Abstract
Gravimetry is a physical method with a large depth of investigation. Traditional applications include surface gravity observations for mining and oil exploration and borehole gravity logging for investigating formation bulk density.
A new application of gravimetry is large-scale reservoir saturation monitoring. Replacement of oil or gas by water leads to density changes in large volumes of the reservoir, which causes changes of the gravity field down hole as well as on the surface. Since borehole gravity sensors are closer to the reservoir than for surface acquired gravity data, borehole gravity data has better spatial resolution and are less affected by near surface changes.
This paper focuses on the problems of inversion of time-lapse gravity data for complex multilayered reservoirs and estimation of the accuracy of the reconstructed oil-water flood front. The traditional bitmap approach (dividing the reservoir into blocks) requires a huge number of parameters and leads to the well-known inversion ambiguity. This ambiguity can be reduced by introducing a priori information.
The basic idea of the presented approach is to obtain this a priori information by biasing the inversion with output from a history matched reservoir simulation data set. In this case, reservoir simulation saturation data from an onshore giant Middle Eastern oil field was used as input. By processing the simulation saturation data, it was possible to understand the behavior of the water saturation and oil-water flood front in the different layers of the reservoir. Using this knowledge, a 3D model of density changes was introduced. This model formed the basis of the optimization inversion algorithm used to fine-tune the actual location of the oil-water flood front on the basis of gravity data.
Numerical examples demonstrate how inversion and accuracy estimates work for data obtained from a realistic reservoir simulation. The proposed inversion technique will depict any differences from the history matched reservoir simulation saturation output and the gravity data; thus, the gravity data will allow enhanced precision of the reservoir simulation history match.
