About the guest
Heather Bedle received a B.S. (1999) in physics from Wake Forest University and later received an M.S. (2005) and a Ph.D. (2008) in geophysics from Northwestern University. After nine years of working with Chevron, she moved to academia to pursue her dream of teaching and mentoring young researchers. Currently, she is PI of the AASPI Consortium, where her research group of 20 total students have published almost 20 peer-reviewed manuscripts in the last two years. Her primary research interests include seismic interpretation, machine learning, and attribute analysis.
The topic of discussion: Seismic reflection data
Seismic reflection data can be used to study surface processes, cryosphere, hydrology, hazards, atmospheric phenomena amongst many other things.
Seismic reflection data can even help scientists forecast volcanic explosions giving them the ability to decipher the subtle signs that reveal how explosive a volcanic eruption is going to be.
While working with seismic reflection data, machine learning enables scientific computing and computational thinking skills to be implemented in many novel ways.
Research in artificial intelligence and machine learning seismic methods can be used to better understand the subsurface and paleoenvironments which is an area of expertise of our GRT Q&A series guest.
In this article, Global Road Technology discusses seismic reflection data with Assistant Professor, Heather Bedle from the University of Oklahoma in Norman, Oklahoma, USA.
