Uncertainty evaluation through ranking of simulation models for bozova oil field

Tonga, Melek Mehlika
Producing since 1995, Bozova Field is a mature oil field to be re-evaluated. When evaluating an oil field, the common approach followed in a reservoir simulation study is: Generating a geological model that is expected to represent the reservoir; building simulation models by using the most representative dynamic data; and doing sensitivity analysis around a best case in order to get a history-matched simulation model. Each step deals with a great variety of uncertainty and changing one parameter at a time does not comprise the entire uncertainty space. Not only knowing the impact of uncertainty related to each individual parameter but also their combined effects can help better understanding of the reservoir and better reservoir management. In this study, uncertainties associated only to fluid properties, rock physics functions and water oil contact (WOC) depth are examined thoroughly. Since sensitivity analysis around a best case will cover only a part of uncertainty, a full factorial experimental design technique is used. Without pursuing the goal of a history matched case, simulation runs are conducted for all possible combinations of: 19 sets of capillary pressure/relative permeability (Pc/krel) curves taken from special core analysis (SCAL) data; 2 sets of pressure, volume, temperature (PVT) analysis data; and 3 sets of WOC depths. As a result, historical production and pressure profiles from 114 (2 x 3 x 19) cases are presented for screening the impact of uncertainty related to aforementioned parameters in the history matching of Bozova field. The reservoir simulation models that give the best match with the history data are determined by the calculation of an objective function; and they are ranked according to their goodness of fit. It is found that the uncertainty of Pc/krel curves has the highest impact on the history match values; uncertainty of WOC depth comes next and the least effect arises from the uncertainty of PVT data. This study constitutes a solid basis for further studies which is to be done on the selection of the best matched models for history matching purposes.


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Citation Formats
M. M. Tonga, “Uncertainty evaluation through ranking of simulation models for bozova oil field,” M.S. - Master of Science, Middle East Technical University, 2011.