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Abstract Near real‐time seismicity forecasting is critically important for decision making during the reservoir creation phase of enhanced geothermal systems (EGS). To compute within a probabilistic framework the seismic hazard and risk posed by induced seismicity, it is necessary to calibrate robust forecast models, quantitatively assess their reliability, and capture the uncertainty of the process. Here, we test the performance of three model classes, each forecasting the induced seismicity observed during the failed 2006–2007 EGS reservoir creation underneath Basel, Switzerland. Each model class represents a logic tree branch that captures the epistemic uncertainty of the process; the aleatory variability is accounted for by bootstrapping of the observed seismicity. We calibrate each model using a range of updating strategies and quantitatively test the performances of the models using likelihood tests. We then define a combined model based on Akaike weights and show that the combined model outperforms, in our pseudoprospective testing environment, all of the individual models. We also show that seismicity recorded during the initial one to three days of seismicity, several days before the onset of felt seismicity, is sufficient for deciding with confidence that the prescribed injection regime will eventually lead to unacceptably high levels of seismicity.

In future distribution grids, prosumers (i.e., energy consumers with storage and/or production capabilities) will trade energy with each other and with the main grid. To ensure an efficient and safe operation of energy trading, in this paper, we formulate a peer-to-peer energy market of prosumers as a generalized aggregative game, in which a network operator is only responsible for the operational constraints of the system. We design a distributed market-clearing mechanism with convergence guarantee to an economically-efficient and operationally-safe configuration (i.e., a variational generalized Nash equilibrium). Numerical studies on the IEEE 37-bus testcase show the scalability of the proposed approach and suggest that active participation in the market is beneficial for both prosumers and the network operator. 11 pages, 8 figures. Published in IEEE Transactions on Smart Grid, 2022

The International Journal of Life Cycle Assessment, 22 (1912) ISSN:0948-3349 ISSN:1614-7502 1927

Fully open or partly open geothermal systems can induce potentially damaging seismicity. How this seismicity should be addressed depends on the geothermal system, its operational characteristics, the geological context, exposed buildings, existing infrastructure and populations, and social concern. This paper proposes an initial screening tool, called Geothermal Risk of Induced seismicity Diagnosis (GRID), for estimating to what extent induced seismicity is of concern for a specific project. A framework for tailor-made risk governance measures is then recommended, including hazard and risk assessment, social site characterization, seismic monitoring, insurance, structural retrofitting, traffic light systems, information and outreach, and public and stakeholder engagement. The proposed framework is currently customized to Switzerland and can be adapted to other regions or geo-energy applications.

We study segregation of a binary mixture of similarly charged particles under shear using particle-based simulations. We simulate particle dynamics using a discrete-element model including electrostatic interactions and find that particles segregate according to their net charge. Particles that are charged twice as strong as other particles of the same electrical sign are seen more at insulating boundaries with which we shear the system. Weakly charged particles, on the other hand, stay more in the center of the sheared bed. We propose a simple model based on electrostatic potential energy to understand this segregation. The model shows that the segregated system we observe in our simulations is indeed the most favorable configuration in terms of electrostatic potential energy. Our simulations further show that for a given packing fraction there is an optimal shear velocity where the segregation maximally intensifies. We show that this maximum results from a competition between diffusional and Coulomb fluxes. For a larger shear velocity, diffusion suppresses segregation.

Abstract

The Journal of Physical Chemistry C, 118 (10) ISSN:1932-7455 ISSN:1932-7447