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.     

Local site effect of a clay site in Shiraz based on seismic hazard of Shiraz Plain

Propagation of seismic waves through soil layers would drastically change the frequency content and amplitude-based features of ground motions at the surface. These alterations are known as seismic site effects. Computation of site effects of high-populated areas such as large cities is of great importance (e.g., it is used in development of seismic microzonation of a region). Shiraz is one of the most populous cities of Iran and is located in a high seismic hazardous region. A representative clay site in this city is selected to assess local site effects. The time series and random vibration theory procedure in the frequency domain are implemented to analyze the aforementioned site. Furthermore, the nonlinear dynamic soil behavior is simulated by the equivalent linear method and the nonlinear method via DEEPSOIL program. Three types of soil column uncertainties such as shear wave velocity, modulus reduction, and damping ratio of soil layers as well as depth of underlying rock half-space (D _bed) are considered herein. The mean amplification and standard deviation of natural logarithm of amplification factors are computed for a variety of analysis types. The results of the current study show that the computed mean and standard deviation of amplification factor in ln units by considering only V _S uncertainty are in good agreement with the corresponding ones by considering V _S and modulus reduction and damping ratio variabilities simultaneously for the studied site. Furthermore, it seems that the effect of bedrock depth in definition of spectral shapes of the Iranian seismic building code should be taken into account.     

Extraction of velocity pulses of pulse-like ground motions using empirical Fourier decomposition

Journal of Seismology - Pulse-like ground motions may have only a distinct strong pulse or multiple pulses within the velocity time-history. These intrinsic pulses are hidden in low-frequency...     

Constitutive model for cyclic behaviour of cohesionless sands

This paper presents a constitutive model for describing the stress-strain response of sands under cyclic loading. The model, formulated using the critical state theory within the bounding surface plasticity framework, is an upgraded version of an existing model developed for monotonic behaviour of cohesionless sands. With modification of the hardening law, plastic volumetric strain increment and unloading plastic modulus, the original model was modified to simulate cyclic loading. The proposed model was validated against triaxial cyclic loading tests for Fuji River sand, Toyoura sand and Nigata sand. Comparison between the measured and predicted results suggests that the proposed modified model can capture the main features of cohesionless sands under drained and undrained cyclic loading.     

Applying an optimized proxy-based workflow for fast history matching

History matching is still one of the main challenging parts of reservoir study especially in giant brown oil fields with lots of wells. In these cases, history matching with conventional manual technique needs many runs and takes months to get a match. In this work, an innovative approach was suggested for fast history matching in a real brown field. The workflow was employed based on an optimized proxy model for history matching of a field consisting of 14 active wells with multiple responses (which are production rate and pressure data) in the south part of Iran. The main important features of the proposed algorithm were defining a proxy model which is response surface method in which 21 model parameters were incorporated based on cubic centered face method. The proxy model was then optimized by one of the most famous algorithms which is genetic algorithm. Proxy model was successfully performed using 256 samples leading into p- value of 0.531 and R ² of 0.91 dataset. As a result, the proposed workflow and algorithm showed good and acceptable results for history matching of studied real model.     

Prediction of Compressional, Shear, and Stoneley Wave Velocities from Conventional Well Log Data Using a Committee Machine with Intelligent Systems

Measurement of compressional, shear, and Stoneley wave velocities, carried out by dipole sonic imager (DSI) logs, provides invaluable data in geophysical interpretation, geomechanical studies and hydrocarbon reservoir characterization. The presented study proposes an improved methodology for making a quantitative formulation between conventional well logs and sonic wave velocities. First, sonic wave velocities were predicted from conventional well logs using artificial neural network, fuzzy logic, and neuro-fuzzy algorithms. Subsequently, a committee machine with intelligent systems was constructed by virtue of hybrid genetic algorithm-pattern search technique while outputs of artificial neural network, fuzzy logic and neuro-fuzzy models were used as inputs of the committee machine. It is capable of improving the accuracy of final prediction through integrating the outputs of aforementioned intelligent systems. The hybrid genetic algorithm-pattern search tool, embodied in the structure of committee machine, assigns a weight factor to each individual intelligent system, indicating its involvement in overall prediction of DSI parameters. This methodology was implemented in Asmari formation, which is the major carbonate reservoir rock of Iranian oil field. A group of 1,640 data points was used to construct the intelligent model, and a group of 800 data points was employed to assess the reliability of the proposed model. The results showed that the committee machine with intelligent systems performed more effectively compared with individual intelligent systems performing alone.     

