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Applications of hybrid models in chemical, petroleum, and energy systems: A systematic review
Mathematical modeling and simulation methods are important tools in studying various
processes in science and engineering. In the current review, we focus on the applications of …
processes in science and engineering. In the current review, we focus on the applications of …
Machine learning in oil and gas exploration: a review
A comprehensive assessment of machine learning applications is conducted to identify the
develo** trends for Artificial Intelligence (AI) applications in the oil and gas sector …
develo** trends for Artificial Intelligence (AI) applications in the oil and gas sector …
Machine learning-A novel approach of well logs similarity based on synchronization measures to predict shear sonic logs
This study proposes a novel approach to predict missing shear sonic log responses more
precisely and accurately using similarity patterns of various wells with similar geophysical …
precisely and accurately using similarity patterns of various wells with similar geophysical …
Log data-driven model and feature ranking for water saturation prediction using machine learning approach
Log-based reservoir characterization is one of the widely used techniques to estimate the
reservoir properties and make decisions about future plans for hydrocarbon production. Use …
reservoir properties and make decisions about future plans for hydrocarbon production. Use …
Ensemble machine learning: An untapped modeling paradigm for petroleum reservoir characterization
The successful applications of the conventional Computational Intelligence (CI) techniques
and Hybrid Intelligent Systems (HIS) in petroleum reservoir characterization have been …
and Hybrid Intelligent Systems (HIS) in petroleum reservoir characterization have been …
A new multi-objective differential evolution approach for simultaneous clustering and feature selection
E Hancer - Engineering applications of artificial intelligence, 2020 - Elsevier
Today's real-world data mostly involves incomplete, inconsistent, and/or irrelevant
information that causes many drawbacks to transform it into an understandable format. In …
information that causes many drawbacks to transform it into an understandable format. In …
Experimental and numerical simulation of erosion-corrosion of 90 steel elbow in shale gas pipeline
W Jia, Y Zhang, C Li, P Luo, X Song, Y Wang… - Journal of Natural Gas …, 2021 - Elsevier
Coexistence of the solid particle erosion and acid liquid corrosion is common in shale gas
gathering and transportation pipelines. It is conceivable that the synergistic effect of erosion …
gathering and transportation pipelines. It is conceivable that the synergistic effect of erosion …
Optimization of subsurface CO2 injection based on neural network surrogate modeling
This study presents a workflow to optimize the location of CO2 injectors in order to maximize
stored volume and prevent fault reactivation due to increases of pore pressure. We combine …
stored volume and prevent fault reactivation due to increases of pore pressure. We combine …
A novel ensemble learning based on Bayesian Belief Network coupled with an extreme learning machine for flash flood susceptibility map**
Reliable flash flood susceptibility maps are a vital tool for land planners and emergency
management officials for early flood warning and mitigation. We have developed a new …
management officials for early flood warning and mitigation. We have developed a new …
Hybrid intelligent systems in petroleum reservoir characterization and modeling: the journey so far and the challenges ahead
Computational intelligence (CI) techniques have positively impacted the petroleum reservoir
characterization and modeling landscape. However, studies have showed that each CI …
characterization and modeling landscape. However, studies have showed that each CI …