A pioneering computational method developed by researchers at UT Austin now enables scientists to use surface mapping data to create detailed images of the Earth’s interior. This breakthrough offers valuable insights into geological processes and earthquake mechanisms, marking a major advancement in Earth sciences.
Researchers at The University of Texas at Austin have revolutionized the way scientists can observe the Earth’s subsurface. Introducing a groundbreaking computational method called “deformation imaging,” this advanced technique harnesses surface data from technologies like GPS, radar and laser scanning to reveal intricate details about the Earth’s crust and mantle, areas crucial for understanding geological processes.
“Material properties like rigidity are critical to understand the different processes that occur in a subduction zone or in earthquake science in general,” Simone Puel, the method’s developer, said in a news release.
Puel, who pursued this project during graduate studies at the UT Austin Jackson School of Geosciences, emphasized the potential of combining this technique with other methods to create comprehensive mechanical models of earthquakes.
“When combined with other techniques like seismic, electromagnetic or gravity, it should be possible to actually produce a much more comprehensive mechanical model of an earthquake in a way that has never been done before,” she added.
Currently a postdoctoral scholar at the California Institute of Technology, Puel published the foundational theory for this method earlier this year. A subsequent study, published in the June issue of Science Advances, showcased the technique using GPS data from Japan’s 2011 Tohoku earthquake, generating subsurface images up to 100 kilometers underground. These images revealed key tectonic and volcanic structures beneath the Pacific Ring of Fire, notably identifying a deep magma reservoir using only surface data — a scientific first.
The technique leverages the Earth’s heterogeneous crust, consisting of materials with varying elasticity that deform unevenly under stress. By simulating the Earth as an elastic material with variable strength in three dimensions, the model calculates subsurface rigidity from the relative movement of GPS sensors during seismic events, producing a 3D depiction of the Earth’s interior.
An exciting aspect of this method is its compatibility with satellite measurements, including data from NASA’s forthcoming NISAR spacecraft. This joint mission with the Indian Space Research Organization promises high-resolution global mapping every 12 days, potentially transforming the way scientists monitor and understand geologically active regions.
Thorsten Becker, a professor at the Jackson School and a co-author of the study, highlighted the method’s promise for monitoring earthquake faults continuously, enhancing our understanding of the earthquake cycle.
Another co-author, Omar Ghattas from the UT Austin Walker Department of Mechanical Engineering and UT Austin Oden Institute for Computational Engineering and Sciences, noted that this advancement could pave the way for creating digital twins of the Earth. These sophisticated models would dynamically integrate new observations to refine and enhance predictive capabilities.
The study included contributions from Dunyu Liu, a computational geoscientist at the University of Texas Institute for Geophysics, and Umberto Villa, a research scientist at the Oden Institute.
This pioneering approach marks a significant leap in Earth sciences, promising to enrich our comprehension of the planet’s inner workings and potentially mitigate the risks associated with seismic activities.