Bi-objective optimization for seismic survey design

Monsegny, Jorge (University of Calgary)


We use the mixed-integer nonlinear optimization algorithm called Particle Swarm Optimization and Mesh Adaptive Direct Search to optimize the design of seismic surveys. Due to the conflicting goals of obtaining a good subsurface illumination at the lowest possible cost, we apply a bi-objective optimization strategy that searches the best options in the illumination and cost senses while builds a Pareto front that shows the trade-off between illumination and cost and allows the survey designer to choose the specific amount of each one of them. The Particle Swarm Optimization part is used to escape local minima and the mixed-integer part is used to deal with integer aspects of a seismic survey design like the number of receivers and sources, to name but a few.

Presentation Date: Monday, September 25, 2017

Start Time: 3:55 PM

Location: Exhibit Hall C/D

Presentation Type: POSTER