Machine-learning modeling of pore pressure variation in geological CO2 storage reservoir

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...

Performance and Limitations of Machine Learning Models for Groundwater Level Prediction Using Hydro-Climatic Variables

Accurate groundwater level (GWL) prediction is essential for sustainable groundwater management and resource planning. However, it is challenging in heterogeneous hydrogeological settings for physics-based models, particularly under limited subsurface characterisation. Machine learning (ML) techniques can capture c...

Prediction of Sand Production in Vertical Oil Well Using Supervised Machine Learning Models

Sand production has become a significant concern in the hydrocarbon recovery process from unconsolidated reservoirs which may result in equipment damage, flow restrictions, and costly operational downtime in vertical oil wells. Accurate prediction of sand production is vital to optimize well integrity. Conventional g...

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

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...

Prediction of Water Saturation Using Physics-Guided Machine Learning in Deep Silurian Shale Gas Reservoirs

Accurate water saturation estimation in deep shale reservoirs is complicated by clay-related additional conductivity and coupled pore, organic-matter, and structural effects. This study develops a feature-level physics-guided machine-learning framework, termed PhysML-Hybrid. Five mechanism-derived descriptor groups rep...