Abstract
The Moho surface, namely the density discontinuity between crust and mantle, is traditionally studied by seismic methods. However, gravity information can contribute to the Moho estimation and, more generally, to the crustal modeling. The contribution is twofold. First, gravimetry generally provides observations with much lower errors than those implied by the mass density uncertainty and other geophysical assumptions. This means that it can be used to validate existing Moho and/or crustal models by forward modeling. Second, gravity inversion is able to provide diffused (not localized) information on the mass distribution, both regionally and globally (thanks to dedicated satellite gravity missions). However, this information is weak due to its intrinsic ill-posedness. This means that it can be used to correct and spatially interpolate existing models, and to complement seismic, magnetic and geological information to create new models. In this work, the problem of estimating the Moho surface by gravity inversion assuming a two-layer model with lateral and vertical density variations is treated at a regional level. The approach consists in linearizing the forward modeling around a reference Moho at a constant depth and then inverting it through a Wiener filter. This is standard in case of two layers with homogeneous density distributions (or with lateral density variations), while it requires some additional considerations and algorithm modifications in case of vertical density variations. The basic idea is to “condensate” the masses inside the Moho undulation on the reference surface used for the linearization, thus requiring the setup of an iterative procedure. A strategy to introduce seismic information into this inversion procedure is proposed too, with the aim of improving the a priori density modeling. A closed loop test is presented for the algorithm assessment, showing the improvement with respect to a standard approach and the capability of the proposed algorithm to reconstruct the originally simulated Moho undulation by also fitting the gravity and seismic data at a level that is consistent with their observation noise.
Highlights
The boundary between the Earth crust and mantle is usually approximated by a sharp discontinuity surface, called Mohorovicić discontinuity or Moho from the name of the Croatian seismologist who discovered it in 1909 (Mohorovičić 1910)
This technique allowed the determination of averaged crustal structure over large regions, the construction of seismic sections along located seismic profiles, and in 1982 the estimation of a first global Moho map (Soller et al 1982)
The models of the CRUST series are based on seismic refraction data published from 1950, on a detailed compilation of ice and sediment thickness, and on statistical predictions for regions such as most of Africa, South America, Greenland, and oceans where no or very few seismic measurements were available
Summary
The boundary between the Earth crust and mantle is usually approximated by a sharp discontinuity surface, called Mohorovicić discontinuity or Moho from the name of the Croatian seismologist who discovered it in 1909 (Mohorovičić 1910). Li and Oldenburg 1998) These methods are usually classified as linear inverse problems, due to the linear relation between the density and the gravity signal once the geometry is known (Blakely 1996), and rely on the discretization of the density distribution by elementary bodies, such as point masses, prisms, tesseroids, etc. They had very important improvements, going from the application of several regularizations (Boulanger and Chouteau 2001) to the more complex integration with a-priori geological information in a Bayesian framework (Marchetti et al 2019; Reguzzoni et al 2019; Rossi et al 2015; Lane et al 2007).
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