On the Potential of 3D Transdimensional Surface Wave Tomography for Geothermal Prospecting of the Reykjanes Peninsula

Seismic travel time tomography using surface waves is an effective tool for three-dimensional crustal imaging. Historically, these surface waves are the result of active seismic sources or earthquakes. More recently, however, surface waves retrieved through the application of seismic interferometry have also been exploited. Conventionally, two-step inversion algorithms are employed to solve the tomographic inverse problem. That is, a first inversion results in frequency-dependent, two-dimensional maps of phase velocity, which then serve as input for a series of independent, one-dimensional frequency-to-depth inversions. As such, a set of localized depth-dependent velocity profiles are obtained at the surface points. Stitching these separate profiles together subsequently yields a three-dimensional velocity model. Relatively recently, a one-step three-dimensional non-linear tomographic algorithm has been proposed. The algorithm is rooted in a Bayesian framework using Markov chains with reversible jumps, and is referred to as transdimensional tomography. Specifically, the three-dimensional velocity field is parameterized by means of a polyhedral Voronoi tessellation. In this study, we investigate the potential of this algorithm for the purpose of recovering the three-dimensional surface-wave-velocity structure from ambient noise recorded on and around the Reykjanes Peninsula, southwest Iceland. To that end, we design a number of synthetic tests that take into account the station configuration of the Reykjanes seismic network. We find that the algorithm is able to recover the 3D velocity structure at various scales in areas where station density is high. In addition, we find that the standard deviation of the recovered velocities is low in those regions. At the same time, the velocity structure is less well recovered in parts of the peninsula sampled by fewer stations. This implies that the algorithm successfully adapts model resolution to the density of rays. It also adapts model resolution to the amount of noise in the travel times. Because the algorithm is computationally demanding, we modify the algorithm such that computational costs are reduced while sufficiently preserving non-linearity. We conclude that the algorithm can now be applied adequately to travel times extracted from station–station cross correlations by the Reykjanes seismic network.

On the Potential of 3D Transdimensional Surface Wave Tomography for Geothermal Prospecting of the Reykjanes peninsula

Seismic travel time tomography using surface waves is an effective tool for three-dimensional crustal imaging. Historically, these surface waves are the result of active seismic sources or earthquakes. More recently, however, also surface waves retrieved through the application of seismic interferometry are exploited. Conventionally, two-step inversion algorithms are employed to solve the tomographic inverse problem. That is, a first inversion results in frequency-dependent, two-dimensional maps of phase velocity, which then serve as input for a series of independent, one-dimensional frequency-to-depth inversions. As such, a two-dimensional grid of localized depth-dependent velocity profiles are obtained. Stitching these separate profiles together subsequently yields a three-dimensional velocity model. Relatively recently, a one-step three-dimensional non-linear tomographic algorithm has been proposed. The algorithm is rooted in a Bayesian framework using Markov chains with reversible jumps, and is referred to as transdimensional tomography. Specifically, the three-dimensional velocity field is parameterized by means of a polyhedral Voronoi tessellation. In this study, we investigate the potential of this algorithm for the purpose of recovering the three-dimensional surface-wave-velocity structure from ambient noise recorded on and around the Reykjanes Peninsula, southwest Iceland. To that end, we design a number of synthetic tests that take into account the station configuration of the Reykjanes seismic network. We find that the algorithm is able to recover the 3D velocity structure at various scales in areas where station density is high. In addition, we find that the standard deviation on the recovered velocities is low in those regions. At the same time, the velocity structure is less well recovered in parts of the peninsula sampled by fewer stations. This implies that the algorithm successfully adapts model resolution to the density of rays. Also, it adapts model resolution to the amount of noise on the travel times. Because the algorithm is computationally demanding, we modify the algorithm such that computational costs are reduced while sufficiently preserving non-linearity. We conclude that the algorithm can now be applied adequately to travel times extracted from (time-averaged) station-station cross correlations by the Reykjanes seismic network.

