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When dealing with seismic and well data interpreters often face certain challenges characteristic of both data types. Well data is very detailed vertically and gives rich detail in specific locations, but the rest of the field remains unknown at that level of detail. Seismic data is almost nearly the opposite; it provides very good resolution laterally, but is much less detailed vertically and typically doesn’t provide a direct measurement of physical properties of interest. Combining both data types, geologic models capable of filling in the gaps between seismic and well data sets have become exceedingly valuable. In this investigation we studied a number of uncertainty reducing workflows associated with both forward and inverse modeling techniques. How can we make predictions as to what attributes will uniquely discriminate between reservoir and non-reservoir rocks and fluids with confidence? Forward modeling of geophysical data uses well-defined geological models to calculate specific seismic field responses. Using available log data combined with geologically reasonable model constraints, geomodelers may construct a number of modeled seismic responses that can be used to validate or annul various working geologic models. In contrast, geophysical inverse modeling techniques attempt to construct a physical property model based off a geophysical response.

Reducing Geologic Uncertainty in Seismic Interpretation: Case Study of Lower Mannville Channels in Western Canadian Sedimentary Basin