SM5.4
Advances in the understanding of the crustal structure through passive and active seismological methodologies

SM5.4

EDI
Advances in the understanding of the crustal structure through passive and active seismological methodologies
Co-organized by EMRP2
Convener: Sergio GammaldiECSECS | Co-conveners: Leonardo ColavittiECSECS, Marco Firetto Carlino, Federica LanzaECSECS, Ortensia Amoroso
Presentations
| Thu, 26 May, 13:20–14:50 (CEST)
 
Room 0.16

Presentations: Thu, 26 May | Room 0.16

Chairpersons: Sergio Gammaldi, Leonardo Colavitti, Ortensia Amoroso
13:20–13:26
13:26–13:36
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EGU22-5048
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solicited
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Highlight
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On-site presentation
Simone Pilia, Mohammed Ali, Mike Searle, Anthony Watts, Brook Keats, and Tyler Ambrose

The Semail ophiolite, a thick thrust sheet of Late Cretaceous oceanic crust and upper mantle, was obducted onto the previously rifted Arabian continental margin in the Late Cretaceous, and now forms part of the United Arab Emirates (UAE)-Oman mountain belt. A deep foreland basin along the west and SW margin of the mountains developed during the obduction process, as a result of flexure due to loading of the ophiolite and underlying thrust sheets. Structural and compositional complexities (e.g., presence of thick sand dunes, relatively shallow high-velocity and dense ophiolite structure) have made geophysical imaging of the sub-ophiolite and mid-lower crustal structure particularly challenging.

A combination of active and passive-source seismic techniques, potential field modelling and surface geological mapping are used to constrain the stratigraphy, velocity structure and crustal thickness beneath the UAE-Oman mountains and its bounding basins. Depth-migrated multichannel seismic-reflection profile data are integrated in the modeling of traveltimes from long offset reflections and refractions, which are used to resolve the crustal thickness and velocity structure along two E-W onshore/offshore transects in the UAE. Additionally, we apply receiver function and virtual deep seismic sounding methods to distant earthquake data recorded along the two transects to image crustal thickness variations. Seismic and geological constraints from the transects have been finally used to model gravity and magnetic anomaly data along two coincident profiles.

Geophysical methods define the Semail ophiolite as a high-velocity, high density, > 15 km thick body dipping to the east. The western limit of the ophiolite is defined onshore by the Semail thrust while the eastern limit extends several km offshore, where it is defined seismically by a ~40–45° normal fault. Emplacement of the ophiolite has probably flexed down a previously rifted continental margin, thus contributing to subsidence of flanking sedimentary basins. The new crustal thickness model presented in this work provides evidence that a crustal root is present beneath the Semail ophiolite, suggesting that folding and thrusting during the obduction process may have thickened the pre-existing crust by 16 km.

How to cite: Pilia, S., Ali, M., Searle, M., Watts, A., Keats, B., and Ambrose, T.: An integrated geophysical approach for imaging of the Semail ophiolite, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5048, https://doi.org/10.5194/egusphere-egu22-5048, 2022.

13:36–13:42
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EGU22-12205
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ECS
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Presentation form not yet defined
Harry Telajan Linang, Amy Gilligan, Jennifer Jenkins, Simone Pilia, Tim Greenfield, Nicholas Rawlinson, Pepen Supendi, Felix Tongkul, and Sri Widiyantoro

The Southeast Asia (SEA) region is tectonically very active as it accommodates the northward movement of the Indo-Australian plate in the south and the westward movement of the Philippine Sea plate in the east. Borneo and Sulawesi are located in the centre of SEA, which is our area of interest. Borneo has an intraplate setting, while Sulawesi is situated above several microplate boundaries. For that reason, Sulawesi is seismically and volcanically more active than Borneo. The tectonic link and evolution between the two islands are not well understood as we are missing some fundamental knowledge, such as the variations in their crustal thickness and structure. This includes the provenance of their respective lithosphere, which may have Eurasian and/or East Gondwana origin.

