Alexis, C., and Tanwi, B., 2008, Integrated geological and geophysical analysis by hierarchical classification combining seismic stratigraphic and AVO attributes: Petroleum Geoscience, 14, 339–354.
Alpana, B., and Hans B., 2002, Determination of facies from well logs using modular neural networks: Petroleum Geoscience, 8, 217–228.
Bagheri, M., and Riahi, M. A., 2014, Seismic facies analysis from well logs based on supervised classification scheme with different machine learning techniques: Arabian Journal of Geosciences, 8(9), DOI 4004001/s48441-041-4934-4.
Bardini, S., Grana, D., and Maffioletti, F., 2010, 3D Geological and Seismic Modelling for Reservoir Characterization: 72nd EAGE Conference & Exhibition incorporating, Barcelona, Spain.
Dumay, J., and Fournier, F., 1988, Multivariate statistical analyses applied to seismic facies recognition: Geophysics, 53, 1151-1159.
Farzadi, P., 2006, Seismic facies analysis based on 3D multi-attribute volume classification, Dariyan Formation, SE Persian Gulf: Journal of Petroleum Geology, 8398, 443-411.
Fournier, F., Dequirez, P. Y., Macrides, G. C., and Rademakers, M., 2002, Quantitative lithostratigraphic interpretation of seismic data for characterization of the Unayzah Formation in central Saudi Arabia: Geophysics, 67, 1372-1381.
Hagan, D. C., 1982, The applications of principal component analysis to seismic data sets: Geoexploration, 20, 93–111.
Hossain, Z., and Mukerji, T., 2011, Statistical Rock Physics and Monte Carlo Simulation of Seismic Attributes for Greensand: 73rd EAGE Conference & Exhibition incorporating, Vienna, Austria.
Linari, V., Santiago, M., Pastore, C., Azbel, K., and Poupon, M., 2003, Seismic facies analysis based on 3D multi-attribute volume classification, La Palma field, Maracaibo, Venezuela: The Leading Edge, 22, 32-36.
Marroquin, I. D., Brault, J. J., and Hart, B. S., 2009, A visual data-mining methodology for seismic facies analysis: Geophysics, 74, 13-23.
Mathieu, P. G., Rice, G. W., 1999, Multivariate analysis used in the detection of stratigraphic anomalies from seismic data: Geophysics, 31, 401-444.
Matlock, R. J., McGowen, R. S., and Asimakopoulos, G., 1985, Can seismic stratigraphy problems be solved using automated pattern analysis and recognition: 55th Annual International Meeting, Society of Exploration Geophysicists, Expanded Abstracts, session S17, 7.
Paparozzi E., Grana, D., Mancini, S., and Tarchiani, C., 2011, Seismic driven probabilistic classification of reservoir facies and static reservoir modeling, 13rd EAGE Conference & Exhibition Incorporating SPE EUROPEC Vienna, Austria, May, 80440.
Saggaf, M. M., Toksoz, M. N., and Marhoon M. I., 2003, Seismic facies classification and identification by competitive neural networks: Geophysics, 92, 4321-4333, 8003.
Simaan, M. A., 1991, A knowledge-based computer system for segmentation of seismic sections based on texture: 61st Annual International Meeting, Society of Exploration Geophysicists, Expanded Abstracts, 289-292.
Taner, M. T., 2001, Seismic attributes: Recorder, 26, 48–56.
Vapnik, V., 1995, The nature of statistical learning theory, Springer- Verlag, New York, 314 pp.
Vapnik, V., 1998, Statistical Learning Theory,Wiley, New York, NY, USA.
West, B., May, S., Eastwood, J. E., and Rossen, C., 2002, Interactive seismic facies classification using textural and neural networks: The Leading Edge, 21, 1042-1049