Streamline-based models have shown great potential in reconciling high resolution
geologic models to production data. In this work we extend the streamline-based
production data integration technique to naturally fractured reservoirs. We use a dualporosity
streamline model for fracture flow simulation by treating the fracture and matrix
as separate continua that are connected through a transfer function. Next, we analytically
compute the sensitivities that define the relationship between the reservoir properties and
the production response in fractured reservoirs. Finally, production data integration is
carried out via the Generalized Travel Time inversion (GTT). We also apply the
streamline-derived sensitivities in conjunction with a dual porosity finite difference
simulator to combine the efficiency of the streamline approach with the versatility of the
finite difference approach. This significantly broadens the applicability of the streamlinebased
approach in terms of incorporating compressibility effects and complex physics.
The number of reservoir parameters to be estimated is commonly orders of magnitude
larger than the observation data, leading to non-uniqueness and uncertainty in reservoir
parameter estimate. Such uncertainty is passed to reservoir response forecast which needs
to be quantified in economic and operational risk analysis. In this work we sample
parameter uncertainty using a new two-stage Markov Chain Monte Carlo (MCMC) that is
very fast and overcomes much of its current limitations. The computational efficiency
comes through a substantial increase in the acceptance rate during MCMC by using a fast
linearized approximation to the flow simulation and the likelihood function, the critical
link between the reservoir model and production data.
The Gradual Deformation Method (GDM) provides a useful framework to preserve
geologic structure. Current dynamic data integration methods using GDM are inefficient
due to the use of numerical sensitivity calculations which limits the method to deforming
two or three models at a time. In this work, we derived streamline-based analytical
sensitivities for the GDM that can be obtained from a single simulation run for any
number of basis models. The new Generalized Travel Time GDM (GTT-GDM) is highly
efficient and achieved a performance close to regular GTT inversion while preserving the
geologic structure.
| Identifer | oai:union.ndltd.org:tamu.edu/oai:repository.tamu.edu:1969.1/2445 |
| Date | 29 August 2005 |
| Creators | Al Harbi, Mishal H. |
| 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 Dissertation, text |
| Format | 2732044 bytes, electronic, application/pdf, born digital |
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