Shale porosity and pyrite intelligent identification based on improved Unet neural network

Jiazhen Liu; Yijun Liu; Zhongtao Wang; Ke Xiong; Di Wu

doi:10.1117/12.3026477

27 March 2024 Shale porosity and pyrite intelligent identification based on improved Unet neural network

Jiazhen Liu, Yijun Liu, Zhongtao Wang, Ke Xiong, Di Wu

Proceedings Volume 13105, International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2023); 1310529 (2024) https://doi.org/10.1117/12.3026477
Event: 3rd International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2023), 2023, Qingdao, China

Abstract

Currently, AI for data image processing has been widely studied in various fields of geology; such research has been greatly improved in terms of timeliness and accuracy, but no AI application with good results has been proposed for the recognition of pores and pyrite in shale images imaged by electron microscopy. To address the problem of intelligent recognition of pores and pyrite in shale images imaged by scanning electron microscopy, this paper proposes to apply Resunet, a novel convolutional neural network combining Resnet and Unet, to the intelligent recognition of pores and pyrite in shale images, and at the same time train the Resunet model through the dataset, evaluate and test the model, and obtain the resU-net semantic segmentation model The correct rate of recognizing pyrite and shale pores reaches 96.42%; the experimental results show that resU-net has the highest recognition accuracy compared to other models in the task of recognizing pyrite and shale pores on scanning electron microscope images, and this study effectively improves the problem of intelligent recognition of pores and pyrite in shale images imaged by electron microscope.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Jiazhen Liu, Yijun Liu, Zhongtao Wang, Ke Xiong, and Di Wu "Shale porosity and pyrite intelligent identification based on improved Unet neural network", Proc. SPIE 13105, International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2023), 1310529 (27 March 2024); https://doi.org/10.1117/12.3026477

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KEYWORDS

Pyrite

Image segmentation

Data modeling

Image processing

Semantics

Convolution

Education and training

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