Summary
Well data reveal reservoir layering with high vertical resolution but are
areally sparse, whereas seismic data have low vertical resolution but are
areally dense. Improved reservoir models can be constructed by integrating
these data. The proposed method combines stochastic seismic inversion results,
finer-scale well data, and geologic continuity models to build ensembles of
flow models.
Stochastic seismic inversions operating at the mesoscale generate rock
property estimates, such as porosity, that are consistent with regional rock
physics and true-amplitude imaged seismic data. These can be used in a
cascading workflow to generate ensembles of fine-scale reservoir models wherein
each realization from the Bayesian seismic inversion is treated as an exact
constraint for a subensemble of fine-scale models. Exact constraints ensure
that relevant interproperty and interzone correlations implied by rock physics
and seismic data are preserved in the downscaled models. Uncertainty in the
rock physics and seismic response is included by using multiple stochastic
inversions in a cascading workflow. In contrast, inexact constraints generally
do not preserve these correlations. We use two-point covariance at the fine
scale to provide prior model thickness and porosity distributions of multiple
facies. A Bayesian formulation uses the kriged data as the prior with the
coarse constraints as the likelihood, and this posterior is sampled using a
Markov Chain Monte Carlo (MCMC) method in a sequential simulation
framework.
These methods generate rich pinchout behavior and flexible spatial
connectivities in the fine-scale model. These flow models are easily
represented on a cornerpoint grid. 2D examples illustrate the interactions of
prior and constraint data, and 3D examples demonstrate algorithm performance
and the effects of stratigraphic variability on flow behavior.
© 2009. Society of Petroleum Engineers
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History
- Original manuscript received:
2 August 2007
- Meeting paper published:
11 November 2007
- Revised manuscript received:
19 June 2009
- Manuscript approved:
16 July 2009
- Published online:
24 September 2009
- Version of record:
22 December 2009
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