Significance of the spatial point pattern and Fry analysis in mineral exploration
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ORIGINAL PAPER
Significance of the spatial point pattern and Fry analysis in mineral exploration Dezhi Zheng 1 & Chunzhong Ni 1 & Shitao Zhang 1 & Zhong Chen 1 & Junwei Zhong 1 & Jun Zhu 1 & Yujian Li 1 & Yongfeng Yan 1 Received: 15 February 2019 / Accepted: 20 August 2020 # Saudi Society for Geosciences 2020
Abstract This study explores the spatial relationship between the spatial distribution features and the fracture distribution of deposits in northeastern Yunnan based on spatial point pattern statistics and the Fry analysis method. The K(r) function value of the spatial point pattern analysis shows that the spatial distribution of lead-zinc deposits displays cluster features. Fry analysis shows that the spatial distribution of lead-zinc deposits can be divided into three distinct scales: the 5-km deposit scale, 20-km ore belt scale, and 100-km regional scale. With a change in the measured scale, the dominant direction in the spatial distribution of the lead-zinc deposits changes from northwest at a scale of 5 km to east-northeast and approximately northeast at a scale of 20 km to nearly north-south at a scale of 100 km. At the deposit and ore belt scales, northwest-southeast-striking faults may control lead-zinc mineralization. At the regional scale, north-south-striking faults affect the spatial distribution of lead-zinc deposits. The seven main orebodies in the Xiaohe lead-zinc deposit in Qiaojia County are used to analyze the features of the Xiaohe lead-zinc orebody. The orebodies at the deposit scale are distributed along a northwest-southeast direction, which seems to confirm the relationship between the northwest-southeast-striking faults and the lead-zinc deposits at the mining area scale, which is also consistent with the Fry analysis results. Keywords K(r) function . Fry analysis . Lead-zinc deposit . Xiaohe town . Northeastern Yunnan
Introduction The presence of a clustered distribution of ore deposits in the shallow crust is a common geological phenomenon that is present in many metallogenic provinces around the world (Dill 2011; Agterberg 2013; Omar et al. 2016). Systematic spatial data analysis can easily identify the spatial distribution features and relationship of deposits in ore-forming provinces (Carlson 1991). Accordingly, spatial point pattern analyses have a long history of use in geology, and many tests and methodologies can be utilized to describe and explore these data, thereby providing an important reference for the spatial distribution of deposits. In addition, Ripley K functions are Responsible Editor: Amjad Kallel * Chunzhong Ni [email protected] 1
Faculty of Land Resource Engineering, Kunming University of Science and Technology, Kunming 650093, China
widely used for spatial point analyses in many different disciplines (e.g., ecology, archeology, epidemiology, and astronomy) (Hanna and Fry 1979; Raines 2008). The Ripley function can be used to reflect the dependence of the spatial distribution of point events in a two-dimensional study area (Ripley 1977). Furthermore, the Fry
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