4382 results about "Oil well" patented technology

Provided is an intelligent monitoring system for an oil development platform. The system includes external environment monitoring of a well platform, internal environment monitoring of the well platform and platform construction, where the external environment monitoring of the well platform includes real-time monitoring of natural environment conditions around an offshore oil development platform, the internal environment monitoring of the well platform includes collection and analysis of various indexes inside the oil well platform, and the platform construction is based on a three-layer structural design including a sensing layer, a transmission layer and an application layer. The sensing layer collects environmental data of ocean and the well platform through an Internet of Things technology, the transmission layer rapidly transmits data to ensure real-time updating of information, and the application layer processes received data to realize fusion and visualization of the data.

The disclosure relates to a technical field of oil monitoring, and in particular to real-time monitoring system for an internal environment of an oil well platform. The system includes: a group of Internet of Things sensors used for collecting data of the internal environment of the oil well platform in real time; a satellite transmission unit communicated with a plurality of Internet of Things sensors and used for receiving data collected by the Internet of Things sensors; the satellite receiving terminal used for receiving data from the satellite transmission unit and transmitting data to a central server; the central server with a data processing function used for receiving data from the satellite receiving terminal and carrying out data integration and analysis; and a control center used for displaying monitoring results and data trends from the central server, and issuing early warning or alarm based on a preset environmental parameter standard.

The invention relates to the technical field of pressure detection, in particular to an oil well pressure anomaly detection method and system based on deep learning, and the method comprises the following steps: collecting a control signal and pressure data, calculating a slope difference and fluctuation to mark a sudden change point, extracting a multi-dimensional feature group to generate a training sample, and constructing a deep learning model to recognize pressure difference anomaly. The oil well pressure abnormal time period is predicted in real time. According to the method, accurate attribution of abnormal fluctuations in the oil well operation process is achieved by constructing the time sequence corresponding relation between control signals and pressure difference sudden change, the target pertinence of pressure change recognition is improved, a sliding structure extracts multi-dimensional dynamic characteristics, the capacity of capturing wellhead or underground pressure micro-amplitude abnormity is enhanced, and the training sample is combined with a control behavior label, so that the accuracy of the abnormal fluctuations in the oil well operation process is improved. The distinguishing capability of the model to different abnormal forms is optimized, the adaptability under complex working conditions is improved, a real-time prediction mechanism ensures that oil well pressure state recognition has continuity, rapidness and high confidence, and risk early warning and operation guarantee in the oil extraction process are effectively supported.

The invention provides an oil well data intelligent management system and method, and relates to the technical field of oil well production. Comprising an edge layer and a platform layer. The edge layer is used for performing anomaly analysis on the oil well data; the platform layer is used for formulating an intervention control strategy according to abnormal oil well data; the edge computing node is used for performing feature extraction on the original oil well data; the model building module is used for building an anomaly detection model in combination with a historical oil well database; the anomaly recognition module is used for inputting the oil well data features into an anomaly detection model for anomaly recognition. According to the method, the edge computing nodes are combined with the lightweight LSTM model, so that the problem of high delay of cloud centralized processing in a traditional scheme is solved, and sudden equipment faults can be accurately captured in a low response period; a dynamically optimized intervention strategy generation mechanism is adopted, core parameters are adaptively adjusted according to different well conditions, a closed-loop control link is formed in cooperation with a cloud continuous iteration diagnosis knowledge base, and the manual inspection frequency and the operation and maintenance cost are reduced.

