Research on logging evaluation method of TOC content of shale gas reservoir in A area
Online published: 2014-06-06
Total organic carbon（TOC） content of shale gas reservoir reflects the hydrocarbon generation potential of shale rocks. It has an important guiding significance for shale gas development to obtain the TOC content accurately by use of conventional logging data which has characteristics of continuousness and high vertical resolution. Therefore, it is especially important to establish highly precise model of the organic carbon content evaluation. Combining the limiting factors of TOC content evaluation methods with the reality of complex lithological changes of A area, we established three kinds of TOC content models to evaluate shale rocks from X well in A area. They are BP neural network, uranium and kerogen. It is concluded that the BP neural network model is with the highest precision to forecast the total organic carbon content, and provide technical support to TOC content evaluation in complex lithology areas.
Key words： Carboniferous; volcanic rock; reservoir; influencing factors; Junggar Basin
LIU Shuangquan , CAO Yuanting , ZHAO Guangliang , ZHU Jun , SHI Ji’an , ZHANG Shuncun . Research on logging evaluation method of TOC content of shale gas reservoir in A area[J]. Lithologic Reservoirs, 2014 , 26(3) : 74 -78 . DOI: 10.3969/j.issn.1673-8926.2014.03.012
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