Suchergebnisse - Multi-objective hybrid shale optimization algorithm

Hierarchical Surrogate-Assisted Evolutionary Algorithm for Integrated Multi-Objective Optimization of Well Placement and Hydraulic Fracture Parameters in Unconventional Shale Gas Reservoir.

Autoren: Zhou, Jun Wang, Haitao Xiao, Cong et al.

Quelle: Energies (19961073); Jan2023, Vol. 16 Issue 1, p303, 24p

Schlagwörter: SHALE gas reservoirs, EVOLUTIONARY algorithms, NET present value, HYDRAULIC fracturing, POWER resources, GLOBAL optimization

Multiobjective Optimization of Groundwater Monitoring Network Based on Improved Quantum Particle Swarm Optimization Algorithm.

Autoren: Gu, Zhiqi Bian, Jianmin Wang, Yu et al.

Quelle: Journal of Water Resources Planning & Management; Sep2025, Vol. 151 Issue 9, p1-14, 14p

Schlagwörter: GROUNDWATER monitoring, MULTI-objective optimization, WATER quality monitoring, PARTICLE swarm optimization, SAMPLING (Process), LEVY processes, WATER chemistry, BOOSTING algorithms

Advancements in Optimization: Critical Analysis of Evolutionary, Swarm, and Behavior-Based Algorithms.

Autoren: Rashed, Noor A. Ali, Yossra H. Rashid, Tarik A.

Quelle: Algorithms; Sep2024, Vol. 17 Issue 9, p416, 47p

Schlagwörter: METAHEURISTIC algorithms, OPTIMIZATION algorithms, EVOLUTIONARY algorithms, PARTICLE swarm optimization, BIBLIOMETRICS

Predicting CO 2 Emissions with Advanced Deep Learning Models and a Hybrid Greylag Goose Optimization Algorithm.

Autoren: Alhussan, Amel Ali Metwally, Marwa Towfek, S. K.

Quelle: Mathematics (2227-7390); May2025, Vol. 13 Issue 9, p1481, 32p

Schlagwörter: MACHINE learning, OPTIMIZATION algorithms, FEATURE selection, CARBON emissions, CLIMATE change mitigation

Metaheuristic multi-objective optimization-based microseismic source location approach with anisotropic P-wave velocity field.

Autoren: Xin Yin Feng Gao Honggan Yu et al.

Quelle: Deep Resources Engineering; Feb2025, Vol. 2 Issue 1, p1-16, 16p

Schlagwörter: METAHEURISTIC algorithms, OPTIMIZATION algorithms, MULTI-objective optimization, WATER tunnels, SEARCH algorithms, WATER diversion

Integrated AutoML-based framework for optimizing shale gas production: A case study of the Fuling shale gas field.

Autoren: Tianrui Ye Jin Meng Yitian Xiao et al.

Quelle: Energy Geoscience; Mar2025, Vol. 6 Issue 1, p1-13, 13p

Schlagwörter: OIL shales, OPTIMIZATION algorithms, GAS wells, COST control, HYDRAULIC fracturing

Deep learning-assisted optimization for enhanced oil recovery and CO2 sequestration considering gas channeling constraints.

Autoren: Zhuang, Xin-Yu Wang, Wen-Dong Su, Yu-Liang et al.

Quelle: Petroleum Science (KeAi Communications Co.); Aug2025, Vol. 22 Issue 8, p3397-3417, 21p

Schlagwörter: ENHANCED oil recovery, CARBON sequestration, DEEP learning, MULTI-objective optimization, SPATIAL analysis (Statistics), MATHEMATICAL optimization, CARBON dioxide flooding, GAS leakage

Design of optimal operational parameters for steam-alternating-solvent processes in heterogeneous reservoirs – A multi-objective optimization approach.

Autoren: Mayo-Molina, Israel Ma, Zhiwei Leung, Juliana Y.

Quelle: Computational Geosciences. Dec2022, Vol. 26 Issue 6, p1503-1535. 33p.

Schlagwörter: *HEAVY oil, *EVOLUTIONARY algorithms, *MASS transfer, *WATER consumption, *HEAT transfer, *SHALE gas reservoirs, *RESERVOIRS

Geografische Kategorien: FORT McMurray (Alta.), ALBERTA

Cerchar abrasiveness index prediction based on rock properties leveraging hybrid soft computing techniques.

Autoren: Rouhani, Mohammad Matin Dolatshahi, Alireza Hasanipanah, Mahdi et al.

Quelle: Scientific Reports; 10/27/2025, Vol. 15 Issue 1, p1-28, 28p

Schlagwörter: GEOTECHNICAL engineering, ROCK properties, ENSEMBLE learning, SOFT computing, RANDOM forest algorithms, METAHEURISTIC algorithms

EUR Prediction for Shale Gas Wells Based on the ROA-CatBoost-AM Model.

Autoren: He, Weikang Li, Xizhe Wan, Yujin et al.

