IAMCS Workshop in Large-Scale Inverse Problems and Uncertainty Quantification
- Texas A&M University
- College Station, TX
- Stephen W. Hawking Auditorium
- George P. and Cynthia Woods Mitchell Institute for Fundamental Physics and Astronomy (MIST)
- Yuguang Chen, Chevron Energy Technology Company
- Uncertainty Quantification for Subsurface Flow Problems Using Coarse-Scale Models
The multiscale nature of geological formations can have a strong impact on subsurface flow processes. In an attempt to characterize these formations at all relevant length scales, highly resolved property models are typically constructed. This high degree of detail greatly complicates flow simulations and uncertainty quantification. To address this issue, a variety of computational upscaling (numerical homogenization) procedures have been developed. In this talk, we present a number of existing approaches, including single-phase and multiphase flow parameters. Emphasis is placed on the performance of these techniques for uncertainty quantification, where many realizations of the geological model are considered. Along these lines, an ensemble-level upscaling approach is described, in which the goal is to provide coarse models that capture flow statistics (such as the cumulative distribution function for oil production) consistent with those of the underlying fine-scale models rather than agreement on a realization-by-realization basis. Numerical results highlighting the relative advantages and limitations of the various methods are presented. In particular, the ensemble-level upscaling approach is shown to provide accurate statistical predictions at an acceptable computational cost.