MPiTOUGH2: A parallel parameter estimation framework for hydrological and hydrogeophysical applications

Commer, Michael; Kowalsky, Michael B.; Doetsch, Joseph; Newman, Gregory A.; Finsterle, Stefan

doi:10.1016/j.cageo.2013.06.011

Cited by 24 publications

(14 citation statements)

References 26 publications

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“…Finally, Commer et al (2014) developed MPiTOUGH2, a version of iTOUGH2 that uses a two-level parallelization approach. Independent TOUGH forward simulations are run in parallel, and at the same time, each TOUGH run is parallelized using domain decomposition.…”

Section: Description Of Simulation-optimization Frameworkmentioning

confidence: 99%

iTOUGH2: A multiphysics simulation-optimization framework for analyzing subsurface systems

Finsterle¹,

Commer²,

Edmiston³

et al. 2017

Computers & Geosciences

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iTOUGH2 is a simulation-optimization framework for the TOUGH suite of nonisothermal multiphase flow models and related simulators of geophysical, geochemical, and geomechanical processes. After appropriate parameterization of subsurface structures and their properties, iTOUGH2 runs simulations for multiple parameter sets and analyzes the resulting output for parameter estimation through automatic model calibration, local and global sensitivity analyses, data-worth analyses, and uncertainty propagation analyses. Development of iTOUGH2 is driven by scientific challenges and user needs, with new capabilities continually added to both the forward simulator and the optimization framework. This review article provides a summary description of methods and features implemented in iTOUGH2, and discusses the usefulness and † Now at: Finsterle GeoConsulting, 2 limitations of an integrated simulation-optimization workflow in support of the characterization and analysis of complex multiphysics subsurface systems.

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Section: Description Of Simulation-optimization Frameworkmentioning

confidence: 99%

iTOUGH2: A multiphysics simulation-optimization framework for analyzing subsurface systems

Finsterle¹,

Commer²,

Edmiston³

et al. 2017

Computers & Geosciences

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“…Kowalsky et al [2011] were the first to link unsaturated and saturated flow and transport in a coupled hydrogeophysical inversion and their application highlights the complexity of real world problems. A parallel computing implementation of this approach [Commer et al, 2014] will enable applications to even more complex environments and larger data sets. Dorn et al [2013] conditioned discrete fracture network realizations such that they were in agreement with field-based single-hole GPR reflection, tracer, hydraulic and televiewer data.…”

Section: Petrophysical Coupling Applied To Transient Groundwater Procmentioning

confidence: 99%

Joint Inversion in Hydrogeophysics and Near‐Surface Geophysics

Linde¹,

Doetsch²

2016

Geophysical Monograph Series

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Key points:• Structural joint inversions of near-surface geophysical data are often favored • Time-lapse geophysical data are sensitive to hydrological state variables • Joint inversion in hydrogeophysics should include flow-and transport modeling This work is published, please cite as: Linde, N., and J. Doetsch, 2016, Joint inversion in hydrogeophysics and near-surface geophysics. in: Integrated imaging of the Earth, M. Moorkamp, P. Lelievre, N. Linde, and A. AbstractThe near-surface environment is often too complex to enable inference of hydrological and environmental variables using one geophysical data type alone. Joint inversion and coupled inverse modeling involving numerical flow-and transport simulators have, in the last decade, played important roles in pushing applications towards increasingly challenging targets. Joint inversion of geophysical data that is based on structural constraints is often favored over model coupling based on explicit petrophysical relationships. More specifically, cross-gradient joint inversion has been applied to a wide range of near-surface applications and geophysical data types. To infer hydrological subsurface properties, the most appropriate approach is often to use temporal changes in geophysical data that can be related to hydrological state variables. This allows using geophysical data as indirect hydrological observables, while the coupling with a flow-and transport simulator ensures physical consistency.Future research avenues include investigating the validity of different coupling strategies at various scales, the spatial statistics of near-surface petrophysical relationships, the influence of the model conceptualization, fully probabilistic joint inversions, and how to include complex prior information in the joint inversion.

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“…The approaches above are somewhat limited to a small number of parameters because of the direct computations of sensitivities. A more general framework was developed by Commer et al [16] that can be applied to larger scale hydrologeophysical problems for a wide range of processes in multiphase flow and solute transport. The authors improved the inversion framework of iTOUGH2 to enable parallel computing and merge it with parallel geophysical simulator for electromagnetic data.…”

Section: Introductionmentioning

confidence: 99%

“…While the work in [16] enables larger scale problems, it can be inefficient due to the finite difference evaluation of derivatives and hydrogeophysical coupling. Our goal here is to improve on this work such that we can solve large scale problems.…”

Section: Introductionmentioning

confidence: 99%

Joint hydrogeophysical inversion: state estimation for seawater intrusion models in 3D

Šteklová

Haber

2016

Comput Geosci

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Seawater intrusion (SWI) is a complex process, where 3D modeling is often necessary in order to monitor and manage the affected aquifers. Here, we present a synthetic study to test a joint hydrogeophysical inversion approach aimed at solving the inverse problem of estimating initial and current saltwater distribution. First, we use a 3D groundwater model for variable density flow based on discretized flow and solute mass balance equations. In addition to the groundwater model, a 3D geophysical model was developed for direct current resistivity imaging and inversion. The objective function of the coupled problem consists of data misfit and regularization terms as well as a coupling term that relates groundwater and geophysical states. We present a novel approach to solve the inverse problem using an Alternating Direction Method of Multipliers (ADMM) to minimize this coupled objective function. The sensitivities are derived analytically for the discretized system of equations, which allows us to efficiently compute the gradients in the minimization procedure and reduce the computational complexity of the problem. The method was tested on different synthetic scenarios with groundwater and geophysical data represented by solute mass fraction data and direct current resistivity data. With the ADMM approach, we were able to obtain better estimates for the solute distribution, compared to just con-sidering each data set separately or solving with a simple coupled approach.Keywords inverse problem · joint inversion · seawater intrusion · variable density flow · DC resistivity · ADMM

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MPiTOUGH2: A parallel parameter estimation framework for hydrological and hydrogeophysical applications

Cited by 24 publications

References 26 publications

iTOUGH2: A multiphysics simulation-optimization framework for analyzing subsurface systems

iTOUGH2: A multiphysics simulation-optimization framework for analyzing subsurface systems

Joint Inversion in Hydrogeophysics and Near‐Surface Geophysics

Joint hydrogeophysical inversion: state estimation for seawater intrusion models in 3D

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