A framework for assessing the uncertainty in wave energy delivery to targeted subsurface formations

Pranav M. Karve, Loukas F. Kallivokas, Lance Manuel

Research output: Contribution to journalArticlepeer-review

12 Scopus citations


© 2015 Elsevier B.V. Stress wave stimulation of geological formations has potential applications in petroleum engineering, hydro-geology, and environmental engineering. The stimulation can be applied using wave sources whose spatio-temporal characteristics are designed to focus the emitted wave energy into the target region. Typically, the design process involves numerical simulations of the underlying wave physics, and assumes a perfect knowledge of the material properties and the overall geometry of the geostructure. In practice, however, precise knowledge of the properties of the geological formations is elusive, and quantification of the reliability of a deterministic approach is crucial for evaluating the technical and economical feasibility of the design. In this article, we discuss a methodology that could be used to quantify the uncertainty in the wave energy delivery. We formulate the wave propagation problem for a two-dimensional, layered, isotropic, elastic solid truncated using hybrid perfectly-matched-layers (PMLs), and containing a target elastic or poroelastic inclusion. We define a wave motion metric to quantify the amount of the delivered wave energy. We, then, treat the material properties of the layers as random variables, and perform a first-order uncertainty analysis of the formation to compute the probabilities of failure to achieve threshold values of the motion metric. We illustrate the uncertainty quantification procedure using synthetic data.
Original languageEnglish (US)
Pages (from-to)26-36
Number of pages11
JournalJournal of Applied Geophysics
StatePublished - Feb 2016
Externally publishedYes

Bibliographical note

KAUST Repository Item: Exported on 2020-10-01
Acknowledgements: The first two authors were partially supported by an Academic Excellence Alliance grant between the King Abdullah University of Science and Technology in Saudi Arabia (KAUST) and the University of Texas at Austin. This support is gratefully acknowledged.
This publication acknowledges KAUST support, but has no KAUST affiliated authors.


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