Geochemical analysis of brine samples for exploration of Borate deposits in the South of Sabzevar

Mohammad-abad Oryan is the only potential source of borate in the North-east of Iran located in 50 km South of Sabzevar. The area is located in tuff marl, tuffaceous marl, volcanic braccia and tuff braccia structures. Remote sensing techniques, geological studies and integration of this data in GIS were applied in an area of about 600 square kilometers to locate the promising areas of borate mineralization for detailed studies (Bemani, 2012). The aim of this detailed geochemical study is to confine the anomaly areas for exploratory drilling and trenching.
Field studies were carried out in 9 geological traverses, mainly in Tonakar and Borje Kharkan area and 126 brine samples were taken from hydrothermal springs and 13 rock samples were taken from trenches. All the samples were analyzed for four elements, including B, K, Li and Mg. In order to determine the threshold quantities of the samples and isolation of anomaly, the data were analyzed using statistical methods including classical statistics, fractal geometry and EDA methods (Bemani, 2012).
Initial data analysis showed that there were no censored data. Also, by applying statistical hypothesis testing, no significant relation was observed between the elements in the two areas (except for Li). Therefore, all the statistical analyses were carried out separately.
After outlier correction, based on the amount of skewedness and histograms and probability plots of different elements, it became clear that none of the elements in the raw data distribution were normal and required to be transformed to be close to normal. In this study, logarithmic and three-parameter logarithm transformation were used in order to normalize the data . Based on the mean values, standard deviation of the normalized data, and background value and threshold, probable and possible anomalies were obtained and geochemical anomaly maps were drawn to identify the promising areas.
With the exception of the fractal pattern, anomaly separation methods are based on the differences of fractal dimensions between communities of geochemical data (Hasanipak and Sharafoddin, 2005). In this study, concentration area fractal method was used to separate anomalies from the background. Using fractal geometry, threshold value corresponding to the two areas (Tonakar and Borje Kharkan) were obtained and were plotted separately on geochemical maps.
Exploratory data analysis (EDA) is an approach to analyze data sets to summarize their main characteristics, often with visual methods (Filliben and Heckert, 2005). Exploratory data analysis is a useful method for analysis of geochemical exploration data. This is a statistical method known as the Robust Statistic classification (Carranza, 2009). In geochemical exploration, box plots, histograms and scatter plot are more practical. According to the box plots, the data of Tonakar and Borje Kharkan areas were classified and threshold levels were determined (Bemani, 2012).
Using the results obtained from different methods, geochemical maps of each area were prepared for all the elements and thresholds were obtained for each method. Moreover, the geochemical maps of each area were plotted for each element. According to the geochemical maps of Tonakar area, boron anomaly was observed in the East and West zones and the anomaly of the latter is larger. These areas were recommended for further detailed exploration and borehole drilling. Also, geochemical maps of Borje Kharkan showed anomaly in the central zone for all of the elements. The results showed that the highest and the lowest amounts of boron in brines samples vary between 6 ppm to 5930 ppm. Among boron and the three other elements (i.e. lithium, magnesium and potassium) a significant correlation was not observed. In terms of frequency, in most cases brines with high levels of boron (more than 1000 ppm) were concentrated in the South East of the Tonakar area. So, this area was suggested for detailed exploration (Bemani et al., 2014). Generally speaking, for considering the spatial distribution of data the fractal method could better identify the anomalies. Also, EDA is a quick and easy method to detect anomalies.