Accounting for Parameter Uncertainty in Reservoir Uncertainty Assessment: The Conditional Finite-Domain Approach

An important aim of modern geostatistical modeling is to quantify uncertainty in geological systems. Geostatistical modeling requires many input parameters. The input univariate distribution or histogram is perhaps the most important. A new method for assessing uncertainty in the histogram, particularly uncertainty in the mean, is presented. This method, referred to as the conditional finite-domain (CFD) approach, accounts for the size of the domain and the local conditioning data. It is a stochastic approach based on a multivariate Gaussian distribution. The CFD approach is shown to be convergent, design independent, and parameterization invariant. The performance of the CFD approach is illustrated in a case study focusing on the impact of the number of data and the range of correlation on the limiting uncertainty in the parameters. The spatial bootstrap method and CFD approach are compared. As the number of data increases, uncertainty in the sample mean decreases in both the spatial bootstrap and the CFD. Contrary to spatial bootstrap, uncertainty in the sample mean in the CFD approach decreases as the range of correlation increases. This is a direct result of the conditioning data being more correlated to unsampled locations in the finite domain. The sensitivity of the limiting uncertainty relative to the variogram and the variable limits are also discussed.     

A BEM–FEM approach for analysis of distresses in pavements

A combined boundary-element–finite-element method is presented for the analysis of distresses in pavements subjected to mechanical and environmental effects. Owing to the spatial dimensions of the problem, the non-homogeneity and the irregular geometry at the pavement joints, a combination of the two methods proves to offer a more realistic solution technique. The advantage of the finite element method (FEM) is in its capabilities of modelling near-field regions at or around the vicinity of the joint, whereas the boundary element method (BEM) is more suitable to model the far-field region at infinity. The three major distresses affecting the serviceability of the pavement system are the temperature, moisture and the applied mechanical loads. The model analyses the stresses and strains resulting from both mechanical and environmental factors in the analysis of a pavement system. Moreover, the infiltration of water through pavement joints, which causes weakening of the subgrade soil, is also analysed. Secondly the curling of the pavement concrete slab under the mechanical and thermal loads and induced friction may cause separation of the pavement structure from its supporting subgrade. Both are treated and modelled in this study. A detailed analysis of the pavement joint with its load transfer device is also performed for the proper assessment of the separation and further extension of the loss of support in the pavement system.     

A dye-tracing test as an aid to studying karst development at an artesian limestone sub-aquifer: Zagros Zone,Iran

A dye-tracing test is employed to study the karst development and flow regime at an artesian limestone sub-aquifer, the Khersan3 Dam site, Zagros Zone, Iran. Tracer breakthrough curves showed an early dominant peak followed by a pronounced tailing effect. The peak concentration was a response to induced pressure during dye injection. The results suggest that the dye was pushed into the small pores and fissures around the injection point during dye injection. Hence, the dye moved out as a result of matrix and fissure diffusive processes and created a long pronounced tailing. The maximum flow velocity in the upper artesian sub-aquifer ranged from 0.97 to 2.9 m/h. However, the mean tracer velocity ranged from 0.19 to 0.51 m/h based on the mean residence tracer time; consequently, the flow regime in the artesian sub-aquifer was determined to be mainly diffusive. The results reveal (1) a low hydraulic gradient from upstream of the dam axis to downstream; consequently, there is no considerable flow; (2) poor karst development and diffuse flow at the tracing test area; (3) a discharge zone at a location downstream of the dam axis which is the main terminal of general flow direction at the dam site.     

From Jurassic rifting to Cretaceous subduction in NW Iranian Azerbaijan: geochronological and geochemical signals from granitoids

Previous interpretations of a Jurassic subduction in Iran were based on trace element classification diagrams for granitoids, but their reliability is questionable, underscored by modern examples of continental break-up zones such as the Baja California. We present new field observations, bulk rock geochemistry, Sr and Nd isotope analyses and U–Pb zircon geochronology to assess the age and tectonic setting of previously undated intermediate to felsic magmatic rocks cropping out in the Precambrian basement of NW Iranian Azerbaijan. The geochronology revealed an uneven distribution in space and time: Late Jurassic (159–154 Ma) intrusions and dikes are alkaline to calc-alkaline. Their melt source is mantle dominated with a distinct continental contribution disclosed by radiogenic isotopes and abundant inherited zircon cores. Mid-Cretaceous (112–96 Ma) plutonic bodies and associated volcanic rocks occur only to the east of the major Siah Cheshmeh–Khoy Fault. They have geochemical signatures typical of a metasomatized mantle. In consistence with the sedimentation history of the area, our new interpretation attributes the Late Jurassic magmatism to thinning of a continental lithosphere in a rift-related setting. Mid-Cretaceous magmatism was produced by oceanic subduction beneath the Central Iran continent. We interpret the 40-Ma age gap between the two magmatic episodes as the time of opening of the oceanic basin witnessed by the Khoy ophiolite in the study area.     

