Hydrogeological assessment of the Tabarteh fault zone by physicochemical analysis and multivariate statistical methods

Hydrogeologically, faults may impede, conduit, exert no influence, or may play a combination of these roles on groundwater flow. The object of this paper is to study the hydrogeological role of the Tabarteh fault, which is located on the border of Zagros and Central Iran tectonic zones in an alluvial aquifer. The recorded data of water table levels, chemical parameters, and discharge rate of wells, in addition to geological maps and geophysical results, were collected and evaluated. The outcrop of travertine in limited areas and the emergence of a few small springs within the alluvium show a barrier role of the fault in the groundwater flow. The spatial analysis of chemical components, head time series, and groundwater flow direction assessment demonstrated that the fault acts as both a barrier and a non-barrier in different sections. The multivariate statistical methods of cluster and discriminant analyses also confirm the dual role of the fault.     

Intrinsic groundwater vulnerability determination at the aquifer scale: a methodology coupling travel time estimation and rating methods

Groundwater vulnerability has been subject of much research due to the valuable information it provides concerning groundwater protection and exploitation potential. Up to now, most groundwater vulnerability studies adopt subjective systems of rating the various factors and subsequently, their results are often ambiguous and contradicting. Within the present study a methodology for the estimation of intrinsic groundwater vulnerability at the aquifer scale is presented. The methodology is based on travel time estimation from specified sources of pollution to the aquifer. Besides the deterministic calculation of travel times, the methodology provides a rating system for each pollution source, based on its relative severity and the estimated threat that it poses to the aquifer. Therefore, it can be regarded as a hybrid method that couples the advantages provided by the physically based methods with those of the subjective rating systems. The methodology is applied to the Neon Sidirochorion aquifer, Northeastern Greece, an overexploited aquifer where river waters, sea waters and lake waters interact, causing groundwater quality deterioration to the aquifer. The results indicated that the proposed groundwater vulnerability assessment methodology is well capturing pollution related to saltwater intrusion and agricultural activities, while it is concluded that the conceptual model is significantly affecting the vulnerability assessment results and therefore has to be previously developed.     

Estimation of air-overpressure produced by blasting operation through a neuro-genetic technique

Blasting operations usually produce significant environmental problems which may cause severe damage to the nearby areas. Air-overpressure (AOp) is one of the most important environmental impacts of blasting operations which needs to be predicted and subsequently controlled to minimize the potential risk of damage. In order to solve AOp problem in Hulu Langat granite quarry site, Malaysia, three non-linear methods namely empirical, artificial neural network (ANN) and a hybrid model of genetic algorithm (GA)–ANN were developed in this study. To do this, 76 blasting operations were investigated and relevant blasting parameters were measured in the site. The most influential parameters on AOp namely maximum charge per delay and the distance from the blast-face were considered as model inputs or predictors. Using the five randomly selected datasets and considering the modeling procedure of each method, 15 models were constructed for all predictive techniques. Several performance indices including coefficient of determination (R ²), root mean square error and variance account for were utilized to check the performance capacity of the predictive methods. Considering these performance indices and using simple ranking method, the best models for AOp prediction were selected. It was found that the GA–ANN technique can provide higher performance capacity in predicting AOp compared to other predictive methods. This is due to the fact that the GA–ANN model can optimize the weights and biases of the network connection for training by ANN. In this study, GA–ANN is introduced as superior model for solving AOp problem in Hulu Langat site.     