The invention relates to the technical field of oil well fault monitoring, and discloses an oil well indicator diagram real-time fault prediction method and system. The method comprises the following steps: acquiring an oil well sensor data stream, buffering and checking data integrity through a sliding window, and aligning multi-channel sensor data by applying a dynamic time warping algorithm to generate a standardized data stream; extracting time domain features based on the data stream, and comparing the time domain features with a historical feature library after principal component analysis dimension reduction to generate a feature difference index; triggering a multi-level threshold strategy according to the difference index, collecting an incremental training data set, finely tuning the model by adopting an elastic weight preserving algorithm, and generating a hot switching ready model; after the model is loaded, a fault probability value is generated through GPU accelerated reasoning, and an early warning event with a timestamp is generated; and finally analyzing the message into an early warning protocol message edge for transmission, and dynamically optimizing system resources based on logs. According to the method, the delay problem of high-frequency data flow is effectively solved, and the fault prediction accuracy and the system response speed are remarkably improved.

The invention relates to the technical field of oil well yield prediction, in particular to an electric submersible pump well yield prediction method fusing an electric submersible pump mechanism and a large language model, and the method comprises the steps: firstly collecting historical production data of an oil field, carrying out the preprocessing, and dividing the data into a training set, a verification set and a test set; according to attributes of all wells in the electric pump well attribute database, storage and transportation mechanism knowledge is established and represented, and a representation result is further refined to obtain an electric pump well mechanism model; inputting attribute parameters of a single well in the gathering and transportation pipe network into a pre-trained large language model to construct a large language model fusing mechanism knowledge, and sequentially training and evaluating; and finally, inputting the data of the test set into a big language model fused with mechanism knowledge for prediction to obtain a prediction result of the yield of each electric pump well in the electric pump well pipe network, introducing reprogramming and text mapping on the basis of the big language model, converting a time sequence prediction task into a language task, and finally obtaining a prediction result of the yield of each electric pump well in the electric pump well pipe network. And a large language model is successfully applied to the field of oil well yield prediction.

The invention relates to the technical field of oil exploitation, and provides a CFD-based electric submersible pump oil-gas-water three-phase flow adaptability analysis method and system, and the method comprises the steps: constructing a three-dimensional geometric model of an electric submersible pump, carrying out the initial grid division through CFD software, and optimizing the grid density through a self-adaptive grid refinement algorithm; setting oil well boundary conditions, a turbulence model and cavitation model parameters; steady-state and unsteady-state simulation calculation is carried out, and a flow field distribution diagram in the electric submersible pump is obtained; key performance parameters are extracted; simulating flow characteristics of oil-gas-water three-phase flow by adopting a turbulence model optimization algorithm based on multiphase flow coupling and combining a turbulence model, a multiphase flow model, an interphase turbulence correction term and an interphase interaction force model; and carrying out adaptability analysis on the oil-gas-water three-phase flow of the electric submersible pump. All-around technical support can be provided for design, operation and maintenance of the electric submersible pump, and technical progress and development of the oil exploitation industry are powerfully promoted.

The invention discloses an oil well water control production pipe column assembly and a using method thereof, and solves the technical problems that the oil well filling efficiency is low, and liquid extraction and production are difficult to achieve at the last stage of production. The device comprises a central pipe, a plurality of bypass isolation packers and water control production assemblies, each water control production assembly comprises a plurality of double-layer screen sleeves and a plurality of water control production short sections, each water control production short section comprises an outer protective cylinder, a setting short section, an AICD valve and a circulating sliding sleeve, the setting short section, the AICD valve and the circulating sliding sleeve are sequentially connected, and the double-layer screen sleeves are connected with the double-layer screen sleeves. An annular flow channel is formed among the setting nipple, the AICD valve, the circulating sliding sleeve and the outer protective cylinder, the setting nipple is used for blocking the side, away from the circulating sliding sleeve, of the annular flow channel, a plurality of circulating holes are formed in the circulating sliding sleeve in a penetrating mode, and a control part used for controlling the circulating holes to be opened and closed at the same time is arranged in the circulating sliding sleeve. The liquid return flow of filling liquid can be increased, the filling efficiency is improved, and liquid extraction and production can be achieved.

