Maximization of wave motion within a hydrocarbon reservoir for wave-based enhanced oil recovery

C. Jeong, L.F. Kallivokas, S. Kucukcoban, W. Deng, A. Fathi

Research output: Contribution to journalArticlepeer-review

26 Scopus citations

Abstract

© 2015 Elsevier B.V. We discuss a systematic methodology for investigating the feasibility of mobilizing oil droplets trapped within the pore space of a target reservoir region by optimally directing wave energy to the region of interest. The motivation stems from field and laboratory observations, which have provided sufficient evidence suggesting that wave-based reservoir stimulation could lead to economically viable oil recovery.Using controlled active surface wave sources, we first describe the mathematical framework necessary for identifying optimal wave source signals that can maximize a desired motion metric (kinetic energy, particle acceleration, etc.) at the target region of interest. We use the apparatus of partial-differential-equation (PDE)-constrained optimization to formulate the associated inverse-source problem, and deploy state-of-the-art numerical wave simulation tools to resolve numerically the associated discrete inverse problem.Numerical experiments with a synthetic subsurface model featuring a shallow reservoir show that the optimizer converges to wave source signals capable of maximizing the motion within the reservoir. The spectra of the wave sources are dominated by the amplification frequencies of the formation. We also show that wave energy could be focused within the target reservoir area, while simultaneously minimizing the disturbance to neighboring formations - a concept that can also be exploited in fracking operations.Lastly, we compare the results of our numerical experiments conducted at the reservoir scale, with results obtained from semi-analytical studies at the granular level, to conclude that, in the case of shallow targets, the optimized wave sources are likely to mobilize trapped oil droplets, and thus enhance oil recovery.
Original languageEnglish (US)
Pages (from-to)205-220
Number of pages16
JournalJournal of Petroleum Science and Engineering
Volume129
DOIs
StatePublished - May 2015
Externally publishedYes

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