Jan Dettmer

Assistant Professor

Department of Geoscience

PhD

University of Victoria, 2007

Diploma

University of Hamburg, 2002

Contact information

Location

Office : ES212

Courses

  • GOPH 351 - Introduction to Geophysics
  • GOPH 671 - Inverse Theory & Applications I
  • GOPH 375 - Natural Disasters and Critical Earth Phenomena

Research and teaching

Research interests

My research interests involve the quantitative study of Earth structures and processes which can only be probed remotely through the inversion of geophysical data, and developing computational methods to truly understand data information content to resolve the Earth. I work on several geophysical inference problems across disciplines and at a variety of scales ranging from studying the fine structure of shallow Earth and seabed to ultra-low velocity zones near the core-mantle boundary.

My work includes point-source and finite-fault inversion to estimate earthquake source parameters with implications for tsunami generation, tsunami waveform inversion for initial seasurface states, teleseismic receiver-function inversion to resolve crust/upper-mantle structure, and seismic waveform inversion to study mantle and core structure. At smaller scales, my work includes seismic noise inversion for earthquake-hazard site assessment (e.g., Dettmer et al. GJI 2012), seismoacoustic inversion for seabed structure including poro-elastic effects such as sound-velocity dispersion (e.g., Dettmer et al. Geophysics 2013), and matched field inversion/full field acoustic tomography (e.g. Dettmer and Dosso 2013).

My research concentrates on developing and applying probabilistic (Bayesian) inversion methods to gain deeper understanding of Earth processes. This work is computationally intensive and includes advanced algorithm development, bridging with the statistics community, and the use of novel hardware (CPU/GPU hybrid computer clusters) to advance geophysical data analysis. Much of the numerical work is carried out on the supercomputer Raijin at the National Computational Infrastructure facility.

Geophysical inverse problems, such as the above, are inherently nonlinear and nonunique, such that a range of solutions (Earth models) may fit the data and must be rigorously accounted for in a meaningful interpretation. Simply considering optimal models (i.e., the model that best fits the observations) is insufficient to study parameter variability, where variability is a measure of the inherent spatial and/or temporal heterogeneity of a geophysical property. Rather, parameter uncertainties, which are a measure of the knowledge of an environmental parameter value, need to be considered. Uncertainty arises from observation errors and limitations in the model (e.g., theory and parametrization) to fully explain the complexity of the observations (i.e., the model approximates reality). Quantifying uncertainty is a prerequisite to studying variability and can be achieved using linear, linearized, and nonlinear probabilistic (Bayesian) methods.

Some specific keywords for my research include:

  • Seismology, acoustical oceanography: Studying the earth and ocean systems with seismic, acoustic, and geodetic measurements. In particular:
    • Earthquake-source inversion (finite-fault and moment tensor inversion with seismic phases, tsunami waveforms, and geodetic data).
    • Waveform inversion for crust, mantle, and core structure.
    • Ambient noise inversion.
    • Geoacoustic inversion for seabed structure, ambient noise geoacoustic inversion (inverting surface-wave generated ocean noise for seabed structure), full wave-field reflection coefficients.
  • Wave propagation in water, visco-elastic, and poro-viscoelastic media. In particular, computation of reflection-coefficients.
  • Natural hazards: Inversion of ambient-noise (micro tremor) recordings for shallow earth structure with applications to seismic site hazard and site amplification prediction. Tsunami-hazard prediction and early warning with advanced inference methods.
  • Inverse theory, Bayesian methods: Quantifying uncertainty of geophysical parameters, optimisation, large scale geophysical inverse problems, trans-dimensional Bayesian models, quantitative model selection and normalising constants, hierarchical Bayesian models and methods, joint inversion, advanced Markov chain Monte Carlo methods, sequential Monte Carlo methods and particle filters.

