Landslides in glacial and periglacial environments are increasingly affected by climate change, with sudden failures reported in high mountain regions and the Arctic. The complex mechanisms behind these events are often poorly understood due to a lack of dense in situ data. We investigate two slow-moving landslides in Arctic Norway (70° N), the Jettan and Gámanjunni landslides, located approximately 10 km apart: Jettan, a complex slide in micaschist and calcite marble situated below the permafrost boundary, and Gámanjunni, a rotational slide in micaschist situated above the permafrost boundary. Using over a decade of multi-physics observations, including geodetic, borehole, seismic, and hydrological data, we examine surface and subsurface deformation. Both landslides display similar seasonal surface velocity patterns, with peaks in spring and autumn, likely influenced by pore-water infiltration. At Jettan, twelve years of inclinometer data in boreholes reveal a transition from steady state to seasonal deformation in two shear zones. Since 2020, spring accelerations have intensified in years coinciding with deeper snowpacks and associated melt. These observations, together with statistical modeling, suggest that the shear-zones are becoming increasingly localized and sensitive to pore-water pressure. Conversely, autumn acceleration is not seen in localized shear zones but manifests as distributed volumetric deformation. Seismic velocity variations within the landslide body also exhibit seasonal patterns that correspond with geodetic velocity, interpreted as changes in landslide rigidity due to water infiltration. This integrated analysis of surface and subsurface data offers new insights into the evolving deformation of Arctic landslides, emphasizing the influence of hydrological forcings on both seasonal and long-term deformation processes.

We assess the methodological limits of estimating earthquake source (stress drop) and high-frequency energy attenuation (κ) characteristics by analysing a dataset of seismic waveforms recorded between 2000 and 2022 from the Horda platform region of the North Sea. We observe a bias in the source spectra with strong, but artificial, magnitude dependence of stress drop. Synthetic tests demonstrate that this bias could be largely eliminated with increased station coverage and recording bandwidth. The κ results do not exhibit the expected increase with distance, which is believed to be due to pronounced lateral and vertical variations in the anelastic attenuation parameter Q across the region. These variations likely reflect contrasts in sediment thickness and the transition from the offshore sedimentary basin with extensional tectonics to the onshore Scandinavian Shield composed of crystalline bedrock. Preliminary κ values within the first 50–100 km range from 0.009–0.023 s, consistent with weathered to hard-rock site conditions and in alignment with other estimates from stable continental regions. Our analysis reveals the challenges that sparse and uneven station distribution, limited recording bandwidth, and strong geological heterogeneity pose for robust parameter estimation. Improved network coverage—particularly through the deployment of ocean-bottom sensors in offshore areas—and higher sampling rates would substantially enhance the reliability and spatial consistency of κ and stress-drop estimates. Overall, our findings underscore the importance of station coverage, bandwidth, and regional geology, and have implications for seismic hazard assessment in offshore and data-limited environments.

Microseismic monitoring forms part of the active risk management system in a well-run CO2 storage project. Apart from providing input to the monitoring and assessment of seismic hazard within and around the storage formation, and potentially providing mitigation via a real-time warning system, microseismic event data can be used for reservoir characterization and optimization of injection operations. This study compares various microseismic sensor technologies used at the Quest CCS site in Alberta, Canada where the monitoring network includes downhole geophones, distributed acoustic sensing (DAS), and surface nodes. We evaluate event detectability and the effectiveness of advanced processing methods in lowering detection thresholds through a multi-stage process including array processing and signal enhancement techniques. Results show that downhole geophones provide the best signal-to-noise ratio and lowest detection thresholds compared to surface nodes and DAS which detect about 80% and 50 % of events, respectively. Advanced processing methods, such as the Cluster Analysis of Trimmed Spectrograms (CATS) and template matching, further reduce detection thresholds, enabling the identification of smaller magnitude events. Additionally, relative event relocation using a modified double-difference method allows for improved spatial resolution of microseismic clusters. The findings highlight the importance of optimizing sensor technology and processing techniques to enhance microseismic monitoring networks, facilitating more accurate detection and characterization of induced seismicity in CCS operations.

Rock anchors are the cornerstones of modern geotechnical engineering. Adequate dimensioning will both reduce cost and improve safety. We here present microseismic monitoring results of rock anchor uplift tests at full scale. The uplift tests were monitored with a network of surface geophones, amongst other sensor systems. These geophones recorded the failure of the rock mass during uplift. Our results show that this approach gives valuable insight into the fracture evolution in time and space. A main fracture cone develops at a 23^∘ angle, and a secondary fracture cone at a 35^∘ .

