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.
The using of recycled aggregates from construction and demolition waste (CDW) can preserve natural aggregate resources, reduce the demand for landfill, and contribute to a sustainable built environment. Concrete demolition waste has been proven to be an excellent source of aggregates for new concrete production. At a technical, economic, and environmental level, roller compacted concrete (RCC) applications benefit various civil construction projects. Roller Compacted Concrete (RCC) is a homogenous mixture that is best described as a zero-slump concrete placed with compacting equipment, uses in storage areas, dams, and most often as a basis for rigid pavements. The mix must be sufficiently dry to support
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Aerial Robot Arms (ARAs) enable aerial drones to interact and influence objects in various environments. Traditional ARA controllers need the availability of a high-precision model to avoid high control chattering. Furthermore, in practical applications of aerial object manipulation, the payloads that ARAs can handle vary, depending on the nature of the task. The high uncertainties due to modeling errors and an unknown payload are inversely proportional to the stability of ARAs. To address the issue of stability, a new adaptive robust controller, based on the Radial Basis Function (RBF) neural network, is proposed. A three-tier approach is also followed. Firstly, a detailed new model for the ARA is derived using the Lagrange–d’A
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Leap Motion Controller (LMC) is a gesture sensor consists of three infrared light emitters and two infrared stereo cameras as tracking sensors. LMC translates hand movements into graphical data that are used in a variety of applications such as virtual/augmented reality and object movements control. In this work, we intend to control the movements of a prosthetic hand via (LMC) in which fingers are flexed or extended in response to hand movements. This will be carried out by passing in the data from the Leap Motion to a processing unit that processes the raw data by an open-source package (Processing i3) in order to control five servo motors using a micro-controller board. In addition, haptic setup is proposed using force sensors (F
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The COVID-19 pandemic has had a huge influence on human lives all around the world. The virus spread quickly and impacted millions of individuals, resulting in a large number of hospitalizations and fatalities. The pandemic has also impacted economics, education, and social connections, among other aspects of life. Coronavirus-generated Computed Tomography (CT) scans have Regions of Interest (ROIs). The use of a modified U-Net model structure to categorize the region of interest at the pixel level is a promising strategy that may increase the accuracy of detecting COVID-19-associated anomalies in CT images. The suggested method seeks to detect and isolate ROIs in CT scans that show the existence of ground-glass opacity, which is fre
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In data transmission a change in single bit in the received data may lead to miss understanding or a disaster. Each bit in the sent information has high priority especially with information such as the address of the receiver. The importance of error detection with each single change is a key issue in data transmission field.
The ordinary single parity detection method can detect odd number of errors efficiently, but fails with even number of errors. Other detection methods such as two-dimensional and checksum showed better results and failed to cope with the increasing number of errors.
Two novel methods were suggested to detect the binary bit change errors when transmitting data in a noisy media.Those methods were: 2D-Checksum me
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This paper describes a newly modified wind turbine ventilator that can achieve highly efficient ventilation. The new modification on the conventional wind turbine ventilator system may be achieved by adding a Savonius wind turbine above the conventional turbine to make it work more efficiently and help spinning faster. Three models of the Savonius wind turbine with 2, 3, and 4 blades' semicircular arcs are proposed to be placed above the conventional turbine of wind ventilator to build a hybrid ventilation turbine. A prototype of room model has been constructed and the hybrid turbine is placed on the head of the room roof. Performance's tests for the hybrid turbine with a different number of blades and different values o
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Most of the medical datasets suffer from missing data, due to the expense of some tests or human faults while recording these tests. This issue affects the performance of the machine learning models because the values of some features will be missing. Therefore, there is a need for a specific type of methods for imputing these missing data. In this research, the salp swarm algorithm (SSA) is used for generating and imputing the missing values in the pain in my ass (also known Pima) Indian diabetes disease (PIDD) dataset, the proposed algorithm is called (ISSA). The obtained results showed that the classification performance of three different classifiers which are support vector machine (SVM), K-nearest neighbour (KNN), and Naïve B
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