Title: From Stability to Intermittent Criticality: Forecasting Anthropogenic Seismicity in Complex Fracture Networks

Presenter: dr hab. Grzegorz Kwiatek

Link: https://teams.microsoft.com/meet/363959519319362?p=Tqi6dydJNdBh4BxzIL

Abstract:

As part of the St1 Deep Heat project (Helsinki, Finland), two hydraulic campaigns were carried out in 2018 and 2020 in adjacent 6-km-deep wells just 500 m apart. Both produced stable, pressure-controlled seismicity with no signs of runaway behavior, which could be kept in check simply by adjusting the injection. Because the two campaigns were so close together and so well recorded, they seemed an ideal case for calibrating (adaptive) traffic-light systems.

Yet when we tried to hindcast the seismicity rates and the largest expected magnitude using a new physics-based method, the two campaigns behaved very differently. The models we fit to each one disagreed on their key parameters, including the seismogenic index, the b-value, and the magnitude-frequency distribution, and their magnitude forecasts were inconsistent, ranging from large overestimates to large underestimates. As a result, we could not simply carry the settings from one stimulation over to its neighbor. The difference came down not to the injection rates alone but to fine structural variations within a heavily fractured reservoir that contained no major faults: small-scale complexity that controlled whether the seismicity stayed stable or began to drift.

To improve the forecasts, we applied machine learning, adding seismo-mechanical parameters that capture how earthquakes cluster and interact and how seismic energy release balances the hydraulic input. We compared the St1 case with two other studies that do contain distinct faults: the Cooper Basin (Australia) and laboratory fluid-injection experiments. Where distinct faults were present, seismo-mechanical parameters improved the forecasts; at St1, however, the distributed fracture network produced seismicity close to random in time and space, leaving little structure for the ML models to learn from. Forecasting deviations from stable behavior is therefore inherently harder in distributed fracture networks than on localized faults.

Laboratory stick-slip experiments on complex faults reveal that as stress builds, the fault enters a state of intermittent criticality. Small-scale asperities gradually break down and interact, collectively preparing the fault surface for a system-size slip by progressively smoothing the short- (mm-to-cm) scale stress field. The runaway earthquake on a complex fault is a statistical event that cannot be predicted deterministically. Nevertheless, the seismo-mechanical parameters and ML techniques may enable detection of the critical state of the system, when a runaway event becomes possible.

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Presenter:

Thomas Hein is a full professor and head of the Institute of Hydrobiology and Aquatic Ecosystem Management at BOKU University (University of Natural Resources and Life Sciences), Vienna, within the Department of Water, Atmosphere and Environment. He leads the BIGER research group, which studies how multiple stressors interact with spatial and long-term change to affect biogeochemical processes and biodiversity in rivers and wetlands, with particular attention to connectivity in aquatic networks and ecosystem resilience.

His research spans river, wetland, and floodplain ecology; aquatic biogeochemistry (nutrient and organic matter cycling, greenhouse gas dynamics, carbon sequestration); river restoration and ecohydrology; and socio-ecohydrological systems science. Much of his work centers on the Danube River basin, including coordination of Danube case studies addressing biodiversity and ecosystem management, as well as broader work on connectivity and restoration in riverine landscapes across Europe and beyond.

Seminar description:

Large river ecosystems, such as the Upper Danube, are highly fragmented due to extensive engineering measures for flood protection, hydropower production, and navigation. These modifications have led to the loss of instream habitat diversity, riparian habitats and floodplains, resulting in significant declines in aquatic biodiversity. Despite these challenges, large rivers continue to provide critical ecosystem services and support various human uses. Over the past 25 years, local-scale restoration measures have been implemented in the Upper Danube to improve the ecological conditions, particularly for fish populations and other organisms. This study applies the meta-ecosystem approach to assessing the cumulative effects of these localised restoration efforts across a 150 km-long river network. The meta-ecosystem approach was applied to integrate local habitat conditions and spatial factors by utilising network metrics. By considering the impacts of historical alterations, with a focus on functional longitudinal and lateral habitat connectivity, we evaluated how restoration measures influence ecosystem functions, resilience, biodiversity, and ecosystem services. Results demonstrated how functional connectivity has decreased over the last 200 years, how restoration measures have improved connectivity over the last 25 years, how fish populations are distributed within the current river network, and the migration patterns exhibited by different species. This approach offers a comprehensive framework for better understanding and guiding future restoration strategies in highly modified river systems.

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Venue: Polytech Tours, 64 avenue Jean Portalis, 37200 Tours, France

Description: This conference will focus on recent advances in the field of EO and field measurements of river systems. It will provide a comprehensive overview of the state of the art, address current scientific challenges and obstacles, and outline future developments related to the use of remote sensing data and its validation on the ground in the field of river science.

Read more: https://www.lestudium-ias.com/events/monitoring-freshwater-systems-earth-observation-field-measurements

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