Enhancing machine learning-based seismic facies classification through attribute selection: application to 3D seismic data from the Malay and Sabah Basins, offshore Malaysia

Abstract Over the past few years, the use of machine learning has gained considerable momentum in many industries, including exploration seismic. While supervised machine learning is increasingly being used in seismic data analysis, some obstacles hinder its widespread application. Seismic facies cl...

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Главные авторы:	Ismailalwali Babikir, Abdul Halim Abdul Latiff, Mohamed Elsaadany, Hadyan Pratama, Muhammad Sajid, Salbiah Mad Sahad, Muhammad Anwar Ishak, Carolan Laudon
Формат:	Artigo
Язык:	Inglês
Опубликовано:	Springer 2024-08-01
Серии:	Geomechanics and Geophysics for Geo-Energy and Geo-Resources
Предметы:	Seismic attributes Seismic facies classification Attribute selection Supervised machine learning Model performance
Online-ссылка:	https://doi.org/10.1007/s40948-024-00846-x
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