Prediction of penetration rate (ROP) is important process in optimization of drilling due to its crucial role in lowering drilling operation costs. This process has complex nature due to too many interrelated factors that affected the rate of penetration, which make difficult predicting process. This paper shows a new technique of rate of penetration prediction by using artificial neural network technique. A three layers model composed of two hidden layers and output layer has built by using drilling parameters data extracted from mud logging and wire line log for Alhalfaya oil field. These drilling parameters includes mechanical (WOB, RPM), hydraulic (HIS), and travel transit time (DT). Five data set represented five formations gathered from five drilled wells were involved in modeling process.Approximatlly,85 % of these data were used for training the ANN models, and 15% to assess their accuracy and direction of stability. The results of the simulation showed good matching between the raw data and the predicted values of ROP by Artificial Neural Network (ANN) model. In addition, a good fitness was obtained in the estimation of drilling cost from ANN method when compared to the raw data.
Were arranged this study on two sections, which included first section comparison between markets proposed through the use of transport models and the use of the program QSB for less costs , dependant the optimal solution to chose the suggested market to locate new market that achieve lower costs in the transport of goods from factories (ALRasheed ,ALAmeen , AlMaamun ) to points of sale, but the second part has included comparison of all methods of transport (The least cost method ,Vogels method , Results Approximations method , Total method) depending on the agenda of transport, which includes the market proposed selected from the first section and choose the way in which check the solution first best suited in terms
... Show MoreVariation orders are an on-going phenomenon in construction and industry projects worldwide, particularly in the province of Sulaimani, where the project's damage from cost and schedule overrun because of variation orders. However, the effect on project costs and time overrun of variation order has yet to be identified. This study evaluates the impact of variation orders on the cost and time off in the Sulaimani governorate. Two hundred twenty-eight projects from various construction sectors built between 2007-2012 were adopted to calculate the contract cost and schedule overruns due to variation orders. Data analysis was applied in the study were descriptive statistics. One-way ANOVA was also applied to determine w
... Show MoreIraq's oil industry has been passed in different periods , began with domination of Western companies to invest in Iraqi oil at twenties of the last century , through the process of nationalization of the shares of those companies , beginning of the seventies , and ending with the new policies adopted by the government recently, which was contracting with international companies to develop the oil industry , because of what the outcome of the oil industry from a decline in artistic and physical ability as a result to the conditions of war and embargo imposed on Iraq before 2003.
The Iraqi government has introduced licensing of a contract to
... Show MoreBackground: It is well known that oral carriage
of Candida species increase in many situations, like
obesity, debility, leukemia, viral infection, use of
certain drugs in addition to diabetes mellitus.
Objective: find the relation between diabetes and
its control on oral carriage of Candida.
Methods: Thirty four hundred oral swabs from
diabetic patients 67% are females and 33% are
males, 41.7% are type 1 diabetes and 58.3% are type
2.different culture media are used.
Results: we found that 37.9% of diabetics had oral
carriage, older age group had more but the
difference is not significant statistically P>0.05, in
addition females carry more Candida than males
P<0.05, while type of diabetes
In this paper, Pentacene based-organic field effect transistors (OFETs) by using different layers (monolayer, bilayer and trilayer) for three different gate insulators (ZrO2, PVA and CYEPL) were studied its current–voltage (I-V) characteristics by using the gradual-channel approximation model. The device exhibits a typical output curve of a field-effect transistor (FET). Source-drain voltage (Vds) was also investigated to study the effects of gate dielectric on electrical performance for OFET. The effect of capacitance semiconductor in performance OFETs was considered. The values of current and transconductance which calculated using MATLAB simulation. It exhibited a value of current increase with increasing source-drain voltage.
In this paper, Pentacene based-organic field effect transistors (OFETs) by using different layers (monolayer, bilayer and trilayer) for three different gate insulators (ZrO2, PVA and CYEPL) were studied its current–voltage (I-V) characteristics by using the gradual-channel approximation model. The device exhibits a typical output curve of a field-effect transistor (FET). Source-drain voltage (Vds) was also investigated to study the effects of gate dielectric on electrical performance for OFET. The effect of capacitancesemiconductor in performance OFETs was considered. The values of current and transconductance which calculated using MATLAB simulation. It exhibited a value of current increase with increasing source-drain voltage.
In this paper we describe several different training algorithms for feed forward neural networks(FFNN). In all of these algorithms we use the gradient of the performance function, energy function, to determine how to adjust the weights such that the performance function is minimized, where the back propagation algorithm has been used to increase the speed of training. The above algorithms have a variety of different computation and thus different type of form of search direction and storage requirements, however non of the above algorithms has a global properties which suited to all problems.
The growing demand for sustainable and environmentally friendly alternatives in road construction has led to the exploration of bio-based materials for bitumen modification. This study investigates the use of sugarcane molasses (SM) as a partial replacement of bitumen, evaluating its performance through an interlaboratory study conducted in India and Iraq. Bio-bitumen binders were prepared by partially replacing 30% of conventional bitumen with sugarcane molasses, and their chemical and thermal behaviour was studied. Additionally, laboratory tests were conducted on bio-bitumen mixtures, evaluating rutting resistance, cracking resistance, moisture susceptibility, and stiffness characteristics. A mechanistic-empirical pavement analysis using
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