New 3D parallel SGILD modeling and inversion

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In this paper, a new parallel modeling and inversion algorithm using a Stochastic Global Integral and Local Differential equation (SGILD) is presented. The authors derived new acoustic integral equations and differential equation for statistical moments of the parameters and field. The new statistical moments integral equation on the boundary and local differential equations in domain will be used together to obtain mean wave field and its moments in the modeling. The new moments global Jacobian volume integral equation and the local Jacobian differential equations in domain will be used together to update the mean parameters and their moments in the ... continued below

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17 p.

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Xie, G.; Li, J. & Majer, E. September 1, 1998.

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Description

In this paper, a new parallel modeling and inversion algorithm using a Stochastic Global Integral and Local Differential equation (SGILD) is presented. The authors derived new acoustic integral equations and differential equation for statistical moments of the parameters and field. The new statistical moments integral equation on the boundary and local differential equations in domain will be used together to obtain mean wave field and its moments in the modeling. The new moments global Jacobian volume integral equation and the local Jacobian differential equations in domain will be used together to update the mean parameters and their moments in the inversion. A new parallel multiple hierarchy substructure direct algorithm or direct-iteration hybrid algorithm will be used to solve the sparse matrices and one smaller full matrix from domain to the boundary, in parallel. The SGILD modeling and imaging algorithm has many advantages over the conventional imaging approaches. The SGILD algorithm can be used for the stochastic acoustic, electromagnetic, and flow modeling and inversion, and are important for the prediction of oil, gas, coal, and geothermal energy reservoirs in geophysical exploration.

Physical Description

17 p.

Notes

OSTI as DE98059389

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  • 18. annual international conference on predictability quantifying uncertainty in models of complex phenomena, Los Alamos, NM (United States), 11-15 May 1998

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  • Other: DE98059389
  • Report No.: LBNL--42252
  • Report No.: CONF-9805106--
  • Grant Number: AC03-76SF00098
  • Office of Scientific & Technical Information Report Number: 676981
  • Archival Resource Key: ark:/67531/metadc710929

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Office of Scientific & Technical Information Technical Reports

Reports, articles and other documents harvested from the Office of Scientific and Technical Information.

Office of Scientific and Technical Information (OSTI) is the Department of Energy (DOE) office that collects, preserves, and disseminates DOE-sponsored research and development (R&D) results that are the outcomes of R&D projects or other funded activities at DOE labs and facilities nationwide and grantees at universities and other institutions.

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  • September 1, 1998

Added to The UNT Digital Library

  • Sept. 12, 2015, 6:31 a.m.

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  • Nov. 6, 2015, 4:07 p.m.

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Xie, G.; Li, J. & Majer, E. New 3D parallel SGILD modeling and inversion, article, September 1, 1998; United States. (digital.library.unt.edu/ark:/67531/metadc710929/: accessed December 11, 2017), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.