Remote monitoring of subsurface fluid flow

点击翻译按钮获取中文摘要

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.