Post‐stack diffraction imaging in vertical transverse isotropy media using non‐hyperbolic moveout approximations

Diffractions carry valuable information about local discontinuities and small‐scale objects in the subsurface. They are still not commonly used in the process of geological interpretation. Many diffraction imaging techniques have been developed and applied for isotropic media, whereas relatively few techniques have been developed for anisotropic media. Ignoring anisotropy can result in low‐resolution images with wrongly positioned or spurious diffractors. In this article, we suggest taking anisotropy into account in two‐dimensional post‐stack domain by considering P‐wave non‐hyperbolic diffraction traveltime approximations for vertical transverse isotropy media, previously developed for reflection seismology. The accuracy of the final images is directly connected to the accuracy of the diffraction traveltime approximations. We quantified the accuracy of six different approximations, including hyperbolic moveout approximation, by the application of a post‐stack diffraction imaging technique on two‐dimensional synthetic data examples.     

Simulation of relationship between river discharge and sediment yield in the semi-arid river watersheds

Complex and variable nature of the river sediment yield caused many problems in estimating the long-term sediment yield and problems input into the reservoirs. Sediment Rating Curves (SRCs) are generally used to estimate the suspended sediment load of the rivers and drainage watersheds. Since the regression equations of the SRCs are obtained by logarithmic retransformation and have a little independent variable in this equation, they also overestimate or underestimate the true sediment load of the rivers. To evaluate the bias correction factors in Kalshor and Kashafroud watersheds, seven hydrometric stations of this region with suitable upstream watershed and spatial distribution were selected. Investigation of the accuracy index (ratio of estimated sediment yield to observed sediment yield) and the precision index of different bias correction factors of FAO, Quasi-Maximum Likelihood Estimator (QMLE), Smearing, and Minimum-Variance Unbiased Estimator (MVUE) with LSD test showed that FAO coefficient increases the estimated error in all of the stations. Application of MVUE in linear and mean load rating curves has not statistically meaningful effects. QMLE and smearing factors increased the estimated error in mean load rating curve, but that does not have any effect on linear rating curve estimation.     

An empirical model for salinity intrusion in alluvial estuaries

The main parameters that affect the salinity intrusion in estuaries are their geometric, hydrologic and hydrodynamic characteristics. The recognition of effective parameters and understanding their roles in the salinity intrusion are required for estuarine water management. In this study, the governing equations of the salinity intrusion processes were scaled to derive the effective dimensionless parameters. Then, a previously verified model, CE-QUAL-W2, was utilized as a virtual laboratory to investigate the effects of different governing parameters on the salinity intrusion. Analysis of the results showed that logarithmic functions can be used to describe the effect of dimensionless parameters obtained by scaling of governing equations. Finally, a formula was suggested to predict the salinity intrusion length based on geometrical and hydrodynamic characteristics of alluvial estuaries.     

Determination of Storage Coefficients During Pumping and Recovery

An aquifer test is used mostly to determine the storage coefficient and transmissivity. Although residual drawdown data are widely used in estimating the transmissivity of aquifers, the estimation of storage coefficients with recovery data is controversial. Some researchers have proposed methods to estimate storage coefficients with recovery data by assuming equality of storage coefficients for the recovery and pumping periods (S = S′). The aim of this study is to determine storage coefficients without such an assumption, that is, S≠S′. The method is a modified version of Banton‐Bangoy's method without considering drawdown data due to pumping. Drawdown is plotted vs. the logarithmic ratio (t′/t) or time since pumping stopped to the duration of pumping and the ratio of storage coefficient during recovery to the storage coefficient from the pumping period (S′/S). The method is verified with one case study and two synthetic examples. Thus, it is possible to determine storage coefficient of pumping period accurately without any data from pumping period by recovery data.     

