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

电磁法在物探中应用广泛，如矿产勘查、油气探测等；水、盐水和二氧化碳的管理，以及水库监测。**然而，在过去，电磁方法受到昂贵的数据收集的影响，我们现在正在收集大量的空间和时间数据，使用新的系统和仪器，这允许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、解释和理解产生的大量数据，就需要应对这些挑战。特别地，在本研究中，我们旨在研究采矿业从此类数据收集中产生的三个主要问题。**第一个问题是大尺度电磁数据的建模和反演。这些数据集通常是从空中收集的，包含数百万个数据点，分布在不同的频率、时间和空间尺度上。它们往往是高分辨率的，覆盖了地球的很大一部分。了解这些数据已成为最近的一个优先事项，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。为了寻找新的开采目标，支持人口增长，以及为页岩气和压裂绘制储层，需要这种测绘。**第二个问题是从通常收集的数据中提取新的信息和设计新的数据收集系统。鉴于高质量的机载数据，我们将研究提取可充电性的潜力，这是一些矿化目标的主要特性。目前，估计可充电性需要基于地面的电极系统，这阻碍了它在大片土地上的使用。**我们建议研究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。远景图预测矿化带的位置，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.