Cyclostratigraphy across a Mississippian carbonate ramp in the Esfahan–Sirjan Basin,Iran: implications for the amplitudes and frequencies of sea-level fluctuations along the southern margin of the Paleotethys

International Journal of Earth Sciences - The Tournaisian–Visean carbonate successions of the Esfahan–Sirjan Basin (ESB) from Sanandaj–Sirjan Zone, Iran, have been used to...     

Database extension for digital soil mapping using artificial neural networks

Cost and time are the two most important factors conditioning soil surveys. Since these surveys provide basic information for modelling and management activities, new methods are needed to speed the soil-mapping process with limited input data. In this study, the polypedon concept was used to extend the spatial representation of sampled pedons (point data) in order to train artificial neural networks (ANNs) for digital soil mapping (DSM). The input database contained 97 soil profiles belonging to 7 different soil series and 15 digital elevation model (DEM) attributes. Pedons were represented in raster format as one-cell areas. The corresponding polypedons were then spatially represented by neighbouring raster cells (e.g. 2 × 2, … up to 6 × 6 cells). The primary database contained 97 pedons (97 cells) that were extended up to 3492 cells (in the case of 6 × 6-cell regions). This approach employed test and validation areas to calculate the respective accuracies of data interpolation and extrapolation. The results showed increased accuracies in training and interpolation (test area) but a poor level of accuracy in the extrapolation process (validation area). However, the overall precision of all predictions increased considerably. Using only topographic attributes for extrapolation was not sufficient to obtain an accurate soil map. To improve prediction, other soil-forming factors, such as landforms and/or geology, should also be considered as input data in the ANN. The proposed method could help to improve existing soil maps by using DSM results in areas with limited soil data and to save time and money in soil survey work.     

Modeling the effects of controlled drainage at a watershed scale using SWATDRAIN

The recently developed SWATDRAIN model was employed to assess the impact of controlled drainage on the water table dynamics, subsurface drainage, and surface runoff in an agricultural watershed in Ontario, Canada. Controlled drainage was defined with a depth of 1.0 m to restrict flow at the drain outlet to maintain the water table at 0.5 m below the surface level during the winter (November–April) and at 0.6 m during the summer (June–August) months. The effects of the absence, or implementation, of drainage water management were predicted for the 3-year period of 1991–1993. Implementing controlled drainage resulted in a 16 % reduction in the mean annual drain flow, while increasing surface runoff by as much as 71 %. This indicates that overall watershed hydrology could be significantly impacted by the implementation of controlled drainage. This research demonstrates the SWATDRAIN model’s ability to predict the controlled drainage in small agricultural watersheds.     

Failure risk assessment of interdependent infrastructures against earthquake,a Petri net approach: case study—power and water distribution networks

Metropolitan areas consist of complicated systems of interconnected infrastructures that are highly interdependent. Disruption of one infrastructure may induce disruption in other interconnected ones. The results from analysis of one infrastructure as an independent system are not realistic without considering the behavior of other interconnected infrastructures. Consequently, the study of the interdependencies among critical infrastructures is important for addressing the cascading effects of a failed infrastructure on the entire network to properly model its performance and help the disaster management team in decision making. In this study, the extended Petri net and Markov chain have been used to demonstrate the power and water infrastructure interdependency with a case study of one of the municipal districts of metropolitan Tehran, the capital of Iran. In this research, three cases have been assessed quantitatively: (1) the intra-dependency effects of different components in each network, (2) the interdependency effects between the considered critical infrastructures and (3) the behavior of the water network considering intra- and interdependency, when the power network fails. The analyses show that considering the mentioned interdependencies has a major influence on their performance simulations and assessment of their exact vulnerability. It is concluded that the failure probability of the water network that is dependent on the failed power network is 1.66 of the independent water network in the studied region. Eventually, the results of the research could be used in design, restoration and disaster management planning for safety assessment of critical infrastructures.