Reactive chemical transport simulations of geologic carbon sequestration: Methods and applications

Z Dai, L Xu, T **ao, B McPherson, X Zhang… - Earth-Science …, 2020 - Elsevier
Chemical reaction simulations are considerably used to quantitatively assess the long-term
geologic carbon sequestration (GCS), such as CO 2 sequestration capacity estimations …

[HTML][HTML] A survey on the application of machine learning and metaheuristic algorithms for intelligent proxy modeling in reservoir simulation

CSW Ng, MN Amar, AJ Ghahfarokhi… - Computers & Chemical …, 2023 - Elsevier
Abstract Machine Learning (ML) has demonstrated its immense contribution to reservoir
engineering, particularly reservoir simulation. The coupling of ML and metaheuristic …

Machine-learning models to predict hydrogen uptake of porous carbon materials from influential variables

S Davoodi, HV Thanh, DA Wood, M Mehrad… - Separation and …, 2023 - Elsevier
Hydrogen (H 2) absorption percentage by porous carbon media (PCM) is important for
identifying efficient H 2 storage media. PCM with H 2-uptakes of greater than 5 wt% are …

Investigation of enhanced CO2 storage in deep saline aquifers by WAG and brine extraction in the Minnelusa sandstone, Wyoming

H Wang, Z Kou, Z Ji, S Wang, Y Li, Z Jiao, M Johnson… - Energy, 2023 - Elsevier
Geological CO 2 sequestration in deep saline aquifers has been extendedly investigated to
reach the goal of carbon neutral as large amount of CO 2 can be reduced in a short time …

Application of machine learning methods for estimating and comparing the sulfur dioxide absorption capacity of a variety of deep eutectic solvents

X Zhu, M Khosravi, B Vaferi, MN Amar… - Journal of Cleaner …, 2022 - Elsevier
Sulfur dioxide (SO 2) is one of the main atmospheric pollutants and an active threat to
human health. SO2 separation from industrial flue gases improves air quality, decreases …

[HTML][HTML] Prediction of CO2 solubility in water at high pressure and temperature via deep learning and response surface methodology

Z Khoshraftar, A Ghaemi - Case Studies in Chemical and Environmental …, 2023 - Elsevier
In the present study, temperature of 313.15–473.15 K and pressure of 0.5–200 MPa have
been developed for the CO 2 solubility simulations via deep learning artificial (ANN) neural …

A new approach for predicting oil mobilities and unveiling their controlling factors in a lacustrine shale system: Insights from interpretable machine learning model

E Wang, Y Fu, T Guo, M Li - Fuel, 2025 - Elsevier
Petroleum remains a vital component of the global energy supply, and the exploration and
development of shale petroleum present significant opportunities for growth. The production …

Integrating the LSSVM and RBFNN models with three optimization algorithms to predict the soil liquefaction potential

M Cai, O Hocine, AS Mohammed, X Chen… - Engineering with …, 2022 - Springer
Liquefaction has caused many catastrophes during earthquakes in the past. When an
earthquake is occurring, saturated granular soils may be subjected to the liquefaction …

A review of machine learning in geochemistry and cosmochemistry: method improvements and applications

Y He, Y Zhou, T Wen, S Zhang, F Huang, X Zou… - Applied …, 2022 - Elsevier
The development of analytical and computational techniques and growing scientific funds
collectively contribute to the rapid accumulation of geoscience data. The massive amount of …

[HTML][HTML] Solubility and interfacial tension models for CO2–brine systems under CO2 geological storage conditions

M Mutailipu, Y Song, Q Yao, Y Liu, JPM Trusler - Fuel, 2024 - Elsevier
Thermodynamic properties of the CO 2–brine pseudo-binary system are essential for the
design of geological carbon storage (GCS) projects, especially those utilizing saline …