indicators of the oil well according to the simulated operating state; Step 3: Compare the simulation running state with the real-time running state, check the deviation of the virtual model, analyze the deviation, and optimize the model parameters of the virtual model based on the deviation analysis results; Step 4: Generate oil well surface warning data based on the evaluation results and the optimization level, and send the oil well surface warning data in real time based on the cooperation mechanism of high-orbit satellites and low-orbit satellites in satellite communications; Wherein, step 2 includes: Based on the business objectives of the oil wells, the fluctuation of the historical production data corresponding to the business objectives is analyzed. Based on the fluctuation analysis results, the valid time periods of the historical production data are filtered to obtain time period screening results. The time period screening results are combined with the historical production data to preset the benchmark values of the measurable sub-goals for each time period; Based on the comprehensive virtual model, the oil well operation status is simulated, and the key performance indicators corresponding to the measurable sub-goals are extracted. The simulation results of each key performance indicator are compared with the corresponding benchmark value to obtain the simulated operation status of the oil well; Classify the simulation running status and evaluate key performance indicators based on the classification results, including: Dynamic classification formula setting for simulation running status based on external influencing factors: ,in, A Represents the simulation operation function; B Represents the operation function of external influencing factors; C Indicates the comprehensive classification value; Represents the frequency domain magnitude of the key performance indicators of the simulation run; Indicates the phase value of the key performance indicator within the segment screening result; The frequency domain amplitude representing the ambient temperature around the oil well; Indicates the phase value of the ambient temperature around the oil well; The frequency domain amplitude representing the equipment health index of the equipment corresponding to oil well monitoring and operation; Phase value indicating the health index of the device; The frequency domain amplitude representing the viscosity of the fluid in the oil well; represents the phase value of the fluid viscosity in the oil well; i represents the i-th importance factor; z represents the z-th influence factor; ; a, b, c as well as d Respectively represent the factors of influence of key performance indicators, ambient temperature, equipment health index and fluid viscosity on comprehensive classification; They represent the importance factors of key performance indicators, ambient temperature, equipment health index, and fluid viscosity to the comprehensive classification; represents the continuous influence function of all weights and amplitudes in each frequency domain; Classify the simulation running status according to the comprehensive classification value and obtain the classification result; ;in, Indicates dynamic reference value; D indicates preset reference value; Indicates the dynamic adjustment value of the benchmark value by external factors; Indicates the ambient temperature value around the oil well; Viscosity value of fluid in oil well; Equipment health index; Indicates the flow fluctuation value within the segment screening result; Indicates the geological characteristic index; a sensitivity index representing the frequency component correlation of the key performance indicator; ,in, 、 、 Represent the proportional gain, integral gain and differential gain respectively; Indicates the current classification result; Indicates the adjustment amount of the classification result; according to The classification results are adjusted and the key performance indicators are evaluated based on the adjusted results.

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