[HTML][HTML] Comparison of machine learning methods for estimating permeability and porosity of oil reservoirs via petro-physical logs

MA Ahmadi, Z Chen - Petroleum, 2019 - Elsevier
This paper deals with the comparison of models for predicting porosity and permeability of
oil reservoirs by coupling a machine learning concept and petrophysical logs. Different …

Connectionist model predicts the porosity and permeability of petroleum reservoirs by means of petro-physical logs: application of artificial intelligence

MA Ahmadi, MR Ahmadi, SM Hosseini… - Journal of Petroleum …, 2014 - Elsevier
In this paper, a new approach based on artificial intelligence concept is evolved to monitor
the permeability and porosity of petroleum reservoirs by means of petro-physical logs at …

Applications of artificial intelligence methods in prediction of permeability in hydrocarbon reservoirs

R Gholami, A Moradzadeh, S Maleki, S Amiri… - Journal of Petroleum …, 2014 - Elsevier
Permeability is one of the critical properties of reservoir rocks that is used to describe the
ability in conducting fluids through pore spaces. This parameter cannot be simply predicted …

Petrophysical assessment and permeability modeling utilizing core data and machine learning approaches–a study from the Badr El Din-1 field, Egypt

S Farouk, S Sen, SS Ganguli, H Abuseda… - Marine and Petroleum …, 2021 - Elsevier
Reservoir petrophysical characterization involving permeability estimation in the laboratory
using core samples is time-consuming and that too accords limited coverage of the sub …

Design of neural networks using genetic algorithm for the permeability estimation of the reservoir

M Saemi, M Ahmadi, AY Varjani - Journal of Petroleum Science and …, 2007 - Elsevier
Permeability is a key parameter associated with the characterization of any hydrocarbon
reservoir. In fact, it is not possible to have accurate solutions to many petroleum engineering …

Prediction of hydrocarbon reservoirs permeability using support vector machine

R Gholami, AR Shahraki… - Mathematical Problems …, 2012 - Wiley Online Library
Permeability is a key parameter associated with the characterization of any hydrocarbon
reservoir. In fact, it is not possible to have accurate solutions to many petroleum engineering …

[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 …

B Rafik, B Kamel - Egyptian journal of petroleum, 2017 - Elsevier
Most commonly, to estimate permeability, we can use values of porosity, pore size
distribution, and water saturation from logging data and established correlations. One …

A new approach to improve neural networks' algorithm in permeability prediction of petroleum reservoirs using supervised committee machine neural network …

S Karimpouli, N Fathianpour, J Roohi - Journal of Petroleum Science and …, 2010 - Elsevier
Reservoir permeability is a critical parameter for the evaluation of hydrocarbon reservoirs.
There are a lot of well log data related with this parameter. In this study, permeability is …

Reservoir porosity and permeability estimation from well logs using fuzzy logic and neural networks

JS Lim, J Kim - SPE Asia Pacific Oil and Gas Conference and …, 2004 - onepetro.org
Petroleum reservoir characterization is a process for quantitatively describing various
reservoir properties in spatial variability using all the available field data. Porosity and …

Neuro-fuzzy system to predict permeability and porosity from well log data: A case study of Hassi R׳ Mel gas field, Algeria

T Aïfa, R Baouche, K Baddari - Journal of Petroleum Science and …, 2014 - Elsevier
Abstract Characterization of shaly sand reservoirs by well log data is a usual way of
describing oil/gas field reservoirs. Over the last few years, several studies have been …