One of the goals of reservoir characterization, particularly in mature reservoirs, is to identify unswept regions containing high oil saturation for targeted infill drilling or enhanced recovery. A common approach to the problem is to generate high resolution distribution of reservoir properties such as permeability and porosity and then conduct flow simulations to identify regions of high oil saturation. One possible alternative to flow simulations would be to generate spatial distribution of properties that are related to fluid saturations and then infer fluid saturation distribution through the use of appropriate correlations.

In this paper we present a field application to infer interwell water saturation distribution by combining cross-well seismic and well data. First, we use a non-parametric transformational approach to correlate sonic velocity with resistivity and porosity at the wells. An iterative procedure using alternating conditional expectations (ACE) forms the basis for this calibration. Next, stochastic cosimulation is carried out to generate conditional realizations of resistivity and porosity in the interwell region. In this cosimulation, cross-well seismic velocity is considered as the secondary data while resistivity and porosity are treated as primary data. Finally, water saturation distribution is deduced from the resistivity and porosity distributions through the use of Archie's law.

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