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Deep learning (DL) phase picking models have proven effective in processing large volumes of seismic data, including successfully detecting earthquakes missed by other standard detection methods. Despite their success, the applicability of existing extensively trained DL models to high-frequency borehole data sets is currently unclear. In this study, we compare four established models [Generalized Seismic Phase Detection (GPD), U-GPD, PhaseNet and EQTransformer] trained on regional earthquakes recorded at surface stations (100 Hz) in terms of their picking performance on high-frequency borehole data (2000 Hz) from the Preston New Road (PNR) unconventional shale gas site, in the United Kingdom (UK). The PNR-1z data set, which we use as a benchmark, consists of continuously recorded waveforms containing over 38 000 seismic events previously catalogued, ranging in magnitudes from −2.8 to 1.1. Remarkably, all four DL models can detect induced seismicity in high-frequency borehole data and two might satisfy the monitoring requirements of some users without any modifications. In particular, PhaseNet and U-GPD demonstrate exceptional recall rates of 95 and 76.6 per cent, respectively, and detect a substantial number of new events (over 15 800 and 8300 events, respectively). PhaseNet's success might be attributed to its exposure to more extensive and diverse instrument data set during training, as well as its relatively small model size, which might mitigate overfitting to its training set. U-GPD outperforms PhaseNet during periods of high seismic rates due to its smaller window size (400 samples compared to PhaseNet's 3000-sample window). These models start missing events below |$M_w$| −0.5, suggesting that the models could benefit from additional training with microseismic data-sets. Nonetheless, PhaseNet may satisfy some users' monitoring requirements without further modification, detecting over 52 000 events at PNR. This suggests that DL models can provide efficient solutions to the big data challenge of downhole monitoring of hydraulic-fracturing induced seismicity as well as improved risk mitigation strategies at unconventional exploration sites. [ABSTRACT FROM AUTHOR]

The article discusses the Collaboratory for the Study of Earthquake Predictability in China (CSEP) and its experiment design and preliminary results in CSEP2.0. It highlights the development of earthquake forecasting models and retrospective forecasting experiments conducted in high-seismicity regions, particularly in the North-South Seismic Belt in Central China. The study evaluates the effectiveness of forecasting models like the Pattern Informatics (PI) algorithm and the Relative Intensity (RI) algorithm, showing consistency with observed earthquake activity within a 5-year forecast window. The research aims to compare forecasting models on short-term, medium-term, and long-term scales, fostering international collaboration in earthquake prediction research. [Extracted from the article]

While deterministically predicting the time and location of earthquakes remains impossible, earthquake forecasting models can provide estimates of the probabilities of earthquakes occurring within some region over time. To enable informed decision‐making of civil protection, governmental agencies, or the public, Operational Earthquake Forecasting (OEF) systems aim to provide authoritative earthquake forecasts based on current earthquake activity in near‐real time. Establishing OEF systems involves several nontrivial choices. This review captures the current state of OEF worldwide and analyzes expert recommendations on the development, testing, and communication of earthquake forecasts. An introductory summary of OEF‐related research is followed by a description of OEF systems in Italy, New Zealand, and the United States. Combined, these two parts provide an informative and transparent snapshot of today's OEF landscape. In Section 4, we analyze the results of an expert elicitation that was conducted to seek guidance for the establishment of OEF systems. The elicitation identifies consensus and dissent on OEF issues among a non‐representative group of 20 international earthquake forecasting experts. While the experts agree that communication products should be developed in collaboration with the forecast user groups, they disagree on whether forecasting models and testing methods should be user‐dependent. No recommendations of strict model requirements could be elicited, but benchmark comparisons, prospective testing, reproducibility, and transparency are encouraged. Section 5 gives an outlook on the future of OEF. Besides covering recent research on earthquake forecasting model development and testing, upcoming OEF initiatives are described in the context of the expert elicitation findings. Plain Language Summary: The exact location, time, and magnitude of future earthquakes cannot be predicted. However, based on past earthquake sequences, it is possible to assess probabilities for future earthquakes. This is called earthquake forecasting. Operational Earthquake Forecasting (OEF) systems are designed to provide near‐real‐time authoritative earthquake forecasts, based on current earthquake activity, to aid the decision‐making of various societal stakeholders. Setting up these systems is complex, involving decisions about which model to use, how to best test the model, and how to turn earthquake probability estimates into practical information. This review captures the current state of OEF worldwide and analyzes expert recommendations on the development, testing, and communication of earthquake forecasts. Section 2 provides an overview of OEF‐related research and the background knowledge required to understand the other parts. Section 3 describes existing OEF systems of Italy, New Zealand, and the United States in detail. Section 4 discusses an elicitation of expert views on modeling, testing, and communicating earthquake forecasts (Mizrahi, Dallo, & Kuratle, 2023, https://doi.org/10.3929/ethz‐b‐000637239). Data from the elicitation allow to identify consensus and dissent on OEF issues and provide guidance for future earthquake forecasting efforts. Finally, Section 5 gives an outlook on future OEF‐related research and planned OEF efforts at various institutions. Key Points: We capture the state of earthquake forecasting systems in Italy, New Zealand, and the United States, and future plans in these and other countriesExperts encourage benchmark comparison, prospective testing, reproducibility and transparency, but avoid endorsing specific models or testsExperts stress the need to co‐design forecast communication products with end‐users to ensure their societal relevance and usefulness [ABSTRACT FROM AUTHOR]