Publications

Submitted (peer-reviewed journals):

Published peer-reviewed journal articles

  • C. Sippl, A. Kumar, and J. Dettmer. A cross-correlation based approach to direct seismogram stacking for receiver side structural inversion. Bull. Seis. Soc. Am. (2017).
  • C. W. Holland, S. Pinson, C Smith, P. Hines, D. Olson, S. E. Dosso, and J. Dettmer. Seabed structure inferences from TREX13 reflection measurements. IEEE J. Ocean. Eng. (2017).
  • J. E. Quijano, S. E. Dosso, J. Dettmer and C. W. Holland. Geoacoustic inversion for the seabed transition layer using a Bernstein polynomial model. J. Acoust. Soc. Am. (2016).
  • R. Benavente, P. R. Cummins, and J. Dettmer. Rapid automated W-phase slip inversion for the Illapel great earthquake (2015, Mw = 8.3). Geophys. Res. Lett. (2016).
  • J. Dettmer, R. Hawkins, P. R. Cummins, J. Hossen, M. Sambridge, R. Hino and D. Inazu Tsunami source uncertainty estimation: the 2011 Japan Tsunami. J. Geophys. Res. (2016).
  • S. Kim, J. Dettmer, J. Rhie, and H. Tkal?i?. Efficient trans-dimensional optimization and Bayesian uncertianty estimation in joint surface wave dispersion and receiver function inversion: application for the southern Korean Peninsula. Geophys. J. Int. (2016).
  • G. A. Warner, S. E. Dosso, J. Dettmer, and D. E. Hannay. Bowhead whale localization using asynchronous hydrophones in the Chukchi Sea. J. Acoust. Soc. Am. (2016).
  • M. J. Hossen, P. R. Cummins, J. Dettmer, and T. Baba. Time Reverse Imaging for Far-field Tsunami Forecasting: 2011 Tohoku Earthquake Case Study. Geophys. Res. Lett. (2015). DOI: 10.1002/2015GL065868.
  • S. E. Dosso, J. Dettmer, and M. J. Wilmut. Efficient localization and spectral estimation of an unknown number of ocean acoustic sources using a graphics processing unit. J. Acoust. Soc. Am. 138 (2015), pp. 2945–2956. DOI: 10.1121/1.4934517.
  • S. Pachhai, J. Dettmer, and H. Tkal?ci´c. Ultra-low velocity zones beneath the Philippine and Tasman Seas revealed by a trans-dimensional Bayesian waveform inversion. Geophys. J. Int. (2015). DOI: 10.1093/gji/ggv368.
  • M. J. Hossen, P. R. Cummins, J. Dettmer, and T. Baba. Tsunami waveform inversion for the 2011 Tohoku earthquake: Importance of dispersion and source kinematics. J. Geophys. Res. (2015), pp. 1–22. DOI: 10.1002/2015JB011942.
  • J. Dettmer, S. E. Dosso, T. Bodin, J. Stip?cevi´c, and P. R. Cummins. Direct-seismogram inversion for receiver-side structure with uncertain source-time functions. Geophys. J. Int. (2015), pp. 1–18. DOI: 10.1093/gji/ggv375.
  • J. E. Quijano, S. E. Dosso, J. Dettmer, and C. W. Holland. Fast computation of seabed spherical-wave reflection coefficients in geoacoustic inversion. J. Acoust. Soc. Am. 138 (2015), pp. 2106–2117.
  • R. A. S. Gehrmann, J. Dettmer, K. Schwalenberg, M. Engels, S. E. Dosso, and Asli Özmaral. Trans-dimensional Bayesian inversion of controlled source electromagnetic data in the German North Sea. Geophys. Prosp. (2015), pp. 1–20. DOI: 10.1111/1365-2478.12308.
  • G. A. Warner, S. E. Dosso, J. Dettmer, and D. E. Hannay. Bayesian environmental inversion of airgun modal dispersion using a single hydrophone in the Chukchi Sea. J. Acoust. Soc. Am. 137 (2015), pp. 3009–3023.
  • S. Pachhai, H. Tkal?ci´c, and J. Dettmer. “Bayesian inference for ultra low velocity zones in the Earth’s lowermost mantle: Multiple-layer ULVZ confirmed beneath the east philippines”. In: J. Geophys. Res. (2014). DOI: 10.1002/2014JB011067.
  • S. E. Dosso, J. Dettmer, G. A. M. W. Steininger, and C. W. Holland. “Efficient trans-dimensional Bayesian inversion for geoacoustic profile estimation”. In: Inverse Problems 30 (2014), p. 114018.
  • G. A. M. W. Steininger, S. E. Dosso, C. W. Holland, and J. Dettmer. “A trans-dimensional polynomial-spline parameterization for gradient-based geoacoustic inversion”. In: J. Acoust. Soc. Am. 136 (2014), pp. 1563–1573.
  • G. A. M. W. Steininger, S. E. Dosso, C. W. Holland, and J. Dettmer. “Estimating seabed scattering mechanisms via Bayesian model selection.” In: J. Acoust. Soc. Am. 136 (2014), pp. 1552–1562.
  • J. Dettmer, R. Benavente, P. R. Cummins, and M. Sambridge. “Trans-dimensional finite-fault inversion”. In: Geophys. J. Int. 199 (2014), pp. 735–751.
