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The AAPG/Datapages Combined Publications Database
AAPG Bulletin
Abstract
AAPG Bulletin, V.
1Manuscript received August 14, 1997; revised manuscript
received June 19, 1998; final acceptance October 5, 1998.
2Geologica, P.O. Box 8034, N-4003 Stavanger, Norway; e-mail:
[email protected]
3Statoil, 4035 Stavanger, Norway; e-mail: [email protected]
ABSTRACT
The diagenetic history is modeled from the time of deposition to present.
Compaction is modeled by an exponential decrease in intergranular volume
as a function of effective stress. The model is consistent with compaction
arising from grain rearrangement, ductile grain deformation, and brittle
failure of grains, and accounts for the effects of fluid overpressures
and stable grain packing configurations. Quartz cementation is modeled
as a precipitation-rate-controlled process according to the method of Walderhaug
(1994, 1996) and Walderhaug et al. (in press).
Input data required for a simulation include effective stress and temperature
histories, together with the composition and texture of the modeled sandstone
upon deposition. Burial history data can be obtained from basin models,
whereas sandstone composition and texture are derived from point-count
analysis of analog thin sections. Exemplar predictions are consistent with
measured porosity, intergranular volume, and quartz cement fractions for
modeled examples from the Quaternary and Tertiary of the Gulf of Mexico
Basin, the Jurassic of the Norwegian shelf, the Ordovician of the Illinois
basin, and the Cambrian of the Baltic region.
Presently available techniques for predicting quantitative reservoir
quality typically are limited in applicability to specific geographic areas
or lithostratigraphic units, or require input data that are poorly constrained
or difficult to obtain. We have developed a forward numerical model (Exemplar)
of compaction and quartz cementation to provide a general method suited
for porosity prediction of quartzose and ductile grain-rich sandstones
in mature and frontier basins. The model provides accurate predictions
for many quartz-rich sandstones using generally available geologic data
as input. Model predictions can be directly compared to routinely available
data, and can be used in risk analysis through incorporating parameter
optimization and Monte Carlo techniques.
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