A critical review of physics-informed machine learning applications in subsurface energy systems

A Latrach, ML Malki, M Morales, M Mehana… - Geoenergy Science and …, 2024 - Elsevier
Abstract Machine learning has emerged as a powerful tool in various fields, including
computer vision, natural language processing, and speech recognition. It can unravel …

Nexus between renewable energy investment, green finance, and sustainable development: Role of industrial structure and technical innovations

J He, W Iqbal, F Su - Renewable Energy, 2023 - Elsevier
The present study highlights the importance of renewable energy investment in achieving
the goal of sustainability. Several studies have been conducted to explore the factors …

An intelligent thermodynamic/economic approach based on artificial neural network combined with MOGWO algorithm to study a novel polygeneration scheme using …

MA Haghghi, A Hasanzadeh, E Nadimi… - Process Safety and …, 2023 - Elsevier
Flash-based geothermal cycles correspond to environmentally friendly and cost-effective
processes in a renewable framework and provide an opportunity for combined cycles …

A comprehensive review of seismic inversion based on neural networks

M Li, XS Yan, M Zhang - Earth Science Informatics, 2023 - Springer
Seismic inversion is one of the fundamental techniques for solving geophysics problems. To
obtain the elastic parameters or petrophysical parameters, it is necessary to establish a …

Modelling minimum miscibility pressure of CO2-crude oil systems using deep learning, tree-based, and thermodynamic models: Application to CO2 sequestration and …

Q Lv, R Zheng, X Guo, A Larestani… - Separation and …, 2023 - Elsevier
The energy demand is still increasing across the globe, while environmental concerns about
global warming effect and greenhouse gases have augmented recently. CO 2 injection into …

Mineral prospectivity mapping over the Gomoa Area of Ghana's southern Kibi-Winneba belt using support vector machine and naive bayes

ED Forson, PO Amponsah - Journal of African Earth Sciences, 2023 - Elsevier
Geospatial modeling of mineral prospective regions is essential, owing to its significant
contribution towards the development and economic gains of many mineral-endowed …

Experimental study on the thermal properties of Al2O3‐CuO/water hybrid nanofluids: Development of an artificial intelligence model

HB Marulasiddeshi, PK Kanti, M Jamei… - … Journal of Energy …, 2022 - Wiley Online Library
In this work, Al2O3 and CuO nanoparticles were synthesized by a novel sol‐gel method.
Then, water‐based Al2O3 and Al2O3‐CuO (50: 50) nanofluids were produced by the two …

Thermodynamic and economic evaluation and optimization of the applicability of integrating an innovative multi-heat recovery with a dual-flash binary geothermal …

A Farajollahi, M Rostami, M Feili, H Ghaebi - Clean Technologies and …, 2023 - Springer
Generally, a stand-alone flash-binary geothermal power plant loses most of its input energy,
so its efficiency declines accordingly. Its overall ability can be augmentable by utilizing …

Deep machine learning based possible atmospheric and Ionospheric precursors of the 2021 Mw 7.1 Japan earthquake

MU Draz, M Shah, P Jamjareegulgarn, R Shahzad… - Remote Sensing, 2023 - mdpi.com
Global Navigation Satellite System (GNSS)-and Remote Sensing (RS)-based Earth
observations have a significant approach on the monitoring of natural disasters. Since the …

Atmospheric Anomalies Associated with the 2021 Mw 7.2 Haiti Earthquake Using Machine Learning from Multiple Satellites

MM Khan, B Ghaffar, R Shahzad, MR Khan, M Shah… - Sustainability, 2022 - mdpi.com
The remote sensing-based Earth satellites has become a beneficial instrument for the
monitoring of natural hazards. This study includes a multi-sensors analysis to estimate the …