This event has ended. Create your own event → Check it out
This event has ended. Create your own
View analytic
Thursday, March 3 • 11:10am - 11:30am
Facilities, Infrastructure & Visualization: Big Seismic Data: Increase Performance for HPC and Interpretation, and Reduce Infrastructure Cost

Sign up or log in to save this to your schedule and see who's attending!


Oil companies and service companies amass seismic data at the rate of hundreds of terabytes or petabytes per year. Driven by an increase in resolution and new acquisition methods, seismic data sets are larger than ever before. As a consequence, data storage system sales is the fastest growing segment according to official numbers.
Another consequence is that the internal networks quickly become a bottleneck. As users require access to increasingly larger datasets, whether pre-stack or post-stack, networks are constantly overloaded. We will present a new software-based approach to significantly improve storage capacity and simultaneously increase effective network bandwidth between central storage and consumers of seismic data. The described approach does not require upgrades or modifications to hardware, and thus enables the oil company or service company to leverage previous investments. Compared to commonly available commercial software, Hue’s implementation is approximately 25 times faster on compression and more than 200 times faster on decompression. This speed ensures that the overhead of compression and decompression is minimized. In fact it becomes a lot faster to access compressed data than the original data, providing a significant I/O boost to any application using the compressed data. As will be described, the proposed approach is generally transparent to end users.

avatar for Michele Isernia

Michele Isernia

VP Strategy & Alliances, Hue Technology N.A
Ideas and Innovation grounded to global business development, mostly in "enterprise" type businesses.

Thursday March 3, 2016 11:10am - 11:30am
BioScience Research Collaborative Building (BRC), Room 103

Attendees (10)