Here, we show the results obtained from the receiver function (RF) study on seismic stations in the region to have a better understanding of the crust and mantle lithosphere beneath the two islands. The RF study includes H-k stacking, time-depth migration of the RF and inversion to estimate crustal thickness and the shear speed variation with depth. The finding from this study shows that the crust in Sulawesi is much more complex than that of Borneo. The crustal thickness gradually changes throughout Borneo, with northern Borneo having an overall thicker crust than other parts of the island. In Sulawesi, the crustal thickness is much more varied across small distances, especially along the northern and southern arms of the island.

We also show some results from the Virtual Deep Seismic Sounding (VDSS) method, which we only applied to the seismic stations in northern Borneo. We used VDSS on Northern Borneo to learn more about its complex tectonic history, such as the two subduction episodes and a continent-continent collision in a recent geological time scale. Our finding reveals a band of alternating thick and thin crust striking NE-SW in this region, which we believed resulted from extensional tectonics related to the Sulu Sea basin opening in the Miocene.

How to cite: Linang, H. T., Gilligan, A., Jenkins, J., Pilia, S., Greenfield, T., Rawlinson, N., Supendi, P., Tongkul, F., and Widiyantoro, S.: Variation of crustal thickness in Borneo and Sulawesi, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12205, https://doi.org/10.5194/egusphere-egu22-12205, 2022.

13:42–13:48
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EGU22-6878
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ECS
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On-site presentation
Shubham Agrawal, Caroline Eakin, and John O'Donnell

A blanket of sedimentary and regolith material covers approximately three-quarters of the Australian continent, obscuring the crustal geology below and potential mineral resources within. Sedimentary basins also trap seismic energy increasing seismic hazard and generating noisy seismograms that make determining deeper crustal and lithospheric structure more challenging. The most fundamental question that can first be asked in addressing these challenges is how thick are the sediments? Borehole drilling and active seismic experiments provide excellent constraints, but they are limited in geographical coverage due to their expense, especially when operating in remote areas. On the other hand, passive-seismic deployments are relatively low-cost and portable, providing a practical alternative for initial surveys. Here we utilize receiver functions obtained for both temporary and permanent seismic stations in South Australia, covering regions with a diverse sediment distribution. We present a straightforward method to determine the basement depth based on the arrival time of the P-converted-to-S phase generated at the boundary between the crustal basement and sedimentary strata above. Utilizing the available borehole data, we establish a simple predictive relationship between Ps arrival time and the basement depth, which could then be applied to other sedimentary basins with some consideration. The method is found to work best for Phanerozoic sediments and offers a way to determine the sediment-basement interface in unexplored areas requiring only temporary seismic stations deployed for < 6 months.

How to cite: Agrawal, S., Eakin, C., and O'Donnell, J.: Calibrating sediment thickness utilizing receiver functions and borehole data, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-6878, https://doi.org/10.5194/egusphere-egu22-6878, 2022.

13:48–13:54
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EGU22-9491
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ECS
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Presentation form not yet defined
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Akash Kharita and Amy Gilligan

Understanding deep crustal structure can provide us with insights into tectonic processes and how they affect the geological record. Deep crustal structure can be studied using a variety of seismological techniques such as receiver function analysis, and surface and body wave tomography. Using models of crustal structure derived from these methods, it is possible to delineate tectonic boundaries and regions that have been affected by similar processes. However, often velocity models are grouped together in a somewhat subjective manner, potentially meaning that some geological insight may be missed. Cluster analysis, based on unsupervised machine learning, can be used to more objectively group together similar velocity profiles and, thus, put additional constraints on the deep crustal structure.

In this study, we apply hierarchical agglomerative clustering to the shear wave velocity profiles obtained by Gilligan et. al. (2016) from the joint inversion of receiver functions and surface wave dispersion data at 59 sites surrounding Hudson Bay. This location provides an ideal natural laboratory to study Precambrian tectonic processes, including the 1.8Ga Trans-Hudson Orogen. We use Ward linkage to define the distance between clusters, as this gives the most physically realistic results, and after testing the number of clusters from 2 to 10 find there are 5 main stable clusters of velocity models. We then compare our results with different inversion parameters, clustering schemes (K-means and GMM), results obtained for Vp (P-wave velocity) and ρ (Density), as well as results obtained for profiles from receiver functions in different azimuths and found that, overall, the clustering results are consistent.

