Reconciling high-resolution geologic models to field production history is still a very
time-consuming procedure. Recently streamline-based assisted and automatic history
matching techniques, especially production data integration by âÂÂtravel-time matching,âÂÂ
have shown great potential in this regard. But no systematic study was done to examine
the merits of travel-time matching compared to more traditional amplitude matching for
field-scale application. Besides, most applications were limited to two-phase water-oil
flow because current streamline models are limited in their ability to incorporate highly
compressible flow in a rigorous and computationally efficient manner.
The purpose of this work is fourfold. First, we quantitatively investigated the
nonlinearities in the inverse problems related to travel time, generalized travel time, and
amplitude matching during production data integration and their impact on the solution
and its convergence. Results show that the commonly used amplitude inversion can be
orders of magnitude more nonlinear compared to the travel-time inversion. Both the
travel-time and generalized travel time inversion (GTTI) are shown to be more robust
and exhibit superior convergence characteristics.
Second, the streamline-based assisted history matching was enhanced in two
important aspects that significantly improve its efficiency and effectiveness. We utilize
streamline-derived analytic sensitivities to determine the location and magnitude of the
changes to improve the history match, and we use the iterative GTTI for model updating.
Our approach leads to significant savings in time and manpower. Third, a novel approach to history matching finite-difference models that combines
the efficiency of analytical sensitivity computation of the streamline models with the
versatility of finite-difference simulation was developed. Use of finite-difference
simulation can account for complex physics.
Finally, we developed an approach to history matching three-phase flow using a
novel compressible streamline formulation and streamline-derived analytic sensitivities.
Streamline models were generalized to account for compressible flow by introducing a
relative density of total fluids along streamlines and a density-dependent source term in
the saturation equation. The analytical sensitivities are calculated based on the rigorous
streamline formulation.
The power and utility of our approaches have been demonstrated using both
synthetic and field examples.
| Identifer | oai:union.ndltd.org:tamu.edu/oai:repository.tamu.edu:1969.1/4139 |
| Date | 30 October 2006 |
| Creators | Cheng, Hao |
| 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 | 5471727 bytes, electronic, application/pdf, born digital |
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