Rate of penetration plays a vital role in field development process because the drilling operation is expensive and include the cost of equipment and materials used during the penetration of rock and efforts of the crew in order to complete the well without major problems. It’s important to finish the well as soon as possible to reduce the expenditures. So, knowing the rate of penetration in the area that is going to be drilled will help in speculation of the cost and that will lead to optimize drilling outgoings. In this research, an intelligent model was built using artificial intelligence to achieve this goal.  The model was built using adaptive neuro fuzzy inference system to predict the rate of penetration in

This study investigates the implementation of Taguchi design in the estimation of minimum corrosion rate of mild-steel in cooling tower that uses saline solution of different concentration. The experiments were set on the basis of Taguchi’s L16 orthogonal array. The runs were carried out under different condition such as inlet concentration of saline solution, temperature, and flowrate. The Signal-to- Noise ratio and ANOVA analysis were used to define the impact of cooling tower working conditions on the corrosion rate. A regression had been modelled and optimized to identify the optimum level for the working parameters that had been founded to be 13%NaCl, 35ᴼC, and 1 l/min. Also a confirmation run to establish the p

Pulsed laser ablation in liquid (PLAL) has become an increasingly important technique for metals production and metal oxides nanoparticles (NPs) and others. This technique has its many advantages compared with other conventional techniques (physical and chemical). This work was devoted for production of zirconia (ZrO2) nanoparticles via PLAL technique from a solid zirconium target immersed in a wet environment in order to study the effect of this environment on the optical properties and structure of ZrO2 nanoparticles. The solutions which used for this purpose is distilled water (D.W). The produces NPs were characterized by mean of many tests such as UV-visible (UV-Vis.), transmission electron microscope (TEM) and Z-Potential. The UV-Vis.

Acne scars are one of the most common problems following acne vulgaris. Despite the extensive list of available treatment modalities, their effectiveness depends upon the nature of the scar. Ablative lasers had been used to treat acne scars; one of them is the fractional CO2 laser. The aim of this study is to evaluate the outcome of fractional CO2 laser in the treatment of acne scars. Methods: Since January 2010 to June 2013, using 10600 nm fractional CO2 laser beams, the acne scar of 400 patients, 188 males and 212 females, mean age of 34 years, have been treated and classified according to severity into four grades following Goodman and Baron classification. Each patient underwent 3-5 sessions once monthly. The mean laser exposure time

Design and Construction system for recording Finger print by laser, and separted the signal to noise by holographic element, was done. For safety, total reflection lighting ensures hat aser earns an not enter An operators eyes. Holographic diffraction grating was used instead of computer program to contrast images.

The purpose of this paper is to depict the effect of adding a hydraulic accumulator to a hydraulic system. The experimental work includes using measuring devices with interface to measure the pressure and the vibration of the system directly by computer so as to show the effect of accumulator graphically for real conditions, also the effects of hydraulic accumulator for different applications
have been tested. A simulation analysis of the hydraulic control system using MATLAB.R2010b to study was made to study the stability of the system depending on the transfer function, to estimate the effect of adding the accumulator on stability of the system. A physical simulation test was made for the hydraulic system using MATLAB to show the ef

It is well known that the rate of penetration is a key function for drilling engineers since it is directly related to the final well cost, thus reducing the non-productive time is a target of interest for all oil companies by optimizing the drilling processes or drilling parameters. These drilling parameters include mechanical (RPM, WOB, flow rate, SPP, torque and hook load) and travel transit time. The big challenge prediction is the complex interconnection between the drilling parameters so artificial intelligence techniques have been conducted in this study to predict ROP using operational drilling parameters and formation characteristics. In the current study, three AI techniques have been used which are neural network, fuzzy i