The invention relates to the technical field of petroleum and natural gas, in particular to a wellhead leakage alarm device, an early warning method and an intelligent wellhead leakage-proof system.The wellhead leakage alarm device comprises a leakage sensor, a reversible battery, a control unit and a storage box, and a sucker rod hole used for installing a sucker rod is formed in the upper end of the storage box. The device is reasonable and compact in structure, when the packing is punctured and leaked on site, produced liquid is sputtered to the sensing surface of the leakage sensor through a gap between a sucker rod and a packing gland, the leakage sensor sends a signal to the control unit, the control unit sends prompt information about the leakage phenomenon, an operator inspects a wellhead according to the prompt information, and the leakage phenomenon is avoided. The device is suitable for well mouth leakage under various working conditions, can meet the requirement for promoting intelligent oil field construction of an oil field, can early warn the risk of oil well mouth leakage in time, reduces the occurrence of well mouth pollution events, realizes unattended operation, provides technical support for green oil field development, and has good popularization and application prospects.

The invention belongs to the technical field of oil well production management, and discloses an electric submersible pump well group management system and method based on digital twinning. According to the method, operation data of an electric submersible pump unit and environmental data in a shaft are collected in real time, a multi-scale digital twinborn model is constructed for the received data, and the mechanical structure and electrical characteristics of the electric submersible pump unit, the multiphase flow dynamic state in the shaft and geological pressure field data are obtained; trend prediction is carried out on operation parameters, energy efficiency indexes and health states of the multi-scale digital twin model of each well; through a machine learning algorithm and an expert knowledge base, trend prediction data is associated with a historical health database, early warning and intelligent diagnosis of equipment faults are completed, and a maintenance strategy is generated. The method can assist managers to make decisions based on the historical health database. According to the invention, unified management and intelligent well patrol of multiple well sites can be realized, and the oil well production management efficiency is greatly improved.

The invention relates to the field of oil and gas well cementation, and discloses an oil well cementation cement slurry system and application thereof. The cement paste system comprises the following components in parts by weight: 100 parts of oil well cement, 20-80 parts of a high-temperature stabilizer, 15-80 parts of a high-temperature reinforcing agent, 0.5-6 parts of a retarder, 2-10 parts of a fluid loss agent, 0.1-2 parts of a defoaming agent and 35-90 parts of water, wherein the high-temperature stabilizer is a mixture containing quartz sand, silica fume and nano-silica which are different in average particle size; the high-temperature reinforcing agent is selected from at least one of pyrophyllite, epidote, actinolite, aluminum stone, sillimanite and boehmite. The cement paste system is mixed by adopting a conventional method, the density and the thickening time are adjustable, the flowing property is good, the water loss is small, the strength of formed cement stone is high, the cement stone does not decline for a long time at the high temperature of 150-240 DEG C, and the technical requirements of deep and ultra-deep high-temperature and high-pressure well cementation construction are completely met.

The invention relates to the technical field of oil field production real-time monitoring and pre-warning, and particularly discloses a three-dimensional modeling simulation method and system for oil and gas production early warning, and the method comprises the steps: constructing an oil and gas well productivity prediction model according to an IPR curve between the oil well yield and the flowing pressure; using a Begs-Brill method to construct a multiphase pipe flow model of the oil field shaft; constructing an oil nozzle flow model according to the relationship between the mass flow and the pressure difference of the oil-gas mixture passing through the oil nozzle equipment of the oil well; and according to the oil and gas well productivity prediction model, the oil field shaft multiphase pipe flow model and the oil nozzle flow model, an oil well production early warning model based on a support vector machine is constructed, so that the production state of an oil well is monitored in real time, and possible problems are predicted and early warned by learning historical data.