The clusters that form correlate well with the surface geology, crustal thickness, regional tectonics and previous geophysical studies concentrated on specific regions. The profiles in the Archean domains (Rae, Hearne and Superior) were clearly distinguished from the profiles in the Proterozoic domains (Southern Baffin Island and Ungava Peninsula). Further, the crust of Melville Peninsula is found to be in the same cluster as the crust of western coast of Ungava Peninsula, suggesting similar crustal structure. Our study shows the promising use of unsupervised machine learning in interpreting deep crustal structure to gain new geological insights.

How to cite: Kharita, A. and Gilligan, A.: Cluster Analysis of Velocity Profiles around Hudson Bay using Unsupervised Machine Learning, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9491, https://doi.org/10.5194/egusphere-egu22-9491, 2022.

13:54–14:00
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EGU22-10828
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Virtual presentation
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Abdul Halim Abdul Latiff

While there are several geological characterizations of Peninsular Malaysia based on the surface geological study, subsurface evaluation based on the seismic data is still lacking. In this work, tomography of the studied region is being investigated through teleseismic earthquake recorded by several seismic stations located along the peninsula. Throughout the tomography analysis, the 1D ak135 global velocity model is used for computing the travel times from the earthquake source to the edge of the 3-D model. In addition, a similar 1-D ak135 model also being used as the starting model for iterative tomography inversion within the 10.5°N to 0.5°S and 96.5°E to 108.0°E boundary region. The seismological data used for this tomography analysis was acquired from 11 stations that shared with International Seismological Centre (ISC) database and Malaysia Meteorological Department (MMD) respiratory. In total, there were 1598 teleseismic earthquakes events recorded in between 2005 to 2016 which satisfy the criteria of 6.0  or larger. Prior to the iterative travel-time computation, the model’s sensitivity and reliability towards the external changes in the data noise and initial conditions were evaluated through the checkerboard resolution test. The synthetic reconstruction images show that the pattern of the checkerboard anomaly is properly recovered at depth of 30 km, 60 km and 90 km with corresponding high and low wave speed have been recovered as per input model. From the 3580 P-wave arrival time, tomography output is generated at 30 km depth interval, from within the crustal layer of 30 km depth, till the uppermost mantle structure of 300 km depth. In addition, the North-South and East-West sections of the peninsula are produced for a better interpretation of the crustal and uppermost mantle layers in the region. In general, the variation from fast to slow wave speed is noticeable in the Northwards trend, apart from KGM station in the Southern Peninsular Malaysia where a slower velocity recorded compared to its surrounding. The Earth’s structure beneath the SRIT, SKLT, SURA, IPM and KUM stations are experiencing a relative negative wave speed perturbation, while the positive wave speed perturbation is recorded beneath JRM, KOM and BTDF stations. The slower wave speed is recorded in Southern Thailand region and continue southward to the North-West part of Peninsular Malaysia, indicated the sedimentation of Semanggol formation that consists of Carboniferous marine shales. It also concluded that Western-Eastern belt separation of the Malay Peninsula is clearly evident from the velocity contrast. In summary, the latest tomography analysis retrieve from teleseismic earthquake provides a new dimension of the subsurface analysis within the Malay Peninsula region.

How to cite: Abdul Latiff, A. H.: Seismic Tomography of Peninsular Malaysia Inferred from Teleseismic Earthquake, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10828, https://doi.org/10.5194/egusphere-egu22-10828, 2022.

