Spatial Distribution of Fractures in the Asmari Formation of Iran in Subsurface Environment: Effect of Lithology and Petrophysical Properties

The distribution of fractures and its dependence on lithology and petrophysical properties of rock in the Asmari Formation were examined using three wells data of one of the largest oil fields of southwestern Iran. Fractures were measured on cut cores. Mineral content and petrophysical data were obtained through thin section study and core plug measurement respectively. Influence of mineral composition and petrophysical property of rocks on fracture density was explored statistically. Increasing quartz (sand) and anhydrite content of rocks decrease and dolomite increases the threshold of fracture densities, however no significant relation was observed between calcite content of rock and fracture density. Increasing porosity and permeability of rock decrease the threshold of fracture density in some of the defined lithology groups. There are significant differences between the lithology groups in terms of fracture density, although the results in the three wells are not the same. In whole data, the highest fracture density can be observed in dolostone. Limestone and impure carbonates hold broader spaced fractures and sandstones display the least fracture density. The average fracture densities in the wells are strictly different. These differences are the result of the structural position of the wells and also the trend of the well and fractures. The distribution of fractures in most lithology groups can be explained by the function: , where F is relative frequency, D is fracture density and a, b, and c are constants.     

Very Low Frequency Remote Sensing Measurements of the Lower Ionosphere at Site of the United Arab Emirates

The proposed research project is aiming for providing basic data for quantitative comparison of lightning-induced disturbances of the ionosphere and the radiation belts in the American, European and Asia sectors. Most of the current data on such phenomena has so far been obtained in the western hemisphere, and the weight of scientific information indicates that lightning-induced effects at high altitudes and in the radiation belts may dominate other processes on a global scale. The proposed research project will facilitate the establishment and conduct of Very Low Frequency observations in the United Arab Emirates as a part of the Asia sector, thus providing a basis for comparison to facilitate global extrapolations and conclusions. Under the proposed project, Stanford University partners with Sharjah University, deploying one of their Very Low Frequency receivers at Sharjah University campus. Sharjah University provides the data digitization and recording equipment to facilitate continuous acquisition of the data. All data from the proposed project will be available for analysis over the Internet, and a series of annual visits are planned to maximize interactions and information exchange between the two universities.     

Cylindrical and spherical electron acoustic solitary waves in the presence of superthermal hot electrons

Propagation of cylindrical and spherical electron-acoustic solitary waves in unmagnetized plasmas consisting of cold electron fluid, hot electrons obeying a superthermal distribution and stationary ions are investigated. The standard reductive perturbation method is employed to derive the cylindrical/spherical Korteweg-de-Vries equation which governs the dynamics of electron-acoustic solitons. The effects of nonplanar geometry and superthermal hot electrons on the behavior of cylindrical and spherical electron acoustic soliton and its structure are also studied using numerical simulations.     

Genealogical concordance,comparative species delimitation,and the specific status of the Caspian pipefish Syngnathus caspius (Teleostei: Syngnathidae)

To evaluate the specific validity of the Caspian pipefish Syngnathus caspius, we used a comparative molecular species delimitation method on a COI barcode library of Syngnathus, as well as principles of genealogical concordance. Comparative species delimitation allowed us to delineate putative species without a priori assignment of individuals to nominal species, while genealogical concordance extended our species delimitation results to multiple genes, multiple codistributed species, and comparisons with biogeographic evidence. All species delimitation analyses including two topology‐based, one network‐based, and one distance‐based analysis showed genetically isolated lineages of pipefish in the Black and Caspian Sea, corresponding to S. abaster and S. caspius, respectively. Mean evolutionary divergence between the two lineages (0.029) was within the range separating species of Syngnathus (0.024–0.217). The interclade/intraclade ratio of variation was comparable to the operational criterion of divergence between clades greater or equal to 10 × the level within clades to recognize separate species. Our argument on taxonomic validity of S. caspius is also supported by the principles of genealogical concordance as a conceptual basis for recognition of biological species. As a second objective, using a limited number of S. caspius specimens from two semi‐confined water bodies along the Caspian Sea south coastal zone (i.e., Anzali Wetland in the west and Gorgan Bay in the east), we searched for a possible matrilineal structure. The retrieved phylogeographic pattern was characterized by a shallow genealogy and lineage distributions varied, most probably caused by low to modest contemporary gene flow between populations of S. caspius across the southern Caspian Sea that are linked tightly through history.     

