A review of permeability-prediction methods for carbonate reservoirs using well-log data
T Babadagli, S Al-Salmi - SPE Reservoir Evaluation & Engineering, 2004 - onepetro.org
The prediction of permeability in heterogeneous carbonates from well-log data represents a
difficult and complex problem. Generally, a simple correlation between permeability and …
difficult and complex problem. Generally, a simple correlation between permeability and …
Modelling minimum miscibility pressure of CO2-crude oil systems using deep learning, tree-based, and thermodynamic models: Application to CO2 sequestration and …
Q Lv, R Zheng, X Guo, A Larestani… - Separation and …, 2023 - Elsevier
The energy demand is still increasing across the globe, while environmental concerns about
global warming effect and greenhouse gases have augmented recently. CO 2 injection into …
global warming effect and greenhouse gases have augmented recently. CO 2 injection into …
Predicting porosity, permeability and water saturation applying an optimized nearest-neighbour, machine-learning and data-mining network of well-log data
DA Wood - Journal of Petroleum Science and Engineering, 2020 - Elsevier
Predicting permeability (Ke), water saturation (Sw) and effective porosity (EP) of oil and gas
reservoir sections from well log data is necessary task because core data is typically not …
reservoir sections from well log data is necessary task because core data is typically not …
Integrating well log interpretations for lithofacies classification and permeability modeling through advanced machine learning algorithms
WJ Al-Mudhafar - Journal of Petroleum Exploration and Production …, 2017 - Springer
In this paper, an integrated procedure was adopted to obtain accurate lithofacies
classification to be incorporated with well log interpretations for a precise core permeability …
classification to be incorporated with well log interpretations for a precise core permeability …
A Review of Phase Behavior Mechanisms of CO2 EOR and Storage in Subsurface Formations
The emissions of CO2 have been recognized as the main cause of climate change. As an
important strategy being used to reduce the CO2 concentration in the atmosphere, carbon …
important strategy being used to reduce the CO2 concentration in the atmosphere, carbon …
[HTML][HTML] Prediction of permeability and porosity from well log data using the nonparametric regression with multivariate analysis and neural network, Hassi R'Mel Field …
Most commonly, to estimate permeability, we can use values of porosity, pore size
distribution, and water saturation from logging data and established correlations. One …
distribution, and water saturation from logging data and established correlations. One …
Gas channels and chimneys prediction using artificial neural networks and multi-seismic attributes, offshore West Nile Delta, Egypt
Abstract Machine learning techniques combined with multi-seismic attributes and well logs
datasets have been successfully used in reducing the risk of drilling operations and …
datasets have been successfully used in reducing the risk of drilling operations and …
Integrating machine learning and data analytics for geostatistical characterization of clastic reservoirs
WJ Al-Mudhafar - Journal of Petroleum Science and Engineering, 2020 - Elsevier
An integrated multidisciplinary workflow of machine learning and data analytics was
conducted for the multivariate geostatistical characterization of clastic reservoirs. This …
conducted for the multivariate geostatistical characterization of clastic reservoirs. This …
Application of adaptive neuro fuzzy interface system optimized with evolutionary algorithms for modeling CO2-crude oil minimum miscibility pressure
A Karkevandi-Talkhooncheh, S Hajirezaie… - Fuel, 2017 - Elsevier
CO 2 injection is known as one of the most reliable enhanced oil recovery techniques. The
success of every gas injection process depends highly on the minimum miscibility pressure …
success of every gas injection process depends highly on the minimum miscibility pressure …
A multiple-input deep residual convolutional neural network for reservoir permeability prediction
Permeability plays an essential role in reservoir-related studies, including fluid flow
characterization, reservoir modeling/simulation, and management. However, operational …
characterization, reservoir modeling/simulation, and management. However, operational …