A 3D GEOLOGIC FRAMEWORK MODEL OF THE SOURCE PHYSICS EXPERIMENT (SPE) PHASE I TEST BED

One of the current challenges in the field of monitoring and verification is source discrimination of low-yield nuclear explosions from background seismicity, both natural and anthropogenic. Work is underway at the Nevada National Security Site to conduct a series of chemical explosion experiments using a multi-institutional, multifaceted, multi-disciplinary approach. The goal of this series of experiments, called the Source Physics Experiments (SPE), is to refine the understanding of the effect of earth structures on source phenomenology and energy partitioning in the source region, the transition of seismic energy from the near field to the far field, and the development of S waves observed in the far field. To fully explore these problems, the SPE series includes tests in both hard and soft rock geologic environments. The project comprises a number of activities, which range from characterizing the shallow subsurface to acquiring new explosion data from both the near field (< 100 m) and the far field (> 100 m to 10 km). The current series (SPE Phase I) is being conducted in a highly fractured, well-characterized granite body (Climax stock). This series includes a total of 7 planned explosions (with different yields and depths of burials), which are conducted in the same hole and monitored by a diverse set of sensors recording characteristics of the explosions, ground-shock, seismo-acoustic energy propagation and permanent strain deformation at the surface. This approach has the distinct advantage of allowing the use of a single test bed to obtain a consistent data set where the phenomenology can be directly compared between tests. This presentation reviews the development of a 3D geologic framework model, which will provide a common input for near and far field numerical modeling and simulations. An existing hydrostratigraphic model has been converted into a seismo-stratigraphic model to be used for the base input of the model. Inputs also include high-resolution geophysical and geologic data such as materials properties data to inform the meshes used for the simulations. Ultimately, the results from this project will provide the next advances in the science of monitoring to enable a physics-based predictive capability. This work was conducted under Contract No. DE-AC52-06NA25946 with the U.S. Department of Energy.