Remote monitoring of subsurface fluid flow

了解地球上地壳中流体的运动，包括土壤水分、地下水和深层储集层中的石油和天然气，具有重要的意义，原因很多。在过去的三十年里，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，这使人们更好地了解了许多过程，如含水层补给、污染物运输、向河口排放农业养分、大坝渗漏、永久冻土退化和海水入侵。这项研究计划的长期目标是提高地球物理方法监测地下流体流动的灵敏度和稳健性。在这笔赠款的五年期限内，我计划将重点放在通过延时电阻率成像(ERI)方法进行监测，特别强调检测和量化发电和采矿中使用的路堤和堆石坝中的危险集中渗漏。这种渗漏可能导致内部侵蚀和管道，这是仅次于溢流的最常见的大坝破坏原因(Fall，2005)。随着大坝平均年龄的增长，对改进的非侵入性监测技术的需求正在增长，对于最近在加拿大(例如Mt.波利，卑诗省，2014)和国外(如巴西，布鲁马迪尼奥，2019年)。电阻率测量可以通过对大坝内的水分含量的影响，或者由于内部侵蚀去除导电粘土颗粒的结果，来检测集中渗漏。渗流还可以随着水库水的温度和总溶解固体(TDS)含量的变化而季节性地改变电阻率，因为它沿着优先通过大坝的路径进行。通过自主的长期监测来搜索这种时变异常可以提供更高的灵敏度。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的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的一个大型水电站大坝进行3D ERI监测的现场试验，我们在那里已经建立了重要的研究基础设施。我们将通过创新电极和测量设计、估计和降低噪声的统计技术、延时成像和时间序列分析来提高ERI监测的空间分辨率、勘探深度和灵敏度。在第三年，我们会扩大工作范围，探讨监测采矿/尾矿坝渗漏危险程度的可行性。在一个或多个矿场进行实地试验之前，将首先进行建模工作，以调查最容易监测的矿坝类型和渗漏情况。

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.