14:00–14:06
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EGU22-11712
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ECS
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On-site presentation
Yanling Liang, Xiaohui Yuan, Bernd Schurr, Frederik Tilmann, Wei Li, and Oo Than

Adjoining the Eastern Himalayan Syntaxis, linking to the Indian slab indentation northward and Andaman slab subduction eastward, Myanmar is one of the most complicated and active tectonic regions in the world, and exposed to a high seismic hazard. The Burmese arc consists of the Indo-Burman Ranges (IBR), an accretionary wedge in the west and the Central Myanmar Basin in the east. It is bounded in the east by the seismically active Sagaing Fault to the Shan Plateau which is part of the Asian plate. Intermediate-depth seismicity below Myanmar occurs at depths up to ~150 km, generally understood to be related to the subducting Burma slab.  An important open question concerns the transition from oceanic subduction to continental subduction/collision along the Burmense arc. The transition is also thought to affect the upper plate crust. In this study, we collected ambient noise data set based on a temporary seismic array in Myanmar in order to constrain the variation of crustal structure. The station array includes 30 broadband stations from a temporary network (code 6C 2019-2021) at GEOFON data center. They were deployed by the German Research Centre for Geosciences (GFZ) and the Department of Meteorology and Hydrology of Myanmar (DMH) across the eastern IBR and Central Myanmar Basin in early 2019  with an average interstation distance of ~60 km and data are available to 2020 for most stations. We calculated the cross-correlations daily for all available station pairs through the NoisePy code and stacked further into yearly time-series. We measured Rayleigh wave group and phase velocity dispersions from cross-correlations by using the frequency-time analysis (FTAN) and calculated maps of phase dispersion. As a next step, we will construct a detailed crustal and upper mantle structure beneath Myanmar.

How to cite: Liang, Y., Yuan, X., Schurr, B., Tilmann, F., Li, W., and Than, O.: Crustal structure beneath northern Myanmar: preliminary results from ambient noise tomography, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11712, https://doi.org/10.5194/egusphere-egu22-11712, 2022.

14:06–14:12
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EGU22-1279
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Virtual presentation
Jordi Diaz, Sergi Ventosa, Martin Schimmel, Mario Ruiz, and Ramon Carbonell

The SANIMS project is focused on the development and application of methods based on seismic ambient noise to image and monitor natural and human-altered environments focusing on two test sites; the Cerdanya Basin in the eastern Pyrenees, and the city of Barcelona. Broad-band and short-period seismometers and a high-density node network have been used to acquire new data.

Broad-band data has been processed using the frequency-dependent phase cross-correlation and time-scale phase-weighted stacking to extract Rayleigh and Love waves. We have obtained Rayleigh and Love group and phase velocities for periods in the 1.5 – 4 s range, that will be inverted to velocity-depth models. The preliminary results show higher velocities to the North, with a well-defined zone with lower than average velocities around the Cerdanya Basin. The geometry of the basin basement has also been investigated using the amplitudes of ambient noise, HVSR methods and RFs, obtaining consistent results. The recently acquired high-density data has already been processed in terms of amplitude variations and will be integrated with the tomographic images.

The data acquired in Barcelona has first been used to monitor human activity during the COVID19 pandemic. Amplitude variations of seismic noise allow to delineate the main geological units of the Barcelona area. HVSR measures using the new data expand the already available results, hence improving the existing seismic hazard maps, and will allow analyzing eventual temporal variations in the measurements. As in the Cerdanya Basin, the data will be used to extract Rayleigh waves and invert for velocities.

Both datasets will also be used to analyze the applicability of the methods based on Rayleigh wave ellipticity inversion of ambient noise and earthquake data to provide S-velocity depth profiles. We expect that the use of ambient noise methods will allow to map the basement and to obtain new higher resolution ambient noise tomographic images of the upper crust in the Cerdanya Basin and to better constrain the subsoil properties of Barcelona. The results in both areas will allow comparing the performance of these methodologies in quiet and noisy areas.

This is a contribution of the SANIMS project (RTI2018-095594-B-I00)

How to cite: Diaz, J., Ventosa, S., Schimmel, M., Ruiz, M., and Carbonell, R.: Imaging the upper crust with ambient seismic noise in natural and urban environments, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1279, https://doi.org/10.5194/egusphere-egu22-1279, 2022.

