[HTML][HTML] Advancing reservoir evaluation: machine learning approaches for predicting porosity curves
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 …
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 …
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 …
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 …
potential, though it remains challenging. One difficulty in gas reservoir prediction using …
Flow unit classification and characterization with emphasis on the clustering methods: a case study in a highly heterogeneous carbonate reservoir, eastern margin of …
M Homaie, A Mahboubi, DJ Hartmann… - Journal of Petroleum …, 2024 - Springer
Previous attempts to classify flow units in Iranian carbonate reservoirs, based on porosity
and permeability, have faced challenges in correlating the rock's pore size distribution with …
and permeability, have faced challenges in correlating the rock's pore size distribution with …
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 …
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
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 …
Cretaceous reservoir in the Zamzama Gas Field (ZGF) situated in Pakistan's Southern Indus …
An integrated comprehensive approach describing structural features and comparative petrophysical analysis between conventional and machine learning tools to …
Z Naseer, U Shakir, M Hussain, QA Ahmad… - … of the Earth, Parts A/B/C, 2025 - Elsevier
More than 70% of the global hydrocarbon reserves are present in carbonated rocks.
Evaluating prospects in carbonate reservoirs is a complicated task because of their unique …
Evaluating prospects in carbonate reservoirs is a complicated task because of their unique …
An integrated Convolutional Neural Network (CNN) prediction framework for in-situ shale oil content based on conventional logging data
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 …
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
The evaluation of permeability plays an essential role in understanding subsurface fluid
behavior, optimizing hydrocarbon recovery, managing reservoir performance, and …
behavior, optimizing hydrocarbon recovery, managing reservoir performance, and …