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中科大地球与行星物理学术报告通知-Ryan Schultz

报告地点:第五教学楼 5101 教室

报告时间:2024-11-20 从 10:00到12:00

报告人:Ryan Schultz(Swiss Seismological Service、ETH Zürich)

报告人简介:

After his MSc at the UofA, Ryan worked at the Alberta Geological Survey for ~8 years maintaining Alberta’s seismic network, cataloguing earthquakes, researching induced seismicity, and developing regulations. Following this, Ryan completed his PhD at Stanford University on the topic of designing risk-informed traffic lights to manage induced earthquakes. Since 2023, he has been working at ETH Zürich as a senior researcher

报告题目:Hydraulic fracturing induced seismicity: Identification, inferences, causes, and management

报告内容简介

报告人简介(续):

and currently co-leads the induced seismicity group within the Swiss Seismological Service.

报告简介:

Induced earthquakes have the potential for loss, as evidenced by cases that have been felt, damaging, or harmful.  On the other hand, when these risks are inadequately managed, resource development moratoriums can also cause harm from opportunity losses.  Thus, the management of their risks is vital to balancing these two considerations.  Earthquakes caused by hydraulic fracturing have been one category of induced earthquake requiring this treatment.  I discuss the history of hydraulic fracturing cases in Canada: starting from monitoring, identification, inferences for causation, and implications for susceptible regions.  Seismological study has provided a high-resolution picture of subsurface fault reactivation.  Complimentary/multidisciplinary efforts have indicated these earthquakes are reactivated via direct pore pressure effects from fluid flow along faults.  Correspondingly, earthquakes tend to be spatially biased in their basin-scale locations, to regions with susceptible features (e.g., high pore pressure, increased fault density).  This susceptibility can be modelled via machine learning approaches, to predict seismogenic regions.  A fundamental understanding of these earthquakes provides a firm foundation for risk management.  I outline a risk-based workflow to estimate red-lights, and highlight findings from the application to multiple sedimentary basins across the globe.  As well, I cover a newly developed statistical test to infer the presence of Mmax restricting the growth of induced seismicity – and highlight the implications for real-time risk management.  Overall, the support of fundamental understanding, coupled with risk-based treatment, has the potential to de-risk energy production.