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首页> 外文期刊>Journal of Geochemical Exploration: Journal of the Association of Exploration Geochemists >Three-dimensional weights of evidence-based prospectivity modeling: A case study of the Baixiangshan mining area, Ningwu Basin, Middle and Lower Yangtze Metallogenic Belt, China
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Three-dimensional weights of evidence-based prospectivity modeling: A case study of the Baixiangshan mining area, Ningwu Basin, Middle and Lower Yangtze Metallogenic Belt, China

机译:基于证据的前瞻性建模的三维权重:以长江中下游成矿带宁武盆地白象山矿区为例

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This study uses geological data for the Baixiangshan iron deposit within the Ningwu Basin of the Middle and Lower Yangtze Metallogenic Belt, China, to create a 3 D prospectivity model that defines prospective areas for fu-. ture exploration for iron mineralization in the study area. The first stage of this modeling was to define geological and mineral deposit models for the Baixiangshan iron deposit, before determining quantitative exploration criteria using 3D spatial analysis; these criteria were then either split into prospective (e.g., positive magnetic anomalies) and unprospective areas using a threshold value (prospective areas have anomalies >980 nT) or were buffered to determine the spatial relationship between these criteria (the locations of faults, the bottom contact of the Lower Huangmaqing Formation, the top contact of the dioritic intrusion, and the location of blocks uplifted during intrusion) and mineralization; the prospective parts of these datasets were then in turn used to define prospective and unprospective areas on binary predictive maps. These binary predictive maps were then combined to create a weights of evidence-based 3D prospectivity model. This model highlights five highly prospective areas >100 m outside of areas of known mineralization that are favorable for exploration in the Baixiangshan mining area, all of which should be considered as high priority targets for future exploration. In addition, the modeling presented here indicates that an approach combining legacy geological data with 3D spatial analysis and weights of evidence modeling can identify the controls on mineralization within known orebodies. This knowledge can then be used to more effectively target areas for future mineral exploration.
机译:这项研究利用中国长江中下游成矿带宁武盆地白象山铁矿床的地质数据,创建了一个3D前景模型,该模型定义了富集的前景地区。研究区铁矿化的实际勘探。建模的第一阶段是在使用3D空间分析确定定量勘探标准之前,为白象山铁矿床定义地质和矿床模型。然后使用阈值将这些标准划分为预期(例如正磁异常)和非预期区域(异常> 980 nT的预期区域),或者将其缓冲以确定这些标准之间的空间关系(断层位置,底部下黄麻青组的接触,闪长岩侵入体的顶部接触,以及侵入过程中隆起的块体的位置)和矿化;然后依次将这些数据集的预期部分用于在二元预测图上定义预期和未预期的区域。然后将这些二进制预测图组合起来,以创建基于证据的3D前景模型权重。该模型突出显示了在已知成矿区之外> 100 m的五个高度有利区域,这些区域有利于白象山矿区的勘探,所有这些都应被视为未来勘探的高度优先目标。此外,此处介绍的建模表明,将遗留地质数据与3D空间分析和证据建模权重相结合的方法可以识别已知矿体中的矿化控制。然后,可以将这些知识用于更有效地瞄准将来的矿物勘探领域。

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