The rise in the frequency of anthropogenic earthquakes due to deep fluid injections is posing serious economic, societal, and legal challenges to many geo-energy and waste-disposal projects. Existing tools to assess such problems are still inherently heuristic and mostly based on expert elicitation (so-called clinical judgment). We propose, as a complementary approach, an adaptive traffic light system (ATLS) that is function of a statistical model of induced seismicity. It offers an actuarial judgement of the risk, which is based on a mapping between earthquake magnitude and risk. Using data from six underground reservoir stimulation experiments, mostly from Enhanced Geothermal Systems, we illustrate how such a data-driven adaptive forecasting system could guarantee a risk-based safety target. The proposed model, which includes a linear relationship between seismicity rate and flow rate, as well as a normal diffusion process for post-injection, is first confirmed to be representative of the data. Being integrable, the model yields a closed-form ATLS solution that is both transparent and robust. Although simulations verify that the safety target is consistently ensured when the ATLS is applied, the model from which simulations are generated is validated on a limited dataset, hence still requiring further tests in additional fluid injection environments.

中文翻译：

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诱导地震性封闭式交通信号灯系统，用于在深层流体注入过程中进行精算决策。

由于注入深层流体而引起的人为地震的频率上升，对许多地能和废物处置项目构成了严重的经济，社会和法律挑战。现有的评估此类问题的工具仍然具有内在的启发性，并且大多基于专家的启发（所谓的临床判断）。作为一种补充方法，我们提出了一种自适应交通信号灯系统（ATLS），该系统是感应地震活动统计模型的功能。它基于地震震级与风险之间的映射关系，提供了风险的精算判断。使用来自六个地下油藏增产实验的数据（主要来自增强地热系统），我们说明了这种数据驱动的自适应预测系统如何保证基于风险的安全目标。建议的模型，首先确认它包括地震活动率和流速之间的线性关系以及后注入的正常扩散过程，该数据可以代表该数据。由于具有可集成性，该模型产生了透明且健壮的封闭形式ATLS解决方案。尽管仿真验证了在应用ATLS时始终可以确保安全目标，但是在有限的数据集上验证了生成仿真所基于的模型，因此仍然需要在其他流体注入环境中进行进一步测试。