The Prospect of Using Three-Dimensional Earth Models to Improve Nuclear Explosion Monitoring and Ground-motion Hazard Assessment

The past 10 years have brought rapid growth in the development and use of three-dimensional (3D) seismic models of Earth structure at crustal, regional, and global scales. In order to explore the potential for 3D seismic models to contribute to important societal applications, Lawrence Livermore National Laboratory (LLNL) hosted a Workshop on Multi-Resolution 3D Earth Models to Predict Key Observables in Seismic Monitoring and Related Fields on 6–7 June 2007, in Berkeley, California. The workshop brought together academic, government, and industry leaders in research programs developing 3D seismic models and methods for nuclear explosion monitoring and seismic ground-motion hazard assessment. The workshop was designed to assess the current state of 3D seismology and to discuss a path forward for 3D Earth models and techniques— how can they be used to achieve measurable increases in our capabilities for monitoring underground nuclear explosions and characterizing seismic ground-motion hazards? This paper highlights some of the presentations, issues, and discussions at the workshop and proposes two specific paths by which to begin quantifying the potential contribution of progressively refined 3D seismic models in critical applied arenas. Seismic monitoring agencies are tasked with detection, location, and characterization of seismic activity in near real time. In the case of nuclear explosion monitoring or seismic hazard, decisions to further investigate a suspect event or to launch disaster relief efforts may rely heavily on real-time analysis and results. Because these are weighty decisions, monitoring agencies are regularly called upon to meticulously document and justify every aspect of their monitoring system. To meet this level of scrutiny and maintain operational robustness, only mature technologies are considered for operational monitoring systems, so operational technology necessarily lags contemporary research. Current monitoring practice is to use relatively simple Earth models that generally afford analytical prediction of seismic observables (see “Examples of Current …

[1]  Qinya Liu,et al.  Tomography, Adjoint Methods, Time-Reversal, and Banana-Doughnut Kernels , 2004 .

[2]  E. Engdahl,et al.  Finite-Frequency Tomography Reveals a Variety of Plumes in the Mantle , 2004, Science.

[3]  R. Youngs,et al.  Attenuation Relationships for Shallow Crustal Earthquakes Based on California Strong Motion Data , 1997 .

[4]  M. Pasyanos,et al.  Reconciling a geophysical model to data using a Markov chain Monte Carlo algorithm: An application to the Yellow Sea–Korean Peninsula region , 2006 .

[5]  Peter Goldstein,et al.  Building and Testing an a priori Geophysical Model for Western Eurasia and North Africa , 2004 .

[6]  M. Sambridge.  Geophysical inversion with a neighbourhood algorithm—I. Searching a parameter space , 1999 .

[7]  Nicholas Rawlinson,et al.  Simultaneous inversion of active and passive source datasets for 3‐D seismic structure with application to Tasmania , 2006 .

[8]  B. Kennett,et al.  Traveltimes for global earthquake location and phase identification , 1991 .

[9]  K. Campbell,et al.  Updated Near-Source Ground-Motion (Attenuation) Relations for the Horizontal and Vertical Components of Peak Ground Acceleration and Acceleration Response Spectra , 2003 .

[10]  Akademii︠a︡ medit︠s︡inskikh nauk Sssr.  Journal of physics , 1939 .

[11]  Chen Ji,et al.  Performance of Two 18-Story Steel Moment-Frame Buildings in Southern California during Two Large Simulated San Andreas Earthquakes , 2006 .

[12]  Michael Antolik,et al.  J 362 D 28 : a new joint model of compressional and shear velocity in the Earth ’ s mantle , 2003 .

[13]  Guust Nolet,et al.  Three-dimensional waveform sensitivity kernels , 1998 .

[14]  P. Maechling,et al.  Strong shaking in Los Angeles expected from southern San Andreas earthquake , 2006 .

[15]  Ilya N. Lomov,et al.  Simulation of hypervelocity penetration in limestone , 2006 .

[16]  Stephen C. Myers,et al.  Regional Travel-Time Uncertainty and Seismic Location Improvement Using a Three-Dimensional a priori Velocity Model , 2003 .

[17]  N. Anders Petersson,et al.  Ground-Motion Modeling of the 1906 San Francisco Earthquake, Part II: Ground-Motion Estimates for the 1906 Earthquake and Scenario Events , 2007 .

[18]  Chen Ji,et al.  A 14.6 billion degrees of freedom, 5 teraflops, 2.5 terabyte earthquake simulation on the Earth Simulator , 2003, ACM/IEEE SC 2003 Conference (SC'03).

