HR: 0800h
AN: T51C-0702    [Abstracts]
TI: Applying Pattern Informatics to Southern California to Image Fault Systems in Three Dimensions
AU: * Perlock, P A
EM: paperloc@uwo.ca
AF: Department of Earth Sciences, University of Western Ontario, Biological and Geological Sciences Bldg 1151 Richmond St., London, ON N6A 5B7, Canada
AU: Tiampo, K F
EM: ktiampo@uwo.ca
AF: Department of Earth Sciences, University of Western Ontario, Biological and Geological Sciences Bldg 1151 Richmond St., London, ON N6A 5B7, Canada
AU: Rundle, J B
EM: rundle@geology.ucdavis.edu
AF: Center for Computational Science and Engineering, University of California, Davis One Shields Avenue, Davis, CA 95616, United States
AB: The Pattern Informatics (PI) method (Tiampo et al., 2002) quantifies spatio-temporal variations in the seismicity of a seismogenic region, yielding a long term forecast for the locations of future earthquakes in the form of a 2-D "hotspot" map. There is an inherent link between changes in seismicity measured by the PI method and changes in the stress on a fault system. As stress accumulates on a fault, the probability of an earthquake occurring on that fault increases resulting in hotspots. Because stress tends to build preferentially on fault, the hotspots should also be preferentially located on fault, outlining its structure. It is for this reason that we propose that the PI method is not only valid for forecasting earthquakes, but can also be used to image heterogeneous stress regions on a fault surface. Here we explore applications of the 3-D PI method to multiple regions in southern California and the potential sources of error. Ultimately, our results show that adding a third dimension to the PI method is both a valid way to forecast future earthquakes at depth, as well as image the underlying fault system.
DE: 4460 Pattern formation
DE: 7223 Earthquake interaction, forecasting, and prediction (1217, 1242)
DE: 7230 Seismicity and tectonics (1207, 1217, 1240, 1242)
SC: Tectonophysics [T]
MN: 2007 Fall Meeting