Uncertainty quantification of coal seam gas production prediction using Polynomial Chaos

作者：McCourt Thomas A^*; Hurter Suzanne; Lawson Brodie; Zhou Fengde; Thompson Bevan; Tyson Stephen; Donovan Diane

来源：Journal of Petroleum Science and Engineering, 2017, 157: 1148-1159.

DOI：10.1016/j.petrol.2017.08.012

• Polynomial Chaos
• Coal seam gas well
• Uncertainty quantification
• Global sensitivity analysis

A surrogate model approximates a computationally expensive solver. Polynomial Chaos is a method used to construct surrogate models by summing combinations of carefully chosen polynomials. The polynomials are chosen to respect the probability distributions of the uncertain input variables (parameters); this allows for both uncertainty quantification and global sensitivity analysis.
In this paper we apply these techniques to a commercial solver for the estimation of peak gas rate and cumulative gas extraction from a coal seam gas well. The polynomial expansion is shown to honour the underlying geophysics with low error when compared to a much more complex and computationally slower commercial solver. We make use of advanced numerical integration techniques to achieve this accuracy using relatively small amounts of training data.

• 出版日期2017-8