An inverse-source problem for maximization of pore-fluid oscillation within poroelastic formations

C. Jeong, L. F. Kallivokas

Research output: Contribution to journalArticlepeer-review

7 Scopus citations


This paper discusses a mathematical and numerical modeling approach for identification of an unknown optimal loading time signal of a wave source, atop the ground surface, that can maximize the relative wave motion of a single-phase pore fluid within fluid-saturated porous permeable (poroelastic) rock formations, surrounded by non-permeable semi-infinite elastic solid rock formations, in a one-dimensional setting. The motivation stems from a set of field observations, following seismic events and vibrational tests, suggesting that shaking an oil reservoir is likely to improve oil production rates. This maximization problem is cast into an inverse-source problem, seeking an optimal loading signal that minimizes an objective functional – the reciprocal of kinetic energy in terms of relative pore-fluid wave motion within target poroelastic layers. We use the finite element method to obtain the solution of the governing wave physics of a multi-layered system, where the wave equations for the target poroelastic layers and the elastic wave equation for the surrounding non-permeable layers are coupled with each other. We use a partial-differential-equation-constrained-optimization framework (a state-adjoint-control problem approach) to tackle the minimization problem. The numerical results show that the numerical optimizer recovers optimal loading signals, whose dominant frequencies correspond to amplification frequencies, which can also be obtained by a frequency sweep, leading to larger amplitudes of relative pore-fluid wave motion within the target hydrocarbon formation than other signals.
Original languageEnglish (US)
Pages (from-to)832-863
Number of pages32
JournalInverse Problems in Science and Engineering
Issue number6
StatePublished - Jul 4 2016
Externally publishedYes

Bibliographical note

KAUST Repository Item: Exported on 2020-10-01
Acknowledgements: This work was partially supported by an Academic Excellence Alliance grant between King Abdullah University of Science and Technology (KAUST) and the University of Texas at Austin and by the Society of Petroleum Engineers STAR Fellowship and the William S. Livingston Fellowship at the University of Texas at Austin awarded to the first author.
This publication acknowledges KAUST support, but has no KAUST affiliated authors.


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