Methods: Visualization
Fields: Earth Science

Project lead: Aleksandr Y. Aravkin (website)

Co-authors: Rajiv Kumar, Oscar López, Damek Davis, Aleksandr Y. Aravkin, Felix J. Herrmann

Collaborators: Dmitriy Drusvyatskiy (UW) and Tristan van Leeuwen (Utrecht)

Overview

An illustration of the scale of the fully sampled 5D seismic data volumeGeophysical exploration, reservoir characterization, and subsurface imaging are all examples of seismic inverse problems. These problems are extremely large scale: model parameters of interest are typically gridded parameter values over a 3-dimensional mesh. Data for these problems are collected over several  months, and literally carried by the truck-full for processing.

Using low-rank nonconvex optimization formulations we can interpolate 80% missing seismic data, obtaining full data volumes from severely under-sampled sources. These volumes are used for further processing and imaging at a fraction of the cost. Some of the results are included below.

For a preprint, please see: http://arxiv.org/abs/1607.02624

An illustration of seismic data after removing 80% jittered sources

 

 

 

 

 

An illustration of seismic data