The invention belongs to the technical field of petroleum machinery, and particularly relates to a combined type polish rod breakage blowout prevention wellhead device which comprises a valve body, a horizontally symmetrical penetrating cavity is formed in the valve body, the two ends of the cavity are blocked and fixed through glands, and a vertically-penetrating annular channel is further formed in the valve body and allows an oil pumping polish rod to pass through. Two gate plates are further symmetrically arranged in the valve body corresponding to the horizontally-symmetrical penetrating cavity, a rib plate is arranged on one side of the cover plate, and a right-angle rubber base is fixedly connected between the gate plates and the rib plate through bolts. The device can be automatically triggered after the oil pumping polish rod is broken and disengaged, a blowout channel is rapidly sealed, oil well back pressure spraying is prevented, environment pollution caused by crude oil spraying is avoided, and the device has the function of guaranteeing sealing between a wellhead device and the oil pumping polish rod during normal production of a rod-pumped well. And the wellhead device can be isolated from the shaft when the packing is maintained and replaced by the oil extraction system of the pumping unit.

The invention provides an oil well casing corrosion monitoring method and device based on machine vision. The method comprises the steps that an image to be subjected to corrosion monitoring is acquired; the to-be-corroded monitoring image is an image of the oil well casing, which is acquired by utilizing preset machine vision equipment; according to a Harris operator positioning and prediction feature algorithm, positioning corrosion feature points in the image to be subjected to corrosion monitoring; based on the corrosion feature points, positioning corrosion geometric features in the image to be subjected to corrosion monitoring by adopting a slope template; the corrosion geometric characteristics are used for analyzing corrosion geometric parameters of oil well casing corrosion; and determining the monitoring result of the oil well casing corrosion according to the corrosion geometric parameters. According to the method, the positioning and prediction accuracy of corrosion characteristics can be improved in a complex environment, the monitoring result of oil well casing corrosion is more accurate and reliable, meanwhile, a large number of sensors do not need to be arranged in the process, and the workload and the cost are reduced.

The invention discloses an oil pumping unit transmission flexible connection fault diagnosis method based on big data and artificial intelligence. The oil pumping unit transmission flexible connection fault diagnosis method sequentially comprises the following steps of S1, collecting monitoring data related to oil pumping unit transmission flexible connection; s2, preprocessing the collected monitoring data; s3, a traditional machine learning method and a deep learning technology are fused, and an oil pumping unit transmission flexible connection fault early warning model is established; s4, analyzing the real-time monitoring data of the flexible connection by using the fault early-warning model, quickly judging abnormal conditions in the real-time monitoring data, making a fault early-warning and analysis report, and providing the fault early-warning and analysis report to a manager; and S5, continuously monitoring and optimizing the early warning model. According to the fault diagnosis method, through data management, an intelligent algorithm and model analysis, the transmission flexible connection state of the oil pumping unit is monitored in real time, potential faults are predicted and diagnosed in advance, and an alarm is given in time when a belt of the oil pumping unit or a steel wire rope of a beam hanger is broken, so that the production efficiency and safety of an oil well are improved, and construction of an intelligent oil field is assisted.

To provide a high-strength stainless steel seamless pipe for oil wells, the high-strength stainless steel seamless pipe having high strength and excellent low-temperature toughness and being excellent in crevice corrosion resistance in an untreated seawater environment.　There is provided a high-strength stainless steel seamless steel pipe for oil wells having a component composition that comprises specific components and that satisfies relationship (1) and relationship (2), with the balance being Fe and unavoidable impurities, having a yield strength of 758 MPa or above, and having an absorption energy vE-10 of 40 J or above at a test temperature of -10°C in a Charpy impact test. Relationship (1): Cr + 0.22 × Ni + 0.38 × (Mo + 0.5 × W) + 0.89 × Cu + 0.09 × Co ≥ 21.4 Cr, Ni, Mo, W, Cu and Co in relationship (1) are the contained amounts (mass %) of the respective elements, and the contained amount of elements that are not contained is deemed to be zero. Relationship (2): Co-Nb ≥ 0.13 Co and Nb in relationship (2) are the contained amounts (mass %) of the respective elements.

