Thursday, June 19

9:45 AM-11:45 AM
Weavers Room

MS39
Optimization Methods in Geophysics

Geophysical parameter estimation is essential for solving the inverse problem. The large number of parameters of subsurface models make optimization methods attractive. This session addresses the use of gradient schemes, linear and non-linear programming, expert systems, simulated annealing, and genetic algorithms. The applications include signal processing, deconvolution, statics corrections, velocity analysis, and other aspects of geophysical inverse theory.

Organizers: Mrinal K. Sen and Jake Aggarwal
University of Texas, Austin

9:45 A Neural Network Optimization Approach to Automate Velocity Estimation for NMO Correction
Carlos Calderon-Macias, University of Texas, Austin; Mrinal K. Sen, Organizer; and Paul L. Stoffa, University of Texas, Austin
10:15 Gene Expression Messy Genetic Algorithms: Foundations and Sub-Quadratic Performance
Hillol Kargupta, Los Alamos National Laboratory
10:45 Title to be announced
Joydeep Ghosh, University of Texas, Austin; and Jake Aggarwal, Organizer
11:15 Title and speaker to be announced

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TJF, 4/30/97
MMD, 5/5/97