PhD position IFB France CO2 Storage

Optimisation of the monitoring strategy of a geological CO2 storage

Social acceptance of geological storage of CO2 will imply using up to date monitoring techniques, that will insure the relevance of the storage. Due to the number of available monitoring techniques and the associated costs, optimising the data management during the life of the storage is a major issue. We can have to provide answers to practical questions such as : In the case of a prospect : where can we drill a new exploration well, given that some data is already available, and that the geological context remains uncertain. In the case of an existing storage, what are the most relevant quantities to monitor : Ph, salinities of the fluids, pressures). In practice, we will have to address saline aquifer storage, both in the filling and storage phases. The proposed techniques are based about Information theory concepts, coupled with Bayesian inversion formalism. The main idea is to maximize the entropy-based distance between prior and posterior probability distributions of the parameters describing the geological/petrophysical storage. These distributions are defined in a bayesian sense using a probabilistic view of inverse problems. This entropy can thus be maximized with respect to the parameters describing the measurements such as the position of observation wells, frequency of data acquisition etc... The same approach can be applied about any parameter set of practical interest : total stored CO2, probability of . In practice, the involved calculations imply the evaluation of large covariance matrix, and of the associated determinants. Sampling techniques will have to be proposed in order to provide tractable calculations. Karhunen Loève decompositions, Monte Carlo sampling will be tested. Real example coming from France or Germany deep saline prospects could serve as practical examples.
Contact: Benoit.NOETINGER@ifp.fr