[go: up one dir, main page]

Jiang et al., 2025 - Google Patents

A Reservoir-Wellbore-Pipeline Integration Method for Gas Lift Performance Optimization Based on Proxy Model and NSGA-II Algorithm of Well Group

Jiang et al., 2025

Document ID
11926388706615457862
Author
Jiang L
Jiang L
Xu J
Wang Y
Guo Y
Zhao X
Cheng Y
Deng Y
Wang L
Zhang L
Cao X
Cui X
Guo S
Yang L
Yang C
Luo Y
Publication year
Publication venue
Abu Dhabi International Petroleum Exhibition and Conference

External Links

Snippet

This study addresses the complex optimization of gas lift well groups supplied by a single compressor unit under fixed total gas volume constraints. The interdependence of well performance and reservoir management requirements-including reservoir pressure limits …
Continue reading at onepetro.org (other versions)

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
    • G06F17/30286—Information retrieval; Database structures therefor; File system structures therefor in structured data stores
    • G06F17/30312—Storage and indexing structures; Management thereof
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
    • G06F17/30861—Retrieval from the Internet, e.g. browsers
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/50—Computer-aided design
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N99/00—Subject matter not provided for in other groups of this subclass
    • G06N99/005—Learning machines, i.e. computer in which a programme is changed according to experience gained by the machine itself during a complete run
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06Q—DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management, e.g. organising, planning, scheduling or allocating time, human or machine resources; Enterprise planning; Organisational models
    • E—FIXED CONSTRUCTIONS
    • E21—EARTH DRILLING; MINING
    • E21B—EARTH DRILLING, e.g. DEEP DRILLING; OBTAINING OIL, GAS, WATER, SOLUBLE OR MELTABLE MATERIALS OR A SLURRY OF MINERALS FROM WELLS
    • E21B43/00—Methods or apparatus for obtaining oil, gas, water, soluble or meltable materials or a slurry of minerals from wells
    • E21B43/12—Methods or apparatus for controlling the flow of the obtained fluid to or in wells
    • E—FIXED CONSTRUCTIONS
    • E21—EARTH DRILLING; MINING
    • E21B—EARTH DRILLING, e.g. DEEP DRILLING; OBTAINING OIL, GAS, WATER, SOLUBLE OR MELTABLE MATERIALS OR A SLURRY OF MINERALS FROM WELLS
    • E21B43/00—Methods or apparatus for obtaining oil, gas, water, soluble or meltable materials or a slurry of minerals from wells
    • E21B43/16—Enhanced recovery methods for obtaining hydrocarbons
    • E—FIXED CONSTRUCTIONS
    • E21—EARTH DRILLING; MINING
    • E21B—EARTH DRILLING, e.g. DEEP DRILLING; OBTAINING OIL, GAS, WATER, SOLUBLE OR MELTABLE MATERIALS OR A SLURRY OF MINERALS FROM WELLS
    • E21B43/00—Methods or apparatus for obtaining oil, gas, water, soluble or meltable materials or a slurry of minerals from wells
    • E21B43/14—Obtaining from a multiple-zone well

Similar Documents

Publication Publication Date Title
Yang et al. Robust optimization of SAGD operations under geological uncertainties
CN116911216B (en) Reservoir oil well productivity factor assessment and prediction method
Thiele et al. Evolve: A linear workflow for quantifying reservoir uncertainty
Castineira et al. Augmented AI Solutions for Heavy Oil Reservoirs: Innovative Workflows That Build from Smart Analytics, Machine Learning And Expert-Based Systems
Alharbi et al. Prediction of oil production through linear regression model and big data tools
Liu et al. Digital wellbore stability prediction with machine learning
Maqui et al. A comprehensive workflow for near real time waterflood management and production optimization using reduced-physics and data-driven technologies
Kalantari-Dahaghi et al. Numerical simulation and multiple realizations for sensitivity study of shale gas reservoir
Liu et al. Multiparameter inversion of reservoirs based on deep learning
Wang et al. Multiobjective history matching using machine learning proxies-assisted iterative rejection sampling
Bahaa et al. Soft computation application: Utilizing artificial neural network to predict the fluid rate and bottom hole flowing pressure for gas-lifted oil wells
Zhuang et al. Co-Optimization of CO2-EOR Strategies Considering the Spatio-Temporal Sequence Prediction of CO2 Flooding and Sequestration
Ahdeema et al. Hybrid optimization technique allows dynamic completion design and control in advanced multilateral wells with multiple types of flow control devices
Choudhary et al. Application of global optimization methods for history matching and probabilistic forecasting—case studies
Liu et al. Accelerated completion optimization with uncertainty reduction through coupled data and physics based hybrid models
Jiang et al. A Reservoir-Wellbore-Pipeline Integration Method for Gas Lift Performance Optimization Based on Proxy Model and NSGA-II Algorithm of Well Group
Zalavadia et al. Technical Resource Potential Estimation Using Machine Learning and Optimization for the Delaware Basin
Qoqandi et al. Production forecasting in tight gas reservoirs using long short-term memory methods (LSTM)
Yang et al. Optimization of multivariate production-injection system for water-alternating-gas miscible flooding in Pubei oil field
Jahanbani Ghahfarokhi Applications of Data-Driven Techniques in Reservoir Simulation and Management
Anumah et al. Application of ANN-Based Proxy and Metaheuristic Algorithms in Well Spacing Optimization in a Fractured Tight Reservoir
Xu et al. Deep Learning-Based Production Forecasting for Liquid-Rich Gas in the Duvernay Shale Play
Adiga Optimizing geothermal well planning under reservoir uncertainty with stochastic programming
Yang et al. Predicting oil production after enhancement techniques using multidimensional feature representation learning: A case study of profile control technique
Yan et al. A Reservoir Dynamic Prediction Model Based on the REROSIM Method: Digital Twin and Simulation Studies Driven by Digital Transformation