[19]  Charles J. Ammon,et al.  Lithospheric Structure of the Arabian Shield from the Joint Inversion of Receiver Function and Surface-Wave Dispersion Observations , 2000 .

[20]  N. Abrahamson,et al.  Empirical Response Spectral Attenuation Relations for Shallow Crustal Earthquakes , 1997 .

[21]  N. Anders Petersson,et al.  Broadband Waveform Modeling of Moderate Earthquakes in the San Francisco Bay Area and Preliminary Assessment of the USGS 3D Seismic Velocity Model , 2008 .

[22]  Freeman Gilbert,et al.  The Effect of Small, Aspherical Perturbations on Travel Times and a Re-examination of the Corrections for Ellipticity , 1976 .

[23]  Gabi Laske,et al.  CRUST 5.1: A global crustal model at 5° × 5° , 1998 .

[24]  M. Dumbser,et al.  An arbitrary high-order discontinuous Galerkin method for elastic waves on unstructured meshes — II. The three-dimensional isotropic case , 2006 .

[25]  Michelle Johnson,et al.  Development and Testing of a 3D Velocity Model for Improved Event Location: A Case Study for the India-Pakistan Region , 2002 .

[26]  Keith L. McLaughlin,et al.  Validation of Regional and Teleseismic Travel-Time Models by Relocating Ground-Truth Events , 2004 .

[27]  I. Lomov,et al.  Numerical simulation of damage using an elastic-viscoplastic model with directional tensile failure , 2003 .

[28]  D. Komatitsch,et al.  The Spectral-Element Method, Beowulf Computing, and Global Seismology , 2002, Science.

[29]  Kim B. Olsen,et al.  Three-Dimensional Dynamic Simulation of the 1992 Landers Earthquake , 1997 .

[30]  Michael Pasyanos.  Reconciling data using Markov chain Monte Carlo: An application to the Yellow Sea-Korean Peninsula region , 2004 .

[31]  M. Dumbser,et al.  An arbitrary high-order discontinuous Galerkin method for elastic waves on unstructured meshes - I. The two-dimensional isotropic case with external source terms , 2006 .

[32]  Arben Pitarka,et al.  3D Elastic Finite-Difference Modeling of Seismic Motion Using Staggered Grids with Nonuniform Spacing , 1999 .

[33]  Ilya N. Lomov,et al.  Three Dimensional Simulation of the Baneberry Nuclear Event , 2004 .

[34]  David M. Boore,et al.  Peak horizontal acceleration and velocity from strong motion records including records from the 1979 Imperial Valley, California, earthquake , 1981 .

[35]  M. Sambridge,et al.  Wave front evolution in strongly heterogeneous layered media using the fast marching method , 2004 .

[36]  C. Bassin,et al.  The Current Limits of resolution for surface wave tomography in North America , 2000 .

[37]  C. H. Chapman,et al.  The computation of seismic travel times , 1983 .

[38]  Michael Antolik,et al.  J362D28: a new joint model of compressional and shear velocity in the Earth's mantle , 2003 .

[39]  Hans-Peter Harjes,et al.  Imaging crustal discontinuities and the downgoing slab beneath western Crete , 2000 .

[40]  Stefan Nilsson,et al.  Stable Difference Approximations for the Elastic Wave Equation in Second Order Formulation , 2007, SIAM J. Numer. Anal..

[41]  Craig A. Schultz,et al.  Improving Sparse Network Seismic Location with Bayesian Kriging and Teleseismically Constrained Calibration Events , 2000 .

[42]  Jeroen Tromp,et al.  Finite-frequency sensitivity kernels for global seismic wave propagation based upon adjoint methods , 2008 .

[43]  Philip J. Maechling,et al.  The SCEC Community Modeling Environment: An Information Infrastructure for System-level Earthquake Science , 2003 .

[44]  Michael E. Pasyanos,et al.  Predicting Geophysical Measurements: Testing a Combined Empirical and Model-Based Approach Using Surface Waves , 2000 .

[45]  Alan L. Jones,et al.  Of Drums and Needles...Disappearing Icons of Seismology , 2003 .

[46]  J. Tromp,et al.  Finite-Frequency Kernels Based on Adjoint Methods , 2006 .

[47]  David R. O'Hallaron,et al.  High Resolution Forward And Inverse Earthquake Modeling on Terascale Computers , 2003, SC.

[48]  Thomas M. Brocher,et al.  Compressional and Shear Wave Velocity Versus Depth in the San Francisco Bay Area, California: Rules for USGS Bay Area Velocity Model 05.0.0 , 2005 .