Download or read book High-order Direct Block Support Simulation and Application at a Gold Mining Complex written by Joa̳o Pedro de Carvalho and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: "Over recent years, new methods have developed the mining production schedule stochastic optimization into a framework that includes, in one mathematical formulation, all the components of a mining complex and optimizes it simultaneously. A mining complex is a set of operations that integrate all aspects in a mineral value chain, starting from the materials extracted from the ground culminating with its transformations into a final product delivered to the mineral market. The framework diverges from past methods that optimize each operation of the mining complex separately, which do not benefit from the coexisting harmony between connected processors. Core inputs of this all-inclusive optimization are the geostatistical simulations quantifying variability and uncertainty of relevant attributes in a given mineral deposit. To date, the state-of-the-art simulation methods can reproduce complex geometries and multi-point connectivity of extreme values. However, the generated realizations are performed at the point-support which requires a post-processing step to generate block-support orebody models, as needed to represent the mineral deposit due to engineering purposes. For example, a multimillion block model requires discretization of the magnitude of hundreds of millions of nodes to simulate. This presents computational challenges in post-processing such a massive model. The first part of this thesis presents the high-order simulation method that generates realizations directly at the block support conditioned to the available data at point support scale. Following the sequential simulation paradigm, the method estimates, at each block location, the cross-support joint probability density function using Legendre-like splines as the set of basis functions needed. The previously simulated blocks are added to the set of conditioning data, which initially contains the available drillhole data. A spatial template, defined by the configuration of the block to be simulated and related conditioning values in both support scales, is used to infer additional high-order statistics from a training image. First, the method is tested in a controlled environment, and the simulated realizations show consistent results reproducing major structures and high-order relations of data. Second, the method is used to simulate a gold deposit, and its efficiency is demonstrated by reproducing spatial statistics up to a fourth-order, coinciding with the ones present in the available drillhole data. The running time of generating one realization with the proposed approach is reduced by a factor of 5 when compared to the point-support version of the algorithm.The second part of the thesis presents a case study where the simulations of the gold deposit mentioned above are incorporated into the simultaneous optimization of a gold mining complex. The resulting life-of-mine (LOM) production schedule yields 5 to 16% higher net present value when compared to the case, where the same mining complex is optimized, but the deposit is modelled through a traditional simulation method based on two-points statistics. The comparison shows that incorporating simulations with more realistic connectivities of high-grade blocks, through the use of high-order direct block simulations, into the optimization results in a more informed LOM production schedule. This shows that the optimization can capitalize on the better understanding of the connectivity of high-grades." --