--> Porosity Prediction by Integration of Sedimentology and Burial History Data: Application to the Norwegian Sector of the North Sea, by R. W. Lahann, H. E. Clifton, A. Skjervoy, and I. Walker; #90986 (1994).

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Abstract: Porosity Prediction by Integration of Sedimentology and Burial History Data: Application to the Norwegian Sector of the North Sea

Richard W. Lahann, H. Edward Clifton, A. Skjervoy, I. Walker

Conoco Norway combined core data with pressure and temperature histories to predict prospect porosities the 14th Norwegian License Application round. An application of the process to the Statfjord Formation in an offshore block illustrates the process. Sample descriptions from cored wells in the Norwegian sector of the Northern North Sea were used to establish textures (grain size and sorting) and porosity ranges around average values, and to evaluate the abundance and distribution of carbonate cements. Comparison of predicted and observed porosities in normally pressured control wells confirmed the porosity model. Construction of overpressure histories consistent with the burial history and current pressure regimes allowed extension of the model to overpressured control wells. Temper ture and pressure histories for prospect locations were based on regional temperature and pressure data and on seismic data for burial histories. The porosity model was then used to predict porosities for all possible textures. Sandstone grain size and sorting frequency distributions determined from core were extrapolated to prospect locations. The sandstone porosity and texture matrices were convolved to generate porosity distribution curves. Minimum productivity cut-offs were applied to the sandstone porosity distributions, yielding net-to-gross sandstone ratios. Regional core and log control was used to map gross sand percentage at prospect locations. The gross sand percentage and net-to-gross sandstone ratios were integrated with section thickness predictions from seismic data and re ional studies to estimate net pay thicknesses, net pay average, and maximum porosities. The net pay thickness and porosity predictions were used to predict well productivities.

AAPG Search and Discovery Article #90986©1994 AAPG Annual Convention, Denver, Colorado, June 12-15, 1994