SUMMARY: The United Kingdom (UK) experiences low-to-moderate levels of seismicity; only 12 onshore earthquakes with local magnitude (ML) ≥ 4.0 have been recorded in the past 20 yr. It is therefore difficult to estimate moment magnitude (Mw) using conventional moment tensor inversion for the majority of UK seismicity, resulting in limited reliable estimates of Mw. To address this, we calibrated coda envelopes at 16 broad-band seismic stations distributed across the UK to produce an Mw catalogue for 100 events with Mw ≥ 2.13 that occurred since 2006. This was achieved using the open-source Coda Calibration Tool, which requires independent source parameter estimates for calibration. For 13 UK events between 2006 and 2022, we used spectral modelling to estimate apparent stress (0.32–1.74 MPa) and moment tensor inversion to estimate Mw (3.35–4.52). These independent source parameters formed a subset of the inputs into the final calibration, which used seismic data from 33 events with coda-derived values of 2.57 $\le $  Mw $\le $ 4.49. The resultant coda calibration parameters were applied to 67 further events (Mw ≥ 2.13). The coda envelopes exhibit slow seismic coda decay across the UK, with significant energy up to 20 Hz, consistent with other regions of low tectonic activity. This Mw catalogue, and the application of the calibration to future UK seismic events, will be useful for both assessing seismic hazard and event characterization. [ABSTRACT FROM AUTHOR]

This article discusses the fundamental difference between the poststructuralist and evolutionary perspective of the postmodern emphasis on multiculturalism. The author discusses how Michael Foucault's relativistic view of the episteme is useful to the extent that it describes how individuals and groups of people generate knowledge, but because it does not recognize how that narrative reflects and is informed by our biological or shared human nature, ultimately the theory does little more than maintain the status quo. The author contends that Darwinian evolutionary theory offers the truest basis with which to deal with the perils and opportunities of being human, as that awareness affects not only the work of teachers and scholars, but also our relationship with the nature which binds us to life on this decreasingly commodious sphere.

The ability to successfully predict the future behavior of a system is a strong indication that the system is well understood. Certainly many details of the earthquake system remain obscure, but several hypotheses related to earthquake occurrence and seismic hazard have been proffered, and predicting earthquake behavior is a worthy goal and demanded by society. Along these lines, one of the primary objectives of the Regional Earthquake Likelihood Models (RELM) working group was to formalize earthquake occurrence hypotheses in the form of prospective earthquake rate forecasts in California. RELM members, working in small research groups, developed more than a dozen 5-year forecasts; they also outlined a performance evaluation method and provided a conceptual description of a Testing Center in which to perform predictability experiments. Subsequently, researchers working within the Collaboratory for the Study of Earthquake Predictability (CSEP) have begun implementing Testing Centers in different locations worldwide, and the RELM predictability experiment—a truly prospective earthquake prediction effort—is underway within the U.S. branch of CSEP. The experiment, designed to compare time-invariant 5-year earthquake rate forecasts, is now approximately halfway to its completion. In this paper, we describe the models under evaluation and present, for the first time, preliminary results of this unique experiment. While these results are preliminary—the forecasts were meant for an application of 5 years—we find interesting results: most of the models are consistent with the observation and one model forecasts the distribution of earthquakes best. We discuss the observed sample of target earthquakes in the context of historical seismicity within the testing region, highlight potential pitfalls of the current tests, and suggest plans for future revisions to experiments such as this one.