[HTML][HTML] Advancing reservoir evaluation: machine learning approaches for predicting porosity curves

N Ali, X Fu, J Chen, J Hussain, W Hussain, N Rahman… - Energies, 2024 - mdpi.com
Porosity assessment is a vital component for reservoir evaluation in the oil and gas sector,
and with technological advancement, reliance on conventional methods has decreased. In …

A novel hybrid machine learning approach and basin modeling for thermal maturity estimation of source rocks in Mandawa Basin, East Africa

CN Mkono, C Shen, AK Mulashani, MR Ngata… - Natural Resources …, 2024 - Springer
Basin modeling and thermal maturity estimation are crucial for understanding sedimentary
basin evolution and hydrocarbon potential. Assessing thermal maturity in the oil and gas …

Applied Machine Learning in Geophysics Taxonomy Review Bibliometrics and Trends in Generative AI

A Shakhatova, M Tolkyn, Z Gulnara… - 2024 IEEE 22nd …, 2024 - ieeexplore.ieee.org
This article presents a methodology to identify key studies using machine learning (ML) in
geophysics. We created a comprehensive database of fundamental articles for a systematic …

Gas-bearing prediction using a hybrid method based on a combination of PCA-FastICA and CNN with the attention mechanism

J Yang, N Lin, K Zhang, C Fu… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Fully utilizing multicomponent seismic data to predict gas-bearing distributions has great
potential, though it remains challenging. One difficulty in gas reservoir prediction using …

Forward and inverse adversarial model applying to well-logging

J Zhou, J Zhang, R Shao, L **ao, G Liao - Engineering Applications of …, 2025 - Elsevier
Geophysical logging is critical for reservoir characterization but is limited by the small
sample problem in machine learning. To address this, we propose the Forward and Inverse …

A comprehensive study on optimizing reservoir potential: Advanced geophysical log analysis of zamzama gas field, southern indus basin, Pakistan

S Hussain, A Atta, C Guo, W Hussain, N Ali… - … of the Earth, Parts A/B/C, 2024 - Elsevier
This study investigates the hydrocarbon and gas potential of the Pab Formation's Late
Cretaceous reservoir in the Zamzama Gas Field (ZGF) situated in Pakistan's Southern Indus …

An integrated Convolutional Neural Network (CNN) prediction framework for in-situ shale oil content based on conventional logging data

L Qiao, S Yang, Q Hu, H Wang… - Journal of the Geological …, 2024 - lyellcollection.org
The quantification of total organic carbon (TOC) and free hydrocarbon content (S1) is crucial
for evaluating the shale oil generation and bearing properties. This study aims to enhance …

Advanced Permeability Prediction Through Two-Dimensional Geological Feature Image Extraction with CNN Regression from Well Logs Data

W Hussain, M Luo, M Ali, SNR Rizvi… - Mathematical …, 2025 - Springer
The evaluation of permeability plays an essential role in understanding subsurface fluid
behavior, optimizing hydrocarbon recovery, managing reservoir performance, and …

Prediction method for the porosity of tight sandstone constrained by lithofacies and logging resolution

W Zhao, Z Zhang, J Liao, J Zhang, W Zhang - Marine and Petroleum …, 2024 - Elsevier
The resource potential of the Upper Triassic Yanchang Formation in the Ordos Basin is
considerably large. However, owing to the low porosity and permeability, poor connectivity …

A Gamma-ray spectroscopy approach to evaluate clay mineral composition and depositional environment: A case study from the lower Goru Formation, Southern …

W Hussain, M Luo, M Ali, HF Al-Khafaji… - Journal of Applied …, 2024 - Elsevier
Sandstone reservoirs often consist of clay minerals, including kaolinite, illite, and chlorite.
These clay minerals have a pronounced effect on the reservoir quality, which makes their …