The potential of different ambient noise methodologies to map the geometry of a small-scale sedimentary basin has been tested using data acquired in the Cerdanya Basin (eastern Pyrenees). We present results based on a 1-year long broad-band deployment covering a large part of the Eastern Pyrenees and a 2-month long high-density deployment covering the basin with interstation distances around 1.5 km. The explored techniques include autocorrelations, ambient noise Rayleigh wave tomography, horizontal-to-vertical spectral ratio, and band-pass filtered ambient noise amplitude mapping. The basement depth estimations retrieved from each of these approaches, based on independent datasets and different implicit assumptions, are consistent, showing that the deeper part of the basin is located in its central part, reaching depths of 600-700 m close to the Têt Fault trace bounding the Cerdanya Basin to the NE. The results show also that when high-density seismic data are available, HVSR and ambient noise amplitude analysis in a selected frequency band are useful tools to quickly map the basement of a sedimentary basin. On the other hand, surface wave tomography, more complex to obtain, provides detailed information on the 3D velocity structure. Besides this methodological aspect, our results help to improve the geological characterization of the Cerdanya Basin and will provide further constraints to refine the seismic risk maps of an area of relevant tourism and economic activity.

How to cite: Diaz, J., Ventosa, S., Schimmel, M., Ruiz, M., Macau, A., Gabàs, A., Martí, D., Akin, Ö., and Verges, J.: Testing multiple ambient noise methodologies to map the basement of small-scale sedimentary basins, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3066, https://doi.org/10.5194/egusphere-egu24-3066, 2024.

Carbon capture and storage (CCS) is a strategy that can be employed to reducing human impact on climate change In the 21st century. Geological storage has been currently considered the most promising strategy. It is reported that there is a large theoretical capacity to store CO₂ in the Precambrian sedimentary succession of the Baltic Basin.

To aid in surveying and evaluating the potential storage reservoirs in the Baltic Sea, a seismic survey was performed over similar geology in the Sudret area of Gotland. Part of the survey consisted of 14-hours passive data, recorded along a 2.8 km profile with 10m receiver spacing and 1ms sample rate using 329 5Hz SmartSolo nodal units in the vicinity of two boreholes that had been drilled earlier.

We retrieved body wave and surface wave virtual shot gathers after applying signal separation and cross correlation calculations. For the body waves, conventional seismic data processing was conducted to obtain a stacked profile; for the surface waves, we could determine the dispersion curve in the frequency range 0.5 to 5.5 Hz and inverted these curves to obtain a velocity model from the ground surface down to c. 1500m depth.

Both the body waves and surface waves provide a high quality and high resolution image of the top of the Ordovician formation and have a good consistency with active seismic data in the same location. Moreover, they revealed some reliable deep geological information which active data cannot provide because of the limited source energy. Compared with active seismic exploration, passive seismic is friendly to the environment and cost effective. In some cases, it is an important complementary or alternative method to active seismic for CO2 storage and monitoring.

How to cite: Wang, Z., Juhlin, C., Hedin, P., Erlström, M., and Sopher, D.: Passive seismic imaging for CO2 geological storage in the Sudret area of Gotland, Sweden, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8975, https://doi.org/10.5194/egusphere-egu24-8975, 2024.

This study presents passive downhole Distributed Acoustic Sensing (DAS) measurements conducted in the Groningen gas field, Netherlands, for subsurface and induced seismicity monitoring. The optical fiber installation, completed in Sept 2015, was partially cemented behind the inner casing along a deviated well (~3800 m), extending into the sandstone reservoir at temperatures ranging from 100-110 degrees Celsius. In Nov 2022, we interrogated the optical fiber utilizing a 10 m gauge length and 1 m sampling spacing.

Within this setup, most DAS traces exhibit the lowest self-noise floor in the frequency range of 0.1 to 30 Hz. Noteworthy is the absence of visible differences between cemented and uncemented sections. Strong ambient seismic noise is observed in the near-surface unconsolidated sediment at approximately 800 m depth. Noise cross-correlation (CC) analysis is performed for DAS channels and DAS seismometer pairs. Surface wave signals in the 0.1 to 1 Hz range are identified in DAS-seismometer CCs, displaying amplitude and polarization changes with depth, following Surface wave theory.

Induced seismicity is also recorded, with wavefields of events exhibiting clear amplitude variations along the fiber, strongly correlating with sonic logging. Our findings suggest that downhole DAS has the potential to characterize the subsurface with high resolution.

