K-means clustering using principal component analysis to automate label organization in multi-attribute seismic facies analysis

USING MACHINE LEARNING AS AN AID TO SEISMIC GEOMORPHOLOGY, WHICH ATTRIBUTES ARE THE BEST INPUT?

(2019) Lennon Infante-Paez et al.   Interpretation-A Journal of Subsurface Characterization

Unsupervised seismic facies classification applied to a presalt carbonate reservoir, Santos Basin, offshore Brazil

(2019) Danilo Jotta Ariza Ferreira et al.   AAPG BULLETIN

A nonparametric approach using clustering analysis to estimate shaliness in shaly-sand formations

(2019) Alexsandro Guerra Cerqueira et al.   JOURNAL OF APPLIED GEOPHYSICS

SEISMIC FACIES ANALYSIS USING MACHINE-LEARNING

(2018) T. Wrona et al.   GEOPHYSICS

Unsupervised machine learning algorithm for detecting and outlining surface waves on seismic shot gathers

(2018) Keyao Xia et al.   JOURNAL OF APPLIED GEOPHYSICS

Multi-attribute k-means clustering for salt boundary delineation from 3D seismic data

(2018) Haibin Di et al.   GEOPHYSICAL JOURNAL INTERNATIONAL

Characterizing a turbidite system in Canterbury Basin, New Zealand, using seismic attributes and distance-preserving self-organizing maps

(2016) Tao Zhao et al.   Interpretation-A Journal of Subsurface Characterization

Geologic pattern recognition from seismic attributes: Principal component analysis and self-organizing maps

(2015) Rocky Roden et al.   Interpretation-A Journal of Subsurface Characterization

A comparison of classification techniques for seismic facies recognition

(2015) Tao Zhao et al.   Interpretation-A Journal of Subsurface Characterization

Using support vector regression to estimate sonic log distributions: A case study from the Anadarko Basin, Oklahoma

(2013) Constantin Cranganu et al.   JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING