Received date: 2009-03-19
Revised date: 2009-06-09
Online published: 2009-12-10
Because of the sampling limitation in the assessment of source rock, we could obtain very limited TOC content data from actually measuring the source rock. With the fine exploration for most basins in China, the finer assessment of source rock is needed. Much attention is paid to the logging data overlaying the TOC content's variation of the source rock. The most advanced overlay method of this technique is artificial neural network. But several neural networks do not make adequate high correlativity when they overlay the TOC content of the carbonate source rock with high degree of maturity. In view of the characteristics of the source rock in the region of interest, this paper attempts a new method to overlay the TOC content, which assembles the crossplot\|sorting, fuzzy-ranking and BP neural network. Using this way to process the logging data and the data of actually measured total organic carbon in Majiagou Formation of Ordos basin, and comparing the results with the results of the ΔlogR method and the fuzzy neural network, we demonstrated that the results of this method have more correlativity with the measured value, and it is helpful for systematically knowing the developing conditions about the Low Palaeozoic source rock in Ordos basin.
Key words： Logging response model; BP neural network; Fuzzy; ranking; TOC content; Ordos basin.
GUO Long,CHEN Jian-fa,MIAO Zhong-ying . Study and Application of a New Overlay Method of the TOC Content[J]. Natural Gas Geoscience, 2009 , 20(6) : 951 -956 . DOI: 10.11764/j.issn.1672-1926.2009.06.951
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