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Title: Three-Dimensional Bayesian Geostatistical Aquifer Characterization at the Hanford 300 Area using Tracer Test Data

Abstract

Tracer testing under natural or forced gradient flow holds the potential to provide useful information for characterizing subsurface properties, through monitoring, modeling and interpretation of the tracer plume migration in an aquifer. Non-reactive tracer experiments were conducted at the Hanford 300 Area, along with constant-rate injection tests and electromagnetic borehole flowmeter (EBF) profiling. A Bayesian data assimilation technique, the method of anchored distributions (MAD) [Rubin et al., 2010], was applied to assimilate the experimental tracer test data with the other types of data and to infer the three-dimensional heterogeneous structure of the hydraulic conductivity in the saturated zone of the Hanford formation. In this study, the Bayesian prior information on the underlying random hydraulic conductivity field was obtained from previous field characterization efforts using the constant-rate injection tests and the EBF data. The posterior distribution of the conductivity field was obtained by further conditioning the field on the temporal moments of tracer breakthrough curves at various observation wells. MAD was implemented with the massively-parallel three-dimensional flow and transport code PFLOTRAN to cope with the highly transient flow boundary conditions at the site and to meet the computational demands of MAD. A synthetic study proved that the proposed method could effectivelymore » invert tracer test data to capture the essential spatial heterogeneity of the three-dimensional hydraulic conductivity field. Application of MAD to actual field data shows that the hydrogeological model, when conditioned on the tracer test data, can reproduce the tracer transport behavior better than the field characterized without the tracer test data. This study successfully demonstrates that MAD can sequentially assimilate multi-scale multi-type field data through a consistent Bayesian framework.« less

Authors:
; ; ; ; ; ;
Publication Date:
Research Org.:
Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1044478
Report Number(s):
PNNL-SA-78432
Journal ID: ISSN 0043-1397; WRERAQ; KP1702030; TRN: US201214%%453
DOE Contract Number:  
AC05-76RL01830
Resource Type:
Journal Article
Journal Name:
Water Resources Research
Additional Journal Information:
Journal Volume: 48; Journal ID: ISSN 0043-1397
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES; AQUIFERS; BOREHOLES; BOUNDARY CONDITIONS; DISTRIBUTION; FLOWMETERS; HYDRAULIC CONDUCTIVITY; MONITORING; PLUMES; SIMULATION; TESTING; TRANSIENTS; TRANSPORT; inverse modeling; tracer data; flow and transport modeling

Citation Formats

Chen, Xingyuan, Murakami, Haruko, Hahn, Melanie S, Hammond, Glenn E, Rockhold, Mark L, Zachara, John M, and Rubin, Yoram. Three-Dimensional Bayesian Geostatistical Aquifer Characterization at the Hanford 300 Area using Tracer Test Data. United States: N. p., 2012. Web. doi:10.1029/2011WR010675.
Chen, Xingyuan, Murakami, Haruko, Hahn, Melanie S, Hammond, Glenn E, Rockhold, Mark L, Zachara, John M, & Rubin, Yoram. Three-Dimensional Bayesian Geostatistical Aquifer Characterization at the Hanford 300 Area using Tracer Test Data. United States. https://doi.org/10.1029/2011WR010675
Chen, Xingyuan, Murakami, Haruko, Hahn, Melanie S, Hammond, Glenn E, Rockhold, Mark L, Zachara, John M, and Rubin, Yoram. 2012. "Three-Dimensional Bayesian Geostatistical Aquifer Characterization at the Hanford 300 Area using Tracer Test Data". United States. https://doi.org/10.1029/2011WR010675.
@article{osti_1044478,
title = {Three-Dimensional Bayesian Geostatistical Aquifer Characterization at the Hanford 300 Area using Tracer Test Data},
author = {Chen, Xingyuan and Murakami, Haruko and Hahn, Melanie S and Hammond, Glenn E and Rockhold, Mark L and Zachara, John M and Rubin, Yoram},
abstractNote = {Tracer testing under natural or forced gradient flow holds the potential to provide useful information for characterizing subsurface properties, through monitoring, modeling and interpretation of the tracer plume migration in an aquifer. Non-reactive tracer experiments were conducted at the Hanford 300 Area, along with constant-rate injection tests and electromagnetic borehole flowmeter (EBF) profiling. A Bayesian data assimilation technique, the method of anchored distributions (MAD) [Rubin et al., 2010], was applied to assimilate the experimental tracer test data with the other types of data and to infer the three-dimensional heterogeneous structure of the hydraulic conductivity in the saturated zone of the Hanford formation. In this study, the Bayesian prior information on the underlying random hydraulic conductivity field was obtained from previous field characterization efforts using the constant-rate injection tests and the EBF data. The posterior distribution of the conductivity field was obtained by further conditioning the field on the temporal moments of tracer breakthrough curves at various observation wells. MAD was implemented with the massively-parallel three-dimensional flow and transport code PFLOTRAN to cope with the highly transient flow boundary conditions at the site and to meet the computational demands of MAD. A synthetic study proved that the proposed method could effectively invert tracer test data to capture the essential spatial heterogeneity of the three-dimensional hydraulic conductivity field. Application of MAD to actual field data shows that the hydrogeological model, when conditioned on the tracer test data, can reproduce the tracer transport behavior better than the field characterized without the tracer test data. This study successfully demonstrates that MAD can sequentially assimilate multi-scale multi-type field data through a consistent Bayesian framework.},
doi = {10.1029/2011WR010675},
url = {https://www.osti.gov/biblio/1044478}, journal = {Water Resources Research},
issn = {0043-1397},
number = ,
volume = 48,
place = {United States},
year = {Fri Jun 01 00:00:00 EDT 2012},
month = {Fri Jun 01 00:00:00 EDT 2012}
}