Drilling deviated wells is a frequently used approach in the oil and gas industry to increase the productivity of wells in reservoirs with a small thickness. Drilling these wells has been a challenge due to the low rate of penetration (ROP) and severe wellbore instability issues. The objective of this research is to reach a better drilling performance by reducing drilling time and increasing wellbore stability.

In this work, the first step was to develop a model that predicts the ROP for deviated wells by applying Artificial Neural Networks (ANNs). In the modeling, azimuth (AZI) and inclination (INC) of the wellbore trajectory, controllable drilling parameters, unconfined compressive strength (UCS), formation

This research has been prepared to isolate and diagnose one of the most important vegetable oils from the plant medical clove is the famous with Alaeugenol oil and used in many pharmaceuticals were the isolation process using a technique ultrasonic extraction and distillation technology simple

A rapid, simple and sensitive spectrophotometric method for the determination of trace amounts of chromium is studied. The method is based on the interaction of chromium with indigo carmine dye in acidic medium and the presence of oxalates as a catalyst for interaction, and after studying the absorption spectrum of the solution resulting observed decrease in the intensity of the absorption. As happened (Bleaching) for color dye, this palace and directly proportional to the chromium (VI) amount was measured intensity of the absorption versus solution was figurehead at a wavelength of 610 nm. A plot of absorbance with chromium (VI) concentration gives a straight line indicating that Beer’s law has been obeyed over the range of 0.5

Biosorption of cadmium ions from simulated wastewater using rice husk was studied with initial concentration of 25 mg/l. Equilibrium isotherm was studied using Langmuir, Freundlich, BET and Timken models. The results show that the Freundlich isotherm is the best fit model to describe this process with high determination coefficient equals to 0.983. There was a good compliance between the experimental and theoretical results. Highest removal efficiency 97% was obtained at 2.5g of adsorbent, pH 6 and contact time 100 min.

A Novel artificial neural network (ANN) model was constructed for calibration of a multivariate model for simultaneously quantitative analysis of the quaternary mixture composed of carbamazepine, carvedilol, diazepam, and furosemide. An eighty-four mixing formula where prepared and analyzed spectrophotometrically. Each analyte was formulated in six samples at different concentrations thus twentyfour samples for the four analytes were tested. A neural network of 10 hidden neurons was capable to fit data 100%. The suggested model can be applied for the quantitative chemical analysis for the proposed quaternary mixture.

Random throwing of industrial waste has a significant impact on the environment unless it takes into account the conditions of engineered destroying and/or re-used. Taking the advantage of re-using waste materials in engineering projects represents a well-planned project in order to resolve a lot of engineering problems for some difficult soils. The objective of this study was to evaluate the capability and effects of Rubber Shreds (RS) from scrap torn belts towards improving the shear strength of soft clay. A direct shear tests were conducted on soft clay-RS mixture. The following parameters were investigated to study the influence of RS content, water content, normal stress, and dilation ratio. From experimental test results it was fou

In this paper, we derived an estimator of reliability function for Laplace distribution with two parameters using Bayes method with square error loss function, Jeffery’s formula and conditional probability random variable of observation. The main objective of this study is to find the efficiency of the derived Bayesian estimator compared to the maximum likelihood of this function and moment method using simulation technique by Monte Carlo method under different Laplace distribution parameters and sample sizes. The consequences have shown that Bayes estimator has been more efficient than the maximum likelihood estimator and moment estimator in all samples sizes