S31E:
Frontiers of Uncertainty Quantification in Geoscientific Inversion Posters


Submit an Abstract to this Session


Session ID#: 52107

Session Description:
Geoscientists employ inversion methods to infer Earth properties and processes. These inferences are based on observations and described by model parameters. However, incomplete and noisy observations, subjective processing and inversion choices, non-uniqueness, and approximate physical theory lead to parameter uncertainty. Therefore, robust interpretation of inversion results requires uncertainty estimation, which relates parameter knowledge to data errors. Rigorous methods for uncertainty quantification are of great practical value across disciplines, particularly those involving predictions, such as probabilistic hazard assessment or hydrologic modeling. For instance, how uncertain are inferred locations of unexploded ordnances, economic resources, or chemical contaminants? How uncertain are tsunami predictions given uncertain earthquake rupture and earth structure knowledge? What role can machine learning play in uncertainty quantification? We invite submissions on all aspects of uncertainty quantification, including theoretical advances and practical applications across all fields of geosciences.
Primary Convener:  Vedran Lekic, University of Maryland, College Park, MD, United States
Conveners:  Burke J Minsley, U.S. Geological Survey, Geology, Geophysics, and Geochemistry Science Center, Denver, United States, Louise Pellerin, Green Geophysics, Berkeley, CA, United States and Jan Dettmer, University of Calgary, Department of Geoscience, Calgary, AB, Canada
Primary Liaison:  Vedran Lekic, University of Maryland, College Park, MD, United States
Chairs:  Vedran Lekic, University of Maryland, Department of Geology, College Park, United States and Jan Dettmer, University of Calgary, Department of Geoscience, Calgary, AB, Canada
OSPA Liaison:  Louise Pellerin, Green Geophysics, Berkeley, CA, United States
Co-Organized with:
Seismology, Near Surface Geophysics, Study of Earth's Deep Interior, Geomagnetism, Paleomagnetism and Electromagnetism, and Hydrology

Proposed Co-Organized Session with:
  • DI - Study of Earth's Deep Interior
  • GP - Geomagnetism, Paleomagnetism and Electromagnetism
  • H - Hydrology
  • NS - Near Surface Geophysics
Index Terms:

1873 Uncertainty assessment [HYDROLOGY]
1990 Uncertainty [INFORMATICS]
3260 Inverse theory [MATHEMATICAL GEOPHYSICS]
3275 Uncertainty quantification [MATHEMATICAL GEOPHYSICS]

Abstracts Submitted to this Session:

