Applications of hybrid models in chemical, petroleum, and energy systems: A systematic review

S Zendehboudi, N Rezaei, A Lohi - Applied energy, 2018 - Elsevier
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 …

Machine learning-A novel approach of well logs similarity based on synchronization measures to predict shear sonic logs

M Ali, R Jiang, H Ma, H Pan, K Abbas, U Ashraf… - Journal of Petroleum …, 2021 - Elsevier
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 …

Hybrid intelligent systems in petroleum reservoir characterization and modeling: the journey so far and the challenges ahead

FA Anifowose, J Labadin, A Abdulraheem - Journal of Petroleum …, 2017 - Springer
Computational intelligence (CI) techniques have positively impacted the petroleum reservoir
characterization and modeling landscape. However, studies have showed that each CI …

Log data-driven model and feature ranking for water saturation prediction using machine learning approach

MI Miah, S Zendehboudi, S Ahmed - Journal of Petroleum Science and …, 2020 - Elsevier
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 …

Ensemble machine learning: An untapped modeling paradigm for petroleum reservoir characterization

FA Anifowose, J Labadin, A Abdulraheem - Journal of Petroleum Science …, 2017 - Elsevier
The successful applications of the conventional Computational Intelligence (CI) techniques
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 …

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 …

A novel method of deep learning for shear velocity prediction in a tight sandstone reservoir

R Jiang, Z Ji, W Mo, S Wang, M Zhang, W Yin, Z Wang… - Energies, 2022 - mdpi.com
Shear velocity is an important parameter in pre-stack seismic reservoir description.
However, in the real study, the high cost of array acoustic logging leads to lacking a shear …

A novel ensemble learning based on Bayesian Belief Network coupled with an extreme learning machine for flash flood susceptibility mapping

A Shirzadi, S Asadi, H Shahabi, S Ronoud… - … Applications of Artificial …, 2020 - Elsevier
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 …

Optimization of subsurface CO2 injection based on neural network surrogate modeling

Z Sun, J Xu, DN Espinoza, MT Balhoff - Computational Geosciences, 2021 - Springer
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 …