DocumentCode
554015
Title
A fuzzy evaluation approach to oil/gas reserves analysis
Author
Cheng Shiqing ; Yu Haili ; Zhou Anquan
Author_Institution
MOE Key Lab., China Univ. of Pet. Beijing, Beijing, China
Volume
1
fYear
2011
fDate
26-28 July 2011
Firstpage
9
Lastpage
12
Abstract
It has been observed that reservoir stochastic modeling technology, which makes uses of the reserve´s parameters in stochastic model, solves the problem that the parameters are difficult to determine in complex reservoirs using traditional volumetric method. The approach, yet, without considering the inherent uncertainty of porosity, oil saturation and net gross ratio, can not determine the factors that play a leading role and evaluate the scale of influences on reserve calculation. In this paper, several sets of reserve calculation scenarios are presented based on the geological attributes of wells of X Oil Field. Using gray association analysis method to determine the reasonable petrophysical parameters, the optimal combinations of the influential factors involved in the calculation are used to compare relevance degrees of different programs. This paper resolves the ambiguity in the process of reserves estimation, following the quantitative assessment of effect of parameters uncertainty on reserve calculation. All we have attempted to achieve is to reduce risks and provide reliable basis in the decision-making of oil reservoir exploration and development.
Keywords
decision making; fuzzy set theory; gas industry; hydrocarbon reservoirs; oil technology; stochastic processes; X oil field; complex reservoir; decision making; fuzzy evaluation; gas reserves analysis; geological attribute; gray association analysis method; oil reserves analysis; oil reservoir exploration; petrophysical parameter; reserve calculation; reserves estimation; reservoir stochastic modeling technology; volumetric method; wells; Analytical models; Correlation; Geology; Petroleum; Reservoirs; Stochastic processes; Uncertainty; fuzzy evaluation; grey correlation; oil reserves; reservoir stochastic modeling; volumetric method;
fLanguage
English
Publisher
ieee
Conference_Titel
Natural Computation (ICNC), 2011 Seventh International Conference on
Conference_Location
Shanghai
ISSN
2157-9555
Print_ISBN
978-1-4244-9950-2
Type
conf
DOI
10.1109/ICNC.2011.6022134
Filename
6022134
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