How to cite: Zhou, W., Stork, A., van Elk, J., David, A., Paulssen, H., and Muntendam-Bos, A.: Subsurface characterization using downhole passive Distributed Acoustic Sensing data in the Groningen gas field, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18794, https://doi.org/10.5194/egusphere-egu24-18794, 2024.

The Vienna Basin (VB) is currently the main target area for deep geothermal exploration in Austria. Knowledge of the subsurface heavily relies on active seismic reflection that are expensive and logistically demanding. Affordable geophysical prospecting methods are needed to reduce subsurface uncertainty. Over the recent years, seismic ambient noise tomography (ANT) has proven to be a cost-effective and environment-friendly exploration technique. Here, we present an ANT of the central Vienna Basin revealing the shear-wave velocity structure of the top 5 km beneath the surface. We deployed an array of ~100 seismic nodal instruments during 6 weeks over summer 2023. We measured fundamental-mode Rayleigh and Love-wave group velocity dispersion from seismic ambient noise and employed transdimensional Bayesian tomography to invert for isotropic group velocity maps at periods ranging from 0.8 to 5.5 s. We then extracted Rayleigh and Love group velocity dispersion curves from the group velocity maps at all locations and jointly inverted them for shear-wave velocity as a function of depth using a transdimensional Bayesian framework. We discuss features observed in our 3D shear-wave velocity model relevant to geothermal exploration.

How to cite: Estève, C., Lu, Y., Bokelmann, G., and Gosselin, J.: Ambient noise tomography for geothermal exploration: the central Vienna basin, Austria, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9327, https://doi.org/10.5194/egusphere-egu24-9327, 2024.

Kim et al. (2023; JGRse) presents an approach to better characterize the P-wave and S-wave velocity structure of the seafloor sediment layer using ocean bottom seismometers. The presence of low-velocity seafloor sediment layers influences the observed seismic record at the seafloor over a broad frequency range, such that detailed knowledge of this sediment structure is essential to predict its effect on teleseismic records. We use the radial component of teleseismic P waves and autocorrelation functions of the radial, vertical, and pressure components of teleseismic P and S waves to obtain sediment layer models using the Markov chain Monte Carlo approach with parallel tempering. Synthetic tests show that the body waves constrain the P- and S-wave impedances and travel times and the P- to S-wave velocity ratio of the sediment layers. The proposed method resolves thin layers at a high resolution, including the uppermost thin (∼50 m to a few hundred meters) low S-wave velocity layer. Real data applications at sites across the Pacific Ocean that are coincident with previous in situ studies demonstrate the effectiveness of this method in characterizing the seafloor sediment unit. Furthermore, we widely apply the methodology to data from various OBS arrays in the Pacific to estimate in-situ sediment structures. The sediment models show multiple layers in some regions, including the top water-saturated layer with low S-wave velocity and high Vp/Vs values. The scaling relationship of Vp/Vs to Vp shows higher values than the previously discussed ones (e.g., Brocher, 2005; Hamilton, 1979). Furthermore, the sediment layer model constrained from the body waves exhibits agreement in predicted Rayleigh wave admittance with the sediment model from the Rayleigh wave admittance (Bell et al., 2015). The sediment models characterized by this new approach will allow us to more accurately predict and correct the effects of sediment layers in generating P- and S-wave reverberations. Additionally, in this presentation, we will discuss how the in-situ high-Vp/Vs multi-layer sediment model differs in predicting the reverberation effects on receiver function analysis for ocean bottom seismometers.

How to cite: Kim, H., Kawakatsu, H., Akuhara, T., and Takeuchi, N.: Characterizing the Seafloor Sediment Layer Using Teleseismic Body Waves Recorded by Ocean Bottom Seismometers, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4428, https://doi.org/10.5194/egusphere-egu24-4428, 2024.

Seismic interferometry using ambient seismic noise is a powerful technique to constrain shear-wave velocities at different scales. Microseismic monitoring is essential to ensure the safety of industrial operations, including hydrocarbon extraction, gas storage and geothermal production. Microseismic monitoring involves recording seismic vibrations continuously, in order to identify and locate local earthquakes. However, most of the recorded seismic signals is ambient noise, that could be used to infer the shear-wave velocities in the area, thus allowing a more accurate location of the seismic events.

This study aims at applying seismic interferometry to ambient noise recorded by two small microsesimic monitoring networks in Switzerland, deployed around geothermal wells. The processing workflow for each station pair includes different steps as (1) cross-correlation of the raw seismic records, (2) analysis of the zero-crossings of the cross-spectra, (3) picking of the dispersion curve and (4) depth inversion. Due to the sparse nature of the seismic networks, surface wave tomography was not applied. Considerations on the topography effects, on the lateral variability of velocities and on the possible resonance effects due to the valley geometry will be done.

