Obtaining an accurate “picture” of the subsurface is not as simple as snapping a picture on a smartphone. Seismic exploration is a key component to creating images of the subsurface and finding essential minerals and oil and gas. The process of building images of the subsurface is akin to ultrasound technology used to image the human body. One of the best known physics-based methods to create geologically-accurate images of the subsurface is called full-waveform inversion (FWI). It is a process by which we can take raw seismic data and through applying an iterative physics-based approach recreate the velocities of sound waves in the subsurface (which can be understood as an image). However, one of the challenges of this physics-based approach is that it is computationally expensive and it typically relies heavily on a good initial velocity model that is close to the answer.

In this webinar, Ben and Kelli will walk you through how they quickly trained a neural network with PyTorch on the latest 4th Gen Intel® Xeon® processor, going directly from seismic data to a subsurface model and bypassing the need for an accurate starting model.

Instructions: You can sit back and watch the show or try out the steps along with the presenters. Either way, we’d like to have you join us! To work along with them, you can set up a free Intel® Developer Cloud account at cloud.intel.com.