relation: https://khub.utp.edu.my/scholars/16479/
title: Feature selection for seismic facies classification of a fluvial reservoir: pushing the limits of spectral decomposition beyond the routine red-green-blue color blend
creator: Babikir, I.
creator: Elsaadany, M.
creator: Hermana, M.
creator: Latiff, A.H.A.
creator: Sajid, M.
creator: Laudon, C.
description: Spectral decomposition is a powerful interpretation tool that provides superior subsurface images of channels and other thinly bedded depositional systems. The analysis of the band-limited components is commonly facilitated through the red-green-blue (RGB) blend, which is limited to three volumes at a time, primarily selected based on the interpreter preference. Fortunately, machine learning technology provides the opportunity to quantitatively use many frequency volumes. We analyze twelve spectral magnitude components using multivariate feature selection techniques. The chosen subsets of features are used to classify seismic facies of a fluvial reservoir in the Malay Basin, offshore Malaysia. We find that the subset of spectral components gives a better classification result than the whole set. The sequential forward selector and the embedded selector of random forest algorithms provide the best subset of features that differentiate the desired classes. © 2022 Society of Exploration Geophysicists and the American Association of Petroleum Geologists.
publisher: Society of Exploration Geophysicists
date: 2022
type: Conference or Workshop Item
type: PeerReviewed
identifier:   Babikir, I. and Elsaadany, M. and Hermana, M. and Latiff, A.H.A. and Sajid, M. and Laudon, C.  (2022) Feature selection for seismic facies classification of a fluvial reservoir: pushing the limits of spectral decomposition beyond the routine red-green-blue color blend.  In: UNSPECIFIED.     
relation: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85146736108&doi=10.1190%2fimage2022-3752042.1&partnerID=40&md5=3f31a7b66493610cc7cb29de6ce7cad9
relation: 10.1190/image2022-3752042.1
identifier: 10.1190/image2022-3752042.1