Setting-up a 3D geological model both from field and subsurface data is a typical task in geological studies involving natural resource evaluation and hazard assessment. In this study a 3D geological model for Mishrif Formation in Garraf oil field has been set-up using Petrel software. Mishrif Formation represents the most important reservoir in Garraf oil field. Four vertical oil wells (GA-4, GA-A1P, GA-3 and GA-5) and one directional well (GA-B8P) were selected in Garraf Oil Field in order to set-up structural and petrophysical (porosity and water saturation) models represented by a 3D static geological model in three dimensions. Structural model shows that Garraf oil field represents a domal structure that shows continuous growth as indicated by the structural maps at top of reservoir units. The structural closure is shifted from GA-3 well to GA-A1P well. Mishrif Formation was divided into ten zones (top Mishrif, M1, M1.2, M2, L1, L1.2, L2, L2.2, L2.3 and L2.4.). Petrophysical model (porosity and water saturation) for Mishrif Formation was set-up from values of porosity and water saturation using Sequential Gaussian Simulation algorithm. According to data analyses and the results from modeling the units (M1.2, L1 and L1.2) are considered as high quality reservoir units due to the high PHIE and low water saturation. Units (L2, L2.2, L2.3 and L2.4) are considered as poor reservoirs because of low PHIE and high water saturation, and non-reservoir units include (Top Mishrif, M1 and M2) therefore, they represent cap units. Cross sections of petrophysical model were conducted to illustrate the vertical and horizontal distribution of porosity and water saturation between wells in the field.
In this paper the wind data that is measured for 12 months (January to December 2011) at Al-Hay district of Wasit province, southern IRAQ country has been analyzed statistically. The wind speed at heights of 10 m above ground level was measured for every 10 minutes interval. The statistical analysis of wind data was performed using WAsP software which is based on Weibull distributions. The Weibull shape and scale parameters is obtained and used in this paper statistics. The achieved results demonstrated that the study area has Annual Mean Energy Production (AMEP) about 219.002 MWh. The computations have been performed on 70m hub‟s height of the turbine and on Earth surface roughness length (0.0, 0.03, 0.1, 0.4, 1.5) m respectively.
The issue of penalized regression model has received considerable critical attention to variable selection. It plays an essential role in dealing with high dimensional data. Arctangent denoted by the Atan penalty has been used in both estimation and variable selection as an efficient method recently. However, the Atan penalty is very sensitive to outliers in response to variables or heavy-tailed error distribution. While the least absolute deviation is a good method to get robustness in regression estimation. The specific objective of this research is to propose a robust Atan estimator from combining these two ideas at once. Simulation experiments and real data applications show that the proposed LAD-Atan estimator
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This study included the extraction properties of spatial and morphological basins studied using the Soil and Water Assessment Tool (SWAT) model linked to (GIS) to find the amount of sediment and rates of flow that flows into the Haditha reservoir . The aim of this study is determine the amount of sediment coming from the valleys and flowing into the Haditha Dam reservoir for 25 years ago for the period (1985-2010) and its impact on design lifetime of the Haditha Dam reservoir and to determine the best ways to reduce the sediment transport. The result indicated that total amount of sediment coming from all valleys about (2.56 * 106 ton). The maximum annual total sediment load was about (488.22 * 103 ton) in year 1988
... Show MoreIn this study, we made a comparison between LASSO & SCAD methods, which are two special methods for dealing with models in partial quantile regression. (Nadaraya & Watson Kernel) was used to estimate the non-parametric part ;in addition, the rule of thumb method was used to estimate the smoothing bandwidth (h). Penalty methods proved to be efficient in estimating the regression coefficients, but the SCAD method according to the mean squared error criterion (MSE) was the best after estimating the missing data using the mean imputation method
An accurate assessment of the pipes’ conditions is required for effective management of the trunk sewers. In this paper the semi-Markov model was developed and tested using the sewer dataset from the Zublin trunk sewer in Baghdad, Iraq, in order to evaluate the future performance of the sewer. For the development of this model the cumulative waiting time distribution of sewers was used in each condition that was derived directly from the sewer condition class and age data. Results showed that the semi-Markov model was inconsistent with the data by adopting ( 2 test) and also, showed that the error in prediction is due to lack of data on the sewer waiting times at each condition state which can be solved by using successive conditi
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... Show MoreThe issue of penalized regression model has received considerable critical attention to variable selection. It plays an essential role in dealing with high dimensional data. Arctangent denoted by the Atan penalty has been used in both estimation and variable selection as an efficient method recently. However, the Atan penalty is very sensitive to outliers in response to variables or heavy-tailed error distribution. While the least absolute deviation is a good method to get robustness in regression estimation. The specific objective of this research is to propose a robust Atan estimator from combining these two ideas at once. Simulation experiments and real data applications show that the p
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Recently Genetic Algorithms (GAs) have frequently been used for optimizing the solution of estimation problems. One of the main advantages of using these techniques is that they require no knowledge or gradient information about the response surface. The poor behavior of genetic algorithms in some problems, sometimes attributed to design operators, has led to the development of other types of algorithms. One such class of these algorithms is compact Genetic Algorithm (cGA), it dramatically reduces the number of bits reqyuired to store the poulation and has a faster convergence speed. In this paper compact Genetic Algorithm is used to optimize the maximum likelihood estimator of the first order moving avergae model MA(1). Simulation results
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Increasing material prices coupled with the emission of hazardous gases through the production and construction of Hot Mix Asphalt (HMA) has driven a strong movement toward the adoption of sustainable construction technology. Warm Mix Asphalt (WMA) is considered relatively a new technology, which enables the production and compaction of asphalt concrete mixtures at temperatures 15-40 °C lower than that of traditional hot mix asphalt. The Resilient modulus (Mr) which can be defined as the ratio of axial pulsating stress to the corresponding recoverable strain, is used to evaluate the relative quality of materials as well as to generate input for pavement design or pavement evaluation and analysis. Based on the aforementioned preface, it is
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