Predicting porosity logs from seismic attributes using geostatistics

Natalia Soubotcheva and Robert R. Stewart

ABSTRACT

At Pikes Peak, the Lower Cretaceous Waseca Formation, about 450 m below the surface, is the producing reservoir. The Waseca is filled with a homogeneous sand unit, an interbedded sand and shale unit, and a capping shale unit. These sands exhibit lithological variation, which affects the porosity distribution. After a proper well-to-seismic tie, we are able to analyze sample-based seismic attributes and select the most reliable ones using cross-validation. Effective porosity logs and various seismic attributes from PP and PS seismic data were used as inputs for porosity prediction. We have found that a probabilistic neural network showed the highest crosscorrelation (86%) between actual and predicted porosity logs at seven wells in the study area. After validation, the predicted volume of porosity along a 2-D seismic line was displayed. This final section provides a geologically realistic porosity distribution and helps in understanding the subsurface image.

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