Laura Pyrak-Nolte

Laura Pyrak-Nolte

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Laura J. Pyrak-Nolte is a distinguished professor of the department of physics and astronomy in the College of Science at Purdue University. She holds courtesy appointments in the Lyle School of Civil Engineering and in the department of Earth, atmospheric and planetary sciences also in the College of Science. Currently she is the vice-president for North America for the International Society of Rock Mechanics and Rock Engineering, past-president of the International Society for Porous Media and past-president of the American Rock Mechanics Association. Pyrak-Nolte is a member of the National Academy of Engineering, a fellow of the American Association for the Advancement of Science, a fellow of the American Geophysical Union, recipient of the Reginald Fessenden Award from the Society of Exploration Geophysicists and a fellow of the American Rock Mechanics Association. Her interests include applied geophysics, experimental and theoretical seismic wave propagation, laboratory rock mechanics, micro-fluidics, particle swarms and fluid flow through Earth materials.


Video Presentation


  • 61251 The modern energy economy often relies on the injection and withdrawal of fluids through fracture networks in rock. Whether for geothermal systems or the sequestration of anthropogenic waste (e.g. CO2), knowledge of the fracture system geometry and how it responds to perturbations in stress and fluid chemistry is crucial for safe and sustainable long-term management of a site. While many geophysical methods can locate and delineate fractures or faults, there is a need to extract physically measurable parameters that are directly linked to hydraulic and mechanical properties of fractures. I will present what we have learned from active and passive monitoring of fractures in the laboratory to illuminate and characterize fractures and an example of machine learning to identified changes in fluid saturation within a fracture set. Illuminating Fractures: Geophysics and Machine Learning
    Illuminating Fractures: Geophysics and Machine Learning