نوع مقاله : مقاله پژوهشی
نویسندگان
1 دانشکده مهندسی معدن و متالورژی، دانشگاه صنعتی امیرکبیر
2 دانشکده معدن، نفت و ژئوفیزیک، دانشگاه صنعتی شاهرود
3 داشکده مهندسی معدن، دانشگاه صنعتی اصفهان
چکیده
کلیدواژهها
موضوعات
عنوان مقاله [English]
نویسندگان [English]
In this paper, Graphical Evaluation and Review Technique (GERT) network analysis technique used in exploration project management for anomaly separation methods and a suitable model will be created by combining two methods of fractal geometry and U spatial statistics. In mineral exploration project (according to situation of geology, geological structure and mineralogical at mineralization area and because of probabilistic nature of them), Fatal mistakes can happen when starting exploration activity for anomaly separation.
Spatial invariance and frequency distribution of samples are the most characteristics of geochemical data to determine the isotropy or anisotropy variation. Since these projects consist of various uncertain and probable activities that may be repeated frequently, we can model those processes as stochastic networks such as GERT network. Therefore, in mining activities GERT networking is applied frequently, and certainly led to increase the accuracy and performance of the process.
This study is mainly focused in the Cu-Au Northern-Dally porphyry deposits that are exposed within the Urumieh-Dokhtar Magmatic Arc. The concentration–area (C-A) fractal model (based on Fractal dimensions) and moving average technique (U special statistic; based on window size ore search radius) have been used for decomposition and separation of anomalous patterns of geochemical data. So the probability of performing a lot of activities already in fractal geometry, reproducibility of a set of activities in U-spatial statistic, or probability of select one of these methods according to exploration project just interpreted with GERT networking.
The result of combining these networks is implemented and show similar result with high overlapping to recognize anomaly area. With step by step implementation of possible activities for each method, Au and Cu show high overlapping in different populations. This finding implies to the precision and accuracy of fractal and U- spatial statistics. Third population with highest dimension and maximum degree of populations break-point in fractal geometry shows that values >560 ppb for Au and >1700 ppm for Cu are distinguished as anomalous data. While, U- spatial statistics indicate the value higher than average+ one standard division (Ū+S) equal to 1.47 (>500 ppb) for Au and equal to 1.45 (1650 ppm) for Cu are the threshold value for anomaly population.
کلیدواژهها [English]