Seismic velocity picking using Hopfield neural network

Kou-Yuan Huang*, Jia Rong Yang

*Corresponding author for this work

Research output: Contribution to journalConference article

4 Scopus citations


The Hopfield neural network (HNN) is adopted for velocity picking in the time-velocity semblance image of seismic data. A Lyapunov function is generated from the velocity picking problem. We use the gradient descent method to decrease the Lyapunov function and derive the equation of motion. According to the equation of motion, each neuron is updated until no change. The linking of the converged network neurons represents the best polyline in velocity picking. We have experiments on simulated seismic data. The picking results are good.

Original languageEnglish
Pages (from-to)5317-5321
Number of pages5
JournalSEG Technical Program Expanded Abstracts
StatePublished - 1 Jan 2015
EventSEG New Orleans Annual Meeting, SEG 2015 - New Orleans, United States
Duration: 18 Oct 201123 Oct 2011

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