The invention discloses a lithology identification method and device for unbalanced logging data. The method comprises the following steps: acquiring logging data of an oil well and a lithology category to be identified; inputting to-be-identified logging data into the trained lithology identification model to obtain a lithology identification result; wherein the trained lithology identification model is obtained by preprocessing training set data through an ADASYN algorithm and training based on a cascade ELM model of a multi-granularity scanning module.

The invention discloses a well station instrument fault intelligent diagnosis system and diagnosis method based on big data and artificial intelligence, and the system comprises a well station instrument data management and acquisition module which collects and stores well station instrument data in real time, and provides a visual data display interface at the same time, so that an operator can know the operation state of a well station in time; the well station instrument data analyzing and processing module is used for analyzing the collected well station instrument data and extracting key index data; according to the well station instrument fault early warning model system, a multi-level early warning model is created, and potential faults of well station instruments can be effectively recognized and predicted; and the well station instrument fault diagnosis and analysis module is used for quickly identifying abnormal conditions in the well station instrument data, making fault early warning and analysis reports and providing the fault early warning and analysis reports to management personnel. According to the intelligent diagnosis system and the diagnosis method, problems possibly occurring in production are analyzed and predicted through an intelligent algorithm and a model, and corresponding measures are taken in advance so as to ensure safety and stability of oil well production.

The invention relates to the technical field of oil well logging, in particular to a core storage short section and a drilling type well wall coring instrument. The core storage pup joint comprises a core storage pup joint base body, a core detection plectrum mechanism, a plectrum cylinder and a core storage cylinder, the plectrum cylinder is arranged on the periphery of the middle part of the core storage short section base body and is used for storing the plectrum; the core storage barrel is arranged in the core storage short section base body and used for storing the taken core; the rock core detection plectrum mechanism is arranged at the first end of the core storage short section base body and is used for counting the taken rock cores and pushing a plectrum to separate the taken rock cores. The drilling type side wall coring device needs to complete drilling coring and rock core recovery underground to guarantee completeness and storage of rock cores, so that the core storage short section is the key technology of the drilling type side wall coring device, and a structural mode that hydraulic pressure provides power to achieve rock core pushing, rock core separation and counting is provided for the drilling type side wall coring device. And the stability and the reliability of the core storage function of the drilling type side wall coring device are ensured.

The invention belongs to the technical field of preparation of hydrogen sulfide stress corrosion resistant oil well pipes, and relates to a 125ksi steel grade hydrogen sulfide stress corrosion resistant oil well pipe material suitable for a normal temperature environment containing 1MPa H2S and a preparation method of the 125ksi steel grade hydrogen sulfide stress corrosion resistant oil well pipe material. B, Ti, V and Nb elements are added, and the contents of Si, Mn and Ni elements, the Cr / Mo ratio and the sum of Nb, V and Ti in steel are controlled; the refined 100% sorbite structure, various compounds and microalloying are obtained through the processes of pure steel smelting, forging, controlled rolling and secondary heat treatment, so that high strength and high toughness in the 125 ksi range are obtained, and meanwhile the hydrogen sulfide corrosion resistance is high. The pipe product obtained by the process method disclosed by the invention has no corrosion cracking phenomenon after being subjected to a corrosion resistance test under the partial pressure of hydrogen sulfide of 1MPa.

Disclosed is a synchronous one-injection and two-production tubing string for a single horizontal well, comprising an oil well pump (100), an upper bridge-type packer (300), an oil production bridge-type working barrel (400), a lower bridge-type packer (500), a hydraulic packer (600), and a soluble bottom plug (700). A first central channel (301) and a first bridge-type channel (302) which are independent of each other are provided in the upper bridge-type packer (300), and a first rubber cylinder structure (305) is provided outside the upper bridge-type packer (300); a second central channel (401) and a second bridge-type channel (402) which are independent of each other are provided in the oil production bridge-type working barrel (400), a lateral opening (403) capable of communicating the second central channel (401) and the outside of the oil production bridge-type working barrel (400) is further provided in the oil production bridge-type working barrel (400), and a temporary pipe (404) capable of sealing and blocking the lateral opening (403) is connected to the lateral opening (403) by means of a temporary shear pin (4041); a third central channel (501) and a third bridge-type channel (502) which are independent of each other are provided in the lower bridge-type packer (500), and a second rubber cylinder structure (505) is provided outside the lower bridge-type packer (500). Water injection at a middle section and oil production at two end sections of a horizontal well can be implemented by means of the tubing string, and injected water and produced liquid flow channels do not interfere with each other.

