Many carbonate reservoirs in the world show a tilted in originally oil-water contact (OOWC) which requires a special consideration in the selection of the capillary pressure curves and an understanding of reservoir fluids distribution while initializing the reservoir simulation models.
An analytical model for predicting the capillary pressure across the interface that separates two immiscible fluids was derived from reservoir pressure transient analysis. The model reflected the entire interaction between the reservoir-aquifer fluids and rock properties measured under downhole reservoir conditions.
This model retained the natural coupling of oil reservoirs with the aquifer zone and treated them as an explicit-region composite system; thus the exact solutions of diffusivity equation could be used explicitly for each region. The reservoir-aquifer zones were linked by a capillary transition zone that reflected the pressure difference across the free water level.
The principle of superposition theorem was applied to perform this link across the free water level to estimate the reflected aquifer pressure drop behavior that holds the fluid contacts in their equilibrium positions.
The results of originally oil water contact positions generated by the proposed model were compared with data obtained from a carbonate oil field; the results given by the model showed full agreement with the actual field data.
In this paper, a self-tuning adaptive neural controller strategy for unknown nonlinear system is presented. The system considered is described by an unknown NARMA-L2 model and a feedforward neural network is used to learn the model with two stages. The first stage is learned off-line with two configuration serial-parallel model & parallel model to ensure that model output is equal to actual output of the system & to find the jacobain of the system. Which appears to be of critical importance parameter as it is used for the feedback controller and the second stage is learned on-line to modify the weights of the model in order to control the variable parameters that will occur to the system. A back propagation neural network is appl
... Show MoreComputer systems and networks are increasingly used for many types of applications; as a result the security threats to computers and networks have also increased significantly. Traditionally, password user authentication is widely used to authenticate legitimate user, but this method has many loopholes such as password sharing, brute force attack, dictionary attack and more. The aim of this paper is to improve the password authentication method using Probabilistic Neural Networks (PNNs) with three types of distance include Euclidean Distance, Manhattan Distance and Euclidean Squared Distance and four features of keystroke dynamics including Dwell Time (DT), Flight Time (FT), mixture of (DT) and (FT), and finally Up-Up Time (UUT). The resul
... Show MoreThere are many different methods for analysis of two-way reinforced concrete slabs. The most efficient methods depend on using certain factors given in different codes of reinforced concrete design. The other ways of analysis of two-way slabs are the direct design method and the equivalent frame method. But these methods usually need a long time for analysis of the slabs.
In this paper, a new simple method has been developed to analyze the two-way slabs by using simple empirical formulae, and the results of final analysis of some examples have been compared with other different methods given in different codes of practice.
The comparison proof that this simple proposed method gives good results and it can be used in analy
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In this paper, first and second order sliding mode controllers are designed for a single link robotic arm actuated by two Pneumatic Artificial Muscles (PAMs). A new mathematical model for the arm has been developed based on the model of large scale pneumatic muscle actuator model. Uncertainty in parameters has been presented and tested for the two controllers. The simulation results of the second-order sliding mode controller proves to have a low tracking error and chattering effect as compared to the first order one. The verification has been done by using MATLAB and Simulink software.
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Objectives: To identify quality of life (QOL) in Myocardial Infarction (MI) patients, and to find out the
relationship between QOL in MI patients and demographic characteristics.
Methodology: A descriptive colTelation study which utilized an assessment approach. The study was carried out
from March 2007 through November 2007 in order to assess the quality of life for patients with myocardial
infarction. A purposive "non-probability" sample of (75) patients with myocardial infarction who were attending
to Baquba General Hospita`l through their visits to that hospital. A questionnaire was adapted and developed
from the World Health Organization Quality of Life Scale (1998). The questionnaire was designed and
consisted
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Abstract
This paper represents a study of the effect of the soil type, the drilling parameters and the drilling tool properties on the dynamic vibrational behavior of the drilling rig and its assessment in the drilling system. So first, an experimental drilling rig was designed and constructed to embrace the numerical work.
The experimental work included implementation of the drill-string in different types of soil with different properties according to the difference in the grains size, at different rotational speeds (RPM), and different weights on bit (WOB) (Thrust force), in a way that allows establishing the charts that correlate the vibration acceleration, the rate of penetration (ROP), and the power
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