A Computational optimized extended model for mineral potential mapping based on WofE method

American Journal of Applied Sciences, Feb, 2009 by Ziaii Mansour, Pouyan Ali, Ziaei Mahdi

INTRODUCTION

A Geographical Information System (GIS) is a computer based system which integrates the data input; data storage and management, data manipulation and analysis and data output for both spatial and attribute data to support decision-making activities Malczewski (5). After over 40 years of development, GIS have been applied to serve important roles in many fields, such as environmental monitoring, resources management, applications in commerce and business fields and different utilities. The ultimate purpose of GIS is to make evaluations or predictions with different specific data integration models to combine spatial and attribute data from various sources to provide support for decision-makers.

According to Bonham-Carter (1), the data integration models in GIS are divided into two categories, data-driven and knowledge-driven model based on different methods for estimation of weights of different evidential maps. In data-driven models, the weights are calculated by using statistical methods and data of evidences in a training area to estimate the spatial relationships between the evidential maps and the final response maps. Data-driven models include Logistic Regression, Weights of Evidence, Neural Network and so on and the weights in those models are calculated from training data. While, the weights are estimated based on experts opinions in knowledge-driven models. The knowledge-driven models include Fuzzy Logic, Dempster-Shafer Belief Theory and their weights are given with experts' opinions.

Weights of evidence model is used to predict a hypothesis about occurrence of an event based on combining known evidence in a study area where sufficient data are available to estimate the relative importance of each evidence by statistical methods. In the case of mineral resources assessment, the evidence consists of a set evidential datasets (maps) and the models are used to predict the hypothesis about the occurrence of a given type of deposit in a study area. The weights are estimated from the measured association between known mineral occurrences and the values on the evidential maps. Based on combination of the evidential maps selected, the final result is extracted as a mineral potential map with a single index representing probability of occurrence of the given type of mineral deposit.

The purpose of this research is to demonstrate working of weighs of evidence model with using an application in the predication of Gold mineral occurrence in the Moalleman zone in Iran. The objectives of this research are: (1) to study the model for prediction of gold deposits in the study area and (2) to evaluate analysis result of application of this model.

In this research, a procedure for prediction of gold deposits using weights of evidence model in GIS and fuzzy c-means clustering together to integrate different evidential datasets, such as geological data, geophysical data, remote sensing and so on, described the results are evaluated.

APPLICATION TO GOLD POTENTIAL MAPPING IN TORUD-CHAH SHIRAN PROVINCEC

The Torud-Chah Shiran range lies in the central to eastern portion of the Alborz mountain system, a mountain chain of complex tectonic, magmatic and stratigraphic history (summarized by Alavi, 1996). On the basis of regional tectonic considerations, Alavi (9) suggested that the Torud-Chah Shiran range and volcanic rocks in the adjacent areas are related to Eocene magmatism in the Central Iran magmatic zone to the south and not to the volcanic rocks of the Alborz magmatic belt to the west. The distribution of Tertiary igneous rocks shows that the western portion of the Alborz arc merges with another Tertiary calc-alkaline magmatic belt, the Urumieh-Dokhtar zone, which runs parallel to the main northwest-trending Zagros thrust. Recently, Hassanzadeh (10) suggested that the two belts were once a single arc but separated by intra-arc extension that started in the late Eocene. Based on the latter view, the Alborz magmatic belt includes Torud-Chah Shiran and represents the northern half of the proto-arc. This arc is characterized by thick accumulations of early to middle Eocene submarine green tuffs (equivalent to the Karaj Formation of central and western Alborz), followed by late Eocene, to possibly early Oligocene, submarine to subaerial lava flows which locally include nepheline-normative and shoshonitic rocks. A series of silica-saturated volcanic rocks occur locally. The intra-arc spreading formed sedimentary basins between the Alborz range and Central Iran, an area characterized by Oligocene mafic-alkaline magmatism Hassanzadeh (10). Chemical compositions of volcanic rocks presented below indicate that Torud-Chah Shiran rocks have a typical arc signature, consistent with this proposed interpretation.

The Torud-Chah Shirin mountain range hosts many mineral showings and abandoned mines, particularly epithermal base metal veins. In addition to Gandy (Au-Ag-Pb-Zn) and Abolhassani (Pb-Zn-Ag-Au), other occurrences include Cheshmeh Hafez (Pb-Zn), Chalu (Cu), Chahmosa (Cu) and Pousideh (Cu). Other types of deposits in this range include placer gold, an underground mine for turquoise at Baghu, skarn deposits and Pb-Zn deposits in carbonate rocks. Gold is probably the product of weathering of nearby quartz sulfide veins hosted by andesitic volcanic rocks. The presence of tourmaline in the wall rocks of these veins may indicate proximity to a porphyry system. An abandoned iron skarn deposit is located at the contact of Cretaceous limestones andesitic lava flows and a quartz monzonite stock 2 km northwest of the study area. Reshm and Khanjar are abandoned Pb-Zn mines located 15 and 10 km. respectively, west of the study area. Ore in these localities occurred principally as veins in Cretaceous dolomitic limestones and consisted of quartz, calcite, galena, sphalerite and pyrite Shamanian (11).