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Wednesday, March 2 • 4:10pm - 4:30pm
Data Analytics Approaches & Tools: Applying Big Data Analytics to Seismic Interpretation

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Machine Learning including deep learning is the core technology in big data analytics. The petroleum industry is one of the big data domains that are facing the challenges of rapidly increasing volume and velocity of data. In this paper, we attempt to demonstrate the applicability of machine learning technology in identifying geological features from seismic data volumes. We compare the differences between traditional methods and machine learning methods in our test cases. We also present our seismic data analytics platform built on top of Hadoop and Spark to provide a productive and scalable platform to facilitate the work of tackling the big data challenges.

Speakers
avatar for Ted Clee

Ted Clee

President, TEC Applications Analysis
Ted is active in the development of seismic applications on parallel distributed systems.
LH

Lei Huang

Assistant Professor, Prairie View A&M University



Wednesday March 2, 2016 4:10pm - 4:30pm
BioScience Research Collaborative Building (BRC), Room 103

Attendees (11)