Remote monitoring of subsurface fluid flow

远程监测地下流体流动

• 批准号: RGPIN-2020-06569
• 负责人: Butler, Karl
• 金额: $ 2.19万
• 依托单位: University of New Brunswick
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=751124
• 关键词: Remote; monitoring; subsurface; fluid; flow

Understanding the movement of fluids in Earth's upper crust, including soil moisture, groundwater, and oil and gas in deep reservoirs is important for a wide variety of reasons. Within the last three decades, geophysical methods have evolved to provide valuable non-invasive approaches for remote sensing of subsurface fluid flow. In the shallow subsurface this has led to improved understanding of numerous processes such as aquifer recharge, contaminant transport, discharge of agricultural nutrients to estuaries, dam seepage, permafrost degradation, and seawater intrusion. The long-term objective of this research program is to improve the sensitivity, and robustness of geophysical methods for monitoring subsurface fluid flow. Over the five-year term of this grant, I plan to focus on monitoring by the time-lapse Electrical Resistivity Imaging (ERI) approach, with special emphasis on the detection and quantification of hazardous concentrated seepage through embankment and rockfill dams used in power generation and mining. Such seepage can lead to internal erosion and piping, which is second only to overtopping as the most common cause of dam failure (Fell, 2005). The need for improved, non-invasive monitoring techniques is growing as the average age of dams rises, and is particularly evident with respect to tailings dams as brought to light by recent high profiles failures in Canada (e.g. Mt. Polley, BC, 2014) and abroad (e.g. Brumadinho, Brazil, 2019). Electrical resistivity surveys can detect concentrated seepage through its effect on moisture content within a dam, or as a consequence of the removal of electrically conductive clay particles by internal erosion. Seepage can also change resistivities seasonally in response to changes in the temperature and total dissolved solids (TDS) content of reservoir water as it following preferential pathways through the dam. Searching for such time-variable anomalies through autonomous long term monitoring can offer improved sensitivity. Regardless, it is a significant measurement challenge to recognize subtle seepage-related resistivity anomalies in the presence of noise and other variability. To begin, my team will conduct a field trial of 3D ERI monitoring at a large hydroelectric power dam in New Brunswick where we have significant research infrastructure already in place. We will pursue improvements in the spatial resolution, depth of exploration and sensitivity of ERI monitoring through innovations in electrode and survey design, statistical techniques for estimating and reducing noise, time-lapse imaging, and time series analysis. In year 3, we will expand our scope to explore the viability of monitoring for hazardous levels of seepage through mining/tailings dams. This will begin with modelling efforts to investigate the types of mining dams and seepage scenarios most amenable to monitoring, prior to undertaking field trials at one or more mine sites.

出于多种原因，了解地球上地壳中的流体运动（包括土壤湿度、地下水以及深层储层中的石油和天然气）非常重要。在过去的三十年中，地球物理方法的发展为地下流体流动的遥感提供了有价值的非侵入性方法。在浅层地下，这使得人们更好地了解含水层补给、污染物迁移、农业养分向河口排放、大坝渗漏、永久冻土退化和海水入侵等众多过程。 该研究计划的长期目标是提高监测地下流体流动的地球物理方法的灵敏度和鲁棒性。在这笔赠款的五年期限内，我计划重点关注延时电阻率成像（ERI）方法的监测，特别强调发电和采矿中使用的堤坝和堆石坝的危险集中渗漏的检测和量化。这种渗漏会导致内部侵蚀和管道堵塞，这是仅次于漫溢的大坝溃坝最常见原因（Fell，2005）。随着水坝平均年龄的增加，对改进的非侵入性监测技术的需求日益增长，对于尾矿坝而言尤其明显，加拿大（例如，不列颠哥伦比亚省波利山，2014年）和国外（例如，巴西布鲁马迪尼奥，2019年）最近发生的引人注目的失败事件所揭示的情况。电阻率测量可以通过其对大坝内含水量的影响或由于内部侵蚀去除导电粘土颗粒的结果来检测集中渗漏。当水库水遵循优先路径通过大坝时，渗流还会随温度和总溶解固体 (TDS) 含量的变化而季节性改变电阻率。通过自主长期监测来搜索此类时变异常可以提高灵敏度。无论如何，在存在噪声和其他变化的情况下识别与渗流相关的细微电阻率异常是一项重大的测量挑战。 首先，我的团队将在新不伦瑞克省的一座大型水力发电大坝进行 3D ERI 监测现场试验，我们已经在那里建立了重要的研究基础设施。我们将通过电极和调查设计、估计和减少噪声的统计技术、延时成像和时间序列分析方面的创新，追求提高 ERI 监测的空间分辨率、探索深度和灵敏度。在第三年，我们将扩大范围，探索监测采矿/尾矿坝渗漏危险水平的可行性。这将首先进行建模工作，以调查最适合监测的矿坝类型和渗漏情况，然后再在一个或多个矿场进行现场试验。