14:12–14:18
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EGU22-10944
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ECS
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Presentation form not yet defined
Martin Balcewicz, Claudia Finger, and Erik H. Saenger

The localization of defects (i.e., fractures or damages) is essential in evaluating and assessing concrete in, for example, bridges. For this reason, this study presents a non-destructive testing method used primarily in passive seismology applied to active ultrasonic waveforms. Changes in the coda wave can provide information about the defect location by comparing two measurements with and without a defect.

The signal comparison of active transducer signals recorded with several receivers for material before and after an applied load is the basis of Active Time-Reverse Imaging (A-TRI). This study applies the TRI technique to the signal-based analysis of reinforced concrete specimens' acoustic emission (AE). Classical time-reverse modeling uses recorded passive signals, recorded laboratory, or field experiments as input. The recorded wavefield is reversed in time and backpropagated numerically through an adequate medium representation. The wavefield will then ideally focus on the original source location. In contrast to the standard passive TRI method, an active ultrasound method using the generated wavefield from an active source is used in A-TRI. The general workflow is divided into two basic steps: (1) Ultrasonic waves are emitted from single or multiple transducers on the surface and propagate through the original medium. Several receivers record the signals. (2) The experiment is repeated with precisely the same setting after a specific loading scenario. However, the potential damage is to be detected in this case. The difference of both signals is reversed in time and used as the input signal for a time-reverse simulation to locate the defect.

We see the A-TRI method as a complementary method to typically used coda-wave interferometry (CWI) to detect velocity changes in the medium. On the other hand, A-TRI can precisely determine the location of the defect. In the following, a feasibility study is presented in which the A-TRI method is applied to a synthetic data set to localize the defect.

How to cite: Balcewicz, M., Finger, C., and Saenger, E. H.: Active time-reverse imaging: Defect detection by coda waves in digital concrete physics, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10944, https://doi.org/10.5194/egusphere-egu22-10944, 2022.

14:18–14:24
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EGU22-6839
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Highlight
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Virtual presentation
Donna Shillington, James Gaherty, Christopher Scholz, Andrew Nyblade, Patrick Chindandali, Richard Wambura Ferdinand, Gabriel Mbogoni, Emily Hopper, Natalie Accardo, Gabrielle Tepp, Ashley Grivalja, David Borrego, and Gabriel Mulibo

Few constraints are available on variations in extension with depth and along-strike in early stage continental rift systems, leaving many questions on the mechanisms of extension and the controlling factors. The Malawi (Nyasa) Rift in the southern East Africa Rift System exemplifies an active, magma-poor, weakly extended continental rift. Between 2014-2016, we collected a multi-faceted, amphibious, active- and passive-source seismic dataset across the northern Malawi Rift as a part of the SEGMeNT (Studies of Extension and maGmatism in Malawi aNd Tanzania) interdisciplinary experiment. Together, analysis and integration of these seismic imaging datasets provide a comprehensive portrait of the style and amount of stretching throughout the lithosphere and along strike.  Broadband scattered-wave imaging and wide-angle seismic reflection/refraction data reveal substantial variations in extension with depth, with much more thinning of the lithospheric mantle than the crust (stretching factors of 3.8 and 1.7, respectively). The modest observed reduction in velocity below the rift from both broadband surface- and body-wave imaging can be explained with small thermal perturbations and without melt. Lower velocities and complex patterns of anisotropy underlie the Rungwe Volcanic Province to the north of the Malawi Rift, suggesting focused lithospheric modification, melting and complex mantle flow below this localized volcanic province.  Active-source seismic refraction and multi-channel seismic (MCS) reflection data quantify cumulative extension accommodated by the border faults and intrarift faults. Border faults have throws up to ~8 km and bound half graben basins. Intrarift faults are also relatively large (throws up to 2.5 km) and active, and they are estimated to account for ~20-25% of cumulative upper crustal extension. Along-strike variations are observed in faulting and in crustal and lithospheric stretching. In this presentation, we will synthesize these seismic imaging results and compare them with complementary constraints, including from other parts of the SEGMeNT project .

