Environment
S. Abbaszade; F. Mohammad Torab; A. Alikhani; H. Molayemat
Abstract
In geochemical exploration, there are various techniques such as univariate and multivariate statistical methods available for recognition of anomalous areas. Univariate techniques are usually utilized to estimate the threshold value, which is the smallest quantity among the values representing the anomalous ...
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In geochemical exploration, there are various techniques such as univariate and multivariate statistical methods available for recognition of anomalous areas. Univariate techniques are usually utilized to estimate the threshold value, which is the smallest quantity among the values representing the anomalous areas. In this work, a combination of the Sequential Gaussian Simulation (SGS) and Gap Statistics (GS) methods was utilized as a new technique to estimate the threshold and to visualize the anomalous regions in the Hararan area, which is located in SE Iran, and consists of copper mineralization that seems to be connected to a porphyry Cu-Mo system. Furthermore, the most important advantage of this method is the reliable assessment of the anomalous areas. In other words, the anomalous areas were discriminated in terms of their probability values. The regions with high probability values were reliable and appropriate to locate the drilling points for a detailed exploration. It not only decreases the risk, cost, and time of exploration but also increases the drilling point reliability and precision of reserve estimation after drilling. In this research work, the results of analysis of 607 lithogeochemical samples for the element Cu were used. The SGS method was performed on the transformed data and 50 realizations were obtained. In the next step, the back-transformed realizations were utilized to obtain an E-type map, which was the average of 50 realizations. Moreover, the results of the GS method showed that the Cu threshold value was 228 ppm in the area. Therefore, using the E-type map, areas with values greater than 228 ppm were introduced as the anomalous areas. Finally, the probability map of the exceeding threshold values was acquired, and the anomalous districts located in the southern part of the studied area were considered as more reliable regions for future detailed exploration and drilling.
H. Molayemat; F. Mohammad Torab
Abstract
Coalbed methane (CBM) plays an important role in coal mining safety and natural gas production. In this work, The CBM potential of B2 seam in Parvadeh IV coal deposit, in central Iran, was evaluated using a combination of local regression and geostatistical methods. As there were 30 sparse methane sampling ...
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Coalbed methane (CBM) plays an important role in coal mining safety and natural gas production. In this work, The CBM potential of B2 seam in Parvadeh IV coal deposit, in central Iran, was evaluated using a combination of local regression and geostatistical methods. As there were 30 sparse methane sampling points in the Parvadeh IV coal deposit, no valid variogram was achieved for the methane content. A multivariate adaptive regression splines (MARS) model was used to reproduce the methane content data based on seam depth, thickness, and ash content. The MARS model results were used in ordinary kriging to estimate the methane content in all mine blocks. A combination of MARS modeling and ordinary kriging in CBM studies is introduced, for the first time, in this paper. The results obtained show that high methane zones are located in the central and south western parts of the deposit. The in situ CBM potential varies from 6.0 to 16.1 m3/t, and it was estimated to be 1.39 billion m3 at the average depth of 267 m in an area of 86.55 km2. Although this volume is remarkable, little is known as how much of this resource is actually producible. Consequently, high methane-bearing zones are highly recommended for further studies as a source of natural gas for extraction and reducing the hazards and explosion risks of underground coal mining.
