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Hydroshearing, or shear stimulation, is recognized as the main method to exploit geothermal energy in hot low-permeability crystalline rocks at depth. It consists of enhancing permeability via injection-induced shear slip and dilation of preexisting fractures. , . Hydroshearing usually causes some induced microseismicity, sometimes of sufficient magnitude to be felt on the surface. Thus, high pressure fluid injection to enhance fracture permeability should be made carefully to avoid inducing earthquakes above the acceptable magnitude.

Geoenergies such as underground gas storage and energy storage, geothermal energy and geologic carbon storage are key technologies on the way to the foreseeable energy transition. The reservoir characterization in these projects remains challenging since predictive modeling approaches face limitations in identifying the spatial distribution of distinct lithologies and their hydro-mechanical properties from downwell testing procedures. Pumping tests are usually carried out to infer permeability, but offer only few observation points in space and require large extrapolation through inversion. The application of Physics Informed Neural Networks (PINN) offers a promising solution which can seamlessly incorporate field data, while enforcing the accordance with physical laws in the domain of study. This concept is implemented via two distinct loss terms for both the physical constraints and for the observational data in the loss function of an Artificial Neural Network (ANN). The physics-informed loss term contains a mass balance equation consisting of a storage and a diffusion component. The process is considered to be purely hydraulic and Darcy flow is assumed. The observational loss term compares the output of the ANN to a set of training data. This set consists of the system’s initial fluid pressure, as well as of a fluid pressure time series at the domain boundaries and at the borehole location. Preliminary results suggest that our PINN model is able to forecast the spatiotemporal fluid pressure distribution in a 2D domain for a variety of pumping test schemes. In this way, we give a first impression of the opportunities that PINN applications offer in the field of reservoir modeling.

To extend geothermal-energy power generation from hydrothermal systems to places without anomalies in the geothermal gradient, fractures of low-permeability rock- typically at 4-6 km depth to find <150°C - should be stimulated to create enhanced geothermal systems (EGS). However, most of the attempts to establish full-scale EGSs have resulted in high induced seismicity as a result of hydraulic stimulation, leading to project cancellation in some occasions. This has created a lot of insecurity in further investments in this kind of system. To achieve widespread deployment of EGSs alongside existing hydrothermal power plants, we need a thorough understanding of the effect of different hydraulic stimulation strategies on both permeability enhancement and induced seismicity. In this chapter, we compared three stimulation strategies in detail - constant rate, step rate and cyclic injection, for a range of dilatancy angles of the stimulated fracture. We find that the extent of fracture reactivation and pressure buildup depends on the injection scheme as well as the dilatancy angle. For a given dilatancy angle, we find that the cyclic-injection scheme provides the highest permeability enhancement as well as the highest slip, whereas both of them are observed to be the lowest for the step-rate injection.

Fluid injection into geological formations for energy resource development frequently induces (micro)seismicity. Moderate- to large-magnitude induced earthquakes may cause injuries and/or economic loss, with the consequence of jeopardizing the operation and future development of these geo-energy projects. To achieve an improved understanding of the mechanisms of induced seismicity, develop forecasting tools and manage the associated risks, it is necessary to carefully examine seismic data from reported cases of induced seismicity and the parameters controlling them. However, these data are challenging to gather together and are time-consuming to collate as they come from different disciplines and sources. Here, we present a publicly available, multi-physical database of injection-induced seismicity (Kivi et al., 2022a; 10.20350/digitalCSIC/14813), sourced from an extensive review of published documents. Currently, it contains 158 datasets of induced seismicity caused by various subsurface energy-related applications worldwide. Each dataset covers a wide range of variables, delineating general site information, host rock properties, in situ geologic and tectonic conditions, fault characteristics, conducted field operations, and recorded seismic activities. We publish the database in flat-file formats (i.e., .xls and .csv tables) to facilitate its dissemination and utilization by geoscientists while keeping it directly readable by computer codes for convenient data manipulation. The multi-disciplinary content of this database adds unique value to databases focusing only on seismicity data. In particular, the collected data aim at facilitating the understanding of the spatiotemporal occurrence of induced earthquakes, the diagnosis of potential triggering mechanisms, and the development of scaling relations of maximum possible earthquake magnitudes and operational parameters. The database will boost research in seismic hazard forecasting and mitigation, paving the way f

On November 26, 2021, the B.1.1.529 COVID-19 variant was classified as the Omicron variant of concern (VOC). Reports of higher transmissibility and potential immune evasion triggered flight bans and heightened health control measures across the world to stem its distribution. Wastewater-based surveillance has demonstrated to be a useful complement for clinical community-based tracking of SARS-CoV-2 variants. Using design principles of our previous assays that detect SARS-CoV-2 variants (Alpha and Delta), we developed an allele-specific RT-qPCR assay which simultaneously targets the stretch of mutations from Q493R to Q498R for quantitative detection of the Omicron variant in wastewater. We report their validation against 10-month longitudinal samples from the influent of a wastewater treatment plant in Italy. SARS-CoV-2 RNA concentrations and variant frequencies in wastewater determined using these variant assays agree with clinical cases, revealing rapid displacement of the Delta variant by the Omicron variant within three weeks. These variant trends, when mapped against vaccination rates, support clinical studies that found the rapid emergence of SARS-CoV-2 Omicron variant being associated with an infection advantage over Delta in vaccinated persons. These data reinforce the versatility, utility and accuracy of these open-sourced methods using allele-specific RT-qPCR for tracking the dynamics of variant displacement in communities through wastewater for informed public health responses.

