Predicting the migration of CO₂ plume using injection data and a distance-metric approach to reservoir-model selection

During the operation of a geological carbon storage project, verifying that the CO₂ plume remains within the permitted zone will be of particular interest both to regulators and to operators. We demonstrate a model selection algorithm that refines an initial suite of subsurface models representing the prior uncertainty to create a posterior set of subsurface models that reflect injection performance consistent with that observed. Such posterior models can be used to represent uncertainty in the future migration of the CO₂ plume. Because only injection data is required, the method provides a very inexpensive method to map the migration of the plume and the associated uncertainty in migration paths. We illustrate the method using a field data set.