Application of Discriminant Analysis and Support Vector Machine in Mapping Gold Potential Areas for Further Drilling in the Sari-Gunay Gold Deposit,NW Iran

In this contribution, we used discriminant analysis (DA) and support vector machine (SVM) to model subsurface gold mineralization by using a combination of the surface soil geochemical anomalies and earlier bore data for further drilling at the Sari-Gunay gold deposit, NW Iran. Seventy percent of the data were used as the training data and the remaining 30 % were used as the testing data. Sum of the block grades, obtained by kriging, above the cutoff grade (0.5 g/t) was multiplied by the thickness of the blocks and used as productivity index (PI). Then, the PI variable was classified into three classes of background, medium, and high by using fractal method. Four classification functions of SVM and DA methods were calculated by the training soil geochemical data. Also, by using all the geochemical data and classification functions, the general extension of the gold mineralized zones was predicted. The mineral prediction models at the Sari-Gunay hill were used to locate high and moderate potential areas for further infill systematic and reconnaissance drilling, respectively. These models at Agh-Dagh hill and the area between Sari-Gunay and Agh-Dagh hills were used to define the moderate and high potential areas for further reconnaissance drilling. The results showed that the nu-SVM method with 73.8 % accuracy and c-SVM with 72.3 % accuracy worked better than DA methods.     

2D probabilistic prediction of sparsely measured earth properties constrained by geophysical imaging fully accounting for tomographic reconstruction ambiguity

Many hydrological, environmental, or engineering exploration tasks require predicting spatially continuous scenarios of sparsely measured borehole logging data. We present a methodology to probabilistically predict such scenarios constrained by ill-posed geophysical tomography. Our approach allows for transducing tomographic reconstruction ambiguity into the probabilistic prediction of spatially continuous target parameter scenarios. It is even applicable to data sets where petrophysical relations in the survey area are non-unique, i.e., different facies related petrophysical relations may be present. We employ static two-layer artificial neural networks (ANNs) for prediction and additionally evaluate, whether the training performance of the ANNs can be used to rank geophysical tomograms, which are mathematically equal reconstructions of physical parameter distributions in the ground. We illustrate our methodology using a realistic synthetic database for maximal control about the prediction performance and ranking potential of the approach. For doing so, we try to link geophysical radar and seismic tomography as input parameters to porosity of the ground as target parameter of ANN. However, the approach is flexible and can cope with any combination of geophysical tomograms and hydrologic, environmental or engineering target parameters. Ranking of equivalent geophysical tomograms based on additional borehole logging data is found to be generally possible, but risks remain that the ranking based on the ANN training performance does not fully coincide with the closeness of geophysical tomograms to ground truth. Since geophysical field data sets do usually not offer control options similar to those used in our synthetic database, we do not recommend the utilization of recurrent ANNs to learn weights for the individual geophysical tomograms used in the prediction procedure.     

Designing infill directional drilling in mineral exploration by using particle swarm optimization algorithm

Geostatistical optimization in designing infill boreholes is an important cost-effective approach in increasing the accuracy of the tonnage and grade of an ore deposit. In this research, a new approach is proposed to design the optimum infill directional boreholes. In the proposed approach, the Kriging estimation variance is considered as the objective function and the number and properties of the optimum boreholes are estimated to minimize the objective function. The optimization procedure is implemented by Particle Swarm Optimization (PSO) algorithm. Range of the spatial and directional properties of new boreholes is determined by considering the primary information of the mineralization and administrative constraint of drilling. Then, the PSO algorithm is iteratively applied, and in each iteration, the variation of the estimated Kriging variance after drilling the new boreholes is determined and properties of the new boreholes are updated. The iterative procedure of the algorithm is continued until minimum Kriging variance is satisfied. The approach was applied to the Dalli Cu-Au porphyry deposit in Iran and three new infill directional boreholes were designed by considering six earlier boreholes from the preliminary exploration stage. New optimum boreholes were located where less information from the preliminary exploration stage exists and the highest variance is considered. Two new boreholes are near to vertical (78°) and the third is an inclined with 55° dip. By drilling these three new boreholes, the estimated grade model could be upgraded by 20%. For simplicity, quickness and the ability to search for the required numbers and specifications of a group of directional boreholes in a 3D environment are the most advantages aspects of the proposed approach.     

New climatic zones in Iran: a comparative study of different empirical methods and clustering technique

Theoretical and Applied Climatology - Recently in agricultural and industrial sectors, researchers have started to classify the climate of a region using empirical methods and clustering. This...     

Studies on the recovery of uranium from nuclear industrial effluent using nanoporous silica adsorbent

In this paper, the sorption of uranium onto nanoporous silica adsorbent in the presence of nitrate, sulfate, chloride, fluoride and phosphate was studied. The effect of contact time between the nanoporous sorbent and aqueous solution, pH and initial concentration of uranium was also investigated. Uranium sorption onto nanoporous silica adsorbent is a very fast process as sorption rate increases with pH increment. Optimum pH for uranium sorption was 4?C8. Experimental sorption isotherm is successfully described by Langmuir and Freundlich models. The results obtained by batch experiments showed that the presence of high concentration of nitrate, sulfate, chloride and phosphate anions alone had no interference with uranium recovery. However, the presence of fluoride ions (>250?mg/L) decreases uranium sorption by about 55?%. The results also showed that the presence of phosphate ions (about 300?mg/L) in solution could remove fluoride interference completely. Finally, the efficiency of the nanoporous silica adsorbent for uranium recovery from wastewater of the uranium conversion facility was investigated.     