Simulation of drilling‐induced compaction bands using discrete element method

Rock failure is observed around boreholes often with certain types of failure zones, which are called breakouts. Laboratory‐scale drilling tests in some high‐porosity quartz‐rich sandstone have shown breakouts in the form of narrow localized compacted zones in the minimum horizontal stress direction. They are called fracture‐like breakouts. Such compaction bands may affect hydrocarbon extraction by forming barriers that inhibit fluid flow and may also be a source of sand production. This paper presents the results of numerical simulations of borehole breakouts using 3D discrete element method to investigate the mechanism of the fracture‐like breakouts and to identify the role of far‐field stresses on the breakout dimensions. The numerical tool was first verified against analytical solutions. It was then utilized to investigate the failure mechanism and breakout geometry for drilled cubic rock samples of Castlegate sandstone subjected to different pre‐existing far‐field stresses. Results show that failure occurs in the zones of the highest concentration of tangential stress around the borehole. It is concluded that fracture‐like breakout develops as a result of a nondilatant failure mechanism consisting of localized grain debonding and repacking and grain crushing that lead to the formation of a compaction band in the minimum horizontal stress direction. In addition, it is found that the length of fracture‐like breakouts depends on both the mean stress and stress anisotropy. However, the width of the breakout is not significantly changed by the far‐field stresses. Copyright © 2013 John Wiley & Sons, Ltd.     

Modeling and assessing the effects of land use changes on runoff generation with the CLUE-s and WetSpa models

Theoretical and Applied Climatology - Land use change is an important determinant of hydrological processes and is known to affect hydrological parameters such as runoff volume, flood frequency,...     

Multi-criteria evaluation of CMIP5 GCMs for climate change impact analysis

Climate change is expected to have severe impacts on global hydrological cycle along with food-water-energy nexus. Currently, there are many climate models used in predicting important climatic variables. Though there have been advances in the field, there are still many problems to be resolved related to reliability, uncertainty, and computing needs, among many others. In the present work, we have analyzed performance of 20 different global climate models (GCMs) from Climate Model Intercomparison Project Phase 5 (CMIP5) dataset over the Columbia River Basin (CRB) in the Pacific Northwest USA. We demonstrate a statistical multicriteria approach, using univariate and multivariate techniques, for selecting suitable GCMs to be used for climate change impact analysis in the region. Univariate methods includes mean, standard deviation, coefficient of variation, relative change (variability), Mann-Kendall test, and Kolmogorov-Smirnov test (KS-test); whereas multivariate methods used were principal component analysis (PCA), singular value decomposition (SVD), canonical correlation analysis (CCA), and cluster analysis. The analysis is performed on raw GCM data, i.e., before bias correction, for precipitation and temperature climatic variables for all the 20 models to capture the reliability and nature of the particular model at regional scale. The analysis is based on spatially averaged datasets of GCMs and observation for the period of 1970 to 2000. Ranking is provided to each of the GCMs based on the performance evaluated against gridded observational data on various temporal scales (daily, monthly, and seasonal). Results have provided insight into each of the methods and various statistical properties addressed by them employed in ranking GCMs. Further; evaluation was also performed for raw GCM simulations against different sets of gridded observational dataset in the area.     

Forecasting monthly inflow with extreme seasonal variation using the hybrid SARIMA-ANN model

The optimal operation of dam reservoirs can be programmed and managed by predicting the inflow to these structures more accurately. To this end, there are various linear and nonlinear models. However, some hydrological problems like inflow with extreme seasonal variation are not purely linear or nonlinear. To improve the forecasting accuracy of this phenomenon, a linear Seasonal Auto Regressive Integrated Moving Average (SARIMA) model is combined with a nonlinear Artificial Neural Network (ANN) model. This new model is used to predict the monthly inflow to the Jamishan dam reservoir in West Iran. A comparison of the SARIMA and ANN models with the proposed hybrid model’s results is provided accordingly. More specifically, the models’ performance in forecasting base and flood flows is evaluated. The effect of changing the forecasting period length on the models’ accuracy is studied. The results of increasing the number of SARIMA model parameters up to five are investigated to achieve more accurate forecasting. The hybrid model predicts peak flood flows much better than the individual models, but SARIMA outperforms the other models in predicting base flow. The obtained results indicate that the hybrid model reduces the overall forecast error more than the ANN and SARIMA models. The coefficient of determination of the hybrid, ANN and SARIMA models were 0.72, 0.64 and 0.58, and the root mean squared error values were 1.02, 1.16 and 1.27 respectively, during the forecast period. Changing the forecasting length also indicated that these models can be used in the long term without increasing the forecast error.