Spatial and temporal multiplet analysis for identification of dominant fluid migration path at The Geysers geothermal field, California

Multiplet analysis is based on the identification of seismic events with very similar waveforms which are used then to enhance seismological analysis e.g. by precise relocation of sources. In underground fluid injection conditions, it is a tool frequently used for imaging of subsurface fracture system. We identify over 150 repeatedly activated seismic sources within seismicity cluster induced by fluid injection in NW part of The Geysers geothermal field (California). Majority of multiple events (ME) occur along N–S oriented planar structure which we interpret as a fault plane. Remaining ME are distributed along structures interpreted as fractures, forming together a system of interconnected cracks enabling fluid migration. Temporal analysis reveals that during periods of relatively low fluid injection the proportion of ME to non-multiple events is higher than during periods of high injection. Moreover, ME which occur within the fault differ in activity rate and source properties from ME designating the fractures and non-multiple events. In this study we utilize observed differences between ME occurring within various structures and non-multiple events to describe hydraulic conditions within the reservoir. We show that spatial and temporal analysis of multiplets can be used for identification and characterization of dominant fluid migration paths.

Remote hydroacoustic-infrasonic detection and characterization of Anak Krakatau eruptive activity leading to, during, and following the December 2018 flank collapse and tsunami

A climactic eruption phase on December 22, 2018, triggered the collapse of the southwest flank and summit of Anak Krakatau stratovolcano, generating a tsunami which struck the coastlines of Sumatra and Java. We employ a selection of remote moored hydroacoustic (H08S, 3307 km; H01W, 3720 km) and infrasonic (IS06, 1156 km; IS07, 3475 km; IS52, 3638 km) stations of the International Monitoring System (IMS) to investigate eruptive activity preceding, during, and after the climactic eruption phase. We observe 6 months of co-eruptive intermittent infrasound at IS06 and powerful infrasound from the climactic eruption on IS06 and IS52. The climactic eruption phase was not detected hydroacoustically, but we observe a ~ 12-day swarm of hydroacoustic signals beginning 24 days before the flank collapse event that we attribute to sustained submarine eruptive activity at Anak Krakatau. We perform hydroacoustic waveform and envelope multiplet analysis to assess event similarity during the hydroacoustic swarm. Hydroacoustic waveforms are not well-correlated, but envelopes with a main pulse duration of ~ 20-s are correlated, with 88.7% of 247 events grouping into two multiplets using a threshold correlation coefficient of 0.75. The repetitive envelopes indicate a repetitive impulsive volcanic process, either underwater submarine explosions or volcanic earthquakes in the solid Earth coupled to the water column from the Sunda Shelf. This study further underscores the potential of remote acoustic technology for detecting and characterizing eruptions at submarine or partially submerged volcanoes.

Silent VLPs At Stromboli: Implications For Slug Vs. Plug

<p>Very long period (VLP) seismic signals observed in volcanic environments are thought to be produced by magma and gas flow through conduits. Stromboli Volcano, Italy, typically produces hundreds of VLPs per day. These have been generally attributed to the flow of gas slugs through the shallow plumbing system and thus linked to the mechanism thought to drive Strombolian explosions. During a 6-day-long seismo-acoustic campaign in May 2018 (a period characterized by relatively low activity) we recorded 1900+ seismic events, the majority of which have significant energy in the VLP (2-100 s) band. We used a coincident STA/LTA trigger to identify seismic events in continuous waveform data and then used the PeakMatch algorithm (Rodgers et al., 2015) to identify seismic multiplets, with a focus on VLPs. To identify explosions, we applied the same coincident trigger to infrasound data, and manually identified gas jetting events using spectrograms and high-pass-filtered (20 Hz) waveforms. </p><p> </p><p>We identified ~250 explosions and ~600 jetting events. Seismic multiplet analysis identified two main families of repeating events. Family 1 (F1) has over 500 events and Family 2 (F2) has over 150 events based on a 0.7 correlation threshold. We find that F1 VLPs coincide in time with ~6% of explosions and ~0.8% of jetting events and F2 VLPs coincide in time with ~28% of explosions and ~2.7% of jetting events (we term these “silent VLPs”). These VLPs do not correspond with lava effusion (Marchetti and Ripepe, 2005; Ripepe et al., 2015). F2 have a higher dominant period (8-10 s) compared to F1 (3-4 s). The repeating VLPs are part of a broadband signal and the higher frequencies start after the VLP. VLP peak amplitudes are generally larger for F1 events. The dip of the VLP particle motion roughly locates the F1 and F2 VLP source centroids beneath the active crater and are stable throughout the dataset. Both VLP displacements show a small outward, large inward, and subsequent large outward motion from the crater. The lack of explosions relative to repeating VLPs does not support the slug model, where a slug rises through a conduit, generates a VLP through interactions with changes in conduit geometry, and then bursts at the lava free surface. Our observations support the plug model (Suckale et al., 2016). We suggest the “silent” VLPs are generated when the gas bubbles interact with and move into the semipermeable plug. Then the plug behaves as a mechanical filter for gas escape and allows for passive and explosive escape mechanisms.</p>

Relocation of clustered earthquakes in the Groningen gas field

Previous locations of earthquakes induced by depletion of the Groningen gas field were not accurate enough to infer which faults in the reservoir are reactivated. A multiplet analysis is performed to identify clusters of earthquakes that have similar waveforms, representing repeating rupture on the same or nearby faults. The multiplet analysis is based on the cross-correlation of seismograms to assess the degree of similarity. Using data of a single station, six earthquake clusters within the limits of the Groningen field were identified for the period 2010 to mid-2014. Four of these clusters were suitable for a relocation method that is based on the difference in travel time between the P- and the S-wave. Events within a cluster can be relocated relative to a master event with improved accuracy by cross-correlating first arrivals. By choosing master events located with a new dense seismic network, the relocated events likely not only have better relative, but also improved absolute locations. For a few clusters with sufficient signal-to-noise detections, we show that the relocation method is successful in assigning clusters to specific faults at the reservoir level. Overall, about 90% of the events did not show clustering, despite choosing low correlation thresholds of 0.5 and 0.6. This suggests that different faults and/or fault segments with likely varying source mechanisms are active in reservoir sub-regions of a few square kilometres.

Measuring couplings in crowded NMR spectra: pure shift NMR with multiplet analysis

Integrating the PSYCHE method for pure shift NMR into 2D J spectroscopy allows each multiplet in a complex proton NMR spectrum to be cleanly extracted.