Sequential approach to joint flow-seismic inversion for improved characterization of fractured media

Seismic interpretation of subsurface structures is traditionally performed without any account of flow behavior. Here we present a methodology for characterizing fractured geologic reservoirs by integrating flow and seismic data. The key element of the proposed approach is the identification—within...

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Bibliographic Details
Main Authors: Kang, Peter Kyungchul, Zheng, Yingcai, Fang, Xinding, Wojcik, Rafal, McLaughlin, Dennis, Brown, Stephen, Burns, Daniel R, Juanes, Ruben, Fehler, Michael
Other Authors: Massachusetts Institute of Technology. Department of Civil and Environmental Engineering
Format: Article
Language:en_US
Published: American Geophysical Union (AGU) 2017
Online Access:http://hdl.handle.net/1721.1/110485
https://orcid.org/0000-0002-4961-6899
https://orcid.org/0000-0002-8814-5495
https://orcid.org/0000-0002-7370-2332
Description
Summary:Seismic interpretation of subsurface structures is traditionally performed without any account of flow behavior. Here we present a methodology for characterizing fractured geologic reservoirs by integrating flow and seismic data. The key element of the proposed approach is the identification—within the inversion—of the intimate relation between fracture compliance and fracture transmissivity, which determine the acoustic and flow responses of a fractured reservoir, respectively. Owing to the strong (but highly uncertain) dependence of fracture transmissivity on fracture compliance, the modeled flow response in a fractured reservoir is highly sensitive to the geophysical interpretation. By means of synthetic models, we show that by incorporating flow data (well pressures and tracer breakthrough curves) into the inversion workflow, we can simultaneously reduce the error in the seismic interpretation and improve predictions of the reservoir flow dynamics. While the inversion results are robust with respect to noise in the data for this synthetic example, the applicability of the methodology remains to be tested for more complex synthetic models and field cases.