An AI natural language processing approach is able to predict future fault friction and the next failure time with high resolution in laboratory earthquakes. The technique applies AI to the fault’s acoustic signals and goes beyond by predicting aspects of the future state of the fault’s physical system.
“The acoustic signals emitted by the laboratory fault contain foreshadowing information about the future fundamental physics of the system through the entire earthquake cycle and beyond, as we now show,” said Paul Johnson, author of the paper. “That’s never been seen before.”
“The deep-learning transformer model we used is synonymous with a language translation model, such as Google Translate, using a codebook to translate a sentence to a different language,” said Chris Johnson, co-author of the paper. “You can think about this as writing an email in English and having the AI translate the English to Japanese while also anticipating your words and autofilling the end of the sentence.”
“Now we are making a future prediction from past data, which is beyond describing the instantaneous state of the system. The model is learning from the waveforms to predict the future fault friction and when the next slip event will occur using only past information, without using any data from the future time step of interest,” said Chris Johnson.
https://phys.org/news/2022-10-ai-physics-future-fault-laboratory.html