New occurrence of potential phosphate resource in northeast Jordan

An exploration program aided by field investigation, exploration drilling, detailed sampling, lithological and petrological studies, geochemical investigation, and resource calculation leads to the discovery of a potential phosphate resource in northeast Jordan close to the international border with Saudi Arabia and Iraq. The studied phosphate is of the Middle Eocene age that belongs to the Wadi Shallala Formation. It is equivalent to the phosphate deposits recorded in the lower part of the Umm Wual Formation in the Turayf region of Saudi Arabia and the Eocene Ratga Formation in the Ethna phosphate deposit west of Iraq. The phosphorites in the region are broadly similar in mineralogical composition and geochemical affinities. X-ray diffraction indicates the presence of francolite with variable amounts of calcite and quartz. Most samples consist of phosphate clasts embedded in carbonate and silica matrix and cement. P₂O₅ content is up to 32.3 % with an average equal to 18.6 %. The impurity is caused by the presence of variable amounts of SiO₂ and CaO. The F% and F/P₂O₅ ratio in studied phosphates is lower compared with that in phosphates from Jordan and Saudi Arabia. The geological and geochemical results were integrated for resource estimation. Three high-grade phosphate layers with ≥23 % P₂O₅ were considered in the calculations. The phosphate resource is classified as an inferred resource. The total volume of the resource is about 649 million tons. The average P₂O₅ content is 24.57, and the stripping ratio is 1:5.8.     

Numerical solution and convergence analysis of steam injection in heavy oil reservoirs

In this paper, the numerical methods for solving the problem of steam injection in the heavy oil reservoirs are presented. We consider a 3-dimensional model of 3-phase flow, oil, water, and steam, with the effect of 3-phase relative permeability. Interphase mass transfer of water and steam is considered; oil is assumed nonvolatile. We apply the simultaneous solution approach to solve the corresponding nonlinear discretized partial differential equation in the fully implicit form. The convergence of finite difference scheme is proved by the Rosinger theorem. The heuristic Jacobian-Free-Newton-Krylov (HJFNK) method is proposed for solving the system of algebraic equations. The result of this proposed numerical method is well compared with some experimental results. Our numerical results show that the first iteration of the full approximation scheme (FAS) provides a good initial guess for the Newton method. Therefore, we propose a new hybrid-FAS-HJFNK method while there is no steam in the reservoir. The numerical results show that the hybrid-FAS-HJFNK method converges faster than the HJFNK method.     

Prediction of water inflow to mechanized tunnels during tunnel-boring-machine advance using numerical simulation

An accurate estimate of the groundwater inflow to a tunnel is one of the most challenging but essential tasks in tunnel design and construction. Most of the numerical or analytical solutions that have been developed ignore tunnel seepage conditions, material properties and hydraulic-head changes along the tunnel route during the excavation process, leading to inaccurate prediction of inflow rates. A method is introduced that uses MODFLOW code of GMS software to predict inflow rate as the tunnel boring machine (TBM) gradually advances. In this method, the tunnel boundary condition is conceptualized and defined using Drain package, which is simulated by dividing the drilling process into a series of successive intervals based on the tunnel excavation rates. In addition, the drain elevations are specified as the respective tunnel elevations, and the conductance parameters are assigned to intervals, depending on the TBM type and the tunnel seepage condition. The Qomroud water conveyance tunnel, located in Lorestan province of Iran, is 36 km in length. Since the Qomroud tunnel involved groundwater inrush during excavating, it is considered as a good case study to evaluate the presented method. The groundwater inflow to this tunnel during the TBM advance is simulated using the proposed method and the predicted rates are compared with observed rates. The results show that the presented method can satisfactorily predict the inflow rates as the TBM advances.     

Subduction-related mafic to felsic magmatism in the Malayer–Boroujerd plutonic complex,western Iran

