Convolutional Neural Networks and Image Patches for Lithological Classification of Brazilian Pre-Salt Rocks

Mateus Roder, Leandro Passos, Clayton Pereira, João Papa, Altanir Mello Junior, Marcelo Fagundes de Rezende, Yaro Silva, Alexandre Vidal

2024

Abstract

Lithological classification is a process employed to recognize and interpret distinct structures of rocks, providing essential information regarding their petrophysical, morphological, textural, and geological aspects. The process is particularly interesting regarding carbonate sedimentary rocks in the context of petroleum basins since such rocks can store large quantities of natural gas and oil. Thus, their features are intrinsically correlated with the production potential of an oil reservoir. This paper proposes an automatic pipeline for the lithological classification of carbonate rocks into seven distinct classes, comparing nine state-of-the-art deep learning architectures. As far as we know, this is the largest study in the field. Experiments were performed over a private dataset obtained from a Brazilian petroleum company, showing that MobileNetV3large is the more suitable approach for the undertaking.

Paper Citation

in Harvard Style

Roder M., Passos L., Pereira C., Papa J., Mello Junior A., Fagundes de Rezende M., Silva Y. and Vidal A. (2024). Convolutional Neural Networks and Image Patches for Lithological Classification of Brazilian Pre-Salt Rocks. In Proceedings of the 19th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: VISAPP; ISBN 978-989-758-679-8, SciTePress, pages 648-655. DOI: 10.5220/0012429100003660

in Bibtex Style

@conference{visapp24,
author={Mateus Roder and Leandro Passos and Clayton Pereira and João Papa and Altanir Mello Junior and Marcelo Fagundes de Rezende and Yaro Silva and Alexandre Vidal},
title={Convolutional Neural Networks and Image Patches for Lithological Classification of Brazilian Pre-Salt Rocks},
booktitle={Proceedings of the 19th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: VISAPP},
year={2024},
pages={648-655},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012429100003660},
isbn={978-989-758-679-8},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 19th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: VISAPP
TI - Convolutional Neural Networks and Image Patches for Lithological Classification of Brazilian Pre-Salt Rocks
SN - 978-989-758-679-8
AU - Roder M.
AU - Passos L.
AU - Pereira C.
AU - Papa J.
AU - Mello Junior A.
AU - Fagundes de Rezende M.
AU - Silva Y.
AU - Vidal A.
PY - 2024
SP - 648
EP - 655
DO - 10.5220/0012429100003660
PB - SciTePress