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boundaries where continental lithosphere is obstructing subduction.
Most of our knowledge about the physical structure and the chemical composition of the Earth's deep interior is inferred from seismic data. The interpretation of seismic waves generally follows the assumption that the Earth's physical structure is grossly layered and that fluctuations of the physical parameters within individual layers are smooth in structure and small in magnitude. While this view greatly facilitates the analytic and interpretative procedure, it is clearly at odds with evidence from outcrops and boreholes, which indicates that compositional, structural and petrophysical heterogeneity in the Earth prevails over a wide range of scales. This book is the first to unify three different views of crustal and upper mantle heterogeneity. It brings together the geological view, which is derived from the analysis of crustal exposures and deep boreholes; the stochastic view, which attempts to find order and structure in these seemingly chaotic data; and the seismological view, which considers the end product of the complex interaction of seismic energy with the heterogeneous structure at depth. John Goff and Klaus Holliger have compiled chapters that explore and quantify the relationship between geological and petrophysical heterogeneity and its seismic response, and use seismic data to probe the fabric of the Earth's interior. Geologists, geostaticians, and geophysicists alike will benefit from the integrative perspective presented in Heterogeneity in the Crust and Upper Mantle: Nature, Scaling, and Seismic Properties, making this text an unparalleled reference for professionals and students in Earth science fields.
We have constructed a model of the three-dimensional velocity structure in the crust and upper mantle beneath NTS. This model was obtained by inversion of teleseismic travel times from NTS explosions reported for a set of globally distributed seismograph stations. Although the geometry is conceptually the reciprocal of the classical geometry involving a localized network and distributed teleseismic sources, several important differences emerge. In particular, the data are contaminated by different error processes, and different correction terms need be applied to the raw travel time data. We present algorithms which take advantage of the large number of raw data initially available to improve to some extent the signal-to-noise ratio, and lead to a reduction of the inverse problem to computationally manageable size. In addition, we show how projection operators can be used to formulate an equivalent inverse problem with smaller dimensions which is insensitive to unknown baseline corrections and similar nuisance parameters. Finally, we develop an algorithm which permits further reduction in problem size by grouping redundant data with minimal loss of information and with further noise reduction.