Unsupervised Clustering of Continuous Ambient Noise Data to Get Higher Signal Quality in Seismic Surveys

Abstract

Seismic interferometry has been shown to extract body wave arrivals from ambient noise seismic data. However, surface waves dominate ambient noise data, so cross-correlating and stacking all available data may not succeed in extracting body wave arrivals. A better strategy is to find portions of the data in which body wave energy dominates and to process only those portions. One challenge is that passive seismic recordings comprise huge volumes of data, so identifying portions with strong body-wave energy could be difficult or time-consuming. We use spatio-temporal features, calculated with data recorded by all receivers together, to perform unsupervised clustering. Using data recorded by a dense seismic array in Sweetwater, TX we were able to identify five clusters, representing a subsets of the complete dataset that contain similar features, and extract a 7 km/s body wave arrival from one cluster. This arrival did not emerge when we performed the same cross-correlation and stacking regimen on the entire dataset.

The Edge of Exploration: An Edge Storage and Computing Framework for Ambient Noise Seismic Interferometry Using Internet of Things Based Sensor Networks

“…Results for each time window are “stacked” (summed) to increase the signal-to-noise ratio and produce a “virtual source gather”, which is an estimate of the Green’s function for subsurface structure beneath the sensor array [ 27 , 28 , 29 , 30 , 31 , 32 , 33 ]. Recent deployments of sensor networks have comprised thousands of stations in remote areas with limited access to the Internet [ 31 , 34 ]. Such deployments could benefit greatly from IoT-enabled wireless sensor networks capable of processing data in the field due to the fact that, while traditional seismic techniques need only record a specified time window following a known seismic source, ANSI results require the processing and stacking of many hours (or days or weeks) of data to reveal low-amplitude waves.…”