Retrieving robust noise-based seismic velocity changes from sparse data sets: synthetic tests and application to Klyuchevskoy volcanic group (Kamchatka)

Abstract

Continuous noise-based monitoring of seismic velocity changes provides insights into volcanic unrest, earthquake mechanisms and fluid injection in the subsurface. The standard monitoring approach relies on measuring traveltime changes of late coda arrivals between daily and reference noise cross-correlations, usually chosen as stacks of daily cross-correlations. The main assumption of this method is that the shape of the noise correlations does not change over time or, in other terms, that the ambient-noise sources are stationary through time. These conditions are not fulfilled when a strong episodic source of noise, such as a volcanic tremor, for example, perturbs the reconstructed Green's function. In this paper, we propose a general formulation for retrieving continuous time-series of noise-based seismic velocity changes without the requirement of any arbitrary reference cross-correlation function (CCF). Instead, we measure the changes between all possible pairs of daily cross-correlations and invert them using different smoothing parameters to obtain the final velocity change curve. We perform synthetic tests in order to establish a general framework for future applications of this technique. In particular, we study the reliability of velocity change measurements versus the stability of noise CCFs. We apply this approach to a complex data set of noise crosscorrelations at Klyuchevskoy volcanic group (Kamchatka), hampered by loss of data and the presence of highly non-stationary seismic tremors.

A quest for unrest in multiparameter observations at Whakaari/White Island volcano, New Zealand 2007–2018

“…6b). We do not interpret the results during the 2012-13 eruptive sequence as they could be contaminated by eruptive tremor sources (Gómez-García et al 2018). The results for the different combinations of components (EN, EZ and ZN, where Z is the vertical component) are provided in Additional file 7: Figure S7.…”

Seismic Velocity Change Patterns Along the San Jacinto Fault Zone Following the 2010 M7.2 El Mayor‐Cucapah and M5.4 Collins Valley Earthquakes

“…The high similarity of results obtained with 𝛽 values between 1 and 7 days shows that the final dv∕v time series are not sensitive to variations within this range. Significant differences occur only if 𝛽 is varied over a wide range (Brenguier et al, 2014;Gómez-García et al, 2018). The value employed does not degrade the daily resolution and hence does not affect the discussion of the transient onset.…”

Short‐ and Long‐Term Variations in the Reykjanes Geothermal Reservoir From Seismic Noise Interferometry

“…With ongoing production over a large area and various injection wells in the RGS, it is challenging to identify time-lapse changes in the coda associated with well operations. To ensure that our results are unbiased by the choice of the reference function, we use all three methods that are currently discussed in the literature to detect time-lapse changes: time evolution of waveform similarity (e.g., D'Hour et al, 2015 ;SÁnchez-Pastor et al, 2018), stretching method (e.g., Brenguier et al, 2011;Hadziioannou et al, 2011;Obermann et al, 2014), and a generalized formulation of the moving window cross-spectral (MWCS) (Brenguier et al, 2014;Gómez-García et al, 2018). The first two methods require a noise response reference of the medium to quantify changes, which is calculated by stacking days with the highest production rate (excluding the days 210-300/2014).…”

“…In monitoring studies with long seismic records, seasonal variations are typically observed (e.g., Gómez-García et al, 2018;Sens-Schönfelder & Wegler, 2006) and typically related to seasonal variations of the ocean noise directivity (Juretzek & Hadziioannou, 2016;Stutzmann et al, 2009), which affect the ballistic waves of the cross correlations (e.g., Froment et al, 2010;Hadziioannou et al, 2011). However, the effects of the seasonal variations are expected to be mostly homogeneous since the study area is very small.…”