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

电磁方法通常用于地球物理勘探，如矿产勘探、碳氢化合物检测、水、咸水和二氧化碳的管理以及油藏监测。**过去，电磁方法需要昂贵的数据收集，现在我们使用新的系统和仪器收集大量的空间和时间数据，这允许我们以低得多的成本收集更高质量和精度的数据。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、解释和理解产生的海量数据，就需要应对这些挑战。具体地说，在本研究中，我们主要针对采矿业在这类数据采集过程中产生的三个主要问题进行研究。**第一个问题是大规模电磁数据的建模和反演。这样的数据集通常是从空中收集的，包含数百万个数据点，分布在空间的一系列频率或时间和尺度上。它们的分辨率往往很高，覆盖了地球的大片区域。理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内较小目标的工具。为了寻找新的采矿目标，支持人口增长，以及绘制页岩气和压裂储集层的地图，需要这种绘图。**第二个问题是从通常收集的数据中提取新信息和设计新的数据收集系统。鉴于高质量的航空数据，我们将调查提取带电能力的潜力，这是一些矿化目标的主要属性。目前，评估可充电性需要带有电极的地面系统，这阻碍了它在大片土地上的使用。**我们建议调查的第三个问题是地球物理和地质数据的整合，以获得远景图。勘探性地图可以预测矿化带的位置，因此可以用来降低矿产勘探的风险。

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.