  • G. A. M. W. Steininger, C. W. Holland, S. E. Dosso, and J. Dettmer. "Seabed roughness parameters from joint backscatter and reection inversion at the Malta Plateau". In: J. Acoust. Soc. Am. (2013), pp. 1833-1842.
  • J. Dettmer and S. E. Dosso. "Probabilistic two-dimensional water-column and seabed inversion with self-adapting parameterizations". In: J. Acoust. Soc. Am. (2013), pp. 2612-2623.
  • J. Dettmer, C. W. Holland, and S. E. Dosso. "Trans-dimensional uncertainty estimation for dispersive seabed sediments". In: Geophysics (2013).
  • C. W. Holland and J. Dettmer. Low frequency in-situ sediment dispersion estimates in the presence of discrete layers and gradients". In: J. Acoust. Soc. Am. 132 (2013), pp. 50-61.
  • G. A. M. W. Steininger, J. Dettmer, C. W. Holland, and S. E. Dosso. "Trans-dimensional joint inversion of seabed scattering and reflection data". In: J. Acoust. Soc. Am. (2013).
  • Quijano, S. E. Dosso, J. Dettmer, L. M. Zurk, M. Siderius, and C. Harrison. "Trans-dimensional geoacoustic inversion of wind-driven ambient noise". In: J. Acoust. Soc. Am. (2013), pp. EL47-EL53.
  • J. Dettmer and S. E. Dosso. "Trans-dimensional matched-field inversion with hierarchical error models and interacting Markov chains". In: J. Acoust. Soc. Am. (2012), pp. 2239-2250.
  • J. E. Quijano, S. E. Dosso, J. Dettmer, L. M. Zurk, M. Siderius, and C. Harrison. Bayesian geoacoustic inversion using wind-driven ambient noise." In: J. Acoust. Soc. Am. 131 (2012), pp. 2658-2667.
  • J. Dettmer, S. Molnar, G. A. M. W. Steininger, S. E. Dosso, and J. F. Cassidy. Trans-dimensional inversion of microtremor array dispersion data with hierarchical autoregressive error models". In: Geophys. J. Int. 188 (2012), pp. 719-734. PDF
  • C. W. Holland, P. L. Nielsen, J. Dettmer, and S. E. Dosso. Resolving meso-scale seabed variability using reflection measurements from an autonomous underwater vehicle". In: J. Acoust. Soc. Am. 131 (2012), pp. 1066-1078. PDF
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  • J. Dettmer, S. E. Dosso, and C. W. Holland. Sequential trans-dimensional Monte Carlo for range-dependent geoacoustic inversion". In: J. Acoust. Soc. Am. 129 (2011), pp. 1794-1806. PDF
  • S.E. Dosso and J. Dettmer. Bayesian matched-field geoacoustic inversion". In: Inverse Problems 27.5 (2011), p. 055009.
  • R. Guo, S.E. Dosso, J. Liu, J. Dettmer, and X. Tong. Nonlinearity in Bayesian 1-D magnetotelluric inversion". In: Geophys. J. Int. 185 (2011), pp. 663-675.
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  • J. Dettmer, S. E. Dosso, and John C. Osler. Bayesian evidence computation for model selection in geoacoustic inversion". In: J. Acoust. Soc. Am. 128 (2010), pp. 3406-3415.
  • J. Dettmer, S. E. Dosso, and C. W. Holland. "Trans-dimensional geoacoustic inversion". In: J. Acoust. Soc. Am. 128 (2010), pp. 3393-3405.
  • J. Dettmer, C. W. Holland, and S. E. Dosso. Analyzing lateral seabed variability with Bayesian inference of seabed reflection inversions". In: J. Acoust. Soc. Am. 126 (2009), pp. 56-69.
  • [7] J. Dettmer, S. E. Dosso, and C. W. Holland. Model selection and Bayesian inference for high resolution seabed reflection inversion". In: J. Acoust. Soc. Am. 125 (2009), pp. 706-716.
  • J. Dettmer, S. E. Dosso, and C. W. Holland. Joint time/frequency-domain inversion of reflection data for seabed geoacoustic proles". In: J. Acoust. Soc. Am. 123 (2008), pp. 1306-1317.
  • J. Dettmer, S. E. Dosso, and C. W. Holland. Full wave-field reflection coefficient inversion. In: J. Acoust. Soc. Am. 122 (2007), pp. 3327-3337.
  • J. Dettmer, S. E. Dosso, and C. W. Holland. Uncertainty estimation in seismo-acoustic reflection travel-time inversion". In: J. Acoust. Soc. Am. 122 (2007), pp. 161-176.
  • [3] C. Vanelle, J. Dettmer, and D. Gajewski. Second-order interpolation of later-arrival travel-times". In: Geophys. Prosp. 54 (2006), pp. 167-176.
  • C. W. Holland, J. Dettmer, and S. E. Dosso. Remote sensing of sediment density and velocity gradients in the transition layer". In: J. Acoust. Soc. Am. 118 (2005), pp. 163-177.
  • C. W. Holland, J. Dettmer, and S. E. Dosso. A technique for measuring in-situ compressional wave velocity dispersion in marine sediments". In: IEEE J. Ocean. Eng. 30 (2005), pp. 748-763

