Repository logo
Log in(current)
Repository logoMIT Open ScholarshipDSpace@MIT
  1. Home
  2. MIT Open Access Articles
  3. MIT Open Access Articles
  4. Sequential approach to joint flow-seismic inversion for improved characterization of fractured media

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

Thumbnail Image
Download
Name

Juanes_Sequential approach.pdf

Size

1.79 MB

Format

Adobe PDF

Checksum (MD5)

6a8b4422b7050998980712a1f5cce39f

Author(s)
Kang, Peter Kyungchul
•
Zheng, Yingcai
•
Fang, Xinding
•
Wojcik, Rafal
•
McLaughlin, Dennis
•
Brown, Stephen
•
Burns, Daniel R
•
Juanes, Ruben
•
Fehler, Michael
Date Issued
February 2016
Journal
Water Resources Research
Publisher
American Geophysical Union (AGU)
Citation
Kang, Peter K. et al. “Sequential Approach to Joint Flow-Seismic Inversion for Improved Characterization of Fractured Media: SEQUENTIAL APPROACH TO JOINT FLOW-SEISMIC INVERSION.” Water Resources Research 52.2 (2016): 903–919. © 2016 American Geophysical Union
Version
Final published version
Abstract
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.
MIT Department
Massachusetts Institute of Technology. Department of Civil and Environmental Engineering
Massachusetts Institute of Technology. Department of Earth, Atmospheric, and Planetary Sciences
Terms of Use
Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
Persistent DSpace Link
http://hdl.handle.net/1721.1/110485
DOI of Published Version
https://doi.org/10.1002/2015wr017412
Repository logo
PrivacyPermissionsAccessibilityContact us
Repository logo
Notify us about copyright concerns.