Microseismic monitoring plays a crucial role in assessing the effectiveness and integrity of Carbon Capture and Storage (CCS) projects. By the detection of microearthquakes we can gain real-time insights into the pressure and stress perturbation due to injection operations, aiding in the detection of potential leakage and ensuring the long-term viability of carbon sequestration efforts.At the Quest CCS site in Alberta, Canada, CO2 injection into a 2 km depth saline reservoir is ongoing since 2015 at a rate of one million tonnes per year. Several hundreds of small-magnitude seismic events have been located in the Precambrian basement below the reservoir. A spatio-temporal analysis of seismicity reveals clustered as well as more diffuse distributions of events. At the Quest site various microseismic monitoring technologies are in place including a downhole 8-level 3-component geophone string, temporary surface nodes arranged in mini-arrays, and downhole optical distributed acoustic sensing (DAS) fiber. The site offers an ideal opportunity to compare and combine the different setups with respect to event detection thresholds and location uncertainties. We demonstrate the importance of advanced signal and array processing techniques and highlight the advantages and disadvantages of different sensor technologies.

The Åknes rockslide is located on the slope of a steeply dipping fjord in Norway in the proximity of urban areas, posing a significant hazard due to its potential to trigger a massive tsunami. This study utilizes data from eight vertically aligned borehole geophones and one broadband seismometer on the surface, collected over a period of approximately 22 months. Previous research has demonstrated that passive seismic monitoring, specifically tracking changes in seismic velocities, can provide precursory indicators of landslide failure. This study aims to assess the potential of this method for monitoring and identifying seasonal patterns in the subsurface properties of the slope. To achieve this, we perform seismic interferometry on various frequency bands to calculate relative seismic velocity changes near the borehole and broadband station.By integrating meteorological data from the study area, we can relate these velocity variations to environmental factors. Our analysis indicates that measurements from borehole sensors demonstrate a positive correlation between temperature and seismic velocity changes during snow-covered months, and a negative correlation during the summer, highlighting the sensitivity of seismic waves to seasonal changes and therefore different environmental regimes. Additionally, results from the broadband sensor reveal a clear decrease in seismic velocities during the melting period, and an increase in seismic velocities with increased precipitation and the reemergence of snow cover, suggesting the seismic velocities being influenced by changes in the water content. These findings advance our understanding of the relationship between calculated relative velocity changes and their connection to complex environmental interactions. This is essential for incorporating seismic velocity monitoring as a tool for assessing the stability of the Åknes slope.

Summary We investigate the use of Distributed Acoustic Sensing (DAS) data acquired along a long telecom cable over the Hengill geothermal area of Iceland to improve our understanding of the subsurface. We do this using two approaches: (1) We use seismic modelling to investigate and understand how different subsurface representations based on published tomographic studies would affect seismic wave propagation which we can directly compare with these recorded signals. (2) Additionally, we investigate the potential of using surface DAS data to estimate event locations of a cluster of earthquakes to identify and characterise fault structures that are otherwise unmapped. Through comparison of shear wave arrival times from the different models, we found that some provide a better fit for certain parts of the cable, but none of the velocity models seems to fit along the entire cable length. As a result of this, a double-difference event location approach was used to minimize the impact of an uncertain velocity model. Furthermore phase-picking of the low SNR DAS data was avoided by using cross-correlations to estimate traveltime differences. The resulting event location estimates were comparable to those provided by the dense nodal array and were sufficient to delineate clear planar fault structures.

Creeping landslides may fail catastrophically, posing significant threats to infrastructure and lives. Landslides weaken over time through rock mass damage processes that may occur by steady-state creep or transient accelerations of slip, called creep bursts. Creep bursts may control landslide stability by inducing short-term damage and strain localization. This study focuses on the & Aring;knes landslide in Norway, which moves up to 6 cm per year and could potentially trigger a large tsunami in the fjord below. An 11-year data set is compiled and analyzed, including kinematic, seismic, and hydrogeological data acquired at the landslide surface and in a series of boreholes. An annual average of two creep bursts with millimeter amplitude has been recorded within the shear zone in each borehole, accounting for approximately 11% of the total displacement. Creep bursts detected simultaneously in multiple boreholes are preceded by increased seismic activity and rising water pressure. However, most creep bursts are observed in only one or a few boreholes. These bursts often happen during seasonal high and low groundwater levels in autumn and spring, respectively, correlating with local peaks in water pressure. No such correlation is observed during summer. We propose that creep bursts can have different causes and hypothesize that rock degradation leads to some creep bursts independent of water pressure variations. In contrast, the largest creep bursts are correlated with variations in absolute water pressure or gradients of water pressure within the shear zone. Our findings emphasize the complexity of a dense data set requiring multiple mechanisms to explain creep burst dynamics.

