Compartmentalization and spatial variations of fluid composition are two primary factors that cause major and expensive differences between predicted and actual performance in the oil field. Fluid compositional variations must be considered in order to acquire fluid samples representative of the reservoir at large, not just of local fluid properties. With detailed fluid knowledge, optimal production strategies and facilities can be devised. In addition, fluid compositional variations can be utilized as a tool to identify compartmentalization because different compartments are likely to be filled with different fluids. The difficulty in the past has been the need to rationalize the process of wireline sample acquisition and lab analysis for only necessary samples. In this paper, Downhole Fluid Analysis (DFA is shown to be the ?missing link,? providing the information necessary to optimize the sampling process and to decide in real time on where sampling is necessary. Decisions can be made early in the sample clean-up phase. In addition, DFA is shown to identify compartmentalization via fluid signature comparisons, sometimes subtle enough to be missed by pressure gradients yet detectable by DFA. Corroborations with vertical pressure interference measurements confirm the methodology. Another byproduct of the DFA is identification of compartments via fluid density inversion. Furthermore, it is shown that DFA is essential for proper sample acquisition of (nearly saturated condensates. DFA is a powerful new tool addressing primary technical concerns for improving the prediction of production.
Identification of vertical compartmentalization and fluid compositional variations enabled by downhole fluid analysis; Case studies.
Mullins, Oliver C., Elshahawi, Hani, Hashem, Mohamed, and Go Fujisawa. "Identification of vertical compartmentalization and fluid compositional variations enabled by downhole fluid analysis; Case studies.." Paper presented at the SPWLA 46th Annual Logging Symposium, New Orleans, Louisiana, June 2005.
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