rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Estimation of Impedance Using Seismic Reflection Data Based on Transdimensional Inversion
  name:
    name part: Dadi, Sireesh Kumar
    role:
      role term: creator
    role:
      role term: author.
  name:
    name part: Gibson, Richard L.
    role:
      role term: thesis advisor.
  name:
    name part: Texas A & M University
    role:
      role term: degree granting institution.
  type of resource: text
  genre: bibliography
  origin info:
    place:
      place term: txu
    date issued: 2015
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: remote
    extent: 1 online resource.
  abstract: Deterministic seismic inversion can obtain optimal results when there is a linear relationship between data and model parameters during local optimization (single optimum solution). For nonlinear geophysical problems and in the presence of multiple local minima for a cost function, global optimization techniques are necessary to characterize the global minimum solution. Stochastic, model-based seismic inversion is a widely used global optimization technique and Markov Chain Monte Carlo (MCMC) method is a natural choice to sample model parameters during the random walk. In this dissertation, I apply a sampling technique called reversible jump Markov Chain Monte Carlo (rjMCMC) to traverse the model space. A key property of this approach is that it automatically changes the layer thicknesses and number of layers, thereby predicting the optimum number of model parameters during inversion. The method applies Bayesian inversion, with rjMCMC sampling, so that it also quantifies the uncertainty in model parameters based on an ensemble of models. I apply Bayesian inversion with rjMCMC sampling for two applications. In the first application, I define upscaling velocity logs as an inversion problem to obtain optimal models and quantify uncertainty of upscaled models at the well location. The upscaled velocity at the well locations can be subsequently used to stabilize velocity inversion during Full waveform Inversion (FWI) for seismic imaging purposes. In the second application, I perform post-stack seismic inversion to obtain shallow impedance structure of the TAMU and Ori volcanoes at the Shatsky Rise oceanic plateau. Since impedance is a rock property, it is used to discriminate basalt rock types, which gives insight into the late-stage evolution of both the volcanoes. The electronic version of this dissertation is accessible from http://hdl.handle.net/1969.1/152595
  note: by Sireesh Kumar Dadi.
  note: "Major Subject: Geophysics"
  note: Includes vita.
  note: Doctor of Philosophy Texas A & M University 2014 http://hdl.handle.net/1969.1/152595
  note: Includes bibliographical references.
  note: Text (Dissertation)
  subject:
    topic: Major Geophysics
  subject:
    topic: Reversible jump MCMC
  subject:
    topic: Bayesian inversion
  subject:
    topic: Well log upscaling
  subject:
    topic: Shatsky Rise
  identifier: http://hdl.handle.net/1969.1/152595
  record info:
    record content source: TXA
    record creation date: 150203
    record change date: 20151206125637.0
    record identifier: in00003500005
    language of cataloging:
      language term: eng