Chasing Magma Around Iceland’s Reykjanes Peninsula

The Icelandic Meteorological Office has been tracking unrest near erupting Fagradalsfjall since December 2019, while researchers elsewhere explore new methods to see Iceland’s seismic swarms.

The application of geodetic observations for near-real time monitoring of Icelandic volcanoes

<p>Ground deformation is frequently one of the first detectable precursors alerting scientists to changes in behavior or the onset of unrest at active volcanoes. GNSS, InSAR, strain and tilt measurements are routinely used by volcano observatories for monitoring pre-eruptive, co-eruptive and post-eruptive deformation. In addition to monitoring signals related to magma migration, deformation observations are used as an input into geodetic modeling to determine the location and rate of magma accumulation and help define the structure of magma plumbing systems beneath active volcanoes.</p><p>This presentation will provide an update of how geodetic observations are being used in conjunction with seismicity and gas measurements, for the near-real time monitoring of key Icelandic volcanoes; to determine their current status, identify the onset and likely cause of unrest, locate magmatic intrusions, determine magma volumes and supply rates and assess the likelihood of eruption. An overview of the current status of the following active volcanoes will be provided: Hekla, Bárðarbunga and Grímsvötn, along with an update of the recent volcano-tectonic unrest on the Reykjanes Peninsula.</p><p>Hekla is one of the most active and dangerous volcanoes in Iceland with approximately 18 eruptions since 1104. Over the past few decades, Hekla erupted at almost regular ~10 year intervals, with the last four eruptions occurring in 1970, 1980–1981, 1991 and 2000. Previous geodetic studies have suggested magma storage at depths of 12-25 km directly beneath the volcanic edifice. However, recent InSAR analysis has detected a localized inflation signal to the west of the volcano. A regional borehole strain meter network has proven instrumental for real-time eruption forecasting at Hekla.</p><p>In the Bárðarbunga volcanic system, the six-month long effusive 2014-2015 Holuhraun eruption was accompanied by gradual caldera collapse of up to 65 m and was preceded by a two-week period of 48 km long lateral dyke propagation with extensive seismicity and deformation. Geodetic observations indicate that Bárðarbunga began to slowly inflate in July 2015. This may be explained by a combination of renewed magma inflow and viscoelastic readjustment of the volcano.</p><p>The Grímsvötn subglacial volcano is the most frequently erupting volcano in Iceland, with eruptions in 1998, 2004 and 2011. A GPS station shows a prominent inflation cycle prior to eruptions. Observations during the 2011 eruption suggest a pressure drop at a surprisingly shallow level (about 2 km depth) during the eruption, in a similar location as in previous eruptions. Deformation at this volcano has now surpassed that observed prior to historic eruptions and its aviation color code is currently elevated to yellow.</p><p>In December 2019, the Reykjanes Peninsula entered a phase of volcano-tectonic unrest characterized by seismic swarms, followed in late January 2020 by inflation detected in near-real time by GNSS and InSAR observations. At the time of writing (mid-January 2021) there have been three magmatic intrusions in the vicinity of Svartsengi, an intrusion beneath Krýsuvík and indications of magma migration at depth along the entirety of the Peninsula.</p>

The possible role of magma and geothermal fluid in the episodic uplift cycles and intense seismicity beneath the Svartsengi high temperature geothermal field, Iceland