An electrically operated catcher mechanism that is part of a lubricator and catcher unit used in conjunction with a bypass plunger in an oil or gas well include an electrically operated mechanism to move between the catch and release positions. The electrically operated catcher mechanism includes a cam rotated by a motor which causes the device to move between catch and release positions.

The invention belongs to the petroleum and natural gas exploitation industry, and particularly relates to a loose sandstone reservoir fracturing filling double-particle-size proppant combination parameter optimization design method, which performs optimization design on specific parameters of the proppant such as filling particle size, filling seam length proportion, filling sequence and the like according to reservoir and oil well conditions and a corresponding double-particle-size combination mode. And finally, effective sand blocking is achieved, meanwhile, invasion blocking and permeability damage of stratum sand to a crack filling layer are reduced, the crack flow resistance is reduced, the comprehensive flow conductivity is improved, and the comprehensive effects of releasing the oil and gas well productivity are achieved.

The invention relates to the technical field of unconventional oil and gas development, in particular to a system and a method for simulating gas-water alternation multi-turn pressing-braising injection and production oil displacement. According to the scheme, a pressing fracture network and a matrix reservoir are equivalently simulated, and pressing-braising injection and production of well soaking time are reasonably considered, so that the result is more accurate, and the oil displacement efficiency is improved. After the fracture core clamping unit and the matrix core clamping unit are exchanged in the forward direction and the reverse direction, a compact core is rapidly saturated, the oil reservoir initialization time is shortened, the influence of multiple fracture parameters on oil displacement in the three stages of pressing, braising and mining can be considered without repeatedly disassembling and assembling the core clamping unit, the fracture form is changed by replacing the fracture forming core, and the oil displacement efficiency is improved. The influence rule of a water-gas composite medium on the oil well pressing-braising-production capacity under different storage and seepage modes can be researched, the different storage and seepage modes comprise a multi-stage fracture-matrix reservoir, a large fracture-matrix reservoir, a micro-fracture-matrix reservoir and an original matrix reservoir, and independence and integrity of a fracture core and a matrix core are ensured; the experiment time is greatly shortened.

The invention provides an oil well oil production prediction method based on CEEMDAN-SA-LSTM, and the method is characterized in that the method comprises the following steps: 1) collecting oil well feature data, complementing missing values, processing abnormal values, and converting a data set into a format suitable for model training; 2) carrying out importance analysis by utilizing a Boruta algorithm, and constructing an oil well oil production characteristic data set; 3) performing data set division on the data converted in the step 2); and 4) carrying out feature decomposition by using CEEMDAN and carrying out data dimension reduction by using PCA to obtain a final component feature data set. 5) inputting the final component feature data set into the SA-LSTM model for training, and constructing a prediction model; 6) adjusting and optimizing the model by adopting a parallel genetic algorithm to obtain an optimal parameter combination; and 7) according to the trained oil well oil production prediction model, using test set data to verify the model performance, and predicting the oil well oil production. The invention discusses the method for predicting the oil production of the oil well by using the CEEMDAN-SA-LSTM model, and the method can obtain a better prediction result.

