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Activity Number:
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179
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Type:
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Invited
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Date/Time:
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Monday, August 7, 2006 : 2:00 PM to 3:50 PM
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Sponsor:
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WNAR
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| Abstract - #305193 |
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Title:
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Uncertainty Estimation in Geophysics
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Author(s):
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Mrinal K. Sen*+
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Companies:
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The University of Texas at Austin
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Address:
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Institute for Geophysics, Austin, TX, 78759,
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Keywords:
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geophysics ; uncertainty
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Abstract:
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Geophysical inverse problems involve estimating subsurface earth model parameters from surface measurements of noisy and inadequate geophysical data. Nonlinearity adds another degree of complexity. We employ a Bayesian formulation to estimate a posterior probability density function in model space. For practical applications, we seek a trade-off between accuracy and computational speed. A Monte Carlo importance sampling is theoretically more accurate, but the convergence rate is very slow. Alternately, we use an approximate greedy sampling algorithm based on multiple very fast simulated annealing algorithm to characterize the marginal PPD. Our numerical experiments with the inversion of resistivity and seismic waveform data reveal that the MVFSA is a useful and practical tool that provides a general framework to combine disparate data types, such as well logs and seismic and core data.
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- The address information is for the authors that have a + after their name.
- Authors who are presenting talks have a * after their name.
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