In-situ experiment reveals CO2 enriched fluid migration in faulted caprock.

The sealing characteristics of the geological formation located above a CO2 storage reservoir, the so-called caprock, are essential to ensure efficient geological carbon storage. If CO2 were to leak through the caprock, temporal changes in fluid geochemistry can reveal fundamental information on migration mechanisms and induced fluid-rock interactions. Here, we present the results from a unique in-situ injection experiment, where CO2-enriched fluid was continuously injected in a faulted caprock analogue. Our results show that the CO2 migration follows complex pathways within the fault structure. The joint analysis of noble gases, ion concentrations and carbon isotopes allow us to quantify mixing between injected CO2-enriched fluid and resident formation water and to describe the temporal evolution of water-rock interaction processes. The results presented here are a crucial complement to the geophysical monitoring at the fracture scale highlighting a unique migration of CO2 in fault zones.

Multi-Disciplinary Monitoring Networks for Mesoscale Underground Experiments: Advances in the Bedretto Reservoir Project.

The Bedretto Underground Laboratory for Geosciences and Geoenergies (BULGG) allows the implementation of hectometer (>100 m) scale in situ experiments to study ambitious research questions. The first experiment on hectometer scale is the Bedretto Reservoir Project (BRP), which studies geothermal exploration. Compared with decameter scale experiments, the financial and organizational costs are significantly increased in hectometer scale experiments and the implementation of high-resolution monitoring comes with considerable risks. We discuss in detail risks for monitoring equipment in hectometer scale experiments and introduce the BRP monitoring network, a multi-component monitoring system combining sensors from seismology, applied geophysics, hydrology, and geomechanics. The multi-sensor network is installed inside long boreholes (up to 300 m length), drilled from the Bedretto tunnel. Boreholes are sealed with a purpose-made cementing system to reach (as far as possible) rock integrity within the experiment volume. The approach incorporates different sensor types, namely, piezoelectric accelerometers, in situ acoustic emission (AE) sensors, fiber-optic cables for distributed acoustic sensing (DAS), distributed strain sensing (DSS) and distributed temperature sensing (DTS), fiber Bragg grating (FBG) sensors, geophones, ultrasonic transmitters, and pore pressure sensors. The network was realized after intense technical development, including the development of the following key elements: rotatable centralizer with integrated cable clamp, multi-sensor in situ AE sensor chain, and cementable tube pore pressure sensor.

Steam caps in geothermal reservoirs can be monitored using seismic noise interferometry.

Harvesting geothermal energy often leads to a pressure drop in reservoirs, decreasing their profitability and promoting the formation of steam caps. While steam caps are valuable energy resources, they also alter the reservoir thermodynamics. Accurately measuring the steam fraction in reservoirs is essential for both operational and economic perspectives. However, steam content estimations are very limited both in space and time since current methods rely on direct measurements within production wells. Besides, these estimations normally present large uncertainties. Here, we present a pioneering method for indirectly sampling the steam content in the subsurface using the ever-present seismic background noise. We observe a consistent annual velocity drop in the Hengill geothermal field (Iceland) and establish a correlation between the velocity drop and steam buildup using in-situ borehole data. This application opens new avenues to track the evolution of any gas reservoir in the crust with a surface-based and cost-effective method.

Monitoring microseismicity of the Hengill Geothermal Field in Iceland.

Induced seismicity is one of the main factors that reduces societal acceptance of deep geothermal energy exploitation activities, and felt earthquakes are the main reason for closure of geothermal projects. Implementing innovative tools for real-time monitoring and forecasting of induced seismicity was one of the aims of the recently completed COSEISMIQ project. Within this project, a temporary seismic network was deployed in the Hengill geothermal region in Iceland, the location of the nation's two largest geothermal power plants. In this paper, we release raw continuous seismic waveforms and seismicity catalogues collected and prepared during this project. This dataset is particularly valuable since a very dense network was deployed in a seismically active region where thousand of earthquakes occur every year. For this reason, the collected dataset can be used across a broad range of research topics in seismology ranging from the development and testing of new data analysis methods to induced seismicity and seismotectonics studies.

Real-time discrimination of earthquake foreshocks and aftershocks.

