Detection of Subtle Hydromechanical Medium Changes Caused By a Small-Magnitude Earthquake Swarm in NE Brazil

Abstract

Abstract-Ambient noise correlation analyses are largely used in seismology to map heterogeneities and to monitor the temporal evolution of seismic velocity changes associated mostly with stress field variations and/or fluid movements. Here we analyse a small earthquake swarm related to a main m R 3.7 intraplate earthquake in North-East of Brazil to study the corresponding post-seismic effects on the medium. So far, post-seismic effects have been observed mainly for large magnitude events. In our study, we show that we were able to detect localized structural changes even for a small earthquake swarm in an intraplate setting. Different correlation strategies are presented and their performances are also shown. We compare the classical auto-correlation with and without pre-processing, including 1-bit normalization and spectral whitening, and the phase auto-correlation. The worst results were obtained for the pre-processed data due to the loss of waveform details. The best results were achieved with the phase cross-correlation which is amplitude unbiased and sensitive to small amplitude changes as long as there exist waveform coherence superior to other unrelated signals and noise. The analysis of 6 months of data using phase auto-correlation and cross-correlation resulted in the observation of a progressive medium change after the major recorded event. The progressive medium change is likely related to the swarm activity through opening new path ways for pore fluid diffusion. We further observed for the auto-correlations a lag time frequency-dependent change which likely indicates that the medium change is localized in depth. As expected, the main change is observed along the fault.

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

“…It is useful to note that the PCC is not affected by large amplitudes and does not require any preprocessing that could yield a loss of information in terms of waveform distortion (Schimmel et al, , ). PCC has been successfully employed in other noise‐based monitoring and imaging studies (e.g., D'Hour et al, ; Romero & Schimmel, ; SÁnchez‐Pastor et al, ).…”

“…The lack of seismic records during a “calm period” causes a strong variability of the seismic medium response. Thus, we focus on the waveform similarity evolution (D'Hour et al, ; SÁnchez‐Pastor et al, ) and time‐lapse changes in velocity (e.g., Brenguier et al, ; Hadziioannou et al, ; Obermann et al, ) using different methods to ascertain the robustness of our findings. We propose a new procedure to discriminate potential changes in time and frequency of such evolution curves through the computation of the S transform (Stockwell et al, ).…”

Single‐station monitoring of volcanoes using seismic ambient noise

“…The technique is also applicable to single stations, using one (or all) component of a one‐component (or three‐component) seismometers. The single‐station approach has been successfully applied to study earthquakes [ Sens‐Schönfelder and Wegler , ; Wegler and Sens‐Schönfelder , ; Hobiger et al ., ; Nakahara , ; D'Hour et al ., ].…”

“…The cross‐correlation (CC) technique has been extensively described over the past decade, with many available reviews [e.g., Larose et al ., ; Bensen et al ., ; Wapenaar et al ., , ; Sens‐Schönfelder and Wegler , ]. Seismic velocity variation measurements using the CC technique are used for monitoring [ Snieder and Hagerty , ; Brenguier et al ., ; Hadziioannou et al ., ] with applications for volcanoes [e.g., Sens‐Schönfelder and Wegler , ; Duputel et al ., ; Mordret et al ., ; Caudron et al ., ], large magnitude earthquakes in the far field [ Wegler and Sens‐Schönfelder , ; Brenguier et al ., ; Ohmi et al ., ; Wegler et al ., ; Hobiger et al ., ; Minato et al ., ], and smaller magnitude earthquakes at smaller distances [ Maeda et al ., ; D'Hour et al ., ]. In most cases, relative velocity changes have been evidenced using a large number of stations and of station pairs.…”

Rushan earthquake swarm in eastern China and its indications of fluid-triggered rupture

“…Fluid-driven earthquake swarms have been studied from a number of perspectives (Legrand et al 2011;Horálek and Š ílený 2013;Leclère et al 2013;Braunmiller et al 2014;D'Hour et al 2016;Schultz et al 2015). The prevailing consensus is that such swarms are triggered by the rupture of a zone containing confined high-pressure aqueous fluid into a preexisting crustal fault system, which prompts release of accumulated stress (Shelly et al 2013a, b).…”