No abstract

Using a simple characterization of the Linnik distribution, discrete-time processes having a stationary Linnik distribution are constructed. The processes are structurally related to exponential processes introduced by Arnold (1989), Lawrance and Lewis (1981) and Gaver and Lewis (1980). Multivariate versions of the processes are also described. These Linnik models appear to be viable alternatives to stable processes as models for temporal changes in stock prices.

Underground nuclear explosions (UNEs) produce radionuclide gases that may seep to the surface over weeks to months. The objective of this research was to quantify the impact of uncertainties in hydrologic parameters (fracture aperture, matrix permeability, porosity, and saturation) and season of detonation on the timing of gas breakthrough. Numerical sensitivity analyses were performed, with barometric pumping providing the primary driving force for gas migration, for the case of a 1 kt UNE at 400-m depth of burial. Gas arrival time was most affected by matrix permeability and fracture aperture. Gases having higher diffusivity were more sensitive to uncertainty in the rock properties. The effect of seasonality in the barometric pressure forcing was found to be important, with detonations in March the least likely to be detectable based on barometric data for Rainier Mesa, Nevada. Monte Carlo realizations were performed with all four parameters varying simultaneously to determine their interrelated effects. The Monte Carlo method was also used to predict the window of opportunity for 133 Xe detection from a 1 kt UNE at Rainier Mesa, with and without matching the model to SF 6 and 3 He data from the 1993 Non-Proliferation Experiment. Results from the data-blind Monte Carlo simulations were similar but were biased toward earlier arrival time and less likely to show detectable 133 Xe. The estimated timing of gas arrival may be used to deploy personnel and equipment to the site of a suspected UNE, if allowed under the terms of the Comprehensive Nuclear Test-Ban Treaty.

Underground nuclear weapon testing produces radionuclide gases which may seep to the surface. Barometric pumping of gas through explosion-fractured rock is investigated using a new sequentially-coupled hydrodynamic rock damage/gas transport model. Fracture networks are produced for two rock types (granite and tuff) and three depths of burial. The fracture networks are integrated into a flow and transport numerical model driven by surface pressure signals of differing amplitude and variability. There are major differences between predictions using a realistic fracture network and prior results that used a simplified geometry. Matrix porosity and maximum fracture aperture have the greatest impact on gas breakthrough time and window of opportunity for detection, with different effects between granite and tuff simulations highlighting the importance of accurately simulating the fracture network. In particular, maximum fracture aperture has an opposite effect on tuff and granite, due to different damage patterns and their effect on the barometric pumping process. From stochastic simulations using randomly generated hydrogeologic parameters, normalized detection curves are presented to show differences in optimal sampling time for granite and tuff simulations. Seasonal and location-based effects on breakthrough, which occur due to differences in barometric forcing, are stronger where the barometric signal is highly variable.

[1] Shelly et al. identified 188 low frequency earthquakes (LFEs) in a one-hour episode of tremor recorded at Japanese Hi-Net borehole stations. Later they proposed that nonvolcanic tremor may consist entirely of a sequence of LFEs. We search for additional LFEs using the subspace detector technique. This method uses a matrix of template waveforms and, via singular value decomposition, builds a set of basis vectors that, in some linear combination, can reproduce the templates or similar events that fall within the subspace. We explore the utility of the method to search for additional LFEs within the subspace spanned by our basis vectors. The results compare well with previous LFE detections. We also compare our results with an independent measure of signal polarization and find that the polarization takes on a distinct character during times of known LFEs. This suggests that signal polarization may also have potential for tremor detection, characterization, and monitoring. Citation: Maceira, M., C. A. Rowe, G. Beroza, and D. Anderson (2010), Identification of low-frequency earthquakes in non-volcanic tremor using the subspace detector method, Geophys. Res. Lett., 37, L06303,