Robust prediction of advanced reservoir petrophysical parameters using conventional logs: Insights from XGB and neural network models

Prediction of Porosity and Permeability Using Well Log and Core Data: A Data-Driven Approach

Accurate prediction of porosity and permeability is very important for reservoir characterization and hydrocarbon extraction. Traditional workflow in the form of empirical correlations is usually difficult, time-consuming, spatially limiting, and entirely dependent on formation geology. The current study examines a dif...

Core-Calibrated Machine Learning–Based Permeability Estimation: A Western Niger Delta Case Study

Accurate permeability estimation is essential for optimum reservoir characterization, simulation, and development planning; however, its prediction remains challenging due to the limited availability of core-derived permeability measurements, often constrained by acquisition cost and data coverage. This study present...

Permeability prediction through machine learning regression in gas hydrate bearing sediments of Krishna-Godavari basin, using NGHP-02 well log data

Advances in the reservoir characterization from well logs using ML and rock physics analysis: a case study from the West Offshore Nile Delta, Egypt

The limited availability of shear-wave velocity (Vs) logs in deep-water reservoirs presents a significant challenge for reliable reservoir characterization and elastic property analysis. This study aims to develop and validate a robust machine learning (ML)-based workflow for predicting Vs from conventional well logs a...

Application of supervised machine learning for predicting and classifying the lithology type of reservoir rock: the case study of Iraq

Accurate lithology identification during subsurface exploration is essential for efficient hydrocarbon production, drilling optimization, and reservoir management. This study investigates automated lithology classification using supervised machine learning (ML) to reduce uncertainty and support operational decision-mak...

Ensemble Machine-Learning-Based Horizontal Permeability Prediction and Hydraulic Flow Unit Characterization of the Hugin Sandstone

Understanding permeability is essential for evaluating reservoir quality and field development planning. Reliable permeability estimation can reduce the uncertainty in reservoir characterization, particularly in intervals where core data are limited. As the industry relies on log-based interpretations and empirical cor...