Student Research is an important part of the undergraduate and graduate experience.  Dr. Bedle advises several student research projects at both levels, tailoring projects to take advantage of the student’s talents and interests.  These projects range from machine learning to seismic attribute analysis, and include seismic interpretation and petrophysical aspects.

For Fall 2022 admission, Dr. Bedle has VERY limited funding for graduate RAs.  Ideally, looking for someone interested in algorithm coding (python) for their RA work.

Graduate Students

  • Ahmet Alyaz  (MS Fall 2021)
    • Depth vs Time migrated Seismic Attributes
  • Alex Vera   (PhD Spring 2023)
    • GANs, rock physics and other cool stuff..
  • Carl Buist (PhD Spring 2023)
    • Subseismic characterization of Devonian Reefs in the Michigan Basin, improving geophysics education, CNN for fossil identification
  • Karelia La Marca Molina (PhD Spring 2023)
    • Machine learning and geothermal
  • Laura Lucia Ortiz ( MS Fall 2022)
    • Stratigraphic analysis of Cenozoic carbonate deposition in the Carnavron Basin, Northwestern Australia
    • Seismic attribute enhanced machine learning of the Permian Basin
  • Emily Jackson (PhD Spring 2025)
  • Marcus Mass (PhD Spring 2025)
  • Mario Ballinas (MS Spring 2023)


Undergraduate Students

Alumni of the SDA/AASPI group

  • Roberto Clairmont (MS Spring 2021)
    • Seismic Attribute Identification through Waveform Analysis, Attenuation
  • Jose Pedro Mora Ortiz (MS Spring 2021)
    • Virtual Reality applications for geophysical research and education
  • Edimar Perico (MS Spring 2021)
  • Clayton Silver (MS Spring 2021)
    • Rock physics and Channel morphology in the Taranaki Basin
  • Julian Chenin (MS Fall 2020)
    • Machine learning applications for gas hydrates
  • Christ Ramos Sanchez (UG Spring 2021)
    • Deepwater channel morphology in the carbonate-rich Carnavron Basin off Northwestern Australia
  • Karen Leopoldino Oliveira (visiting PhD 2019-2020)
  • Diana Salazar Florez (intern summer 2020)
    • KNN ML for seismic facies analysis
  • Pete Reilly (Spring 2020)
    • Multi-attribute attribute machine learning methods for imaging internal clinoform structures and lithology (2019-2020)
    • Statistical Characterization of Shallow Subsurface Structure in Oklahoma using well-log data (2018-2019)