Quantitative Study of the Maceral Groups of Laminae Based on Support Vector Machine

Identifying organic matter in laminae is fundamental to petroleum geology; however, many factors restrict manual quantification. Therefore, computer recognition is an appropriate method for accurately identifying microscopic components. In this study, we used support vector machine (SVM) to classify...

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Bibliographic Details
Published in:Applied sciences 2022-09, Vol.12 (18), p.9046
Main Authors: Wu, Yuanzhe, Fan, Yunpeng, Liu, Yan, Li, Kewen, Zeng, Tingxiang, Ma, Yong, Tian, Yongjing, Xu, Yaohui, Wen, Zhigang, Xie, Xiaomin, Teng, Juan
Format: Article
Language:English
Subjects:
Accuracy
Algorithms
Classification
Geology
laminae
Laminates
Light
Macerals
Machine learning
Methods
Micrography
Minerals
Organic matter
organic petrology
Petroleum geology
Petrology
Photomicrographs
Quantitative analysis
Software
Statistical analysis
Statistics
Support vector machines
SVM
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Summary:Identifying organic matter in laminae is fundamental to petroleum geology; however, many factors restrict manual quantification. Therefore, computer recognition is an appropriate method for accurately identifying microscopic components. In this study, we used support vector machine (SVM) to classify the preprocessed photomicrographs into seven categories: pyrite, amorphous organic matter, mineral matter, alginite, sporinite, vitrinite, and inertinite. Then, we performed a statistical analysis of the classification results and highlighted spatial aggregation of some categories using the kernel density estimation method. The results showed that the SVM can satisfactorily identify the macerals and minerals of the laminae, and its overall accuracy, kappa, precision, recall, and F1 are 82.86%, 0.80, 85.15%, 82.86%, and 82.75%, respectively. Statistical analyses revealed that pyrite was abundantly distributed in bright laminae; vitrinite and sporinite were abundantly distributed in dark laminae; and alginite and inertinite were equally distributed. Finally, the kernel density maps showed that all classification results, except inertinite, were characterized by aggregated distributions: pyrite with the distribution of multi-core centers, alginite, and sporinite with dotted distribution, and vitrinite with stripe distribution, respectively. This study may provide a new method to quantify the organic matter in laminae.
ISSN:2076-3417
2076-3417
DOI:10.3390/app12189046