Summary We present results and lessons learned from microseismic monitoring at megaton-scale CCS sites. The data examples allow the comparison of different network configurations and sensor technologies including surface, downhole, and DAS. Comparison of different sites reveals what information is most important to resolve, and at what scale, in order to be of value for storage operations. We can derive some basic criteria for network design aiming at obtaining this information in the most robust and cost-effective way.

Summary Distributed Acoustic Sensing (DAS) has emerged as a technology with many advantages over traditional borehole geophones for the long-term seismic monitoring of CCS fields. DAS can provide a much denser spatial sampling than a geophone string at a relatively low cost per sensor. However, current DAS systems have much higher noise floor than geophones meaning that small events may be harder to detect. Here we investigate the monitoring capabilities of downhole DAS compared to a nearly co-located geophone string at the Quest CCS Facility in Alberta, Canada. For high SNR events the dense spatial sampling and larger aperture provided by DAS offers a much more detailed image of the wavefield than can be provided by geophones. However, detection of smaller events can be a challenge as DAS has much lower (40 times smaller) SNR than geophones on a trace-by-trace comparison. Despite the lower SNR, event detection can be improved though advanced processing. Stacking over neighbouring channels increases SNR by a factor of two and boosts detectability from 33% to 44%. Finally, we present a DAS event detector based on coherent semblance stacking over expected moveouts which boosts the detection rates up to 53%, and shows potential for further improvements.

Microseismic monitoring represents a key surveillance technology to verify the integrity of subsurface CO2 storage sites. The precise location of microseismic events is first and foremost a direct and immediate indication of caprock and seal behavior but could also provide insight into CO2 plume migration. Tiny precursor movements provide diagnostic information about injection-related reservoir and caprock dynamics long before potential seal failure occurs. We present a case study from the Quest CCS facility in Canada, where a variety of different monitoring technologies are employed. We present the different microseismic sensor technologies and array configurations currently installed at the site and compare them against each other with respect to their reliability and effectiveness in providing the required verification information.

Summary The initial idea of the Iceland Deep Drilling Project (IDDP) was to produce geothermal fluids from supercritical (SC) temperature and pressure. If SC fluids, with specific enthalpy close to 3000 kJ/kg can be harvested, the electricity produced from each geothermal well may be significantly increased. Play-fairway analysis (PFA) originates in the petroleum industry. The PFA approach has been adapted to geothermal systems, with several demonstration projects carried out in the USA. In the EU project DEEPEN, PFA has been adapted to SC geothermal systems, which will usually be blind systems, masked by a conventional geothermal system above. A major task to be performed in PFA, is the integration of various types of geophysical and geological and datasets, to derisk the geothermal play elements. In this paper, we outline a methodology where multigeophysical inversion is used as part of PFA. The methodology is demonstrated in the Hengill volcanic system on Iceland.

Slow-creeping landslides may fail catastrophically, posing significant threats to infrastructure and lives. Landslides weaken over time through rock mass damage processes that may occur by slow steady-state creep or transient accelerations of slip, called creep bursts. Creep bursts may control landslide stability by inducing short-term damage and strain localization. This study focuses on the Åknes landslide in Norway, which moves up to 6 centimetres per year and could potentially trigger a large tsunami in the fjord lying below. Here, an eleven-year dataset is compiled and analyzed, including kinematic, seismic, and hydrogeological data acquired at the landslide surface and in a series of boreholes. Creep bursts with millimetre amplitude are detected in the landslide’s shear zone. An annual average of two creep burst events have been recorded within the shear zone in each borehole, accounting for approximately 11% of the total displacement. Creep bursts phased over multiple boreholes are preceded by increased seismic activity and water pressure increase. However, most creep bursts are observed in only one or a few boreholes. Creep bursts often occur during the seasonal high and low levels of groundwater, correlating with local peaks in water pressure, but no such correlation is observed during summer. We propose that on one side, the progressive wear of asperities leads to creep bursts being uncorrelated to water pressure changes. Conversely, enhanced stress corrosion causes creep bursts to correlate to water level fluctuations. Our findings offer unique insights into landslide mechanics, correlating shear zone dynamics with surface displacement and environmental parameters.

