期刊
JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING
卷 78, 期 1, 页码 119-130出版社
ELSEVIER SCIENCE BV
DOI: 10.1016/j.petrol.2011.05.010
关键词
TOC; Gadvan Formation; South Pars field; geochemistry; intelligent systems; Delta LogR technique
资金
- NIOC
- Petro Pars
Potentially, TOC content is affected by logging data in a source rock (density, sonic, neutron and resistivity logs). Hence, to analyze these logs, which we make a quick and reliable assessment of a source rock. So, it is a quick and economically cheaper method rather than direct geochemical analysis. A source rock interval poses to less density, lower velocity, higher sonic porosity, higher gamma ray values and increase in resistivity. In this research, Gadvan Formation was studied in two boreholes as potential of source rock. The log data of two wells were used to construct of intelligent models in a source rock of the South Pars Gas field in southwest of Iran. A suite of geophysical logs (neutron, density, sonic and resistivity logs) and cutting chip data samples data were applied for determining TOC content of this formation. Rock-Eval pyrolysis data reveal that Gadvan Formation is poor source rock (less than 0.5%). Hence we attempted a correlation between geophysical data and direct TOC content measurements of using Delta Log R, Rock-Eval, neural network and fuzzy logic techniques. The results showed that intelligent models were successful for prediction of TOC content from conventional well logs data. Meanwhile, similar responses from other different intelligent methods indicated that their validity for solving complex problems. (C) 2011 Elsevier B.V. All rights reserved.
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