Tombua Reservoir Modeling
: Using MPS to
Facilitate Geologically Robust Connectivity
Beeson, Dale1, Ricardo Van-Deste2, Sebastien Strebelle3 (1) ChevronTexaco, Bellaire, TX (2) Sonangol, Luanda, Angola (3) ChevronTexaco, San Ramon, CA
The Tombua field was discovered with
the Tombua-1 well bore in 2001. It is part of the Tombua-Landana
project which is a major CVX-lead deepwater development encompassing 470 square
kilometers in
Tombua reservoir modeling
relies heavily upon
seismic
imaging to help predict and spatially distribute the reservoir
properties. A principal component (PCA) workflow is used to predict volume
shale which is then transformed into reservoir PKS values. Tombua
modeling is heavily dependant upon the
seismic
imaging for conditioning the
spatial distribution of reservoir properties. However, where reservoir sands
are poorly imaged by the
seismic
data, especially the thinner channel sands at
depth, difficulty arises in
modeling
reservoir body continuity/connectivity
using conventional variogram-based geostatistical simulation methods.
Model variograms represent “nearest neighbor” measures for
guiding channel simulations and are dependant upon the seismic
imaging. When
the channel continuity is poorly imaged, the geostatistical
simulation continuity suffers. Variogram-based models
for the thinner channel sands are often poorly connected even though our
geologic analog data as well as much of our
seismic
imaging suggest more connected
solutions. Since reserves are largely a function of producibility
via reservoir connectivity, this is a significant concern. Our solution has
been to incorporate geologically robust channel training images using
Multi-Point Statistics (MPS) to develop much improved model-based connectivity.