Development of GIS technology and singularity-based nonlinear theories for prediction of mineral deposit

矿产资源对大多数国家的可持续发展至关重要。根据目前的人口和消费趋势，预计世界对矿物的使用将会增加。对矿产资源日益增长的需求促使勘探和生产进入前沿地区，如冰川沉积物、崩积层和冲积层、水、沙漠和植被覆盖的地区，这些地区掩盖了资源而无法识别。覆盖区矿产资源预测和找矿工作面临着覆盖带来的多重问题，如缺乏直接观测，部分地区受覆盖影响，反映地下成矿作用的基本地球化学和物探信号可能较弱、混合或部分缺失。国际上已经进行了大量的基础研究，以了解矿床上盖层的原生矿化、次生矿元素的分散以及相应的地表介质异常的形成，以便开发更好、更强大的深钻方法和技术，帮助被盖区勘探。然而，对于估计地下未发现矿产资源的可能性和概率，仍然没有一致的协议。必须发展有效的技术，提取和综合资料，以预测被覆盖地区的矿产资源。地质复杂性领域的跨学科研究表明，许多类型的极端地质过程，如地震、飓风和矿化，都是单一的过程，可能导致异常数量的能量释放或质量积累，通常局限于狭窄的时间或空间间隔。由于这类奇异事件的发生罕见，且时间和空间范围有限，因此很难对其进行预测。现代地球物理、地球化学和遥感技术创造的高分辨率地图和数据大大增加了科学家绘制地球表面单一事件响应图的可能性。近年来，诸如乘级联过程、自组织临界、混沌和多重分形等非线性理论的发展极大地促进了地球科学的发展。奇异过程的最终产物被建模为分形或多重分形，为解决复杂地质资源和地质灾害问题的非线性模型和方法的创新提供了新的科学基础。例如，申请人基于奇异性和自相似理论开发的新的尺度不变滤波方法已成功应用于矿床预测的地质异常表征和识别。本建议的主要目标是进一步发展基于奇点的非线性理论和信息提取/集成技术，以预测在被运输的沙漠、风化层和冰川沉积物覆盖的地区未发现矿藏的位置。本文提出的主要任务是：(1)建立新的数学模型，用于模拟由乘级联机制向上运移引起的矿床上介质中元素浓度异常的形成；(2)基于奇异性和自相似理论的矿化弱复杂异常提取新技术；(3)基于乘级联过程和空间决策建模过程的多种地理信息整合新技术，支持覆盖区未发现矿床预测。这些研究将以来自加拿大安大略省阿比提比地区和世界其他地方的案例研究进行演示。

Mineral resources are essential for sustainable development of most nations. Based on current population and consumption trends, the world’s use of minerals is expected to grow. The increasing demand for mineral resources is driving exploration and production into frontier regions such as areas covered by glacial sediments, colluvium and alluvium, water, desert and vegetation that conceal a resource from recognition. Prediction of mineral resources and mineral exploration in covered areas face multiple problems imposed by the cover such as lack of direct observation and essential geochemical and geophysical signals reflecting underneath mineralization might be weak, mixed and partially missing due to the influence of cover in some areas. There have been substantial fundamental studies underway in the international community to understand the primary mineralization, the secondary ore element dispersion in covers over mineral deposits and accordingly formation of anomalies in the surface media in order to develop better and more powerful deep-penetrating methods and technologies to help exploration in covered areas. However, there is still no coherent protocol for estimating the possibility and probability of undiscovered mineral resources beneath cover. Effective technologies must be developed for extraction and integration of information for predicting mineral resources in covered areas. Interdisciplinary studies in the field of geocomplexity have demonstrated that many types of extreme geo-processes such as earthquakes, hurricanes and mineralization are singular processes that may result in anomalous amounts of energy release or mass accumulation that, generally, are confined to narrow intervals in time or space. Due to rare occurrence and limited time and space scope, prediction of these types of singular events is difficult. High resolution maps and data created by modern geophysical, geochemical and remote sensing technologies have significantly increased the possibility for scientists to map the responses of singular events on the earth surface. Recent development of nonlinear theories such as multiplicative cascade processes, self-organized criticality, chaos and multifractals have significantly advanced geosciences. The end products of singular processes have been modeled as fractals or multifractals which have provided a new scientific foundation for innovation of nonlinear models and methods for solving complex geo-resources and geo-hazards problems. For example, new scale-invariant filtering methods developed by the applicant based on singularity and self-similarity theories have been successfully applied for characterization and identification of geo-anomalies for prediction of mineral deposits. The main objective of this proposal is to further develop singularity-based nonlinear theories and information extraction/integration techniques for predicting location of undiscovered mineral deposits in regions covered by transported deserts, regolith and glacial sediments. The main tasks are proposed to develop: (1) New mathematical models for modelling formation of anomalies of element concentration in media over mineral deposits due to upward migration of multiplicative cascade mechanisms; (2) Novel information technologies based on singularity and self-similarity theories for mineralization-associated weak and complex anomalies extraction from geochemical and geophysical data; and (3) New technologies based on multiplicative cascade processes and spatial decision modelling processes for integrating diverse geoinformation in support of predicting undiscovered mineral deposits in covered areas. The studies will be demonstrated with case studies from Abitibi district of Ontario, Canada and elsewhere in the world.