This work presents a new approach that combines the comprehensive capabilities
of the ensemble Kalman filter (EnKF) and the flow path information from streamlines to
eliminate and/or reduce some of the problems and limitations of the use of the EnKF for
history matching reservoir models. The recent use of the EnKF for data assimilation and
assessment of uncertainties in future forecasts in reservoir engineering seems to be
promising. EnKF provides ways of incorporating any type of production data or time
lapse seismic information in an efficient way. However, the use of the EnKF in history
matching comes with its shares of challenges and concerns. The overshooting of
parameters leading to loss of geologic realism, possible increase in the material balance
errors of the updated phase(s), and limitations associated with non-Gaussian permeability
distribution are some of the most critical problems of the EnKF. The use of larger
ensemble size may mitigate some of these problems but are prohibitively expensive in
practice.
We present a streamline-based conditioning technique that can be implemented
with the EnKF to eliminate or reduce the magnitude of these problems, allowing for the
use of a reduced ensemble size, thereby leading to significant savings in time during field
scale implementation. Our approach involves no extra computational cost and is easy to
implement. Additionally, the final history matched model tends to preserve most of the
geological features of the initial geologic model.
A quick look at the procedure is provided that enables the implementation of this
approach into the current EnKF implementations. Our procedure uses the streamline path
information to condition the covariance matrix in the Kalman Update. We demonstrate
the power and utility of our approach with synthetic examples and a field case. Our result shows that using the conditioned technique presented in this thesis, the
overshooting/undershooting problems disappears and the limitation to work with non-
Gaussian distribution is reduced. Finally, an analysis of the scalability in a parallel
implementation of our computer code is given.
| Identifer | oai:union.ndltd.org:tamu.edu/oai:repository.tamu.edu:1969.1/4859 |
| Date | 25 April 2007 |
| Creators | Arroyo Negrete, Elkin Rafael |
| Contributors | Datta-Gupta, Akhil |
| Publisher | Texas A&M University |
| Source Sets | Texas A and M University |
| Language | en_US |
| Detected Language | English |
| Type | Book, Thesis, Electronic Thesis, text |
| Format | 14670953 bytes, electronic, application/pdf, born digital |
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