Reflection imaging with earthquake sources and dense arrays

Abstract

The Mw 5.8 earthquake that occurred in Louisa County, Virginia, on 23 August 2011 provided an opportunity to record with several “high density” seismic arrays, in addition to traditional, sparse temporary seismic networks. Traditional aftershock networks consist of a few dozen stations spread over tens of kilometers. As a result, the recorded seismic waveforms suffer from spatial aliasing that is so severe that many types of waveform processing are not applicable. Here we report the results of recording with a large number of oil industry‐type instruments deployed at a spacing that is an order of magnitude closer than in traditional deployments. The objective was to image subsurface structure with array methods, using the aftershocks as sources. The dense array recorded continuously for 12 days and consisted of 172 vertical component seismometers that were placed at 200–400 m and a 60 km long three‐component regional profile with stations every 2 km. We demonstrate how processing techniques from Vertical Seismic Profiling can produce high‐resolution 3‐D reflection images of structure beneath the array. These images display reflectivity that correlates with that observed on a nearby deep reflection survey collected by the U.S. Geological Survey. Of particular interest is a strong reflector imaged across multiple profiles. Our analysis demonstrates how a surface array of seismometers can provide 3‐D images of structure using microearthquake sources when wavefields are sampled sufficiently densely.

The 2015 Gorkha Earthquake: Earthquake Reflection Imaging of the Source Fault and Connecting Seismic Structure With Fault Slip Behavior

“…As shown in previous studies (e.g., Nakagawa et al, 2005;Quiros et al, 2017), conventional common midpoint processing cannot be applied to earthquake data because the reflection point does not lie at the midpoint between source and receiver, so we applied the Common Reflection Point (CRP) transformation as used in Vertical Seismic Profiling (Nakagawa et al, 2005;Quiros et al, 2017). As shown in previous studies (e.g., Nakagawa et al, 2005;Quiros et al, 2017), conventional common midpoint processing cannot be applied to earthquake data because the reflection point does not lie at the midpoint between source and receiver, so we applied the Common Reflection Point (CRP) transformation as used in Vertical Seismic Profiling (Nakagawa et al, 2005;Quiros et al, 2017).…”

“…As shown in previous studies (e.g., Nakagawa et al, 2005;Quiros et al, 2017), conventional common midpoint processing cannot be applied to earthquake data because the reflection point does not lie at the midpoint between source and receiver, so we applied the Common Reflection Point (CRP) transformation as used in Vertical Seismic Profiling (Nakagawa et al, 2005;Quiros et al, 2017). Although previous studies (Nakagawa et al, 2005;Quiros et al, 2017) applied the CRP transformation using a 1-D velocity model, we applied the CRP transformation to the aftershock data set using a tomography-derived 3-D P wave velocity model. Reflection points and their relevant traveltime from earthquake source to receiver were calculated using a 3-D finite difference traveltime algorithm (Hole & Zelt, 1995).…”

The future of passive seismic acquisition

“…This was a message emphasized by many other speakers. Larry Brown (Cornell University) showed how dense arrays allow reflection seismic methods, normally relying on expensive explosive seismic sources, to be applied using natural earthquake sources (Quiros et al 2017). Brandon Schmandt (University of New Mexico) highlighted the varied uses of these networks, looking at temporal changes in river and groundwater transport (Schmandt et al 2017 figure 2) and imaging on crustal and lithospheric scales.…”

The Future of Broadband Passive Seismic Acquisition

“…This was a message repeated by many other speakers. Larry Brown (Cornell University) showed how dense arrays allow reflection seismic methods, normally relying on expensive explosive seismic sources, to be applied by using natural earthquake sources (Quiros et al, 2017). Brandon Schmandt (University of New Mexico) highlighted the varied use of these networks, looking at temporal changes in river and groundwater transport (Schmandt et al, 2017), seismic imaging (Ranasinghe et al, 2018),monitoring volcanoes (Glasgow et al, 2018) (Figure 2) and imaging on crustal and lithospheric scales.…”