<p>The highly productive high temperature geothermal fields in Iceland are located within active volcanic systems on the plate boundaries. When an earthquake swarm or an unusual surface uplift or subsidence occur, it is important to assess the hazards and whether the unrest is triggered or controlled by volcanic or anthropogenic processes, or a combination of both.</p><p>On January 22nd, 2020, a rapid, large-scale uplift (14 km x 12 km) started at the Svartsengi geothermal field on the plate boundary of the Reykjanes Peninsula, along with an intense earthquake swarm that began simultaneously about 3 km east of the centre of uplift. The centre of uplift was located about 1 km west of Mt. Thorbjörn, in the middle of the Svartsengi geothermal field, close to the reinjection wells. Over a period of 6 months, three such uplift cycles occurred, each lasting for several weeks and followed by periods of relatively rapid subsidence. The duration and timing of the uplift-subsidence cycles appears to follow a clear trend where the successive inflation episodes lasted longer but with lower inflation rate.</p><p>The centres of uplift and the deflation cycles are the same and remained stationary. The accompanied intense earthquake swarms migrated along the 40 km long oblique plate boundary of the Reykjanes Peninsula, demonstrating a major plate tectonic event. The maximum depth of earthquakes was close to 4.5 km directly above the centre of uplift but extending to 6-7 km in the surroundings where the maximum magnitudes reached M<sub>W</sub> 4.8.</p><p>A few weeks after the onset of the unrest, nine additional seismic stations were deployed to densify the local seismic network in place. In addition, complimentary data from an existing 21 km long fibre optics cable were used to monitor high-frequency linear strain rates. Both measures led to a significant improvement in the earthquake detection and location which predominantly occurred in swarms. Likewise, InSAR data analysis of temporal uplift cycles was performed, repeated gravity measurements at permanent sites were performed, and resistivity was remeasured at chosen sites.  </p><p>Multiple different elementary models were developed and tested to explain the cyclic excitation of the uplift, subsidence, and seismicity. While the individual unrest episodes might be controlled by possible magma intrusions into the lower crust, our favoured model explains the spatio-temporal pattern of ground uplift by the rise and diffusion of pore pressure in a 4-5 km deep geothermal aquifer. To distinguish between different models, we use multi-disciplinary geophysical datasets, such as deformation, seismicity, and gravity.</p>

Temporal seismic velocity changes during the 2020 rapid inflation at Mt. Thorbjorn-Svartsengi, Iceland, using ambient seismic noise

<p>The Reykjanes peninsula, SW Iceland, was struck by intense earthquake swarm activity that occurred in January-July 2020 due to repeated magmatic intrusions in the Reykjanes-Svartsengi volcanic system. GPS and InSAR observations confirmed surface deformation centered near Mt. Thorbjorn, and during the unrest period, approximately ~14,000 earthquakes (-2≤M≤4.9) were reported at the Icelandic Meteorological Office (IMO). We investigate the behavior of the crust as a response to these repeated intrusions to provide insights into volcanic unrest in the Reykjanes peninsula. Our study presents temporal seismic wave velocity variations (dv/v, in percent) based on ambient noise seismic interferometry using continuous three-component waveforms collected by IMO, (http://www.vedur.is) for the period from April 2018 to November 2020. The state-of-the-art MSNoise software package (http://www.msnoise.org) is used to calculate cross-correlations of ambient seismic noise and to quantify the relative seismic velocity variations. We observe that magmatic intrusions in the vicinity of Mt. Thorbjorn-Svartsengi have considerably reduced the seismic wave velocities (dv/v, -1%) in the 1-2 Hz frequency band. Seismic velocity changes were compared with local seismicity, GPS and InSAR data recorded close to the repeated intrusions, and modelled volumetric strain changes. We found a good correlation between the dv/v variations and the available deformation data. The Rayleigh wave phase-velocity sensitivity kernels showed that the changes occurring at depths down to ~3-4 km in the crust were captured by our measurements. We interpret the relative seismic velocity decrease to be caused by crack opening induced by intrusive magmatic activity. Monitoring the Mt. Thorbjorn-Svartsengi volcanic unrest is crucial for successful early warning of volcanic hazards since the center of uplift is only 2km away from a fishing village and major infrastructure in the area, such as water supply and geothermal power. For the first time in Iceland, we have provided near-real-time dv/v variations to obtain a more complete picture of this magmatic activity. Our findings are supported by the analysis of other primary monitoring streams. We propose that this technique may be useful for early detection of future intrusions/increased magmatic activity. This study is supported by the Icelandic Research Fund, Rannis (Grant No: 185209-051).</p>