A convolutional neural network (CNN) was implemented to automatically classify 15 years of seismic signals recorded by an eight-geophone network installed around the back scarp of the Åknes rock slope in Norway. Eight event classes could be identified and are adapted from the typology proposed by Provost et al. (2018), of which five could be directly related to movements on the slope. Almost 60 000 events were classified automatically based on their spectrogram images. The performance of the classifier is estimated to be near 80 %. The statistical analysis of the results shows a strong seasonality of the microseismic activity at Åknes with an annual increase in springtime when snow melts and the temperature oscillates around the freezing point, mainly caused by events within classes of low-frequency slope quakes and tremors. The clear link between annual temperature variations and microseismic activity could be confirmed, supporting thawing and freezing processes as the origins. Other events such as high-frequency and successive slope quakes occur throughout the year and are potentially related to the steady creep of the sliding plane. The huge variability in the annual event number cannot be solely explained by average temperatures or varying detectability of the network. Groundwater recharge processes and their response to precipitation episodes are known to be a major factor of sliding at Åknes, but the relationship with microseismic activity is less obvious and could not be demonstrated.

A case study with seismic geophone data from the unstable Åknes rock slope in Norway is considered. This rock slope is monitored because there is a risk of severe flooding if the massive-size rock falls into the fjord. The geophone data is highly valuable because it provides 1000 Hz sampling rates data which are streamed to a web resource for real-time analysis. The focus here is on building a classifier for these data to distinguish different types of microseismic events which are in turn indicative of the various processes occurring on the slope. There are 24 time series from eight 3-component geophone data for about 3500 events in total, and each of the event time series has a length of 16 s. For the classification task, novel machine learning methods such as deep convolutional neural networks are leveraged. Ensemble prediction is used to extract information from all time series, and this is seen to give large improvements compared with doing immediate aggregation of the data. Further, self-supervised learning is evaluated to give added value here, in particular for the case with very limited training data.

<p>The Hengill geothermal area is located in southwest Iceland on the plate boundary between the North American and Eurasian plates and is one of the most active seismic zones on the island with thousands of natural earthquakes per year. In addition, seismicity is induced due to active production and injection operations, including the two largest geothermal power plants in Iceland, Nesjavellir and Hellisheiði. In addition, this area is the next target region for the Iceland Deep Drilling Project (IDDP) in search for supercritical geothermal fluids. Detecting and imaging fault zones at high resolution is therefore an important contribution to evaluate the optimum drilling location. We analyze thousands of microseismic events in the area that occurred between December 2018 and August 2021. These events were recorded on different permanent and temporary seismometer networks in the area. In addition, we recorded distributed acoustic sensing (DAS) data along a 25 km long fiber optic telecommunication cable near the Nesjavellir geothermal power plant. We analyze event clustering with a waveform cross-correlation approach and find a clear spatial separation of event clusters delineating planar structures. Clusters experience different temporal evolutions where some develop steadily and others as sudden bursts. Spatial variations of Gutenberg’s b-value and event stress drops show patterns consistent with tomographic seismic velocity inversions. Furthermore, focal mechanisms indicate very consistent source mechanisms within selected event clusters. Along the fiber path, we study waveform characteristics, which correlate with mapped geological features.  Data segments that are recorded where the fiber crosses fault zones exhibit long-tailed codas that may indicate trapping of seismic energy in low-velocity zones around active faults.</p>

To understand fluid induced seismicity, we have designed a large-scale laboratory experiment consisting of a one-cubic-meter sandstone with an artificial fault cut and fluid-injection boreholes. The sandstone block is assembled in a true triaxial loading frame and equipped with 38 piezoelectric sensors to locate and characterise acoustic emission events. The differential stress on the artificial fault is increased in stages to bring it towards a critically stressed state. After each stage of differential stress increase, fluids are injected at low pressures through boreholes to test the potential of fault re-activation. In addition, a high-pressure injection was conducted that created a hydraulic fracture from the injection borehole towards the artificial fault. The newly generated fluid pathway resulted in an activation of the complete block through a stick-slip movement. We compare acoustic emission measurements from the laboratory experiment with seismicity observations from the field-scale CO2 injection at Decatur, Illinois, U.S., and conclude that the existence of fluid pathways plays a decisive role for the potential of induced seismicity.