Quelle: Applied Sciences (2076-3417); Feb2025, Vol. 15 Issue 4, p2156, 22p

Schlagwörter: MACHINE learning, SHALE gas, OPTIMIZATION algorithms, OIL shales, GAS wells

A New Comprehensive Model to Simulate and Optimize Fluid Flow in Complex Well‐Formation System for In Situ Leaching Uranium.

Autoren: Li, Zhaokun Su, Xuebin Jiao, Yangquan et al.

Quelle: Energy Science & Engineering; Mar2025, Vol. 13 Issue 3, p1089-1102, 14p

Schlagwörter: URANIUM mining, MULTI-objective optimization, OPTIMIZATION algorithms, INJECTION wells, COMPLEX fluids

Hybrid Model Based on Copula Mutual Information and SSA-BP: Analysis of Key Factors and Prediction of Stable Gas Production.

Autoren: Luo, Zhifeng Xi, Haojiang

Quelle: Arabian Journal for Science & Engineering (Springer Science & Business Media B.V. ); Apr2025, Vol. 50 Issue 7, p4673-4685, 13p

Schlagwörter: OPTIMIZATION algorithms, GAS wells, COALBED methane, FEATURE selection, MACHINE learning

An Enhanced Moss Growth Optimization Algorithm with Outpost Mechanism and Early Stopping Strategy for Production Optimization in Tight Reservoirs.

Autoren: Wang, Chenglong Tan, Chengqian Cheng, Youyou

Quelle: Biomimetics (2313-7673); Oct2025, Vol. 10 Issue 10, p704, 25p

Schlagwörter: GLOBAL optimization, PETROLEUM reservoirs, OPTIMIZATION algorithms, RESOURCE allocation, METAHEURISTIC algorithms

Intelligent Collaborative Optimization Method for Multi-Well Plunger Gas Lifting Process on Platform.

Autoren: Yang, Zhi Wang, Qingrong Wang, Yunfu et al.

Quelle: Processes; Aug2025, Vol. 13 Issue 8, p2534, 15p

Schlagwörter: OIL well gas lift, PARTICLE swarm optimization, DYNAMIC models, GAS extraction, MATHEMATICAL programming, EDGE computing, STATISTICAL decision making

基于混合优化算法和深度神经网络模型结合的 致密砂岩气藏裂缝参数优化. (Chinese)

Alternate Title: Fracture parameter optimization of tight sandstone gas reservoirs based on the hybrid optimization algorithm and deep neural network model. (English)

Autoren: 罗山贵 赵玉龙 肖红林 et al.

Quelle: Natural Gas Industry; Sep2024, Vol. 44 Issue 9, p140-151, 12p

Schlagwörter: ARTIFICIAL neural networks, MACHINE learning, OPTIMIZATION algorithms, LATIN hypercube sampling, SWARM intelligence, GAS reservoirs, HORIZONTAL wells

Research on Intelligent Optimization of Wellbore Trajectory in Complex Formation.

Autoren: Gu, Haipeng Yan, Tie Wu, Yang

Quelle: Applied Sciences (2076-3417); Feb2025, Vol. 15 Issue 3, p1364, 17p

Schlagwörter: PARTICLE swarm optimization, TRAJECTORY optimization, MULTI-objective optimization, GAS well drilling, LEARNING strategies

An Enhanced Grasshopper Optimization Algorithm with Outpost and Multi-Population Mechanisms for Dolomite Lithology Prediction.

Autoren: Yu, Xinya Zunu, Parhat

Quelle: Biomimetics (2313-7673); Aug2025, Vol. 10 Issue 8, p494, 22p

Schlagwörter: OPTIMIZATION algorithms, ROCK properties, ALGORITHMS, MATHEMATICAL optimization, MATHEMATICAL programming

Machine learning-based fracturing parameter optimization for horizontal wells in Panke field shale oil.

Autoren: Li, Weirong Zhang, Tianyang Liu, Xinju et al.

Quelle: Scientific Reports; 3/13/2024, Vol. 14 Issue 1, p1-16, 16p

Schlagwörter: HORIZONTAL wells, PARTICLE swarm optimization, SHALE oils, OIL fields, FLOOD warning systems, PETROLEUM reservoirs

A hybrid machine learning optimization algorithm for multivariable pore pressure prediction.

Autoren: Song Deng Hao-Yu Pan Hai-Ge Wang et al.

Quelle: Petroleum Science (KeAi Communications Co.); Feb2024, Vol. 21 Issue 1, p535-550, 16p

Optimization Algorithms and Their Applications and Prospects in Manufacturing Engineering.

Autoren: Song, Juan Wang, Bangfu Hao, Xiaohong

Quelle: Materials (1996-1944); Aug2024, Vol. 17 Issue 16, p4093, 30p

Schlagwörter: OPTIMIZATION algorithms, MANUFACTURING processes, ARTIFICIAL intelligence, TAGUCHI methods, GENETIC engineering