Assessment of a spatial multi-criteria evaluation to site selection underground dams in the Alborz Province,Iran

Most part of Iran is arid and semi-arid; thus in most parts of the region, groundwater is the only source of water. This research presents a method based on a spatial multi-criterion evaluation (SMCE) for designing possible sites of underground dams and ranks them according to their suitability. The method was tested for siting underground dams in the Alborz Province, Iran. At first, screening algorithm was applied using exclusionary criteria, and thirty-one potential areas were recognized in the study area. In the next step, a suitable gorge or valley was recognized using the combination of basic maps and extensive field surveys (long axis of tank level) in each potential area. Subsequently, the analytical hierarchy process was used as a powerful tool for decision-making in the SMCE in order to evaluate different criteria for underground dam sites. SMCE techniques were then applied to combine the criteria, and obtain a suitability map in the study area. These sites were then compared and ranked according to their main criteria such as water, storage, axis and socio-economics. All these criteria were assessed through geographical information system modelling. This method shows passable results and could be used for site selection of underground dams in other regions of Iran.     

Semi Automatic Road Extraction by Fusion of High Resolution Optical and Radar Images

Two new methods for fusion of high-resolution optical and radar satellite images have been proposed to extract roads in high quality in this paper. Two fusion methods, including neural network and knowledge-based fusion are introduced. The first proposed method consists of two stages: (i) separate road detection using each dataset and (ii) fusion of the results obtained using a neural network. In this method, the neural networks are separately applied on high-resolution IKONOS and TerraSAR-X images for road detection, using a variety of texture parameters. The outputs of two neural networks, as well as the spectral features of optical image, are used in a third neural network as inputs. The second method is a knowledge-based fusion using thresholds of narrow roads and vegetation gray levels. First roads are extracted from each source separately. The outputs are then compared and advantages and disadvantages of each data source are investigated . The results obtained from accuracy assessment show the efficiency of the proposed methods. Furthermore, the comparison of the results showed the superiority of the first algorithm.     

Inverse problem theory to chemo-poroelastic parameters estimation: an analytical/experimental investigation

Shale formation swelling is one of the main factors affecting wellbore instability and associated problems in drilling operation. In order to eliminate these problems, it is important to investigate formation characteristics and understand mechanisms of rock-fluid interaction, from chemical/mechanical point of view. Shale membrane efficiency is known as an important parameter affecting wellbore instability. In order to measure this parameter, many mathematical models and experimental efforts have been carried out which consider mechanical-chemical processes for rock-fluid interactions. In this study, the field equations governing the problem have been derived based on the linear chemo-poroelastic theory and solved using analytical/numerical methods. Afterward, a comprehensive workflow to characterize the chemo-poroelastic parameters of illite-rich shale is conducted in the laboratory. In fact, mineralogical and apparent properties of shale sample have been described and some setups were performed such as triaxial test and membrane efficiency. Then genetic algorithm has been applied to solve an inverse problem and get a match between experimental data and modeling results. Ultimately, the three important properties in shale-fluid interactions, i.e., shale membrane efficiency, hydraulic, and chemical diffusivity coefficient have been estimated. Comparing the simulation results with the experimental data indicates that the simulation model can appropriately simulate the pore pressure transmission test. With this approach, the required parameters can be estimated with good accuracy without using time-consuming and costly tests.     

Statistical modeling the effect of sediment physicochemical properties on the concentration of heavy metal (case study: Musa Creek,SW Iran)

Heavy metal accumulation in sediments is important even at low levels due to their irresolvable character and harmful effects. Therefore, contamination of creeks, especially their sediments, is highly important for scientific communities. This study investigates the relationship between heavy metal accumulation and some physicochemical parameters of sediments (pH, EC, calcium carbonate, texture, specific gravity, density, porosity and percentage of organic matter) in a stretch of Musa Creek beaches. The results showed that the studied sediments are extremely salty and have slight variations in terms of pH. Although there are mostly clay-sized sediments in the studied area, their mineralogical composition contains calcite with smaller amounts of dolomite, aragonite and halite minerals. The correlation between each of the parameters and heavy metal concentration was modeled using OLS regression. Cr, Ni, Zn and Pb concentrations are positively correlated with each other and inversely correlated with Cd. The accumulation of heavy metals is directly related to parameters such as EC, organic matter, clay and silt, specific gravity and porosity; it is negatively related to calcium carbonate, sand and density parameters. Owing to slight variations, the pH parameter lacks any significant correlation with heavy metal concentrations.