Unsupervised Machine Learning Applied to Seismic Interpretation: Towards an Unsupervised Automated Interpretation Tool

Unsupervised Machine Learning Applied to Seismic Interpretation: Towards an Unsupervised Automated Interpretation Tool

Seismic interpretation is a fundamental process for hydrocarbon exploration. This activity comprises identifying geological information through the processing and analysis of seismic data represented by different attributes. The interpretation process presents limitations related to its high data vo...

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Bibliographic Details
Main Authors: Alimed Celecia, Karla Figueiredo, Carlos Rodriguez, Marley Vellasco, Edwin Maldonado, Marco Aurélio Silva, Anderson Rodrigues, Renata Nascimento, Carla Ourofino
Format: Article
Language:English
Published: MDPI AG 2021-09-01
Series:Sensors
Subjects:
unsupervised machine learning
seismic interpretation
image segmentation
well logs clustering
Online Access:https://www.mdpi.com/1424-8220/21/19/6347

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