A Global-Local Experience of 2D Acoustic FWI on a Real Data Set

Galuzzi, Bruno G.; Tognarelli, Andrea; Stucchi, E.

doi:10.3997/2214-4609.201800887

Cited by 1 publication

(1 citation statement)

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“…Global optimization methods (GOMs) have presented themselves as an alternative to estimate a starting model for Full Waveform Inversion (FWI) -even when using real data (Galuzzi et al, 2018). GOMs are an interesting choice since a proper parameterization technique coupled with sufficient computing power allow for a reduction of the time and effort required to build an initial estimate of the velocity model.…”

Section: Introductionmentioning

confidence: 99%

Towards automatically building starting models for full-waveform inversion using global optimization methods: A PSO approach via DEAP + Devito

Mojica

Kukreja

2019

SEG Technical Program Expanded Abstracts 2019

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In this work, we illustrate an example of estimating the macromodel of velocities in the subsurface through the use of global optimization methods (GOMs). The optimization problem is solved using DEAP (Distributed Evolutionary Algorithms in Python) and Devito, python frameworks for evolutionary and automated finite difference computations, respectively. We implement a Particle swarm optimization (PSO) with an "elitism strategy" on top of DEAP, leveraging its transparent, simple and coherent environment for implementing of evolutionary algorithms (EAs). The high computational effort, due to the huge number of cost function evaluations (each one demanding a forward modeling step) required by PSO, is alleviated through the use of Devito as well as through parallelization with Dask. The combined use of these frameworks yields not only an efficient way of providing acoustic macro models of the P-wave velocity field (V p ), but also significantly reduces the amount of human effort in fulfilling this task.

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Section: Introductionmentioning

confidence: 99%