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

GIS技术和基于奇点的非线性矿床预测理论的发展

• 批准号: RGPIN-2014-05441
• 负责人: Cheng, Qiuming
• 金额: $ 2.19万
• 依托单位: York University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2014
• 资助国家: 加拿大
• 起止时间: 2014-01-01 至 2015-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=567178
• 关键词: Development; GIS; technology; singularity; based

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.

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，预计世界矿物的使用量将增加。对矿产资源日益增长的需求正在推动勘探和生产进入前沿地区，例如被冰川沉积物、崩积层和冲积层、水、沙漠和植被覆盖的地区，这些地区隐藏着无法识别的资源。覆盖区的矿产资源预测和矿产勘探面临着覆盖带来的多重问题，如缺乏直接观测，反映地下矿化的基本地球化学和地球物理信号可能很弱，混合和部分缺失，这是由于某些地区的覆盖影响。国际上已经开展了大量的基础研究，以了解原生矿化、矿床覆盖层中次生矿元素的分散以及相应的地表介质异常的形成，从而开发更好、更强大的深穿透方法和技术，帮助在覆盖区进行勘探。然而，仍然没有一个连贯一致的协议来估计盖层下未被发现的矿产资源的可能性和概率。必须开发有效的技术，以便提取和综合信息，预测覆盖区的矿物资源。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，飓风和矿化是单一的过程，可能会导致异常数量的能量释放或质量积累，一般来说，局限于狭窄的时间或空间间隔。这类奇异事件由于发生频率低、时空范围有限，预测难度大。现代地球物理、地球化学和遥感技术所产生的高分辨率地图和数据大大增加了科学家绘制地球表面奇异事件响应图的可能性。近年来，非线性理论如倍增级联过程、自组织临界性、混沌和多重分形等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模拟为分形或多重分形，为解决复杂地质资源与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依据。例如，申请人基于奇异性和自相似性理论开发的新的尺度不变滤波方法已成功地应用于地质异常的表征和识别，以预测矿床。这项建议的主要目标是进一步发展基于奇异性的非线性理论和信息提取/综合技术，以预测被迁移的沙漠、风化层和冰川沉积物覆盖的地区中未发现的矿藏的位置。主要任务是：（1）建立矿床上方介质中元素浓度异常形成的数学模型，建立基于奇异性和自相似性理论的新信息技术，从地球化学和地球物理数据中提取与矿化有关的弱异常和复杂异常;和（3）基于乘法级联过程和空间决策建模过程的新技术，用于整合各种地理信息，以支持预测覆盖区内未发现的矿藏。这些研究将通过来自加拿大安大略Abitibi区和世界其他地方的案例研究加以展示。