Horizontal wells are of great interest to the petroleum industry today because they provide an attractive means for improving both production rate and recovery efficiency. The great improvements in drilling technology make it possible to drill horizontal wells with complex trajectories and extended for significant depths.
The aim of this paper is to present the design aspects of horizontal well. Well design aspects include selection of bit and casing sizes, detection of setting depths and drilling fluid density, casing, hydraulics, well profile, and construction of drillstring simulator. An Iraqi oil field (Ajeel field) is selected for designing horizontal well to increase the productivity. Short radius horizontal well is suggested fo

In this work, a step-index fiber with core index  and cladding index  has been designed. Single-mode operation can be obtained by using a fiber with core diameters 4–13 µm operating at a wavelength of 1.31 µm and by 4–15 µm at 1.55 µm. The fundamental fiber mode properties such as phase constant, effective refractive index, mode radius, effective mode area and the power in the core were calculated. Distributions of the intensity and the amplitude were shown.

Biodiesel define as the mono-alkyl esters of vegetable oil and animal fats is an alternative diesel fuel that is steadily gaining attention because the combustion of fossil fuels such as coal, oil and natural gas has been identify as a major cause of the increase in the concentration of carbon dioxide in the earth’s atmosphere and causing global warming.
The present work concerns with estimating the physical properties experimentally such as kinematic viscosity, density, flash point and carbon residue of biodiesel that produced by the esterification reaction of methanol and oleic acid with homogeneous catalysts H2SO4 in a lab-scale packed reactive distillation column using the best operating conditions of methanol to oleic acid 8:1,

A group of acceptance sampling to testing the products was designed when the life time of an item follows a log-logistics distribution. The minimum number of groups (k) required for a given group size and acceptance number is determined when various values of Consumer’s Risk and test termination time are specified. All the results about these sampling plan and probability of acceptance were explained with tables.

This paper presents L₁-adaptive controller for controlling uncertain parameters and time-varying unknown parameters to control the position of a DC servomotor. For the purpose of comparison, the effectiveness of L₁-adaptive controller for position control of studied servomotor has been examined and compared with another adaptive controller; Model Reference Adaptive Controller (MRAC). Robustness of both L₁-adaptive controller and model reference adaptive controller to different input reference signals and different structures of uncertainty were studied. Three different types of input signals are taken into account; ramp, step and sinusoidal. The L₁-adaptive controller ensured uniformly bounded

The study was carried out at field agriculture in Baghdad–Iraq in 2015. For purpose evaluated the performance the selected implements tillage, suitable tire pressure and speed tractor under silt clay loam to measured Effective field capacity, Actual Time for plowing One Donam ( hr), Appearance Tillage ( number of clods > 10 cm), Fuel consumption measure in two unit (L/Donam and L/hr) and Machinery Unit Energy Requirement ( kw.hr / Donam). Split – split plot design under randomized complete block design with three replications using Least Significant Design 5 % was used. Three factor used in this experiment included Two types of plows included Chisel and Disk plows which represented main plot, Three Tires Inflation Pressure was second fa

This paper proposes a new structure of the hybrid neural controller based on the identification model for nonlinear systems. The goal of this work is to employ the structure of the Modified Elman Neural Network (MENN) model into the NARMA-L2 structure instead of Multi-Layer Perceptron (MLP) model in order to construct a new hybrid neural structure that can be used as an identifier model and a nonlinear controller for the SISO linear or nonlinear systems. Weight parameters of the hybrid neural structure with its serial-parallel configuration are adapted by using the Back propagation learning algorithm. The ability of the proposed hybrid neural structure for nonlinear system has achieved a fast learning with minimum number