Trends In Nuclear Explosion Monitoring Research Development PDF Download

The last ten 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 June 6 and 7, 2007 in Berkeley, California. The workshop brought together academic, government and industry leaders in the research programs developing 3D seismic models and methods for the nuclear explosion monitoring and seismic ground motion hazard communities. The workshop was designed to assess the current state of work in 3D seismology and to discuss a path forward for determining if and how 3D Earth models and techniques can 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. In order to meet this level of scrutiny and maintain operational robustness requirements, only mature technologies are considered for operational monitoring systems, and 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 Monitoring Practice below). Empirical relationships or corrections to predictions are often used to account for unmodeled phenomena, such as the generation of S-waves from explosions or the effect of 3-dimensional Earth structure on wave propagation. This approach produces fast and accurate predictions in areas where empirical observations are available. However, accuracy may diminish away from empirical data. Further, much of the physics is wrapped into an empirical relationship or correction, which limits the ability to fully understand the physical processes underlying the seismic observation. Every generation of seismology researchers works toward quantitative results, with leaders who are active at or near the forefront of what has been computationally possible. While recognizing that only a 3-dimensional model can capture the full physics of seismic wave generation and propagation in the Earth, computational seismology has, until recently, been limited to simplifying model parameterizations (e.g. 1D Earth models) that lead to efficient algorithms. What is different today is the fact that the largest and fastest machines are at last capable of evaluating the effects of generalized 3D Earth structure, at levels of detail that improve significantly over past efforts, with potentially wide application. Advances in numerical methods to compute travel times and complete seismograms for 3D models are enabling new ways to interpret available data. This includes algorithms such as the Fast Marching Method (Rawlison and Sambridge, 2004) for travel time calculations and full waveform methods such as the spectral element method (SEM; Komatitsch et al., 2002, Tromp et al., 2005), higher order Galerkin methods (Kaser and Dumbser, 2006; Dumbser and Kaser, 2006) and advances in more traditional Cartesian finite difference methods (e.g. Pitarka, 1999; Nilsson et al., 2007). The ability to compute seismic observables using a 3D model is only half of the challenge; models must be developed that accurately represent true Earth structure. Indeed, advances in seismic imaging have followed improvements in 3D computing capability (e.g. Tromp et al., 2005; Rawlinson and Urvoy, 2006). Advances in seismic imaging methods have been fueled in part by theoretical developments and the introduction of novel approaches for combining different seismological observables, both of which can increase the sensitivity of observations to Earth structure. Examples of such developments are finite-frequency sensitivity kernels for body-wave tomography (e.g. Marquering et al., 1998; Montelli et al., 2004) and joint inversion of receiver functions and surface wave group velocities (e.g. Julia et al., 2000).