Carbonate matrix stimulation technology has progressed tremendously in the last decade through creative laboratory research and novel fluid advancements. Still, existing methods for optimizing the stimulation of wells in vast carbonate reservoirs are inadequate. Consequently, oil and gas wells are stimulated routinely to expand production and maximize recovery. Matrix acidizing is extensively used because of its low cost and ability to restore the original productivity of damaged wells and provide additional production capacity. The Ahdeb oil field lacks studies in matrix acidizing; therefore, this work provided new information on limestone acidizing in the Mishrif reservoir. Moreover, several reports have been issued on the difficulties encountered during the stimulation operation of the Ahdeb oil field, particularly for the development of the Mishrif reservoir. Since the new core flooding system is built to operate safely and straightforwardly. This study introduced the results of Matrix acidizing experiments, covering the most recent developments in linear core flooding. High-permeability flow pathways are created, and a longer and wider wormhole was generated at a high acid injection rate (6.67 cc/min). The acid efficiency curve yielded the lowest pore volume injected at the breakthrough of the PV_(bt-opt) is 2.73 and the v_(i-opt)=0.6 cm/min; thus, the optimum injection rate that results in an optimal possible wormhole and the least quantity of acid being used for this reservoir is 2.16 cc/min. This research evaluated the impact of matrix acidizing treatment on acoustic characteristics, which studies show are lacking or have never been investigated previously. Furthermore, in the assessment of geomechanical rock properties and elastic and petrophysical parameters before and after acid injection, one of the new concepts discovered during the lab experiment observation of the acoustic waveform before and after acid treatment for the tested rock sample is that the initial arrival time before acid treatment is 21.6 microseconds, with a delay of 31.2 microseconds attributed to the wormhole channel and mineral disintegration. CT-Scan applications in matrix acidizing were investigated in this research; additionally, a 3D view of plug samples was constructed to represent the wormhole extension via CT-processing software. A license of Stimpro Stimulation Software has been used to validate the experimental work to the field scale, making it the most comprehensive instrument for planning and monitoring matrix acid treatment and utilizing actual data to provide a far better knowledge of the well's reaction, with methods that represent the reality of what is happening in the reservoir before, during, and after matrix acid treatments, through the post-treatment skin factor which is the most often utilized statistic for analyzing stimulation treatments and relies on the geometry of the wormholed zone. The acid treatment evaluated for the well AD-12, primarily for the zone Mi4; matrix acid treatments can have their production behavior predicted or matched using the reservoir simulation and production analysis option, employing the numerical simulation license software Petrel (Schlumberger) and Rubis (KAPPA) to determine the efficacy of previous treatments and the economics associated with future treatments. The estimated oil gain volume and percentage for the Mi4 unit in Ad-12 using particularly skin value -3.97 computed from Stimpro software for real stimulation acid job, it is yield enhancement in production of oil gain volume 6154 barrels as well as 105% increase of gain percentage for three months after matrix acidizing.
Hiding technique for dynamic encryption text using encoding table and symmetric encryption method (AES algorithm) is presented in this paper. The encoding table is generated dynamically from MSB of the cover image points that used as the first phase of encryption. The Harris corner point algorithm is applied on cover image to generate the corner points which are used to generate dynamic AES key to second phase of text encryption. The embedded process in the LSB for the image pixels except the Harris corner points for more robust. Experimental results have demonstrated that the proposed scheme have embedding quality, error-free text recovery, and high value in PSNR.
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Wastewater projects are one of the most important infrastructure projects, which require developing strategic plans to manage these projects. Most of the wastewater projects in Iraq don’t have a maintenance plan. This research aims to prepare the maintenance management plan (MMP) for wastewater projects. The objective of the research is to predict the cost and time of maintenance projects by building a model using ANN. The research sample included (15) completed projects in Wasit Governorate, where the researcher was able to obtain the data of these projects through the historical information of the Wasit Sewage Directorate. In this research artificial neural networks (ANN) technique was used to build two models (cost
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<span>We present the linearization of an ultra-wideband low noise amplifier (UWB-LNA) operating from 2GHz to 11GHz through combining two linearization methods. The used linearization techniques are the combination of post-distortion cancellation and derivative-superposition linearization methods. The linearized UWB-LNA shows an improved linearity (IIP3) of +12dBm, a minimum noise figure (NF<sub>min.</sub>) of 3.6dB, input and output insertion losses (S<sub>11</sub> and S<sub>22</sub>) below -9dB over the entire working bandwidth, midband gain of 6dB at 5.8GHz, and overall circuit power consumption of 24mW supplied from a 1.5V voltage source. Both UWB-LNA and linearized UWB-LNA designs are
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The physical behavior for the energy distribution function (EDF) of the reactant particles depending upon the gases (fuel) temperature are completely described by a physical model covering the global formulas controlling the EDF profile. Results about the energy distribution for the reactant system indicate a standard EDF, in which it’s arrive a steady state form shape and intern lead to fix the optimum selected temperature.
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Ultraviolet photodetectors have been widely utilized in several applications, such as advanced communication, ozone sensing, air purification, flame detection, etc. Gallium nitride and its compound semiconductors have been promising candidates in photodetection applications. Unlike polar gallium nitride-based optoelectronics, non-polar gallium nitride-based optoelectronics have gained huge attention due to the piezoelectric and spontaneous polarization effect–induced quantum confined-stark effect being eliminated. In turn, non-polar gallium nitride-based photodetectors portray higher efficiency and faster response compared to the polar growth direction. To date, however, a systematic literature review of non-polar gallium nitride-
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Alzheimer’s disease (AD) is a progressive disorder that affects cognitive brain functions and starts many years before its clinical manifestations. A biomarker that provides a quantitative measure of changes in the brain due to AD in the early stages would be useful for early diagnosis of AD, but this would involve dealing with large numbers of people because up to 50% of dementia sufferers do not receive formal diagnosis. Thus, there is a need for accurate, low-cost, and easy to use biomarkers that could be used to detect AD in its early stages. Potentially, electroencephalogram (EEG) based biomarkers can play a vital role in early diagnosis of AD as they can fulfill these needs. This is a cross-sectional study that aims to demon
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A method has been demonstrated to synthesise effective zeolite membranes from existing crystals without a hydrothermal synthesis step.
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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
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