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RISS 인기검색어
- 검색키워드
- 저자 : Fatemeh Alimadadi (검색결과 1 건)
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Amin Fakhri,Mohammadhassan Behroozi,Fatemeh Alimadadi,Hossein Sadati 제어로봇시스템학회 2008 제어로봇시스템학회 국제학술대회 논문집 Vol.2008 No.10
Obtaining physical reservoir characteristics is extremely important and necessary to determine the correlations, productions and field development. Reservoir characteristics include porosity, permeability, cementation, and the like which are obtained from petrophysic and petrographic analyses. From these properties porosity is the most important static property of petroleum reservoirs that can be used to perceive permeability, fluid behaviors, capillary pressure, and sedimentological interpretations. One of the goals of prediction, accomplished in this paper, is to find out the missed porosity logs to interpret a gas reservoir in the well due to available and suitable petrophysical logs gathered from near wells. In some wells, we cannot measure a number of petrophysical properties whereas wells are maybe washed out or the borehole tools are not available for old wells. Therefore, petroleum geologist should pursue some methods to transfer accessible data into faulty wells. It means that they predict missed data using information which is available in its near wells. For prediction purposes of this property, “esistivity Logs” “amma Ray Log” and “onic Log”will have to be used as input information. The relationships of porosity logs versus the logs mentioned above are absolutely nonlinear. Soft computing methods are one of the powerful approaches used to identify lost data.
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