The Malayer–Boroujerd plutonic complex (MBPC) in western Iran, consists of a portion of a magmatic arc built by the northeast verging subduction of the Neo-Tethys plate beneath the Central Iranian Microcontinent (CIMC). Middle Jurassic-aged felsic magmatic activity in MBPC is manifested by I-type and S-type granites. The mafic rocks include gabbroic intrusions and dykes and intermediate rocks are dioritic dykes and minor intrusions, as well as mafic microgranular enclaves (MMEs). MBPC Jurassic-aged rocks exhibit arc-like geochemical signatures, as they are LILE- and LREE-enriched and HFSE- and HREE-depleted and display negative Nb–Ta anomalies. The gabbro dykes and intrusions originated from metasomatically enriched garnet-spinel lherzolite [Degree of melting (f_mel) ~ 15%] and exhibit negative Nd and positive to slightly negative ε_Hf(T) (+ 3.0 to ? 1.6). The data reveal that evolution of Middle Jurassic magmatism occurred in two stages: (1) deep mantle-crust interplay zone and (2) the shallow level upper crustal magma chamber. The geochemical and isotopic data, as well as trace element modeling, indicate the parent magma for the MBPC S-type granites are products of upper crustal greywacke (f_mel: 0.2), while I-type granites formed by partial melting of amphibolitic lower crust (f_mel: 0.25) and mixing with upper crustal greywacke melt in a shallow level magma chamber [Degree of mixing (f_mix): 0.3]. Mixing between andesitic melt leaving behind a refractory dense cumulates during partial crystallization of mantle-derived magma and lower crustal partial melt most likely produced MMEs (f_mix: 0.2). However, enriched and moderately variable ε_Nd(T) (? 3.21 to ? 4.33) and high (⁸⁷Sr/⁸⁶Sr)_i (0.7085–0.7092) in dioritic intrusions indicate that these magmas are likely experienced assimilation of upper crustal materials. The interpretations of magmatic activity in the MBPC is consistent with the role considered for mantle-derived magma as heat and mass supplier for initiation and evolution of magmatism in continental arc setting, elsewhere.     

Air pollution forecasting from sky images with shallow and deep classifiers

Air pollution is one of the most important problems in the new era. Detecting the level of air pollution from an image taken by a camera can be informative for the people who are not aware of exact air pollution level be declared daily by some organizations like municipalities. In this paper, we propose a method to predict the level of the air pollution of a location by taking an image by a camera of a smart phone then processing it. We collected an image dataset from city of Tehran. Afterward, we proposed two methods for estimation of level of air pollution. In the first method, the images are preprocessed and then Gabor transform is used to extract features from the images. At the end, two shallow classification methods are employed to model and predict the level of air pollution. In the second proposed method, a Convolutional Neural Network(CNN) is designed to receive a sky image as an input and result a level of air pollution. Some experiments have been done to evaluate the proposed method. The results show that the proposed 9 method has an acceptable accuracy in detection of the air pollution level. Our deep classifier achieved accuracy about 59.38% which is 10 about 6% higher than traditional combination of feature extraction and classification methods.     

Ghaleh-khargushi rhyodacite and Gorid andesite from Iran: characterization,uses, and durability

Durability of building stones is an important issue in sustainable development. Crystallization of soluble salts is recognized as one of the most destructive weathering agents of building stones. For this reason, durability of Ghaleh-khargushi rhyodacite and Gorid andesite from Iran was investigated against sodium sulfate crystallization aging test. Petrographic and physico-mechanical properties and pore size distribution of these stones were examined before and after the aging test. The characteristics of the microcracks were quantified with fluorescence-impregnated thin sections. Durability and physico-mechanical characteristics of Ghaleh-khargushi rhyodacite are mainly influenced by preferentially oriented preexisting microcracks. Stress induced by salt crystallization led to the widening of preexisting microcracks in Ghaleh-khargushi rhyodacite, as confirmed by the pore size distributions before and after the aging test. The preexisting microcracks of Gorid andesite were attributed to the mechanical stress induced by contraction of lava during cooling. The number of transcrystalline microcracks was significantly increased after the aging test. The degree of plagioclase microcracking was proportional to its size. Durability of the studied stones depends on initial physico-mechanical properties, pore size distribution, and orientation of microcracks. Initial effective porosity is found to be a good indicator of the stones’ durability. Salt crystallization resulted in an increase in the effective porosity with a parallel decrease in the wave velocities. Surface microroughness parameters increased with the development of salt crystallization-induced microcracking. Gorid andesite showed higher quality and durability than Ghaleh-khargushi rhyodacite.