Artificial neural network model for reservoir petrophysical properties: porosity, permeability and water saturation prediction
AN Okon, SE Adewole, EM Uguma - Modeling Earth Systems and …, 2021 - Springer
Prediction of reservoir petrophysical properties from well-logs data has evolved from the use
of experts' knowledge and statistics to the use of artificial intelligence (AI) models. Several AI …
of experts' knowledge and statistics to the use of artificial intelligence (AI) models. Several AI …
[HTML][HTML] A data-driven approach to predict compressional and shear wave velocities in reservoir rocks
T Olayiwola, OA Sanuade - Petroleum, 2021 - Elsevier
Compressional and shear wave velocities (V p and V s respectively) are essential reservoir
parameters that can be used to delineate lithology, calculate porosity, identify reservoir …
parameters that can be used to delineate lithology, calculate porosity, identify reservoir …
Improved model development and feature ranking for rock permeability prediction by coupling petrophysical log data and ensemble machine learning techniques
Permeability is a crucial petrophysical rock parameter to assess the reservoir flow ability to
capture the reservoir quality and reservoir characterization during petroleum field …
capture the reservoir quality and reservoir characterization during petroleum field …
[PDF][PDF] Predictive models for oil in place for oil rim reservoirs in the Niger Delta using machine learning approach
KW Tugwell, A Livinus - Petroleum & Petrochemical Engineering …, 2023 - researchgate.net
One of the key factors that analysts consider when calculating the economics of oil field
development is the amount of oil in place (OIP). Conventional methods used for its …
development is the amount of oil in place (OIP). Conventional methods used for its …
Machine Learning Approach for Reservoir Petrophysical Properties Prediction from Well-Logs Data in the Niger Delta
AE Eyo, AN Okon, KW Tugwell - SPE Nigeria Annual International …, 2024 - onepetro.org
In this study, machine learning (ML) models were developed to predict permeability (k),
porosity (φ) and water saturation (Sw) using 1241 datasets obtained from well-logs data in …
porosity (φ) and water saturation (Sw) using 1241 datasets obtained from well-logs data in …
Application of Machine Learning for Estimating Petrophysical Properties of Carbonate Rocks Using NMR Core Measurements
Abstract Evaluation of petrophysical properties such as porosity, permeability, and
irreducible water saturation is crucial for reservoir characterization to determine the …
irreducible water saturation is crucial for reservoir characterization to determine the …