Rescaled Range Analysis and Mineralization Information Extraction

• Published in: 2010 International Conference on Computing, Control and Industrial Engineering Vol. 2; pp. 210 - 213
• Main Authors: Li Wan, Jun Deng, Xiaocheng Deng, Qingfei Wang, Jiaoxiu Ling
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01-06-2010
• Subjects: Data mining; Fractals; Geology; Gold; Hurst exponent; Industrial engineering; Information analysis; Laboratories; long-range dependence; Mineralization; mineralization intensity; Ores; rescaled range analysis; Stochastic processes
• ISBN: 9780769540269; 0769540260
• DOI: 10.1109/CCIE.2010.171

Rescaled range (R/S) analysis of random events is known as to reveal the persistent or antipersistent nature of the process, while the Hurst exponent is the key parameter to determine the level of antipersistent. With a set of data from Dayingezhuang Gold Deposit, Shandong Province, China, the Stochastic Process of Au element content sequences various with the drilling depth is studied by the rescaled range analysis (R/S) method. Results show that Hurst exponents of non-mineralized zone are smaller than those of mineralized zone. The Hurst exponents of mineralized zone are greater than 0.66, which means that the stochastic processes obey the fraction Brownian motion and have long-range dependence. These results can provide a theoretical support for the establishment of the regional metallogenic prediction model.