Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
5471097 | Applied Mathematical Modelling | 2017 | 27 Pages |
Abstract
By analysing the results of this population of models approach we can identify the similarities between wells based on the parameter distributions, and understand the sensitivity of key model parameters. We show by example that high correlation between wells based on their parameter values may be an indicator of their similarity. A combinatorial sum of the predicted gas production is compared against the individual gas volumes (given in terms of percentage of the total volume) measured at the compression facility as a way of further calibrating a subpopulation of models.
Related Topics
Physical Sciences and Engineering
Engineering
Computational Mechanics
Authors
Steven Psaltis, Troy Farrell, Kevin Burrage, Pamela Burrage, Peter McCabe, Timothy Moroney, Ian Turner, Saikat Mazumder, Tomasz Bednarz,