NSERC Industrial Research Chair in Advanced Computational Methods for Geophysical Electromagnetics Modeling, Inversion and Integration

电磁法常用于地球物理勘探，如矿产勘探、碳氢化合物探测;水、盐水和CO2的管理，以及水库监测。而在过去，电磁方法遭受昂贵的数据收集，我们现在收集大量的数据在空间和时间，使用新的系统和仪器，这使得我们以更低的成本收集更高质量和准确性的数据。硬件和数据收集系统的这些改进带来了新的挑战，如果我们要使用，解释和理解所产生的大量数据，就需要应对这些挑战。特别是，在这项研究中，我们的目标是研究三个主要问题，从这样的数据收集，为采矿业。第一个问题是大规模电磁数据的建模和反演。这些数据集通常从空中收集，包含不同频率或时间和空间尺度的数百万个数据点。它们往往具有高分辨率，覆盖地球的巨大体积。了解这些数据已成为最近的优先事项，作为绘制大规模地质结构以及这些结构中较小目标的工具。为了寻找新的开采目标，支持人口增长，以及绘制页岩气和压裂储层图，需要进行这种测绘。第二个问题是从通常收集的数据中提取新信息，并设计新的数据收集系统。鉴于高质量的机载数据，我们将研究提取带电性的潜力，这是一些矿化目标的主要属性。目前，估计充电率需要基于地面的系统与电极，这阻碍了其使用在大面积的land.The第三个问题，我们建议调查的地球物理和地质数据的整合，以获得远景图。探矿图可预测矿化带的位置，因此可用于减少矿产勘探的风险。

Electromagnetic methods are commonly used for geophysical explorations in applications such as mineral exploration, hydrocarbon detection; management of water, salt water and CO2, and reservoir monitoring.Whereas, in the past, electromagnetic methods suffered from expensive data collection, we are now collecting massive amounts of data over space and time, using new systems and instrumentation, which allow for higher quality and accuracy of the data we collect, at much lower cost. These improvements in hardware and data collection systems bring new challenges that need to be met, if we are to use, interpret and understand the massive amounts of data generated. In particular, in this research we aim to study three main problems that arise from such data collection, for the mining industry.The first problem is the modeling and inversion of large scale electromagnetic data. Such data sets are routinely collected from the air and contain millions of data points over a range of frequencies or times and scales in space. They tend to be of high resolution and cover a huge volume of the earth. Understanding these data has become a recent priority as a tool to map large-scale geological structures as well as smaller targets within those structures. This mapping is needed in order to find new mining targets, support population growth, as well as map reservoirs for shale gas and fracturing.The second problem is the extraction of new information from commonly collected data and the design of new data collection systems. Given high quality airborne data, we will investigate the potential to extract chargeability, that is the leading property of some mineralized targets. Currently, estimating chargeability requires ground-based systems with electrodes, which hampers its use over large regions of land.The third problem we propose to investigate is the integration of the geophysical and geological data in order to obtain prospectivity maps. Prospectivity maps predict the locations of mineralized zones and therefore can be used to reduce risk in mineral exploration.