Hierachical Bayesian models and sparsity: L2-magic (Invited) (403015)
Daniela Calvetti, Case Western Reserve University, Cleveland, OH, United States and Erkki Somersalo, Case Western Reserve University, Mathematics, Applied Mathematics, and Statistics, Cleveland, OH, United States
Deformation source optimization by using deep neural networks (416861)
Hannes Vasyura-Bathke, University of Potsdam, Institut für Erd- und Umweltwissenschaften, Potsdam, Germany, Marius Kriegerowski, Helmholtz Centre Potsdam GFZ German Research Centre for Geosciences, Potsdam, Germany, Gesa M. Petersen, University of Potsdam, Potsdam, Germany and Matthias M Ohrnberger, Institute of Geosciences, University of Potsdam, Potsdam, Germany
Bayesian Framework for Structural Uncertainty Estimation of Land Models (428816)
Khachik Sargsyan, Sandia National Laboratories, Albuquerque, NM, United States, Daniel M Ricciuto, Oak Ridge National Laboratory, Environmental Sciences Division, Oak Ridge, TN, United States and Cosmin Safta, Sandia National Laboratories, Livermore, CA, United States
A Deep Learning-based Inversion Approach for Simultaneous Identification of a Contaminant Source and Highly Heterogeneous Hydraulic Conductivity Field (409435)
Nicholas Zabaras, University of Notre Dame, Center for Informatics and Computational Science, Notre Dame, IN, United States and Shaoxing Mo, Nanjing University, Nanjing, China
Monte Carlo Method for Advanced Detection in Tunnel Using 3D Resistivity FE Modelling on Unstructured Grids (409766)
Xiaoping Wu1, Daiming Hu2, Xiaodong Yang2 and Yang Liu2, (1)University of Science and Technology of China, School of Earth and Space Sciences, Hefei, China, (2)University of Science and Technology of China, Hefei, China
Quantifying Uncertainties in the Inference of Lithospheric Heat Flow (464400)
Marcus Haynes, Geoscience Australia, Canberra, ACT, Australia; Australian National University, Research School of Earth Sciences, Canberra, ACT, Australia
Assessing Accuracy and Tradeoffs from Several Power Spectral Density Estimate Algorithms (368125)
Robert E Anthony, USGS Geologic Hazards Science Center, Golden, CO, United States, Adam T Ringler, USGS Geologic Hazards Science Center, Golden, United States, Manoch Bahavar, IRIS Data Management System, Seattle, WA, United States, Keith D. Koper, University of Utah, Department of Geology and Geophysics, Salt Lake City, United States, Joseph M Steim, Quanterra Inc, Shirley, MA, United States, Danielle F Sumy, Incorporated Research Institutions for Seismology - IRIS, Washington, United States and David Wilson, USGS Geologic Hazards Science Center, Albuquerque, United States
Direct Bayesian inversion for 2D/3D velocity structure in surface-wave tomography (383726)
Jeremy Gosselin1, Pascal Audet1 and Andrew J Schaeffer2, (1)University of Ottawa, Department of Earth and Environmental Sciences, Ottawa, ON, Canada, (2)Geological Survey of Canada, Pacific Division, Sidney, ON, Canada
Transdimensional receiver function waveform inversion (411120)
Scott Burdick, Wayne State University, Department of Environmental Science and Geology, Detroit, MI, United States, Makayla Myers, Wayne State University, Geology Department, Detroit, United States and Sarah J Brownlee, Wayne State University, Environmental Science and Geology, Detroit, Michigan, United States
Square-root variable-metric (SRVM) based null-space shuttle: a characterization of the non-uniqueness in elastic full-waveform inversion (FWI) (386832)
Qiancheng Liu and Daniel B Peter, King Abdullah University of Science and Technology, Physical Sciences and Engineering, Thuwal, Saudi Arabia
Tree based trans-D inversion of seismic data (454397)
Anandaroop Ray1, Sam Kaplan2, Uwe Albertin1 and John Washbourne2, (1)Chevron Corporation Houston, Geophysical R&D, Houston, TX, United States, (2)Chevron Corporation Houston, Houston, United States
Towards a holistic quantification of uncertainties in traveltime datasets derived from seismic reflection and refraction data (353766)
Cericia Martinez, CSIRO, Perth, WA, Australia and Juerg R Hauser, Deep Earth Imaging, CSIRO, Perth, WA, Australia
A Bayesian Approach to Sn Blockage and Left Censored Data Imputation in the Middle East (369813)
Hongjun Hui1, Eric A Sandvol2, Haya Aldossary3 and Scott H. Holan3, (1)University of Missouri Columbia, Columbia, MO, United States, (2)University of Missouri, Department of Geological Sciences, Columbia, United States, (3)University of Missouri, Columbia, MO, United States
Trans-dimensional Inversion and Uncertainty Quantification in Seabed Geoacoustics (436015)
Stan E Dosso1, Jan Dettmer2, Charles William Holland3, Josee Belcourt1, Julien Bonnel4, Dag Tollefsen5 and David P Knobles6, (1)University of Victoria, School of Earth and Ocean Sciences, Victoria, BC, Canada, (2)University of Calgary, Department of Geoscience, Calgary, AB, Canada, (3)Pennsylvania State University, University Park, PA, United States, (4)Woods Hole Oceanographic Institution, Applied Ocean Physics & Engineering, Woods Hole, MA, United States, (5)Norwegian Defence Research Establishment, Tonsberg, Norway, (6)KSA, LLC, Austin, TX, United States
Estimating near-surface explosion yield and its uncertainty using regional seismic envelopes (438643)
Seung-Hoon Yoo, Weston Geophysical Corp., Lexington, MA, United States and Sean Ricardo Ford, Lawrence Livermore National Laboratory, Livermore, CA, United States

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