Monitoring the thermal state of permafrost by automated time-lapse capacitive resistivity imaging

地下过程的长期监测越来越依赖于创新现场传感器的智能、系统数据收集。拟议项目的目的是开发一种新的技术概念，用于无创体积成像和永久冻土热状态的常规时间监测。在世界气象组织（WMO）全球气候观测系统（GCOS）的监测框架内，多年冻土已被确定为全球气候变化的六个冰冻圈指标之一。永冻层温度的变化与孔隙水的冻结或融化有关，导致电阻率的显著变化。无创评估和体积监测电阻率的变化是由四维电阻率断层扫描（ERT）。具有适当空间和时间分辨率的层析成像重建可以实现直观的可视化，并为冻融过程的定量分析开辟了重要的机会，包括校准永久冻土温度。然而，尽管传统ERT方法具有广泛的吸引力，但电传感器需要与地面进行电耦合。这需要将金属电极物理地植入活动层（受季节性冻结和融化的影响）或下面的永久冻土中。因此，由于传感器与基岩、土壤或建筑材料之间的接触电阻在冻结和融化时的高水平和大变化，这可能会导致现场测量的重大实际限制。使用一种新的电容耦合ERT方法，我们建议证明使用永久性原位电容传感器进行延时层析测量的技术可行性，以远程监测永久冻土的热状态。这将大大提高实验室永久冻土模拟实验和实地实际应用的监测能力。这项工作将包括数值模拟，以确定在现场和实验室规模上进行体积成像和长期监测永久冻土温度所需的最佳分布式电容传感器网络。在此基础上，设计了一个多传感器自动时延数据采集的测量系统，并建立了一个可行的实验室原型系统架构。随后，将开发一个功能台式样机，并演示多传感器数据采集和自动化操作的技术可行性。最后，我们将验证在受控实验室实验中进行自动时移温度校准CRI测量的概念，该实验模拟了基岩中永久冻土的生长、持续和融化。

Long-term monitoring of subsurface processes increasingly relies on intelligent, systematic data collection by innovative field sensors. The aim of the proposed project is to develop a new technology concept for the non-invasive volumetric imaging and routine temporal monitoring of the thermal state of permafrost. Permafrost has been identified as one of six cryospheric indicators of global climate change within the monitoring framework of the World Meteorological Organization (WMO) Global Climate Observing System (GCOS). Changes in permafrost temperature, associated with the freezing or thawing of pore water, result in significant changes in electrical resistivity. Non-invasive assessment and volumetric monitoring of resistivity changes are facilitated by 4D Electrical Resistivity Tomography (ERT). Tomographic reconstruction with appropriate spatial and temporal resolution enables intuitive visualisation and opens up the important opportunity for quantitative analysis of freeze-thaw processes, including the calibration to permafrost temperature. However, despite the broad appeal of conventional ERT methodology, electrical sensors require galvanic coupling with the ground. This requires that metal electrodes are physically implanted into the active layer (which is subject to seasonal freezing and thawing) or into the underlying permafrost. As a result, this can lead to significant practical limitations on field measurements due to high levels of and large variations in contact resistances between sensors and the host bedrock, soil or building material as it freezes and thaws. Using a novel capacitively-coupled ERT approach, we propose to demonstrate the technical feasibility of undertaking time-lapse tomographic measurements using permanent, in-situ capacitive sensors to remotely monitor the thermal state of permafrost. This will lead to significant improvements in monitoring capability, both for permafrost simulation experiments in the laboratory and for practical applications in the field. The work will include numerical simulation to determine optimal distributed capacitive sensor networks required for volumetric imaging and long-term monitoring of permafrost temperature, both at the field and laboratory scale. Based on the results, a measurement system for multi-sensor automated time-lapse data acquisition will be designed and a viable architecture for a laboratory prototype system will be established. Subsequently, a functional benchtop prototype will be developed and technical feasibility of multi-sensor data acquisition and automated operation will be demonstrated. Finally, we will validate the concept of making automated time-lapse temperature-calibrated CRI measurements in controlled laboratory experiments that simulate permafrost growth, persistence and thaw in bedrock.