Identification of geochemical anomalies through combined sequential Gaussian simulation and grid-based local singularity analysis

2018 ◽  
Vol 118 ◽  
pp. 52-64 ◽  
Author(s):  
Jian Wang ◽  
Renguang Zuo
Minerals ◽  
2019 ◽  
Vol 9 (6) ◽  
pp. 368 ◽  
Author(s):  
Dingjie Chen ◽  
Junhao Wei ◽  
Wenhui Wang ◽  
Wenjie Shi ◽  
Huan Li ◽  
...  

Geochemical anomalies play an important role in mineral exploration, because they are closely related to the formation of ore deposits. In this paper, the Au in the geochemical samples of 1:50,000 stream sediments in the Gouli exploration area, Qinghai Province, is selected as an example. The cumulative frequency method, local singularity analysis, and exploration data analysis method are used to process the Au data and determine the abnormal thresholds. Robust principal component analysis is used to explore the elemental associations. Among them, the effect of local singularity analysis is the best and it delineates the weak geochemical anomalies not delineated by cumulative frequency method and exploration data analysis method, which shows its superiority. Robust principal component analysis shows that Sb, W, and As are closely related to Au mineralization. Three anomalous areas are delineated in the Gouli exploration area. Gold ore-body is found to occur within anomaly area I. The other anomalous areas are highly consistent with abnormal elemental composition of Sb, W, and As. Moreover, these two areas are extremely conformable with the high-value areas determined by the binary state method. The optimality of the three methods are compared comprehensively, it is pointed out that it is more reasonable to use the local singularity analysis to determine the abnormal threshold. The anomaly areas II and III of Au determined by local singularity analysis have shown great potential for prospecting.


2007 ◽  
Vol 14 (3) ◽  
pp. 317-324 ◽  
Author(s):  
◽  
◽  
◽  

Abstract. There are many phenomena in nature, such as earthquakes, landslides, floods, and large-scale mineralization that are characterized by singular functions exhibiting scale invariant properties. A local singularity analysis based on multifractal modeling was developed for detection of local anomalies for mineral exploration. An iterative approach is proposed in the current paper for improvement of parameter estimations involved in the local singularity analysis. The advantage of this new approach is demonstrated with de Wijs's zinc data from a sphalerite-quartz vein near Pulacayo in Bolivia. The semivariogram method was used to illustrate the differences between the raw data and the estimated data by the new algorithm. It has been shown that the outcome of the local singularity analysis consists of two components: singularity component characterized by local singularity index and the non-singular component by prefractal parameter.


2017 ◽  
Vol 50 (1) ◽  
pp. 97-120 ◽  
Author(s):  
Raphaël Nussbaumer ◽  
Grégoire Mariethoz ◽  
Erwan Gloaguen ◽  
Klaus Holliger

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