Estimation of Pore Volume Compressibility in Carbonate Reservoir Rocks Based on a Classification

Geotechnical and Geological Engineering - This study examined the petrographically classification, petrological and petrophysical characteristics by taking a vast range of carbonate reservoir rock...     

Prediction of Rock Abrasivity Index (RAI) and Uniaxial Compressive Strength (UCS) of Granite Building Stones Using Nondestructive Tests

Geotechnical and Geological Engineering - Rock abrasivity index (RAI) and uniaxial compressive strength (UCS) are two key parameters for assessing abrasivity and durability of building stones,...     

Formulation of the Caspian Sea’s legal regime using a joint zone approach

The legal regime of the Caspian Sea has been determined under Treaties 1921 and 1940 by and between Iran and former Soviet Union. In fact, we are neither to explain it nor to determine. As understood from the provisions therein, the exploitation and use of the Caspian Sea by both countries are based on the Condominium. However, there is a 10-nautical mile strip as exclusive fishing areas which have been allocated to the states under the 1940 treaty. It means that Soviet Union and Iran may benefit the marine livings resources out of that strip on an equal manner. This right also includes the seabed and underlying bed. So, the legal regime of this sea may be based on a 10-nautical mile exclusive region for all five states and the remaining part as common and joint area under an agreement until an explaining and supervising organization is established to exploit and supervise over living and non-livings resources.     

Support vector machines and feed-forward neural networks for spatial modeling of groundwater qualitative parameters

The present study attempts to model the spatial variability of three groundwater qualitative parameters in Guilan Province, northern Iran, using artificial neural networks (ANNs) and support vector machines (SVMs). Data collected from 140 observation wells for the years 2002–2014 were used. Five variables, X and Y coordinates of the observation well, distance of the observation well from the shoreline, areal average 6-month rainfall depth, and groundwater level at the day of water quality sampling, were considered as primary input variables. In addition, nine qualitative variables were also considered as auxiliary input variables. Electrical conductivity (EC), sodium concentration (Na⁺), and sulfate concentration (SO₄ ^2?) of the groundwater in the region were estimated using ANNs and SVMs with different input combinations. The results showed that both ANNs and SVMs work well when the only primary input variable is the well location. The ANN yielded an RMSE of 1.03 mEq/l for SO₄ ^2?, 1.05 mEq/l for Na⁺, and 203.17 μS/cm for EC, using the X and Y coordinates of the observation wells in the study area. In the case of SVM, these values were, respectively, 0.87, 0.87, and 176.68. Considering the auxiliary input variables (pH, EC, and the concentrations of Na⁺, K⁺, Ca²⁺, Mg²⁺, Cl^?, SO₄ ^2?, and HCO₃ ^?) resulted in a significant decrease in the RMSE of both ANNs (0.22, 0.30, and 33.04) and SVMs (0.26, 0.34, and 36.23). Comparing these RMSE values with those of cokriging interpolation technique (0.59, 0.98, and 177.59) indicated that ANNs and SVMs produced more accurate estimates of the three qualitative parameters. The relative importance of auxiliary input variables was also determined using Gamma test. The output uncertainty of ANNs and SVMs were determined using p-factor and d-factor. The results showed that SVMs have less uncertainty than ANNs.     

Tensionless–frictionless interaction of flexible annular foundation with a transversely isotropic multi‐layered half‐space

A transversely isotropic multi‐layered half‐space, with axis of material symmetry perpendicular to the free surface, supports a flexible either annular or solid circle foundation. The contact area of the foundation and the half‐space is considered to be both frictionless and tensionless. The foundation is assumed to be affected by a vertical static axisymmetric load. Detailed analysis of the interaction of these two systems with different thickness of layers is the target of this paper. With the use of ring load Green's functions for both the foundation and the continuum half‐space, an integral equation accompanied with some inequalities is introduced to model the complex BVP. With the incorporation of ring‐shape FEM, we are capable of capturing both regular and singular solution smoothly. The validity of the combination of the analytical and numerical method is proved with comparing the results of this paper with a number of benchmark cases of both linear and nonlinear interaction of circular and annular foundation with half‐space. Some new illustrations are presented to portray the aspect of the anisotropy and layering of the half‐space. Copyright © 2014 John Wiley & Sons, Ltd.     

Effects of over-consolidation history on flow instability of clean and silty sands

Acta Geotechnica - This article presents an experimental program under the constant volume condition to investigate the influence of over-consolidation on flow instability of clean and silty sand...     

Evaluation of four supervised learning methods for groundwater spring potential mapping in Khalkhal region (Iran) using GIS-based features

One important tool for water resources management in arid and semi-arid areas is groundwater potential mapping. In this study, four data-mining models including K-nearest neighbor (KNN), linear discriminant analysis (LDA), multivariate adaptive regression splines (MARS), and quadric discriminant analysis (QDA) were used for groundwater potential mapping to get better and more accurate groundwater potential maps (GPMs). For this purpose, 14 groundwater influence factors were considered, such as altitude, slope angle, slope aspect, plan curvature, profile curvature, slope length, topographic wetness index (TWI), stream power index, distance from rivers, river density, distance from faults, fault density, land use, and lithology. From 842 springs in the study area, in the Khalkhal region of Iran, 70 % (589 springs) were considered for training and 30 % (253 springs) were used as a validation dataset. Then, KNN, LDA, MARS, and QDA models were applied in the R statistical software and the results were mapped as GPMs. Finally, the receiver operating characteristics (ROC) curve was implemented to evaluate the performance of the models. According to the results, the area under the curve of ROCs were calculated as 81.4, 80.5, 79.6, and 79.2 % for MARS, QDA, KNN, and LDA, respectively. So, it can be concluded that the performances of KNN and LDA were acceptable and the performances of MARS and QDA were excellent. Also, the results depicted high contribution of altitude, TWI, slope angle, and fault density, while plan curvature and land use were seen to be the least important factors.