As hydrothermal systems are limited to certain types of geologies, we need to create more Enhanced Geothermal Systems (EGSs) in order to scale electricity generation from geothermal energy. These are usually low-permeability rocks at depths of 4-6 km with temperatures >150ºC, which need to be stimulated to enable sufficient flow rates. Most of the previous attempts to create EGSs ended with high induced seismicity as an effect of hydraulic stimulation. The seismic activity led to cancellation of some projects along with creating a negative perception on both public and investors. Hence, it is crucial for us to have a detailed understanding of the hydro-mechanical (HM) processes taking place in the fractures leading to permeability enhancement (and consequent induced seismicity). We compare the HM response of the fracture for constant-rate injection, step-rate injection and cyclic injection protocols used in hydraulic stimulation. Our results suggest that the extent of fracture reactivation and pressure buildup relies on the injection protocol along with the dilatancy angle. For a particular dilatancy angle, we find that the cyclic injection protocol provides the highest permeability enhancement along with the highest slip, whereas both of them are observed to be the lowest for the step-rate injection protocol.

Geothermal energy presents a promising prospect as a substantial contributor to the globallow-carbon energy landscape. Most ofthe currently utilized energy comes from conventional geothermal systems that are either water or vapor dominated, and are limited to certain types of geologies. To scale up energy production from geothermal sources, exploration of alternative systems, such as Enhanced Geothermal Systems (EGS), supercritical geothermal systems, and closed loop geothermal systems, is imperative. Each of these systems, however, poses unique challenges for a successful deployment. In the case of EGS, hydraulic stimulation plays a critica! role in enhancing permeability within the poorly permeable, heatrich crystalline basement. A successful stimulation operation demands the achievement ofthe desired permeability, while effectively managing induced seismicity. A few EGS projects, notably Basel and Pohang, encountered difficulties in controlling postinjection seismicity, resulting in their eventual cancellation anda negative public perception of EGS. The injection protocols followed at these sites, namely step rate and cyclic injection protocols, were clearly inefficient in mitigating post-injection seismic events. Hence, it is essential to discern the differences between various injection protocols (i.e., constant rate, step rate and cyclic) in stimulation processes. We conducta numerical modeling study to investigate the hydromechanical (HM) response of a single fracture within an EGS to these protocols. The analysis revealed that these protocols yield comparable permeability enhancements. However, the cyclic injection protocol induced maximum slip during the injection phase, while the step rate protocol induced the largest slip during the post-injection phase. lmportantly, our findings emphasize that seismic activity primarily depends on the employed injection protocol rather than the vol u me of injected water. Simulation results also show that bleeding-off at

Geothermal systems require reliable reservoir characterization to increase the production of this renewable source of heat and electricity. We apply state-of-the-art Physics Informed Neural Networks (PINN) to model the fluid pressure evolution p(x,y,t) for the 2D reservoir domain. We set up a PINN for inferring p(x,y,t) by constraining an Artificial Neural Network’s (ANN) loss function with data and physics. In addition to time series measurements at the well location, we enforce the initial condition and boundary conditions. Since we lack observation points within deep geothermal reservoirs, we minimize the residual of a mass balance partial differential equation (PDE) on random collocation points inside the domain. Inside the PDE two data-driven ANNs are used to estimate the heterogeneous permeability field of the fractured reservoir k(x,y) and the flow rate at the injection borehole Q(t). We then train a separate ANN to estimate p(x,y,t), which leads to more stable modeling results than training these ANNs in parallel. We fine-tune these models by adapting the concept of dimensionless PDEs to the specific scaling requirements of ANNs. In addition, the weighting of loss terms is tested for several adaptive weighting schemes to find the optimum results. Our preliminary results indicate that with PINN and our current setup, we can infer the fluid pressure evolution for a high permeability contrast inside the reservoir while having only a small amount of observation points inside the domain.

Background & Aims: Subcutaneous vedolizumab formulation has been shown to be as effective and safe as the intravenous one in randomized control trials. Real-life data are limited especially for patients receiving long-term intravenous therapy. This study aimed to evaluate the safety and effectiveness of switching from intravenous to subcutaneous vedolizumab in a large cohort of patients with stable clinical remission.Methods: In this prospective cohort study, we enrolled consecutive patients attending our center between September 2021 and April 2022. The baseline demographic characteristics, 12- and 24-weeks follow-up clinical activity, C-reactive protein levels, and adverse events were recorded. The primary endpoint was to assess combined steroid-free clinical remission plus biochemical remission 24-week after the switch.Results: 93 patients (43 Crohn's disease, 50 ulcerative colitis), switched to subcutaneous vedolizumab after a median duration of intravenous treatment of 36 months [IQR 16-52]. At baseline, 80 patients (86%) had a combined remission. At 24-week, 89.2% (n=74) maintained combined steroid-free clinical remission plus biochemical remission. 25 adverse events were reported, mostly SARS-CoV-2 infections and injection site reactions, with a further four recurrence episodes. Twelve patients (12.9%) discontinued subcutaneous administration and restarted intravenous vedolizumab.Conclusions: Switching from intravenous to subcutaneous vedolizumab can be considered effective and safe for maintaining remission in patients with inflammatory bowel disease. In addition, this might reduce healthcare costs. However, large-scale real-life studies with long-term follow-up are necessary.