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 classification—a crucial aspect in this field—particularly faces challenges such as the selection of appropriate input attributes. Plethora of seismic attributes have been created over the years, and new ones are still coming out. Yet, several have been deemed redundant or geologically meaningless. In... Mehr ...