How to cite: Barone, I., Brovelli, A., and Cassiani, G.: Seismic interferometry applied to microseismic monitoring networks in mountain areas, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7809, https://doi.org/10.5194/egusphere-egu24-7809, 2024.

In the last decade, passive seismic techniques have found use in the mineral exploration sector. In particular, ambient noise tomography is a low cost viable option that can outperform competing geophysical methods when imaging down to a few kilometers depth. However, at present it does not belong to the core approaches (e.g. magnetic, gravity, etc.) mainly due to a lack of experience in the industry. Novel approaches often go through a period of testing where the industry is familiarized with the technique and expectations are "adjusted". In order to speed up this testing period, an extensive review of the technique and its capabilities for real geological settings is required.

In this work, we build geological models of well known mineral deposits and generate ambient noise cross correlation functions (ccfs) for synthetic deployments. The ccfs are then used in a state of the art fully probabilistic ambient noise tomography to assess the strengths and weaknesses of this technique. This work will allow the industry to better understand the methods capabilities and adjust their expectations for exploration purposes. 

How to cite: Gal, M., Oliver, G., Lecocq, T., and Gunner, G.: Assessing the Accuracy and Feasibility of Ambient Noise Tomography for Copper Exploration: Insights from Synthetic Data Generation with Realistic Geological Models, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13672, https://doi.org/10.5194/egusphere-egu24-13672, 2024.

We use ambient noise tomography (ANT) to image the Hillside Iron-Ore-Copper-Gold (IOCG) deposit at prospect-scale, leveraging Fleet's direct-to-satellite technology for real-time data analysis. Our results capture aspects of the deposit's known geology, including depth of cover, structures linked to mineralisation, and the mineralised host rock, and identifies several new features, including the behavior of key structures down to 1 km depth and lithological variation that underlies the Hillside deposit. Results are compared to existing magnetic, gravity, induced-polarization and drilling data. An analysis of model convergence rates with respect to environmental noise conditions (signal-to-noise ratio) shows that real-time analysis can reduce data collection at the site to within 50% of traditional deployment times. We conclude by commenting on the efficacy of ANT for IOCG exploration more broadly.

How to cite: Jones, T., Olivier, G., Murphy, B., Gal, M., Smith, N., North, B., Burrows, D., Cole, L., Went, C., and Olsen, S.: Real-time Ambient Seismic Noise Tomography of the Hillside IOCG Deposit, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13498, https://doi.org/10.5194/egusphere-egu24-13498, 2024.

Improved passive seismic imaging of sedimentary basins plays a crucial role in improving our understanding of basin inversion tectonics and sedimentary-hosted mineral systems. The Central African Copperbelt of Zambia and the Democratic Republic of Congo is hosted in the Neoproterozoic Katangan sedimentary basin and accounted for 8.8% of global copper production in 2021 (World Economic Forum, 2024). Despite this, the tectonic evolution of the basin in Northern Zambia is currently unclear, significantly hampering our understanding of the Cu, Co and Ni mineralisation in that area. To investigate the geodynamics that shaped this region, and to assess the suitability of MEMS-accelerometers for passive seismic imaging of sedimentary basins, an array of nodal accelerometers was deployed around the Kansanshi Mine (NW Zambia), previously Africa’s largest Cu mine. Surface wave phase velocities in the mine and surrounding area were analysed using ambient noise tomography, with average Rayleigh wave phase velocities ranging from 3.05 +/- 0.2 km/s at 3 s period to 3.5 +/- 0.15 at 6 s period. The S-wave velocity at points of particular interest was examined using iterative non-linear inversions of surface wave dispersion curves constructed from the tomography results. These S-wave profiles provide new insight into the structural configuration of the Kansanshi copper mine and show that the mine overlies a large thickness of sediments from which the copper could be scavenged. This study illustrates the efficacy of performing ambient noise tomography on MEMS-accelerometer data to investigate the structures controlling the inversion of sedimentary basins and the formation of sedimentary-hosted metal deposits at a local to regional scale.

How to cite: Mackay-Champion, T., Harmon, N., Mutelekesha, S., Chanda, M., Hudson, T., Kendall, J.-M., and Daly, M. C.: Imaging of sediment-hosted Cu deposits using ambient noise tomography: a case study of the Kansanshi Cu-mine, Zambia., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16563, https://doi.org/10.5194/egusphere-egu24-16563, 2024.