Quantitative Prediction of Blind Ore Deposits

The issues of energy and mineral resources research, are not only frontier scientific issues, but also national demand issues. The rapid development of China’s economy has expanded the demand for mineral resources (incl. resource quantity and types) tremendously in recent years. At the same time, the known shortage of mineral resources has made it increasingly difficult to find them, leading to an increasing supply-demand contradiction in mineral resources. Facing with such a severe situation of mineral resources, it is urgent to solve the problems of difficult identification, difficult discovery and difficult utilization, as well as new types, new depths, and new techniques, which require high attention to the joint research and development of new theories, new technologies and new methods. In particular, nowadays the object of mineral exploration has been from locating the superficial deposits, shallow deposits, easy-to-identify deposits to concealed deposits, deep deposits, difficult-to-identify deposits in China, the difficulty in prospecting is swelling, and the success rate of mineral exploration depends more on intensified study in metallogenic laws, mineral resources prediction theories and scientific evaluation methods.

Predicting mineral outcomes entails making informed decisions in contexts characterized by uncertainty (Zhao in Earth Sci Front 14(05):1–10 (2007)) and constitutes a sophisticated system engineering endeavor. This procedural undertaking necessitates adherence to contemporary principles of metallogeny, as well as the systematic exploration and assessment of mineral resources, grounded in robust geological fundamentals and comprehensive analyses of metallogenic patterns. Moreover, it is contingent upon the utilization of cutting-edge earth exploration technologies, sophisticated information processing methods, predictive models, and methodologies, coupled with the expertise and practical experience of seasoned professionals.

This chapter provides a systematic exposition of the principles and methodological system for 2D prediction and evaluation of mineral resources based on the GIS platform. It focuses on data collection and preprocessing, prospecting model establishment, quantification and transformation of digital models, analysis and extraction of metallogenic geological conditions, as well as implementation methods for positional, quantitative assessment, and fixed-probability prediction. By extensively collecting geological, geophysical, geochemical, remote sensing geological, and mineral data in the study area while summarizing metallogenic laws in-depth guided by theories such as geological anomaly ore-forming theory and comprehensive information mineral evaluation, multivariate geological prospecting information is extracted using the GIS platform. Mathematical models like Weights of Evidence are employed to synthesize this information for delineating favorable ore-forming areas.

The southern margin of the North China craton, characterized by a platform-type double-layer crust structure with a complex geological evolution history, represents a typical northern craton land block and is an important area for copper resource in China. Based on the systematical summary of the Precambrian geological evolution in the region, this chapter categorizes the main types and metallogenic periods of copper deposits, and analyzes and summarizes the accumulation process and post-mineralization preservation conditions. A prospecting model for copper deposits on the southern margin of the North China craton is established and The GIS platform is utilized to quantitatively extract favorable metallogenic information which is kept by the metallogenic process including the material source, the mi gration channel, the accumulation space, the ore-induced anomaly, etc., as well as to analyze post-mineralization preservation conditions quantitatively in this chapter. Based on quantitative analysis results of the metallogenic process, two Grade A_s (A_2-1, A_2-2) and two Grade B_s (B_2-1, B_2-2) prospective areas are proposed. Subsequently, mineral resources are predicted by using the Deposit Model method resulting in the delineation of five prospective areas (three Grade A_s: A_3-1, A_3-2, A_3-3; two Grade B_s: B_2-1, B_2-2). The prospective areas identified through both prediction methods exhibit significant overlap or adjacency with known deposits indicating favorable metallogenic conditions and great potential for the prospecting of copper resource.

This chapter meticulously delineates the theories and methodologies integral to the 3D quantitative prediction of mineral resources. Drawing upon established tenets within mathematical geology, multivariate statistical analysis, and metallogenic prediction theory, the realization of 3D mineral resource prediction is facilitated through sophisticated approaches such as computer-generated 3D geological body modeling and advanced 3D visualization technology. This undertaking is firmly grounded in the robust framework of well-established 2D metallogenic prediction research methods and workflow.

The 3D quantitative prediction method of mineral resources refers to the technical route, process and main technical method for realizing the 3D quantitative prediction. In this chapter, with basic geological data as the data foundation and mineralization laws as the geological theory guidance for ore exploration, a 3D geological data model is used for ore exploration analysis to achieve quantitative prediction and evaluation of mineral resources and to realize the conversion from 2D prediction to 3D prediction.

Through a meticulous examination of comprehensive datasets, we have acquired an in-depth comprehension of the metallogenic geological context prevailing in the investigated region. Building upon this understanding, a 3D geological model of the Jiaojia gold metallogenic belt was formulated, and an exhaustive prospecting model was synthesized. Commencing from this model, we employed the cubic prediction model to establish a block model specific to the study area. By ascribing values to individual blocks and scrutinizing the conducive conditions associated with each prediction factor, we devised a quantitative prediction model for the Jiaojia gold metallogenic zone.

This study focused on the Laochang ore field located in Gejiu, Yunnan Province, China, with the ore field used as a case study for scrutinizing a 3D quantitative prediction and assessment methodology applicable to mine scale. This involved a comprehensive synthesis of the geological backdrop of the Laochang ore field with established metallogenic theory, resulting in a thorough examination of the geological model governing the region. We extensively utilized available exploration data and harnessed the capabilities of 3S technologies (GIS, RS, GPS) to extract a wealth of multivariate information encompassing geological, geographical, remote sensing, geophysical, and geochemical datasets.