The invention provides an oil well operation state analysis system and method, and relates to the technical field of oil well monitoring, and the system comprises an acquisition module which collects oil well operation data in real time; the data processing module preprocesses the operation data to obtain input data; the data analysis module constructs a 1D-CNN network model, and optimizes the 1D-CNN network model by using a grey wolf optimization algorithm to obtain an optimal analysis model; inputting the input data into the optimal analysis model to obtain abnormal data; the fault diagnosis module constructs a random forest network model, and optimizes the random forest network model by using an improved South goose algorithm to obtain an optimal diagnosis model; inputting the abnormal data into the optimal diagnosis model to obtain an abnormal type; and the early warning module receives the abnormal data and the abnormal type to generate a report and transmits the report to a user. Abnormal data are diagnosed through the fault diagnosis module, the abnormal type is obtained, and the oil well operation state analysis accuracy is improved.

The invention provides an oil-water well oil pipe thread profile measurement method based on three-dimensional point cloud adaptive slicing. The method comprises the following steps: step 1, obtaining an oil pipe thread three-dimensional point cloud image; 2, normalizing the 3D point cloud data; 3, extracting a global feature recognition point cloud image, carrying out point cloud positioning, and segmenting point cloud data; step 4, extracting the labeled detection area for denoising processing; step 5, segmenting the 3d point cloud image into a plurality of square blocks; step 6, performing projection mapping processing on the plurality of point cloud blocks from front view, top view and side view angles to obtain a pseudo picture; and step 7, carrying out pseudo image matching and combining with a loss function to judge whether the image is qualified. According to the oil-water well oil pipe thread profile measurement method based on the three-dimensional point cloud self-adaptive slicing, operation reworking caused by oil pipe sealing leakage is reduced, the working efficiency is improved, the crude oil yield loss is reduced, and it is avoided that the liquid supply capacity of an oil well is reduced due to leakage.

The invention discloses an oil field yield prediction method and system based on a digital twinborn technology, and relates to the technical field of oil field monitoring. The method is characterized by comprising the following steps: acquiring oil field production process data and oil field historical yield data; preprocessing the oil field production process data; constructing a twinborn model, inputting the preprocessed oil field production process data and oil field historical yield data into the twinborn model for oil field yield prediction, and obtaining an oil field yield prediction result; wherein an improved random forest algorithm is adopted in the digital twin model, and a self-adaptive lifting strategy and a dynamic depth control mechanism are combined; the output data and the original data are combined and input into the bidirectional xLSTM model for prediction, so that the accuracy and generalization ability of yield prediction are improved; by analyzing production data of the oil well, the model can effectively capture complex dynamic changes in the production process of the oil field, and therefore accurate prediction of the yield of the oil field is achieved.

A methodology for optimizing the recovery from a system of wells is provided. The method is executed via a processor of a computing system. The method includes receiving input data for a system of wells. The method also further includes predicting, via a trained virtual flow meter, virtual flow rates for the system of wells for a scenario using a predicted pressure and temperature for the scenario. The predicted pressure and temperature are generated based on the input data. The method includes generating a production optimization recommendation based on the predicted virtual flow rates and a received rule for the system of wells. The method includes adjusting a manipulative parameter of a well in the system of wells based on production optimization recommendation.

The invention discloses a multiphase metering modeling system and a multiphase metering method for oil well produced substances. An oil well multiphase medium extraction simulation device of the system is used for measuring throttling pressure difference signals and temperature drop amplitude before and after a gas phase and a liquid phase of different flow combinations are mixed and pass through a selected oil nozzle, and an experimental data set is obtained; the metering model building module is used for building an oil well multiphase produced medium metering model based on the experimental data set, and a gas phase mass content calculation model is used for representing the relation among the fluctuation standard deviation of the throttling pressure difference before and after the oil nozzle, the temperature drop amplitude and the gas phase mass content; the total mass flow calculation model is a linear function relation between the ratio of the arithmetic square root of the average value of the throttling pressure difference before and after the oil nozzle device to the total mass flow and the gas phase mass content. The model established by using the system can accurately and conveniently meter the oil well multiphase produced medium, is wide in application range, and is still suitable for complex working conditions such as high gas-liquid ratio; and the ground technological process is simple, and the metering cost is low.