Improving
Net-to-Gross Reservoir Estimation with Small-Scale Geological Modeling
Phillips, Peter1, Renjun Wen1 (1) Geomodeling
Technology Corp,
Geoscientists have often been frustrated
by the arbitrary assignment of petrophysical log
cut-offs to define reservoir intervals capable of hosting producible
hydrocarbon. The traditional practice is to derive
"pseudo-permeability" from well logs such as gamma ray, density, and
sonic. However, this indirect approach can introduce large errors in estimates
of net-to-gross reservoir and, hence, reserve volumes.
We introduce a method for improving the
accuracy of net-to-gross reservoir estimation with a small-scale geological
modeling and upscaling approach. The first step is to
generate cm- to dm-scale geological models for representative flow units in a
well interval. The approach combines stochastic and deterministic modeling
methods to mimic the sedimentary processes behind siliciclastic
deposition. The resulting 3D models accurately simulate bedding structures
observed in core and outcrop, and capture the geological heterogeneities that
impact fluid flow.
The second step is to populate the
resulting "digital rock models" with porosity and permeability values
derived from core. Finally, by applying flow-based upscaling
algorithms, we upscale the models to the well-log scale and calibrate modeled permeabilities to core and log data. The upscaling output includes facies-dependent
property values that honor both core measurements and small-scale heterogeneities
observed at core scale. The resulting property models provide a scientifically
sound basis for calculating net reservoir. The modeling and upscaling
approach was applied to a reservoir characterization study to identify net
reservoir below the resolution of conventional petrophysical
logs. The results helped to resolve major discrepancies between the static and
dynamic reservoir model.
AAPG Search and Discover Article #90063©2007 AAPG Annual Convention, Long Beach, California