Conference proceedings:

  • J. Dettmer, S. E. Dosso, and C. W. Holland. “Exploiting data parallelism and population Monte Carlo on massively-parallel architectures for geoacoustic inversion”. In: Proc. Meet. Acoust. 19 (2013). Invited. DOI:10.1121/1.4799784.
  • J. Dettmer and S. E. Dosso. “Probabilistic two dimensional joint water-column and seabed inversion”. In: Proc. Meet. Acoust. 19 (2013). Invited. DOI: 10.1121/1.4800601.
  • S. E. Dosso and J. Dettmer. “Efficient Bayesian multi-source localization using a graphical processing unit”. In: Proc. Meet. Acoust. 19 (2013). DOI: 10.1121/1.4800527.
  • S. E. Dosso and J. Dettmer. “Studying the sea with sound”. In: Proc. Meet. Acoust. 19 (2013). Invited plenary lecture. DOI: 10.1121/1.4798952.
  • * G. A. M. W. Steininger, S. E. Dosso, C. W. Holland, and J. Dettmer. “Seabed roughness parameters for the Malta Plateau from joint backscatter and reflection inversion”. In: Proc. Meet. Acoust. 19 (2013). DOI: 10.1121/1.4800717.
  • * G. A. M. W. Steininger, J. Dettmer, S. E. Dosso, and C. W. Holland. “Geoacoustic inversion via trans-dimensional sampling over seabed and error models”. In: Proc. Meet. Acoust. 19 (2013). DOI: 10.1121/1.4801339.
  • J. E. Quijano, S. E. Dosso, and J. Dettmer. “A Bayesian framework for geoacoustic inversion of wind-driven ambient noise in shallow water”. In: Can. Acoust. 40 (2012), pp. 80–81.
  • * G. A. M. W. Steininger, J. Dettmer, C. W. Holland, and S. E. Dosso. “Simulation study of joint trans-dimensional Bayesian inversion of scattering and reflection data”. In: Can. Acoust. 32 (2012), pp. 82–83.
  • J. Dettmer, S. E. Dosso, and C. W. Holland. “Geoacoustic inversion with strongly correlated errors.” In: Can. Acoust. 32 (2004), pp. 194–195.
  • M. J. Wilmut, S. E. Dosso, and J. Dettmer. “Data error estimation in matched-field geoacoustic inversion”. In: Can. Acoust. 32 (2004), pp. 192–193.