Fractal pattern integration for mineral potential estimation

Abstract

Concepts of fractaYmultifractal dimensions and fractal measure were used to derive the prior and posterior probabilities that a small unit cell on a geological map contains one or more mineral deposits. This has led to a new version of the weights of evidence technique which is proposed for integrating spatial datasets that exhibit nonfractal and fractal patterns to predict mineral potential. The method is demonstrated with a case study of gold mineral potential estimation in the Iskut River area, northwestern British Columbia. Several geological, geophysical, and geochemical patterns (Paleozoic-Mesozoic sedimentary and volcanic elastic rocks; buffer zones around the contacts between sedimentary rocks and Mesozoic intrusive rocks; a linear magnetic anomaly; and geochemical anomalies for Au and associated elements in stream sediments)were integrated with the gold mineral occurrences which have fractal and multifractal properties with a box-counting dimension of 1.335 • 0.077 and cluster dimension of 1.219.4-0.037.

Spatial data analysis of mineral deposit point patterns: Applications to exploration targeting

“…This reasoning is similar to the concept of fractal dimensions (Mandelbrot, 1983;Cheng et al, 1996;Carranza, 2009) used to characterise self-similarity and scale dependency of a spatial pattern. Fractal analysis for ore fields with N 0.5 t of gold in each indicates a bifractal distribution with a cross-over distance of~40 km (Fig.…”

Data-driven based logistic function and prediction-area plot for mineral prospectivity mapping: a case study from the eastern margin of Qinling orogenic belt, central China

“…5b so as to obtain a prospectivity map. This method was proposed by Cheng (1994) and has been used and approved by a number of geologists (Cheng et al, 1994(Cheng et al, , 1996Cheng and Agterberg, 1995;Xiang et al, Wei and Pengda, 2002;Weiberg et al, 2004;Hodkiewicz et al, 2005;Ford and Blenkinsop, 2008;Raines, 2008;Satyabrata Behera,2019;Chen, 2019). It applies the logarithm of the concentration and the logarithm of the corresponding area greater or equal to concentration as the X-axis and Y-axis separately, which can reflect the fractal characteristics inherent in the prediction map.…”

Controls on Cu mineralization in central part of the Kerman porphyry copper belt, SE Iran:constraints from structural and spatial pattern analysis

“…Fractal analysis of a certain mineral deposit type and its occurrence to infer their geologic controls have been demonstrated by Carlson (1991), Wei and Pengda (2002), Cheng and Agterberg (1995), Cheng et al (1996), Ford and Blenkinsop (2008), Raines (2008), Carranza et al (2008) and Carranza (2009).…”