Rock Classification Based on Image Processing and Neural Networks

Xin Shan Wei; Chun Long Rong; Jun Xiang Nan; Guo Jian Cheng; Ye Liu

doi:10.4028/www.scientific.net/AMM.568-570.685

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 568-570Rock Classification Based on Image Processing and...

Rock Classification Based on Image Processing and Neural Networks

Abstract:

For the identification complexity of rock microstructure, based on numerical analysis of rock section images, an automatic rock texture classification method and identification system is proposed in this paper. Digital grey image processing of rock thin section is used for features extraction, the features are then as inputs to the neural network model, the model output is the rock microstructure classification. 100 pieces of rock section images from Sulige region in Changqing Oilfield are used for the experiment; the whole dataset is randomly divided into 70 images for training datasets, 15 images for validation datasets and 15 images for testing datasets. It is shown that the correct classification rate for automatic identification of rock microstructure is about 93.3%. Therefore, the proposed method for solving geological problem is effective and can get a good identification performance for rock microstructure classification quickly and accurately.

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Periodical:

Applied Mechanics and Materials (Volumes 568-570)

Pages:

685-690

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.568-570.685

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Online since:

June 2014

Authors:

Xin Shan Wei, Chun Long Rong, Jun Xiang Nan, Guo Jian Cheng*, Ye Liu

Keywords:

Image Processing, Neural Network (NN), Rock Classification, Rock Texture

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* - Corresponding Author

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