Download This Paper Open PDF in Browser Add Paper to My Library Share: Permalink Using these links will ensure access to this page indefinitely Copy URL Integrating Induced Seismicity for Enhanced Subsurface Structural Interpretation at the Decatur, Illinois Sequestration Site. 8 Pages Posted: 30 Nov 2022 Last revised: 1 Dec 2022 See all articles by Sherilyn Williams-StroudSherilyn Williams-StroudUniversity of Illinois Urbana-ChampaignAnna Maria DichiaranteNORSARNadege LangetNORSARHannes LeetaruThe University of Illinois at Urbana-ChampaignS. GreenbergIllinois State Geological SurveyFrantisek Stanekaffiliation not provided to SSRNLeo Eisneraffiliation not provided to SSRN Date Written: November 28, 2022 Abstract Induced microseismic activity detected and located during and after injection of super-critical carbon dioxide (scCO2) in the Illinois Basin – Decatur Project (IBDP) was used to help determine pathways the fluid took over time and to assess the risk of felt seismicity with injection. The microseismic activity at the site indicates locations where existing fractures and faults were reactivated but does not display a direct correlation with the locations of faults mapped in the seismic reflection volume. Most of the induced seismicity occurs below the reservoir in the fractured low porosity/permeability igneous basement rocks where fault identification proved problematic. Faults interpreted in the 2D and 3D seismic reflection data acquired are relatively small (a few 100s of m) and also have small interpretable displacements of up to 10 m on the largest faults. Temporal bursts of seismic activity define planar orientations of smaller structures within the individual clusters that are oriented oblique to the main trends. The poor correlation between the faults interpreted in the reservoir and the reactivated structures in the basement are indicative of their development in different tectonic regimes. Timing of the development of major structural trends around the Basin are consistent with the structural elements found at Decatur and help to explain the different orientations of faults. Combining the passive seismic results with the active seismic image interpretation enables an interpretation of the subsurface structure that is also consistent with the tectonic evolution of the basin. Keywords: structural interpretation, reflection seismic, induced seismicity, fault reactivation, fractures, subsurface fluid flow Suggested Citation: Suggested Citation Williams-Stroud, Sherilyn and Dichiarante, Anna Maria and Langet, Nadege and Leetaru, Hannes and Greenberg, S. and Stanek, Frantisek and Eisner, Leo, Integrating Induced Seismicity for Enhanced Subsurface Structural Interpretation at the Decatur, Illinois Sequestration Site. (November 28, 2022). Available at SSRN: https://ssrn.com/abstract=4287276 Sherilyn Williams-Stroud (Contact Author) University of Illinois Urbana-Champaign ( email ) 615 E Peabody DrChampaign, IL 61820United States Anna Maria Dichiarante NORSAR ( email ) KjellerNorway Nadege Langet NORSAR ( email ) KjellerNorway Hannes Leetaru The University of Illinois at Urbana-Champaign S. Greenberg Illinois State Geological Survey 615 E Peabody DrChampaign, IL 61820United States Frantisek Stanek affiliation not provided to SSRN Leo Eisner affiliation not provided to SSRN Download This Paper Open PDF in Browser Do you have a job opening that you would like to promote on SSRN? 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From June to August 2021, we deployed a dense seismic nodal network across the Hengill geothermal area in southwest Iceland to image and characterize faults and high-temperature zones at high resolution. The nodal network comprised 498 geophone nodes spread across the northern Nesjavellir and southern Hverahlíð geothermal fields and was complemented by an existing permanent and temporary backbone seismic network of a total of 44 short-period and broadband stations. In addition, we recorded distributed acoustic sensing data along two fiber optic telecommunication cables near the Nesjavellir geothermal power plant with commercial interrogators. During the time of deployment, a vibroseis survey took place around the Nesjavellir power plant. Here, we describe the network and the recorded datasets. Furthermore, we show some initial results that indicate a high data quality and highlight the potential of the seismic records for various follow up studies, such as high-resolution event location to delineate faults and body- and surface-wave tomographies to image the subsurface velocity structure in great detail.

One of the latest self-supervised learning (SSL) methods, VICReg, showed a great performance both in the linear evaluation and the fine-tuning evaluation. However, VICReg is proposed in computer vision and it learns by pulling representations of random crops of an image while maintaining the representation space by the variance and covariance loss. However, VICReg would be ineffective on non-stationary time series where different parts/crops of input should be differently encoded to consider the non-stationarity. Another recent SSL proposal, Temporal Neighborhood Coding (TNC) is effective for encoding non-stationary time series. This study shows that a combination of a VICReg-style method and TNC is very effective for SSL on non-stationary time series, where a non-stationary seismic signal time series is used as an evaluation dataset.