Vincenzo Lipari

vlipari@ogs.it

I am a senior researcher at the National Institute of Oceanography and Applied Geophysics - OGS, a leading Italian research institute in geosciences and environmental sciences. I apply my expertise in signal processing, inverse problems, machine learning, and applied mathematics to develop innovative solutions for the exploration and monitoring of natural resources and geological hazards.

My goal is to achieve advancements in geophysical signal processing, exploration seismology and mathematical modeling, while contributing to the sustainable development and management of the Earth’s resources and environment.

news

Jan 15, 2016	A simple inline announcement with Markdown emoji!
Nov 07, 2015	A long announcement with details
Oct 22, 2015	A simple inline announcement.

latest posts

Jan 27, 2024	a post with code diff
Jan 27, 2024	a post with advanced image components
Jan 27, 2024	a post with vega lite

selected publications

Equivariant imaging for self-supervised regularly undersampled seismic data interpolation

Weiwei Xu , Vincenzo Lipari, Paolo Bestagini , and 3 more authors

In SEG International Exposition and Annual Meeting , 2022

Abs

Because of the restriction of complex field conditions and economic circumstance, seismic data is usually undersampled in the spatial domain, which needs to be interpolated to meet the requirements of following seismic data processing such as seismic imaging. We present a seismic data interpolation method via an end-to-end self-supervised deep learning framework. Specifically, a CNN is trained only using the observed undersampled seismic data itself. Furthermore, based on the equivariance of seismic data with respect to shift and undersampling, a training strategy that enforces both the measurement consistency and the equivalence is utilized. Experiments on regularly undersampled synthetic and field data interpolation show the effectiveness of our presented method in comparison with deep image prior (DIP) based interpolation method.