Sand production in unconsolidated reservoirs has become a cause of concern for production engineers. Issues with sand production include increased wellbore instability and surface subsidence, plugging of production liners, and potential damage to surface facilities. A field case in southeast Iraq was conducted to predict the critical drawdown pressures (CDDP) at which the well can produce without sanding. A stress and sanding onset models were developed for Zubair reservoir. The results show that sanding risk occurs when rock strength is less than 7,250 psi, and the ratio of shear modulus to the bulk compressibility is less than 0.8 1012 psi2. As the rock strength is increased, the sand free drawdown and depletion becomes larger. The CDDP

In this paper two ranking functions are employed to treat the fuzzy multiple objective (FMO) programming model, then using two kinds of membership function, the first one is trapezoidal fuzzy (TF) ordinary membership function, the second one is trapezoidal fuzzy weighted membership function. When the objective function is fuzzy, then should transform and shrinkage the fuzzy model to traditional model, finally solving these models to know which one is better

The License Plate (LP), is a rectangular metal plate that contains numbers and letters. This plate is fixed onto the vehicle's body. It is used as a mean to identify the vehicle. The License Plate Recognition (LPR) system is a mean where a vehicle can be identified automatically using a computer system. The LPR has many applications, such as security applications for car tracking, or enforcing control on vehicles entering restricted areas (such as airports or governmental buildings). This paper is concerned with introducing a new method to recognize the Iraqi LPs using local vertical and horizontal projections, then testing its performance. The attained success rate reached 99.16%, with average recognition time around 0.012 second for re

     The paper shows how to estimate the three parameters of the generalized exponential Rayleigh distribution by utilizing the three estimation methods, namely, the moment employing estimation method (MEM), ordinary least squares estimation method (OLSEM),  and maximum entropy estimation method (MEEM). The simulation technique is used for all these estimation methods to find the parameters for the generalized exponential Rayleigh distribution. In order to find the best method, we use the mean squares error criterion. Finally, in order to extract the experimental results, one of object oriented programming languages visual basic. net was used

There are many aims of this book: The first aim is to develop a model equation that describes the spread of contamination through soils which can be used to determine the rate of environmental contamination by estimate the concentration of heavy metals (HMs) in soil. The developed model equation can be considered as a good representation for a problem of environmental contamination. The second aim of this work is to design two feed forward neural networks (FFNN) as an alternative accurate technique to determine the rate of environmental contamination which can be used to solve the model equation. The first network is to simulate the soil parameters which can be used as input data in the second suggested network, while the second network sim

 Alternative  distribution  to estimate the Dose – Response  model in bioassay  excrement

This research   concern to study five different distribution (Probit , Logistic, Arc sine , extreme value , One hit  ), to estimate  dose –response model by using m.l.e  and probit method This is done by determining different  weights in each  distribution in addition find all particular statistics for vital model . 

The acceptance sampling plans for generalized exponential distribution, when life time experiment is truncated at a pre-determined time are provided in this article. The two parameters (α, λ), (Scale parameters and Shape parameters) are estimated by LSE, WLSE and the Best Estimator’s for various samples sizes are used to find the ratio of true mean time to a pre-determined, and are used to find the smallest possible sample size required to ensure the producer’s risks, with a pre-fixed probability (1 - P^*). The result of estimations and of sampling plans is provided in tables.

Key words: Generalized Exponential Distribution, Acceptance Sampling Plan, and Consumer’s and Producer Risks

         The aim of this paper is to present a method for solving of system of first order initial value problems of ordinary differential equation by a semi-analytic technique with constructing polynomial solutions for decreasing dangers of lead. The original problem is concerned using two-point osculatory interpolation with the fit equals  numbers of derivatives at the end points of an interval [0 , 1].

A field experiment was conducted at the field of the Dept. of Field Crop Sci. / College of Agriculture / University of Baghdad . The objective was to determine the values of relative constant of three – way and double crosses of maize . Ten inbreds were used and crossed during spring and fall seasons of 2009 to produce three - way and double crosses , and ten hybrids were taken from each group . The ten hybrids were grown and selfed during spring 2010 to produce 2 seed . Three way and double crosses were sown with their parents and 2 seed during fall 2010 in RCBD with four replicates . Leaf area , total dry matter , row/ear , grain/ear , grain weight and grain weight/plant of hybrids , parents and 2 plants were taken . Results showed that

Mixture experiments are response variables based on the proportions of component for this mixture. In our research we will compare the scheffʼe model with the kronecker model for the mixture experiments, especially when the experimental area is restricted.

     Because of the experience of the mixture of high correlation problem and the problem of multicollinearity between the explanatory variables, which has an effect on the calculation of the Fisher information matrix of the regression model.

     to estimate the parameters of the mixture model, we used the (generalized inverse ) And the Stepwise Regression procedure