 

How to cite: Shillington, D., Gaherty, J., Scholz, C., Nyblade, A., Chindandali, P., Wambura Ferdinand, R., Mbogoni, G., Hopper, E., Accardo, N., Tepp, G., Grivalja, A., Borrego, D., and Mulibo, G.: Controls on early-stage, magma-poor rifting from top-to-bottom seismic imaging of the Malawi (Nyasa) Rift, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-6839, https://doi.org/10.5194/egusphere-egu22-6839, 2022.

14:24–14:30
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EGU22-3056
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ECS
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On-site presentation
Lea Gyger, Pilar Sánchez-Pastor, Hansruedi Maurer, Anne Obermann, and Stefan Wiemer

The Hengill area, located a few km west of Reykjavik, is situated on the triple junction of three large geological features: the onshore section of the Mid-Atlantic Ridge, called the Reykjanes Peninsula Oblique Rift, the Western Volcanic Zone and the South Iceland Seismic Zone. This area hosts two large-scale geothermal power plants, Nesjavellir and Hellisheiði. Both are producing electricity and hot water. Hengill is also one of the targets of the Iceland Deep Drilling Project that aims at finding and exploiting supercritical fluids.

In summer 2021, a nodal network of 500 5 Hz geophones was deployed in the area over a period of 2 months. It complemented seismic data from a network of broadband stations that were already deployed earlier. In July 2021, a vibroseis experiment was conducted in the area in form of two surveys performed by a fully electrical seismic vibrator truck.  The seismic waveforms were recorded by parts of the nodal network. In this study, we focus on the survey conducted along the road leading to the Nesjavellir geothermal power plant, in Mosfellsheiði. The aim of the survey in Mosfellsheiði is to obtain new insights on a low-velocity anomaly as well as on a yet poorly understood seismic cluster that has been detected in the area by previous studies.

To study the velocity and attenuation structure of the area, we computed a first arrival travel time tomography and an attenuation profile. Finally, we compared our results with an existing 3D seismic ambient noise tomography Vs model of the area as well as with known local subsurface properties, such as resistivity and mineralogy.

The final results of this vibroseis study could be useful for finding new geothermal resources in the Nesjavellir area.

How to cite: Gyger, L., Sánchez-Pastor, P., Maurer, H., Obermann, A., and Wiemer, S.: Imaging potential geothermal resources in the Hengill volcanic area (Iceland) with active-source seismics recorded by a dense nodal array, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3056, https://doi.org/10.5194/egusphere-egu22-3056, 2022.

14:30–14:36
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EGU22-11885
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ECS
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On-site presentation
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Sergio Gammaldi, Amir Ismail, and Aldo Zollo

The imaging of volcanic structures by means of seismic techniques is aimed at the structural characterization and monitoring purposes. The quiescent volcano of the Solfatara belong to the caldera of the Campi Flegrei Italy, a resurgent nested caldera that has been extensively investigated through active seismic investigation.

The fumaroles of Bocca Grande and Bocca Nuova at the Solfatara volcano, represent some of the main markers of deep magmatic shallow hydrothermal activity. In this article we identify the gas accumulation zone using the attributes and scaled Poisson ratio extracted from multi-2D seismic profiles. The 400 m long profiles,  have been acquired during the active experiment RICEN (Repeated Induced Earthquake and Noise) performed in the context of the EU project MEDSUV between May and November 2014. The seismic arrays were deployed along the NE-SW and NW-SE directions within the crater across the zones of the fumaroles and the “fangaia”.

The time- and depth-sections are reconstructed after applying residual statics, DMO corrections, CMP gathering, and the post-stack Kirchhoff migration technique. The energy, root mean square, envelope, and sweetness attributes have been computed and extracted for determining the maximum and minimum values of amplitude zones on the migrated, post-stack seismic sections. Furthermore, we have investigated the time-gain attribute, which is used to interpret deep reflectors, and the variance attribute, that is a geometrical attribute providing information on location of faults, discontinuities, and chaotic zones. To better detail the reflectivity of shallow events, enhanced by the post stack attributes, the Amplitude Versus Offset (AVO) technique has also been used to discriminate and identify shallow gas pockets. The seismic profile, seismic attributes, and near-surface structural interpretation of the Solfatara volcano have been combined into a final structural image of the Solfatara subsoil. This show a clear evidence of the fluids trapping zones at 10-50 m depth beneath the crater's surface, as well as their migration paths down to 150 meters depth.

