Sandia National Laboratories and Los Alamos National Laboratory partnered to develop a 3-D model of the Earth's mantle and crust called SALSA3D, or Sandia-Los Alamos 3D.
The model uses a scalable triangular tessellation and seismic tomography to map the Earth's "compressional wave seismic velocity," a property of the rocks and other materials inside the Earth that indicates how quickly compressional waves travel through them and is one way to accurately locate seismic events, Sandia geophysicist Sandy Ballard said.
SALSA3D also reduces the uncertainty in the model's predictions, an important feature for decision-makers who must take action when suspicious activity is detected, he added.
"When you have an earthquake or nuclear explosion, not only do you need to know where it happened, but also how well you know that. That's a difficult problem for these big 3-D models. It's mainly a computational problem," Ballard said.
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"The math is not so tough, just getting it done is hard, and we've accomplished that," said Ballard.
In recent tests, SALSA3D was able to predict the source of seismic events over a geographical area that was 26 per cent smaller than the traditional one-dimensional model and 9 per cent smaller than a recently developed Regional Seismic Travel Time (RSTT) model used with the one-dimensional model.
Sandia recently released SALSA3D's framework - the triangular tessellated grid on which the model is built - to other Earth scientists, seismologists and the public.
By standardising the framework, the seismological research community can more easily share models of the Earth's structure and global monitoring agencies can better test different models. Both activities are hampered by the plethora of models available today, Ballard said.
Sandia uses historical data from 118,000 earthquakes and 13,000 current and former monitoring stations worldwide collected by Los Alamos Lab's Ground Truth catalogue.
"We apply a process called seismic tomography where we take millions of observed travel times and invert them for the seismic velocities that would create that data set. It's mathematically similar to doing linear regression, but on steroids," Ballard said.