Improved characterization of heterogeneous permeability in saline aquifers from transient pressure data during freshwater injection

Peter K. Kang, Jonghyun Lee, Xiaojing Fu, Seunghak Lee, Peter K. Kitanidis, Ruben Juanes

Research output: Contribution to journalArticlepeer-review

11 Scopus citations

Abstract

Managing recharge of freshwater into saline aquifers requires accurate estimation of the heterogeneous permeability field for maximizing injection and recovery efficiency. Here we present a methodology for subsurface characterization in saline aquifers that takes advantage of the density difference between the injected freshwater and the ambient saline groundwater. We combine high-resolution forward modeling of density-driven flow with an efficient Bayesian geostatistical inversion algorithm. In the presence of a density difference between the injected and ambient fluids due to differences in salinity, the pressure field is coupled to the spatial distribution of salinity. This coupling renders the pressure field transient: the time evolution of the salinity distribution controls the density distribution which then leads to a time-evolving pressure distribution. We exploit this coupling between pressure and salinity to obtain an improved characterization of the permeability field without multiple pumping tests or additional salinity measurements. We show that the inversion performance improves with an increase in the mixed convection ratio—the relative importance between viscous forces from injection and buoyancy forces from density difference. Our work shows that measuring transient pressure data at multiple sampling points during freshwater injection into saline aquifers can be an effective strategy for aquifer characterization, key to the successful management of aquifer recharge.

Original languageEnglish (US)
Pages (from-to)4444-4458
Number of pages15
JournalWater Resources Research
Volume53
Issue number5
DOIs
StatePublished - May 1 2017
Externally publishedYes

Bibliographical note

Funding Information:
Peter K. Kang and Seunghak Lee acknowledge Ministry of Land, Infrastructure and Transport, Korea (16AWMP-B066761?04), the Future Research Program (2E27030) funded by the Korea Institute of Science and Technology (KIST), and the National Research Foundation of Korea grant funded by the Korean Government (MSIP) (2016, University-Institute cooperation program) for their support. Jonghyun Lee and Peter K. Kitanidis acknowledge the support of the National Science Foundation through its ReNUWIt Engineering Research Center (www.renuwit.org; NSF EEC-1028968). Jonghyun Lee was also supported in part by an appointment to the Postgraduate Research Participation Program at the U.S. Army Engineer Research and Development Center, Coastal and Hydraulics Laboratory (ERDC-CHL) administered by the Oak Ridge Institute for Science and Education through an interagency agreement between the U.S. Department of Energy and ERDC. Xiaojing Fu and Ruben Juanes acknowledge support from the U.S. Department of Energy through a DOE Mathematical Multifaceted Integrated Capability Center (grant DE-SC0009286), and from the MIT International Science and Technology Initiatives (MISTI) through a Global Seed Funds award. The data to reproduce the work can be obtained from the first author: Peter K. Kang (pkkang@kist.re.kr).

Publisher Copyright:
© 2017. American Geophysical Union. All Rights Reserved.

Keywords

  • Principal Component Geostatistical Approach
  • density-driven flow
  • managed aquifer recharge
  • saline aquifer
  • subsurface imaging

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