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Title: Hierarchical Bayesian method for mapping biogeochemical hot spots using induced polarization imaging

In floodplain environments, a naturally reduced zone (NRZ) is considered to be a common biogeochemical hot spot, having distinct microbial and geochemical characteristics. Although important for understanding their role in mediating floodplain biogeochemical processes, mapping the subsurface distribution of NRZs over the dimensions of a floodplain is challenging, as conventional wellbore data are typically spatially limited and the distribution of NRZs is heterogeneous. In this work, we present an innovative methodology for the probabilistic mapping of NRZs within a three-dimensional (3-D) subsurface domain using induced polarization imaging, which is a noninvasive geophysical technique. Measurements consist of surface geophysical surveys and drilling-recovered sediments at the U.S. Department of Energy field site near Rifle, CO (USA). Inversion of surface time domain-induced polarization (TDIP) data yielded 3-D images of the complex electrical resistivity, in terms of magnitude and phase, which are associated with mineral precipitation and other lithological properties. By extracting the TDIP data values colocated with wellbore lithological logs, we found that the NRZs have a different distribution of resistivity and polarization from the other aquifer sediments. To estimate the spatial distribution of NRZs, we developed a Bayesian hierarchical model to integrate the geophysical and wellbore data. In addition, the resistivity imagesmore » were used to estimate hydrostratigraphic interfaces under the floodplain. Validation results showed that the integration of electrical imaging and wellbore data using a Bayesian hierarchical model was capable of mapping spatially heterogeneous interfaces and NRZ distributions thereby providing a minimally invasive means to parameterize a hydrobiogeochemical model of the floodplain.« less
Authors:
 [1] ;  [2] ;  [3] ;  [1] ;  [1] ;  [1] ;  [1]
  1. Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States). Earth Sciences Division
  2. Vienna Univ. of Technology (Austria). Dept. of Geodesy and Geoinformation
  3. Vienna Univ. of Technology (Austria). Dept. of Geodesy and Geoinformation; Univ. of Bonn (Germany). Steinmann Inst. and Dept. of Geophysics
Publication Date:
Grant/Contract Number:
AC02-05CH11231
Type:
Accepted Manuscript
Journal Name:
Water Resources Research
Additional Journal Information:
Journal Volume: 52; Journal Issue: 1; Related Information: © 2015. American Geophysical Union. All Rights Reserved.; Journal ID: ISSN 0043-1397
Publisher:
American Geophysical Union (AGU)
Research Org:
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Sponsoring Org:
USDOE Office of Science (SC), Biological and Environmental Research (BER) (SC-23)
Country of Publication:
United States
Language:
English
Subject:
58 GEOSCIENCES; 54 ENVIRONMENTAL SCIENCES; 37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CHEMISTRY; 47 OTHER INSTRUMENTATION; biogeochemical hot spots; induced polarization imaging; Bayesian hierarchical model
OSTI Identifier:
1439188
Alternate Identifier(s):
OSTI ID: 1402275