Evaluation of Organic Matter, Hydrocarbon Source, and Depositional Environment of Onshore Warkalli Sedimentary Sequence from Kerala-Konkan Basin, South India

Mathews, Runcie P.; Singh, Bhagwan D.; Singh, Vikram P.

doi:10.1007/s12594-018-1035-2

Cited by 10 publications

(1 citation statement)

References 73 publications

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“…The field of petroleum geology involves the identification and quantification of organic matter in laminae [2][3][4], widely adopting the methods used in organic petrology to identify different macerals [5,6]. The characteristics and maturity of insoluble organic matter are utilized in related research on organic matter sources, types, sedimentary environment, and resource evaluation [7][8][9][10]. However, the quantitative analysis of macerals is usually performed manually [11,12], which relies on the standards established by the International Committee for Coal and Organic Petrology [13] and American Society for Testing and Materials standard D2799-13 (2013) [14].…”

Section: Introductionmentioning

confidence: 99%

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

Fan

Liu

et al. 2022

Applied Sciences

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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.

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