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Wiggins, SM, Dorman LM, Cornuelle BD, Hildebrand JA.  1996.  Hess Deep rift valley structure from seismic tomography. Journal of Geophysical Research-Solid Earth. 101:22335-22353.   10.1029/96jb01230   AbstractWebsite

We present results from a seismic refraction experiment conducted across the Hess Deep rift valley in the equatorial east Pacific. P wave travel times between seafloor explosions and ocean bottom seismographs are analyzed using an iterative stochastic inverse method to produce a velocity model of the subsurface structure. The resulting velocity model differs from typical young, fast spreading, East Pacific Rise crust by approximately +/-1 km/s with slow velocities beneath the valley of the deep and a fast region forming the intrarift ridge. We interpret these velocity contrasts as lithologies originating at different depths and/or alteration of the preexisting rock units. We use our seismic model, along with petrologic and bathymetric data from previous studies, to produce a structural model. The model supports low-angle detachment faulting with serpentinization of peridotite as the preferred mechanism for creating the distribution and exposure of lower crustal and upper mantle rocks within Hess Deep.

Wiggins, SM, Dorman LM, Cornuelle BD.  1997.  Topography can affect linearization in tomographic inversions. Geophysics. 62:1797-1803.   10.1190/1.1444280   AbstractWebsite

Linearized inverse techniques commonly are used to solve for velocity models from traveltime data. The amount that a model may change without producing large, nonlinear changes in the predicted traveltime data is dependent on the surface topography and parameterization. Simple, one-layer, laterally homogeneous, constant-gradient models are used to study analytically and empirically the effect of topography and parameterization on the linearity of the model-data relationship. If, in a weak-velocity-gradient model, rays turn beneath a valley with topography similar to the radius of curvature of the raypaths, then large nonlinearities will result from small model perturbations. Hills, conversely, create environments in which the data are more nearly linearly related to models with the same model perturbations.