Predicting reservoir parameters such as lithology, porosity, permeability, and fluid saturation is essential for estimating" reserves, selecting placement of development wells, and forecasting production. To this end, new methods are presented that integrate three-dimensional (3-D) seismic data with well-log, core, and geological information and significantly improve the spatial characterization of reservoirs. Seismic data are used not only to derived detailed 3-D depth images of the reservoir geometry and faulting, but also to infer spatial and temporal variations of rock parameters relevant to production.

To illustrate the contribution of seismic data to reservoir description, we discuss a case study in the Taber area, Alberta, Canada. The reliability of an integrated reservoir description based on estimates of petrophysical properties (such as porosity and net pore volume) deterministically derived from seismic data is assessed. We compare, at two well locations, the accuracy of different projections of these parameters obtained through an integrated approach incorporating seismic information, and by a conventional approach relying solely on well log and core data. In addition, we further evaluate the validity of the seismically enhanced model by comparing results of history matching obtained from each model. This comparison highlights the importance of including seismic data at earlier stages of a field development program.

An alternate approach to extract petrophysical properties from seismic data capitalize on the existence of patterns of correlation in the data. Geostatistical techniques analyze patterns of variations using spatial correlation functions to produce detailed reservoir models consistent with both seismic and well data. Errorqualified estimates of reservoir properties are derived in keeping with uncertainties in the various measurements. These techniques are presented and also applied to the Taber data set.

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