The shapes of geological boundaries such as contacts and faults play a crucial role in the transportation, deposition and preservation of metals in magmatic and hydrothermal systems. Analyzing the shapes of geological boundaries, in particular those associated with mineralization, is an important step in 3D mineral prospectivity modeling. However, existing methods of shape analysis are limited in the adaptation of various shapes, scales and topologies of geological boundaries. This paper presents a general method of shape analysis based on mathematical morphology (MM), which is a generalization of the original MM method for shape analysis. The generalization extends the applicability of the original MM method from closed surfaces to general surfaces, while inheriting the real 3D and multi-scale analysis capabilities of the original method. This is achieved by regarding MM operations on 3D sphere structural elements as their equivalent operations, and redefining the operations to general surfaces. The generalized MM method enables us to handle complex 3D shapes such as overturned and/or recumbent geological boundaries as well as incomplete shapes due to weathering processes and data unavailability. The proposed method was applied to analyze the shape of an intrusive contact in the Fenghuangshan Cu ore field, Eastern China, whose shape was in the form of a non-closed surface. This analysis revealed a stronger spatial association between the large concave parts of the contact zone and the mineralization. Due to its enhanced adaptability to different shapes, the generalized MM method, compared with the original MM method, allows us to capture shape features that are more plausible for the geological setting.
相似文献Exploring the spatial relationships between various geological features and mineralization is not only conducive to understanding the genesis of ore deposits but can also help to guide mineral exploration by providing predictive mineral maps. However, most current methods assume spatially constant determinants of mineralization and therefore have limited applicability to detecting possible spatially non-stationary relationships between the geological features and the mineralization. In this paper, the spatial variation between the distribution of mineralization and its determining factors is described for a case study in the Dingjiashan Pb–Zn deposit, China. A local regression modeling technique, geological weighted regression (GWR), was leveraged to study the spatial non-stationarity in the 3D geological space. First, ordinary least-squares (OLS) regression was applied, the redundancy and significance of the controlling factors were tested, and the spatial dependency in Zn and Pb ore grade measurements was confirmed. Second, GWR models with different kernel functions in 3D space were applied, and their results were compared to the OLS model. The results show a superior performance of GWR compared with OLS and a significant spatial non-stationarity in the determinants of ore grade. Third, a non-stationarity test was performed. The stationarity index and the Monte Carlo stationarity test demonstrate the non-stationarity of all the variables throughout the area. Finally, the influences of the degree of non-stationary of all controlling factors on mineralization are discussed. The existence of significant non-stationarity of mineral ore determinants in 3D space opens up an exciting avenue for research into the prediction of underground ore bodies.
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