Reproductive traits of the freshwater shrimp Caridina fossarum Heller, 1862 (Decapoda, Caridea, Atyidae) in the Ghomp-Atashkedeh spring (Iran)

In the present study, some biological traits of Caridina fossarum reproduction are studied in the Ghomp-Atashkedeh spring (Fasa, Shiraz, Iran), for the first time. This Iranian endemic freshwater species was studied from April 2007 to March 2008. Minimum sexable size (MSS) and absolute or relative size at the onset of maturity (SOM and RSOM) in terms of carapace length (CL) was found to be 2.4 mm, 4.3 mm and 55%, respectively. Sex ratio showed variations on a monthly basis. Sex reversal is a possible scenario for C. fossarum because the size-specific sex ratio revealed a reverse pattern. Based on the proportions of ovigerous females, the main breeding season was determined to be from April to August, demonstrating a peak during early spring. There is a period of extended recruitment at water temperatures above 20 °C. The size at which 50% of females are mature was estimated at CL = 5.03 mm from the proportion of ovigerous females during the breeding season. The pleopodal egg number varied from 3 to 75 eggs per female with a mean value 34.39 ± 14.27. The results showed that although there is a significant relationship between carapace length CL and pleopodal egg number, it is not the most important factor affecting potential fecundity in C. fossarum due to the low values of slope (= 1.51) and determination coefficient (= 0.052).     

A 2-year study of soil tillage and cattle manure application effects on soil fauna populations under Zea Mays cultivation, in western Iran (Sanandaj)

The absence of environmentally sensitive soil management systems can be considered as one of the major risks to sustainability of agricultural soils in Iran. Tillage is the most critical operation in soil management designed to achieve high crop yield, but it can adversely affect the soil fauna in several ways. In the present study, assessment of soil fauna was carried out in Western Iran in 2008 and 2009 in soil subjected to conventional (CT), minimum (MT) and no (NT)-tillage systems and amended with three levels of cattle manure (CM). Earthworm, mite, springtail and nematode populations were measured as indicators of macro, meso and micro fauna groups, respectively. Soil moisture and bulk density were also determined. Generally, low populations of soil fauna were observed consistent with expectations under similar conditions for this region. Earthworm populations were low and had a patchy distribution. Tillage and CM were found to have no effects on soil mites in both years. Soil springtails were reduced by soil tillage, indicating their sensivity to soil disturbance induced by tillage. In 2008, the nematode population was greater with application of 40 ton ha^?1 CM applications (113 N.100 g soil^?1). Soil tillage-induced disturbance reduced nematode population in 2009 (214 N.100 g soil^?1 at CT). Minimum seedbed preparation besides less soil disturbance makes MT a proper tillage system for Zea mays cultivation. Cattle manure application increased Z. mays’ biomass, but according to our results its annual application is not recommended. There were no changes in BD in both years. We conclude that in short-term studies, soil nematode populations are suitable biological indices (under similar soil and climatic conditions) for the ecological comparison of agricultural management systems in Iran.     

Neuro-fuzzy reaping of shear wave velocity correlations derived by hybrid genetic algorithm-pattern search technique

Shear wave velocity is a critical physical property of rock, which provides significant data for geomechanical and geophysical studies. This study proposes a multi-step strategy to construct a model estimating shear wave velocity from conventional well log data. During the first stage, three correlation structures, including power law, exponential, and trigonometric were designed to formulate conventional well log data into shear wave velocity. Then, a Genetic Algorithm-Pattern Search tool was used to find the optimal coefficients of these correlations. Due to the different natures of these correlations, they might overestimate/underestimate in some regions relative to each other. Therefore, a neuro-fuzzy algorithm is employed to combine results of intelligently derived formulas. Neuro-fuzzy technique can compensate the effect of overestimation/underestimation to some extent, through the use of fuzzy rules. One set of data points was used for constructing the model and another set of unseen data points was employed to assess the reliability of the propounded model. Results have shown that the hybrid genetic algorithm-pattern search technique is a robust tool for finding the most appropriate form of correlations, which are meant to estimate shear wave velocity. Furthermore, neuro-fuzzy combination of derived correlations was capable of improving the accuracy of the final prediction significantly.