How to cite: Gammaldi, S., Ismail, A., and Zollo, A.: The updated multi-2D image of the gas accumulation zone inferred by seismic attributes and AVO analysis at the Solfatara Volcano, Italy, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11885, https://doi.org/10.5194/egusphere-egu22-11885, 2022.

14:36–14:42
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EGU22-4592
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Presentation form not yet defined
Graziella Barberi, Domenico Patanè, Luciano Scarfì, and Mauro Coltelli

In this work we present a new tomographic inversion of the velocity structure and hypocenter parameters at Mt. Etna, carried out by the larger seismic dataset never used than to the previous tomographies. The result of tomographic inversion, including the 3D distributions of P and S velocities, Vp/Vs ratio, and accurate source locations, has been obtained based on the integration of active seismic data (151.403 P-phases from 4.112 shots) acquired during the 2014 TOMO-ETNA experiment (EC-FP7 MED-SUV and EUROFLEET2 MED-SUV.ISES projects) and 10.955 selected local earthquakes data (218.473 P-phases and 39.073 S-phases), recorded by a total number of 262 stations of the INGV permanent seismic network and from the onland and OBS temporary network. For the inversion we used the tomoDDPS algorithm [Zhang et al., 2009] and the input velocity model previously obtained with the PARTOS code (Moreno et al. 2016), considering a total number of 1.580.343 P and 228.663 S differential times.

Based on our data selection and inversion strategy, we obtain a strongly improved 3-D high-resolution Vp, Vs and Vp/Vs models both onland and offshore the volcano, discovering for the first time, in the peripherical part of the edifice: i) on-land, the presence of two subvolcanic complexes in the south-eastern and southern flanks, west to Acicastello-Acitrezza and Paternò and Motta, respectively, where the Etna’s ancient volcanisms (500 to 110 ka) manifested and ii) the presence of a ca. N-S oriented high velocity anomaly (5.0-6.5 km/s) located offshore southeast of Etna area, suggesting a clear interplay between submarine volcanic manifestations and tectonic setting. This body extending from about the sea level to ca. 8 km b.s.l. confirms the observation of a large and intense magnetic positive anomaly (>700 nT) related to deep sources (Cavallaro et al., 2016), evidenced by the magnetic survey carried out during TOMO-ETNA.

 

How to cite: Barberi, G., Patanè, D., Scarfì, L., and Coltelli, M.: Discovery of scattered subvolcanic complexes that feeded the volcanism in the area of Etna, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4592, https://doi.org/10.5194/egusphere-egu22-4592, 2022.

14:42–14:48
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EGU22-11919
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Virtual presentation
Marco Firetto Carlino, Luciano Scarfì, Flavio Cannavò, Graziella Barberi, Domenico Patanè, and Mauro Coltelli

The analysis of the b-value, i.e. the slope of the Gutenberg & Richter frequency-magnitude distribution of earthquakes, provides the chance to investigate the local stress conditions with great resolution, especially in active volcanic areas, where seismic productivity is generally high.

In this work we investigated the seismicity of Mt. Etna between 2005 and 2019, focusing on one of the largest known episodes of unrest in December 2018, when most of the intruding magma aborted its ascent inside the volcano. We found a possible stress concentration zone along magma pathways that may have inhibited the occurrence of a larger, more complete eruption. The b-values time series strongly increase about 19 days before the December 2018 unrest event, while a sharp drop of b started 2 days in advance. 

Our results suggest that the study of the b-value, in broader correlation with other monitoring measurements, may offer an opportunity to investigate the volcano state and improve the assessment of impending volcanic eruptions.

How to cite: Firetto Carlino, M., Scarfì, L., Cannavò, F., Barberi, G., Patanè, D., and Coltelli, M.: Monitoring the b-value unravels critical stress-changes along magma pathways: results from Etna volcano, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11919, https://doi.org/10.5194/egusphere-egu22-11919, 2022.

14:48–14:50