… on SEM images within a predictive framework for permeability estimation are lacking. In
order to close this gap, we introduce a deep learning (DL) algorithm for the direct prediction of …

… of various machine learning algorithms for the prediction of … alteration of porosity and
permeability after reservoir desalination … First, we estimate salts concentrations with corresponding …

… a robust hybrid GA-WNN algorithm possessing the benefit of optimized parameters and
number of neurons and is capable of estimating the permeability of reservoirs from well log data …

… learning algorithm, via the use of multiple networks and the generation of virtual samples (see
later sections), to estimate permeability … core permeability to provide multiple permeability …

… This indirect measurement data is assimilated into process models (eg, through parameter
estimation algorithms) to estimate permeability. A significant advantage of such non-invasive …

… and ANN output is 0.85 while this parameter between core permeability and GA_ANN output
is 0.99). Accordingly, the genetically trained network is able to predict/estimate permeability …

… learning methods have proven to resolve the issues encountered during reservoir permeability
estimation. … the subject of machine learning algorithms used to predict permeability of a …

… machine learning methods including conventional artificial neural network, genetic algorithm…
of hybridized machine learning methods in porosity and permeability estimations can lead …

… algorithms or kriging) to estimate permeability between wells across large areas. This …
Machine learning methods described in this paper can aid in estimating permeability values using …

… and genetic algorithms for the prediction of permeability in tight … more reliable way to estimate
the permeability of very tight … learning techniques for the estimation of the permeability of …