[1]
A.A. Konaté, H. Pan, H. Ma, X. Cao, Y.Y. Ziggah, Oloo M, N. Khan, Application of dimensionality reduction technique to improve geo-physical log data classification performance in crystalline rocks, Journal of Petroleum Science and Engineering 133 (2015) 633-645.
DOI: 10.1016/j.petrol.2015.06.035
Google Scholar
[2]
C.M. Gifford, A. Agah, Collaborative multi-agent rock facies classification from wireline well log data, Engineering Applications of Artificial Intelligence 23 (2010) 1158–1172.
DOI: 10.1016/j.engappai.2010.02.004
Google Scholar
[3]
H.C. Chang, D.C. Kopaska-Merkel, H.C. Chen, Identification of lithofacies using Kohonen self-organizing maps, Computers & Geosciences 28 (2002) 223–229.
DOI: 10.1016/s0098-3004(01)00067-x
Google Scholar
[4]
W.J. Al-Mudhafar, Integrating well log interpretations for lithofacies classification and permeability modeling through advanced machine learning algorithms, J Petrol Explor Prod Technol 7 (2017) 1023–1033.
DOI: 10.1007/s13202-017-0360-0
Google Scholar
[5]
A. Kadkhodaie, R. Rezaee, Intelligent sequence stratigraphy through a wavelet-based decomposition of well log data, Journal of Natural Gas Science and Engineering (2017).
DOI: 10.1016/j.jngse.2017.02.010
Google Scholar
[6]
P. Kraipeerapun, C.C. Fung, K.W. Wong, Lithofacies classification from well log data using neural networks, interval neutrosophic sets and quantification of uncertainty, International Journal of Mathematical and Computer Sciences 3:1 (2007) 28-32.
DOI: 10.1109/icnc.2007.359
Google Scholar
[7]
I.Y. Tian, H. Xu, X.Y. Zhang, H.J. Wang, T.C. Guo, L.J. Zhang, X.L. Gong, Multi-resolution graph-based clustering analysis for lithofacies identification from well log data: Case study of intraplatform bank gas fi elds, Amu Darya Basin, Applied Geophysics 13(4) (2016) 598-607.
DOI: 10.1007/s11770-016-0588-3
Google Scholar
[8]
S. Maiti, R.K. Tiwari, H.J. Kumpel, Neural network modelling and classification of lithofacies using well log data: a case study from KTB borehole site, Geophys. J. Int. 169 (2007) 733–746.
DOI: 10.1111/j.1365-246x.2007.03342.x
Google Scholar
[9]
L. Qi, T.R. Carr, Neural network prediction of carbonate lithofacies from well logs, Big Bow and Sand Arroyo Creek fields, Southwest Kansas, Computers & Geosciences 32 (2006)947-964.
DOI: 10.1016/j.cageo.2005.10.020
Google Scholar
[10]
H.J. Yang, H.P. Pan, H. Ma, A.A. Konate, J. Yao, B. Guo, Performance of the synergetic wavelet transform and modified K-means clustering in lithology classification using nuclear log, Journal of Petroleum Science and Engineering (2016).
DOI: 10.1016/j.petrol.2016.02.031
Google Scholar
[11]
D.R. Velis, Statistical segmentation of geophysical log data, Math Geol 39 (2007) 409–417.
DOI: 10.1007/s11004-007-9103-y
Google Scholar
[12]
M. Banesh, The determination of lithofacies using an optimized neural network and well log Data, Petroleum Science and Technology 32 (2014) 897–903.
DOI: 10.1080/10916466.2011.604056
Google Scholar