eprintid: 20644
rev_number: 3
eprint_status: archive
userid: 1
dir: disk0/00/02/06/44
datestamp: 2026-07-21 06:29:12
lastmod: 2026-07-21 06:29:12
status_changed: 2026-07-21 06:29:12
type: article
metadata_visibility: show
creators_name: Babikir, Ismailalwali
creators_name: Abdul Latiff, Abdul Halim
creators_name: Elsaadany, Mohamed
creators_name: Pratama, Hadyan
creators_name: Sajid, Muhammad
creators_name: Mad Sahad, Salbiah
creators_name: Ishak, Muhammad Anwar
creators_name: Laudon, Carolan
title: Enhancing machine learning-based seismic facies classification through attribute selection: application to 3D seismic data from the Malay and Sabah Basins, offshore Malaysia
ispublished: pub
note: Cited by: 10; All Open Access; Gold Open Access; Green Open Access
date: 2024
publisher: Springer Science and Business Media Deutschland GmbH
official_url: https://www.scopus.com/pages/publications/85201317695?origin=resultslist
id_number: 10.1007/s40948-024-00846-x
full_text_status: none
publication: Geomechanics and Geophysics for Geo-Energy and Geo-Resources
volume: 10
number: 1
refereed: TRUE
issn: 23638419
citation:   Babikir, Ismailalwali and Abdul Latiff, Abdul Halim and Elsaadany, Mohamed and Pratama, Hadyan and Sajid, Muhammad and Mad Sahad, Salbiah and Ishak, Muhammad Anwar and Laudon, Carolan  (2024) Enhancing machine learning-based seismic facies classification through attribute selection: application to 3D seismic data from the Malay and Sabah Basins, offshore Malaysia.  Geomechanics and Geophysics for Geo-Energy and Geo-Resources, 10 (1).   ISSN 23638419