Towards real-time assessment of convergence criteria in seismic interferometry: Selective stacking of cross-correlations at the San Emidio geothermal field

Abstract

Seismic field logistics, particularly recording geometry and duration, can be made significantly more efficient in ambient-noise interferometry if strategies for ensuring timely convergence of Empirical Green's Functions (EGFs) can be devised. Quantitative measures of each cross-correlation panel's constructive contribution to the final result are needed to ensure the best result with the shortest recording duration. We investigate the utility of a variety of seismic data features to improve the convergence of EGFs in ambient-noise interferometry with a dataset acquired at the San Emidio Geothermal Field, Nevada. We identify two features, “rms energy” and “kurtosis”, that succeed in distinguishing cross-correlation panels that contribute to EGF convergence from those that degrade the stacked result. Using either of these features allows us to selectively stack data and enhance signal quality at greater offsets and recover weaker arrivals than is possible by stacking all available data. The data used in this study were acquired in May 2019 by a 144-element array of 4.5 Hz geophones recorded by Reftek 130 digitizers in a configuration that was augmented by embedded processors to perform real-time, in-field processing. Such capabilities, coupled with selective stacking strategies, may help minimize the time, cost, and effort required to determine the best possible EGFs.