Implementation of adaptive models and solvers to Enhance Oil Recovery (EOR) problems.
One of the main challenges of our century is to increase the quantity of oil production from the reservoirs around the world. Roughly 2 trillion barrels of petroleum resources are left behind in used sites. For this reason, Enhanced Oil Recovery (EOR) technologies are continuously investigated and updated. The main difficulty for the EOR techniques is the realization of realistic and reliable models of the reservoirs. Such models are in fact extremely complex. The flow of the fluids is described by highly non-linear differential equations and many quantities are evolving during the process of extraction. It is evident as the realization of an accurate model can become challenging, many simplifications are often taken into account. Some of the effects that are usually neglected to achieve such simplified models are:
* Transient wettability alteration
* Dynamic capillary and hysteresis
Each of these plays a fundamental role in a full comprehension of the flow, especially in the case of EO Recoveries.
The objective of the Ph.D. is to develop accurate and reliable numerical tools suited for complex EOR simulations on the Darcy scale, including such effects. The study of the linearization schemes, implemented to threat the non-linear quantities involved, will be of particular interest for its complexity. The conceived approach will combine adaptive models and solver simulation.
- 2020. Iterative schemes for surfactant transport in porous media. Computational Geosciences. 18 pages.