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Journal ArticleDOI

Generalized Nonlinear Inverse Problems Solved Using the Least Squares Criterion

Albert Tarantola, +1 more
- 01 May 1982 - 
- Vol. 20, Iss: 2, pp 219-232
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TLDR
In this article, a general definition of the nonlinear least squares inverse problem is given, where the form of the theoretical relationship between data and unknowns may be general (in particular, nonlinear integrodierentia l equations).
Abstract
We attempt to give a general definition of the nonlinear least squares inverse problem. First, we examine the discrete problem (finite number of data and unknowns), setting the problem in its fully nonlinear form. Second, we examine the general case where some data and/or unknowns may be functions of a continuous variable and where the form of the theoretical relationship between data and unknowns may be general (in particular, nonlinear integrodierentia l equations). As particular cases of our nonlinear algorithm we find linear solutions well known in geophysics, like Jackson’s (1979) solution for discrete problems or Backus and Gilbert’s (1970) a solution for continuous problems.

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Citations
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Book ChapterDOI

3-D Structural geological models: Concepts, methods, and uncertainties

TL;DR: This chapter provides an entry point to recent developments in geological modeling methods, helps researchers in the field to better consider uncertainties, and supports the integration of geological observations and knowledge in geophysical interpretation, modeling and inverse approaches.
Journal ArticleDOI

Splitting Functions of Long-Period Normal Modes of the Earth

TL;DR: In this paper, a nonlinear inverse problem of estimating the splitting coefficients, cst, using, as data, observed spectra of the multiplet for an array of sources and receivers is solved by an iterative, least squares procedure in which the individual data are the complex spectral values obtained by Fourier transformation of windowed, long-period accelerograms from the International Deployment of Accelerometers (IDA) network.
Journal ArticleDOI

On the bulk composition of the lower mantle: Predictions and limitations from generalized inversion of radial seismic profiles

TL;DR: In this paper, the problem of obtaining the thermal structure and bulk chemical composition of the lower mantle from its seismologically determined velocity and density profiles, and the most recent results on the elastic properties of the relevant phases (including, of particular importance, shear moduli) was examined.
Journal ArticleDOI

Rupture process of the 1983 Japan Sea (Akita-Oki) earthquake using a waveform inversion method

TL;DR: In this paper, the rupture process of the 1983 Japan Sea earthquake (MJMA = 7.7) is determined by applying waveform inversion of displacement-type, strong motion records based on the Bayesian method.
Journal ArticleDOI

Earthquake locations and three‐dimensional fault zone structure along the creeping section of the San Andreas fault near Parkfield, CA: Preparing for SAFOD

TL;DR: In this article, the authors find high-Vp/Vs anomalies that correlate with low-resistivity features in a magnetotelluric model that are interpreted to represent fluids and locate a magnitude 2 earthquake that is a potential target event for the final stage of SAFOD drilling.
References
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Book

Linear statistical inference and its applications

TL;DR: Algebra of Vectors and Matrices, Probability Theory, Tools and Techniques, and Continuous Probability Models.
Journal ArticleDOI

Uniqueness in the Inversion of Inaccurate Gross Earth Data

TL;DR: In this article, it was shown that a given set G of measured gross Earth data permits such a construction of localized averages, and if so, how to find the shortest length scale over which G gives a local average structure at a particular depth if the variance of the error in computing that local average from G is to be less than a specified amount.
Journal ArticleDOI

The general linear inverse problem - Implication of surface waves and free oscillations for earth structure.

TL;DR: In this paper, the discrete general linear inverse problem is reduced to a set of m equations in n unknowns and a linear combination of the eigenvectors of the coefficient matrix can be used to determine parameter resolution and information distribution among the observations.