Surficial deposits on salt diapirs (Zagros Mountains and Persian Gulf Platform, Iran): Characterization, evolution, erosion and the influence on landscape morphology

The surfaces of salt diapirs in the Zagros Mountains are mostly covered by surficial deposits, which significantly affect erosion rates, salt karst evolution, land use and the density of the vegetation cover. Eleven salt diapirs were selected for the study of surficial deposits in order to cover variability in the geology, morphology and climate in a majority of the diapirs in the Zagros Mountains and Persian Gulf Platform. The chemical and mineralogical compositions of 80 selected samples were studied mainly by X-ray powder diffraction and X-ray fluorescence. Changes in salinity along selected vertical profiles were studied together with the halite and gypsum distribution. The subaerial residuum formed from minerals and rock detritus released from the dissolved rock salt is by far the most abundant material on the diapirs. Fluvial sediments derived from this type of residuum are the second most common deposits found, while submarine residuum and marine sediments have only local importance. The mineralogical/chemical composition of surficial deposits varies amongst the three end members: evaporite minerals (gypsum/anhydrite and minor halite), carbonates (dolomite and calcite) and silicates-oxides (mainly quartz, phyllosilicates, and hematite). Based on infiltration tests on different types of surficial deposits, most of the rainwater will infiltrate, while overland flow predominates on rock salt exposures. Recharge concentration and thick accumulations of fine sediment support relatively rich vegetation cover in some places and even enable local agricultural activity. The source material, diapir relief, climatic conditions and vegetation cover were found to be the main factors affecting the development and erosion of surficial deposits. A difference was found in residuum type and landscape morphology between the relatively humid NW part of the studied area and the arid Persian Gulf coast: In the NW, the medium and thick residuum seems to be stable under current climatic conditions. Large sinkholes and blind valleys with sinking streams are common. On other diapirs, the original thick residuum is undergoing erosion and the new morphology is currently represented by salt exposures and badland-like landscapes or by fields of small sinkholes developed in the thin residuum. Models for evolution of the subaerial residuum and the diapir landscape/morphology are described in this paper. While the thick residuum with vegetation has very low erosion rates, the salt exposures and thin residuum are eroded rapidly. During wet periods (e.g. early Holocene), the diapirs rose and salt glaciers expanded as the influx of salt mass was much faster compared to erosion. After the onset of an arid climate, c. 6 ka BP, the rising of the some diapir surfaces decreased or even reversed due to acceleration of erosion thanks to vegetation degradation and changes in the residuum type and thickness.     

Comparing grain size distribution of sediment and original soil under raindrop detachment and raindrop-induced and flow transport mechanism

The grain size distribution (GSD) of sediment in comparison with the original soil GSD is discussed under different slopes (5, 15 and 25%) and rainfall intensities (30, 60 and 90 mm h^–1 with respective duration of 30, 15 and 10 min) but identical runoff (15 mm). The sediment quantification was carried out by raindrop-induced flow transport (RIFT) or/and transport by flow (FT) using a rainfall simulator and a 6 × 1 m² erosion plot and a silt loam. The results show a high degree of enrichment for size classes of 2–4 and 4–8 μm and a high degree of depletion for size classes of >63 μm under different slopes and rainfall intensities. In addition, the results show that the experimental enrichment ratio (ER) for particle size <16 μm under different slopes and rainfall intensities was greater than 1, while the ER for particle size >32 μm was less than 1.     

Effects of rainfall patterns on runoff and rainfall-induced erosion

Rainfall-induced erosion involves the detachment of soil particles by raindrop impact and their transport by the combined action of the shallow surface runoff and raindrop impact.Although temporal variation in rainfall intensity(pattern)during natural rainstorms is a common phenomenon,the available information is inadequate to understand its effects on runoff and rainfall-induced erosion processes.To address this issue,four simulated rainfall patterns(constant,increasing,decreasing,and increasing-decreasing)with the same total kinetic energy were designed.Two soil types(sandy and sandy loam)were subjected to simulated rainfall using 15 cm×30 cm long detachment trays under infiltration conditions.For each simulation,runoff and sediment concentration were sampled at regular intervals.No obvious difference was observed in runoff across the two soil types,but there were significant differences in soil losses among the different rainfall patterns and stages.For varying-intensity rainfall patterns,the dominant sediment transport mechanism was not only influenced by raindrop detachment but also was affected by raindrop-induced shallow flow transport.Moreover,the efficiency of equations that predict the interrill erosion rate increased when the integrated raindrop impact and surface runoff rate were applied.Although the processes of interrill erosion are complex,the findings in this study may provide useful insight for developing models that predict the effects of rainfall pattern on runoff and erosion.     

The role of blocking system in heavy precipitation of Iran (a case study: southeast of Iran January 2008)

This article concerns the analysis of the heavy precipitation, which allows investigating the effect of the blocking system on the unusual precipitation and temperature occurrence in Iran. The days of January 2008 have been the coldest days during the history of recorded data in Iran. Variation of precipitation during January 2008 compared with long-term data (30 years) shows the maximum positive anomaly in the stations located in southeast of Iran. However, the precipitation in consecutive days, 14–15 and 15–16 of January, produce a more important proportion of the heavy precipitation in this region. In order to study the role of the blocking system related to heavy precipitation in January 2008, the position and movement of the atmospheric systems including cyclones, anticyclones, fronts, and wind fields have been analyzed by the use of synoptic maps by the environment to circulation approach. Consequently, the weather maps indicated that the blocking system over the north of the Caspian Sea has caused the relatively deep low trough on January 5, 7, 14, 15, and 16, 2008, while the thermal and moisture gradients in the warm section of air masses have produced heavy precipitation. As a result, wind field of low levels (850 hPa) provided remarkable moisture fed by the Arabian Sea, Oman Sea, and Persian Gulf in the study area. Furthermore, the speed of wavelength and the position of the blocking system associated with the heavy precipitation can be clearly identified.