Collaborative Research: Coupled flow-geomechanical models applied to assess earthquake triggering in tectonically active regions – The Los Angeles basin, CA

诱发地震活动，或由人类活动引起的地震，是一个日益增长的社会问题，影响美国和世界各地的碳氢化合物和地热能生产，天然气储存和地下碳固存工作。在很少或没有自然地震活动的地区，构造地震和诱发地震的区别通常很简单。然而，在构造活跃地区，区分自然地震和诱发地震的难度要大得多，特别是后者只能通过地震的规模、频率或地理分布随时间的变化来检测。此外，这些地区的诱发地震活动带来了巨大的风险，因为人类活动可能引发更大和更具破坏性的地震。这项研究开发了最先进的，基于物理的模型，以调查如何近世纪的生产和废水注入的油气田的洛杉矶盆地，加州，影响了该地区的断层的稳定性。这些模型将考虑由构造和人为过程引起的断层应力变化，从而有助于区分构造事件和诱发事件。这项研究将推进调查和管理洛杉矶和其他构造活跃地区触发地震活动的方法，该项目开发了耦合地质力学和多相流体流动模型，以评估过去油气开采和污水回注对油田的影响世纪在加利福尼亚州洛杉矶盆地的地震活动。为了描述断层的力学和水力行为，以及压力变化和全应力张量对断层滑动的影响，本项目将采用先进技术，通过严格的非线性多相地质力学公式，对断层油藏中的耦合流动和地质力学进行建模。这些模拟将在详细的油藏模型中进行，这些模型嵌入盆地中构造活动断层系统的区域描述中。洛杉矶盆地作为一个优秀的实验室，研究触发地震活动，因为它广泛的现场操作，丰富的断层和水库数据，和历史的诱发地震活动和地面沉降。我们将从威尔明顿油田开始开始研究，该油田已生产超过25亿桶石油，造成地面沉降达9米。研究人员收集了5000多口威尔斯井的完整生产和注入计划（1936-2020年），用储层压力和地表变形测量值校准了他们的模型。然后，模拟将扩大到盆地规模，评估现场作业如何影响20多个活跃的走滑和逆冲断层系统的地震活动。这将包括对地震活动模式的详细分析，包括由机器学习目录记录的地震活动模式，以及对大型事件的关注（例如，1933年长滩M 6.3），发生在附近的领域。其目标是通过沿着功能更强的建模工具，更好地了解触发地震活动，从而以最小化地震危险的方式管理地下能源运营。该奖项反映了NSF的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。

Induced seismicity, or earthquakes caused by human activities, are a growing societal concern affecting hydrocarbon and geothermal energy production, gas storage, and subsurface carbon sequestration efforts in the Unites States and throughout the world. Distinguishing between tectonic and induced earthquakes is generally straightforward in areas with little or no natural seismicity. In tectonically active regions, however, discriminating between natural and induced seismicity is far more challenging, particularly as the latter may only be detected by changes in the size, frequency, or geographic distribution of earthquakes over time. Moreover, induced seismicity in these regions poses great risks, as human activities may trigger larger and more destructive earthquakes. This study develops state-of-the-art, physics-based models to investigate how nearly a century of production and waste-water injection in hydrocarbon fields of the Los Angeles basin, California, have impacted the stability of faults in the area. These models will consider stress changes on faults caused both by tectonic and anthropogenic processes, thus helping to distinguish between tectonic and induced events. This study will advance methodologies to investigate and manage triggered seismicity in Los Angeles and other tectonically active regions, as well as address the growing concerns about induced seismicity in a tectonically active region with a population of nearly 20 million people.This project develops coupled geomechanical and multiphase fluid flow models to assess the impact of hydrocarbon production and wastewater reinjection in petroleum fields over the past century on seismic activity in the Los Angeles basin, CA. To describe the mechanical and hydraulic behavior of faults, and the influence of the change in pressure as well as full stress tensor on fault slip, this project will employ advanced techniques for modeling coupled flow and geomechanics in faulted reservoirs with a rigorous formulation of nonlinear multiphase geomechanics. These simulations will be performed in detailed models of reservoirs embedded in regional descriptions of the tectonically active fault systems in the basin. The Los Angeles basin serves as an excellent laboratory to study triggered seismicity because of its extensive field operations, wealth of fault and reservoir data, and history of induced seismicity and ground surface subsidence. We will begin the study with the Wilmington field, which has produced more that 2.5 billion barrels of oil causing up to 9 meters of ground subsidence. The researchers have gathered the complete production and injection schedules (1936-2020) for more than 5000 wells to calibrate their models with reservoir pressure and measurements of ground surface deformation. Simulations will then be expanded to the basin scale, assessing how field operations have influenced seismicity on more than 20 active strike-slip and thrust fault systems. This will include detailed analysis of seismicity patterns, including those recorded by machine learning-enabled catalogs, as well as focus on large events (e.g., 1933 Long Beach M 6.3) that occurred in the vicinity of fields. The goal is to gain an improved understanding of triggered seismicity, along with more capable modeling tools, that can be used to manage subsurface energy operations in ways that minimize seismic hazard.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.