A systematic review of data science and machine learning applications to the oil and gas industry
This study offered a detailed review of data sciences and machine learning (ML) roles in
different petroleum engineering and geosciences segments such as petroleum exploration …
different petroleum engineering and geosciences segments such as petroleum exploration …
[HTML][HTML] Review of application of artificial intelligence techniques in petroleum operations
S Bahaloo, M Mehrizadeh, A Najafi-Marghmaleki - Petroleum Research, 2023 - Elsevier
In the last few years, the use of artificial intelligence (AI) and machine learning (ML)
techniques have received considerable notice as trending technologies in the petroleum …
techniques have received considerable notice as trending technologies in the petroleum …
Application of gradient boosting regression model for the evaluation of feature selection techniques in improving reservoir characterisation predictions
Feature Selection, a critical data preprocessing step in machine learning, is an effective way
in removing irrelevant variables, thus reducing the dimensionality of input features …
in removing irrelevant variables, thus reducing the dimensionality of input features …
Log data-driven model and feature ranking for water saturation prediction using machine learning approach
Log-based reservoir characterization is one of the widely used techniques to estimate the
reservoir properties and make decisions about future plans for hydrocarbon production. Use …
reservoir properties and make decisions about future plans for hydrocarbon production. Use …
[HTML][HTML] Prediction of water saturation from well log data by machine learning algorithms: Boosting and super learner
F Hadavimoghaddam, M Ostadhassan… - Journal of Marine …, 2021 - mdpi.com
Intelligent predictive methods have the power to reliably estimate water saturation (Sw)
compared to conventional experimental methods commonly performed by petrphysicists …
compared to conventional experimental methods commonly performed by petrphysicists …
Machine Learning in Oil and Gas Exploration-A Review
A comprehensive assessment of machine learning applications is conducted to identify the
developing trends for Artificial Intelligence (AI) applications in the oil and gas sector …
developing trends for Artificial Intelligence (AI) applications in the oil and gas sector …
Ensemble machine learning assisted reservoir characterization using field production data–an offshore field case study
Estimation of fluid saturation is an important step in dynamic reservoir characterization.
Machine learning techniques have been increasingly used in recent years for reservoir …
Machine learning techniques have been increasingly used in recent years for reservoir …
Connectionist and mutual information tools to determine water saturation and rank input log variables
Abstract Characterization of petroleum reservoirs plays an important role to effectively
manage and forecast the recovery performance. A number of subset log variables such as …
manage and forecast the recovery performance. A number of subset log variables such as …
[HTML][HTML] Evaluation of Gas Hydrate Saturation Based on Joint Acoustic–Electrical Properties and Neural Network Ensemble
Natural gas hydrates have great strategic potential as an energy source and have become a
global energy research hotspot because of their large reserves and clean and pollution-free …
global energy research hotspot because of their large reserves and clean and pollution-free …
Subsurface porosity estimation: A case study from the Krishna Godavari offshore basin, eastern Indian margin
AK Joshi, K Sain - Journal of Natural Gas Science and Engineering, 2021 - Elsevier
Porosity is one of the fundamental petrophysical parameters essential for appraisal of
hydrocarbon reserve and planning production operations. Several interpretation techniques …
hydrocarbon reserve and planning production operations. Several interpretation techniques …