Immediately after a large earthquake, the main question asked by the public and decision-makers is whether it was the mainshock or a foreshock to an even stronger event yet to come. So far, scientists can only offer empirical evidence from statistical compilations of past sequences, arguing that normally the aftershock sequence will decay gradually whereas the occurrence of a forthcoming larger event has a probability of a few per cent. Here we analyse the average size distribution of aftershocks of the recent Amatrice-Norcia and Kumamoto earthquake sequences, and we suggest that in many cases it may be possible to discriminate whether an ongoing sequence represents a decaying aftershock sequence or foreshocks to an upcoming large event. We propose a simple traffic light classification to assess in real time the level of concern about a subsequent larger event and test it against 58 sequences, achieving a classification accuracy of 95 per cent.

Communicating Earthquake Preparedness: The Influence of Induced Mood, Perceived Risk, and Gain or Loss Frames on Homeowners' Attitudes Toward General Precautionary Measures for Earthquakes.

Despite global efforts to reduce seismic risk, actual preparedness levels remain universally low. Although earthquake-resistant building design is the most efficient way to decrease potential losses, its application is not a legal requirement across all earthquake-prone countries and even if, often not strictly enforced. Risk communication encouraging homeowners to take precautionary measures is therefore an important means to enhance a country's earthquake resilience. Our study illustrates that specific interactions of mood, perceived risk, and frame type significantly affect homeowners' attitudes toward general precautionary measures for earthquakes. The interdependencies of the variables mood, risk information, and frame type were tested in an experimental 2 × 2 × 2 design (N = 156). Only in combination and not on their own, these variables effectively influence attitudes toward general precautionary measures for earthquakes. The control variables gender, "trait anxiety" index, and alteration of perceived risk adjust the effect. Overall, the group with the strongest attitudes toward general precautionary actions for earthquakes are homeowners with induced negative mood who process high-risk information and gain-framed messages. However, the conditions comprising induced negative mood, low-risk information and loss-frame and induced positive mood, low-risk information and gain-framed messages both also significantly influence homeowners' attitudes toward general precautionary measures for earthquakes. These results mostly confirm previous findings in the field of health communication. For practitioners, our study emphasizes that carefully compiled communication measures are a powerful means to encourage precautionary attitudes among homeowners, especially for those with an elevated perceived risk.

Variations in earthquake-size distribution across different stress regimes.

The earthquake size distribution follows, in most instances, a power law, with the slope of this power law, the 'b value', commonly used to describe the relative occurrence of large and small events (a high b value indicates a larger proportion of small earthquakes, and vice versa). Statistically significant variations of b values have been measured in laboratory experiments, mines and various tectonic regimes such as subducting slabs, near magma chambers, along fault zones and in aftershock zones. However, it has remained uncertain whether these differences are due to differing stress regimes, as it was questionable that samples in small volumes (such as in laboratory specimens, mines and the shallow Earth's crust) are representative of earthquakes in general. Given the lack of physical understanding of these differences, the observation that b values approach the constant 1 if large volumes are sampled was interpreted to indicate that b = 1 is a universal constant for earthquakes in general. Here we show that the b value varies systematically for different styles of faulting. We find that normal faulting events have the highest b values, thrust events the lowest and strike-slip events intermediate values. Given that thrust faults tend to be under higher stress than normal faults we infer that the b value acts as a stress meter that depends inversely on differential stress.

Real-time forecasts of tomorrow's earthquakes in California.

Despite a lack of reliable deterministic earthquake precursors, seismologists have significant predictive information about earthquake activity from an increasingly accurate understanding of the clustering properties of earthquakes. In the past 15 years, time-dependent earthquake probabilities based on a generic short-term clustering model have been made publicly available in near-real time during major earthquake sequences. These forecasts describe the probability and number of events that are, on average, likely to occur following a mainshock of a given magnitude, but are not tailored to the particular sequence at hand and contain no information about the likely locations of the aftershocks. Our model builds upon the basic principles of this generic forecast model in two ways: it recasts the forecast in terms of the probability of strong ground shaking, and it combines an existing time-independent earthquake occurrence model based on fault data and historical earthquakes with increasingly complex models describing the local time-dependent earthquake clustering. The result is a time-dependent map showing the probability of strong shaking anywhere in California within the next 24 hours. The seismic hazard modelling approach we describe provides a better understanding of time-dependent earthquake hazard, and increases its usefulness for the public, emergency planners and the media.

Earth science: microseismicity data forecast rupture area.

On 28 September 2004 there was an earthquake of magnitude 6.0 at Parkfield, California. Here we show that the size distribution of the micro-earthquakes recorded in the decades before the main shock occurred allowed an accurate forecast of its eventual rupture area. Applying this approach to other well monitored faults should improve earthquake hazard assessment in future.