Dr. Bedle is an Assistant Professor at the University of Oklahoma in the School of Geosciences. Her research and teaching focus on the application and development of advanced seismic interpretation. Some research stems from her time as a petroleum geophysicist using rock physics models coupled with seismic reflection data interpretation, and some from her experience as a whole-earth seismologist. All of the projects are based in her interest in understanding what lurks out-of-sight beneath our feet.
Seismic reflection data is currently the main investigative data being utilized. Current projects in her research group are combining seismic interpretation with developments in machine learning, seismic attributes, and rock physics. These methods work as compliments to aid in extracting additional information from the seismic waveforms. Additional details and recent publications can be found on the AASPI website.
Dr. Bedle also researches how scientists learn to interpret seismic data, as well as how to improve the learning process at both the academic and professional levels. New projects are being developed to improve education in active learning spaces, as well as testing the capability of virtual reality to improve seismic interpretation education and research.
Dr. Bedle is also involved in with several programs with the Society of Exploration Geophysicists (SEG). She was recently recognized as the outstanding volunteer of the year (2018) for her work with the SEG Wiki project, is the faculty mentor for OU’s first SEG Evolve team and the OU SEG Student Chapter, and is working with OU’s SEG Challenge Bowl team.
Current research projects in the SDA (Subsurface Detective Agency):
- Identifying ‘invisible’ gas hydrates to improve gas hydrate quantification
- Seismic geomorphology studies for channel development, lithology, and fluid identification
- Application of multi-dimensional seismic attribute analysis for fluid discrimination
- Machine learning applications for lithologic and fluid discrimination
- Convolutional neural network (CNN) machine learning applications for lithology and fossil identification
- Fizz-gas discrimination
- Destruction of the North China and Wyoming cratons
Future curiosities (ie. projects being formulating and seeking data or funding for student researchers):
- Kerogen quantification from seismic
- Deep gas carbonates
- Unconventional Reservoir Analysis (seeking data!)
You can find out more about Dr. Bedle and her research lab on: