Reservoir study has been developed in order to get a full interesting of the Nahr Umr formation in Ratawi oil field. Oil in place has been calculated for Nahr Umr which was 2981.37 MM BBL. Several runs have been performed to get matching between measured and calculated of oil production data and well test pressure. In order to get the optimum performance of Nahr Umr many strategies have been proposed in this study where vertical and horizontal wells were involved in addition to different production rates. The reservoir was first assumed to be developed with vertical wells only using production rate of (80000–125000) STB/day. The reservoir is also proposed to produce using horizontal wells besides vertical wells with pr

This paper proposes an on-line adaptive digital Proportional Integral Derivative (PID) control algorithm based on Field Programmable Gate Array (FPGA) for Proton Exchange Membrane Fuel Cell (PEMFC) Model. This research aims to design and implement Neural Network like a digital PID using FPGA in order to generate the best value of the hydrogen partial pressure action (PH₂) to control the stack terminal output voltage of the (PEMFC) model during a variable load current applied. The on-line Particle Swarm Optimization (PSO) algorithm is used for finding and tuning the optimal value of the digital PID-NN controller (kp, ki, and kd) parameters that improve the dynamic behavior of the closed-loop digital control fue

Artificial Intelligence Algorithms have been used in recent years in many scientific fields. We suggest employing artificial TABU algorithm to find the best estimate of the semi-parametric regression function with measurement errors in the explanatory variables and the dependent variable, where measurement errors appear frequently in fields such as sport, chemistry, biological sciences, medicine, and epidemiological studies, rather than an exact measurement.

Permeability determination in Carbonate reservoir is a complex problem, due to their capability to be tight and heterogeneous, also core samples are usually only available for few wells therefore predicting permeability with low cost and reliable accuracy is an important issue, for this reason permeability predictive models become very desirable.

   This paper will try to develop the permeability predictive model for one of  Iraqi carbonate reservoir from core and well log data using the principle of Hydraulic Flow Units (HFUs). HFU is a function of Flow Zone Indicator (FZI) which is a good parameter to determine (HFUs).

   Histogram analysis, probability analysis and Log-Log plot of Reservoir Qua

The turning process has various factors, which affecting machinability and should be investigated. These are surface roughness, tool life, power consumption, cutting temperature, machining force components, tool wear, and chip thickness ratio. These factors made the process nonlinear and complicated. This work aims to build neural network models to correlate the cutting parameters, namely cutting speed, depth of cut and feed rate, to the machining force and chip thickness ratio. The turning process was performed on high strength aluminum alloy 7075-T6. Three radial basis neural networks are constructed for cutting force, passive force, and feed force. In addition, a radial basis network is constructed to model the chip thickness ratio. T

Reservoir rock typing integrates geological, petrophysical, seismic, and reservoir data to identify zones with similar storage and flow capacities. Therefore, three different methods to determine the type of reservoir rocks in the Mushrif Formation of the Amara oil field. The first method represents cluster analysis, a statistical method that classifies data points based on effective porosity, clay volume, and sonic transient time from well logs or core samples. The second method is the electrical rock type, which classifies reservoir rocks based on electrical resistivity. The permeability of rock types varies due to differences in pore geometry, mineral composition, and fluid saturation. Resistivity data are usually obtained from w

The objective of this study is to ascertain the pivotal role of headlines in captivating viewers' attention toward news bulletins. Additionally, it aims to explore the factors that contribute to the correlation between headlines and the public's acceptance or rejection of the meticulously crafted news articles presented through these bulletins. The study delves into the mechanisms employed in writing and editing headlines, focusing on their style, expert composition, and intriguing nature. These factors inevitably influence the level of acceptance and engagement of the viewership with the news articles disseminated via the news bulletins. Employing a descriptive methodology, the researcher distributed 200 question