识别俄克拉何马州和加利福尼亚州潜在的诱发地震并评估统计显著性
Identifying potentially induced seismicity and assessing statistical significance in Oklahoma and California
AI总结：
本文提出一种基于网格块纵向研究和似然比检验的统计方法，用于从大型数据集中识别诱发地震并评估显著性，应用于加州和俄克拉何马州废水处置与地震数据，确认俄州存在高度显著的诱发地震关联，加州结果则尚不确定。
摘要：
我们开发了一种用于从大型数据集中识别诱发地震的统计方法，并将该方法应用于加利福尼亚州和俄克拉何马州数十年的废水处置和地震活动数据。该方法对多种潜在陷阱具有稳健性。研究区域被划分为网格块。我们采用纵向研究设计，在每个网格块内沿时间序列寻找地震活动与废水注入之间的关联。纵向设计有助于控制废水注入的非随机应用。我们定义了一个足够灵活的统计模型，以描述具有时间相关性和高峰度的地震活动观测。在每个网格块中，我们找到将诱发地震危险性与每年注入的废水总量相关联的模型参数的最大似然估计。为评估显著性，我们在每个网格块以及加利福尼亚州和俄克拉何马州两个州分别计算似然比检验统计量。使用重采样来经验性地推导参考分布，用于从似然比统计量估计p值。在俄克拉何马州，分析以极高的置信度发现与废水处置（或其他相关活动，如储层枯竭）相关的地震活动已经发生。在加利福尼亚州，分析发现与废水处置相关的地震活动可能已经发生，但结果不够强，无法得出定论。我们识别出废水处置与地震活动之间时间关联明显的区域。我们的方法可应用于其他数据集，扩展以识别增加诱发地震危险性的风险因素，或修改以检验自然地震和诱发地震的替代统计模型。
英文摘要：
We develop a statistical method for identifying induced seismicity from large datasets and apply the method to decades of wastewater disposal and seismicity data in California and Oklahoma. The method is robust against a variety of potential pitfalls. The study regions are divided into gridblocks. We use a longitudinal study design, seeking associations between seismicity and wastewater injection along time-series within each gridblock. The longitudinal design helps control for non-random application of wastewater injection. We define a statistical model that is flexible enough to describe the seismicity observations, which have temporal correlation and high kurtosis. In each gridblock, we find the maximum likelihood estimate for a model parameter that relates induced seismicity hazard to total volume of wastewater injected each year. To assess significance, we compute likelihood ratio test statistics in each gridblock and each state, California and Oklahoma. Resampling is used to empirically derive reference distributions used to estimate p-values from the likelihood ratio statistics. In Oklahoma, the analysis finds with extremely high confidence that seismicity associated with wastewater disposal (or other related activities, such as reservoir depletion) has occurred. In California, the analysis finds that seismicity associated with wastewater disposal has probably occurred, but the result is not strong enough to be conclusive. We identify areas where temporal association between wastewater disposal and seismicity is apparent. Our method could be applied to other datasets, extended to identify risk factors that increase induced seismic hazard, or modified to test alternative statistical models for natural and induced seismicity.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
