Details

Title

Neural Networks In Mining Sciences – General Overview And Some Representative Examples

Journal title

Archives of Mining Sciences

Yearbook

2015

Issue

No 4

Authors

Divisions of PAS

Nauki Techniczne

Publisher

Committee of Mining PAS

Date

2015[2015.01.01 AD - 2015.12.31 AD]

Identifier

DOI: 10.1515/amsc-2015-0064 ; ISSN 0860-7001

Source

Archives of Mining Sciences; 2015; No 4

References

Silva (2015), Artificial neural networks to support petrographic classification of carbonate - siliciclastic rocks using well logs and textural information of vol, Journal Applied Geophysics, 118, doi.org/10.1016/j.jappgeo.2015.03.027 ; Asoodeh (2015), The Estimation of Stoneley Wave Velocity from Conventional Well Log Data : Using an Integration of Artificial Neural Networks Part A Utilization , and Environmental Effects ) vol no, Energy Sources Recovery, 3, 309, doi.org/10.1080/15567036.2011.585383 ; Wonseok (2014), Development and application of the artificial neural network based technical screening guide system to select production methods in a coalbed methane reservoir - Exploration - and - Exploitation, Energy, 32, 791. ; Aliouane (2013), Fractal analysis based on the continuous wavelet transform and lithofacies classification from well - logs data using the self - organizing map neural network of Geosciences, Arabian Journal, 6, 1681, doi.org/10.1007/s12517-011-0459-4 ; Morshedi (2014), The simulation of microbial enhanced oil recovery by using a two - layer perceptron neural network and Technology vol no, Petroleum Science, 22, 2700, doi.org/10.1080/10916466.2011.572106 ; Konate (2015), Capability of self - organizing map neural network in geophysical log data classification : Case study from the CCSD - MH of vol, Journal Applied Geophysics, 37, doi.org/10.1016/j.jappgeo.2015.04.004 ; Ghiasi Freez (2012), The Application of Committee Machine with Intelligent Systems to the Prediction of Permeability from Petrographic Image Analysis and well logs Data : a case Study from the South pars gas Field South Iran and Technology, Petroleum Science, 30, 20. ; Olatunji (2013), Extreme Learning Machines Based Model for Predicting Permeability of Carbonate Reservoir of Digital Content Technology and its Applications, International Journal, 7, 450. ; Nooruddin (2014), Using soft computing techniques to predict corrected air permeability using Thomeer parameters air porosity and grain density Computers vol, Geosciences, 72. ; Wei Zheng (2014), Complex lithology automatic identification technology based on fuzzy clustering and neural networks th International Conference on Fuzzy Systems and Knowledge Discovery, IEEE, 227. ; Wei (2014), An effective detection method based on IPSO - WNN for acoustic telemetry signal of well logging while drilling International - Conference - on - Information - Electronics - and - Electrical - Engineering - ISEEE, Science, 49. ; Li Yang (2012), Application of factor neural network in multi - expert system for oil - gas reservoir protection of Theoretical and Applied Information Technology, Journal, 46, 303. ; Ghiasi (2015), Rigorous models to optimise stripping gas rate in natural gas dehydration units, Fuel, 140.
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