Dec 20, 2021 · In this article, we present the attempt to predict the lithofacies by feeding logging segments, and for the first time model the logging ...

This article presents the attempt to predict the lithofacies by feeding logging segments, and for the first time model the logging lith ofacies ...

SegLog consists of a backbone. U-Net module and a statistics-guided pixel enhancement (SPE) module. The. U-Net learns the semantic similarity of the loggings, ...

To solve these challenges, we propose a novel geophysical logging segmentation network entitled SegLog. Specifically, we develop a global statistics pooling sub ...

Sep 2, 2024 · In this paper, we propose a semi-supervised learning method with feature learning capability based on semi-supervised generative adversarial network (SSGAN)

SegLog: Geophysical Logging Segmentation Network for Lithofacies Identification · Unilateral Alignment: An interpretable machine learning method for geophysical ...

SegLog: Geophysical logging segmentation network for lithofacies identification. IEEE Transactions on Industrial Informatics, 2021, 18(9): 6089-6099 ...

SegLog: Geophysical Logging Segmentation Network for Lithofacies Identification ... Identifying borehole lithofacies through geophysical loggings is a ...

A ramified lithology identification model based on neural network (CNN) and bi-directional long short-term memory (Bi-LSTM) is established to solve the problem ...

SegLog: Geophysical Logging Segmentation Network for Lithofacies Identification. IEEE Trans. Ind. Informatics 18(9): 6089-6099 (2022). [+][–]. Coauthor network.