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.
Machine learning models have recently provided great promise in diagnosis of several ophthalmic disorders, including keratoconus (KCN). Keratoconus, a noninflammatory ectatic corneal disorder characterized by progressive cornea thinning, is challenging to detect as signs may be subtle. Several machine learning models have been proposed to detect KCN, however most of the models are supervised and thus require large well-annotated data. This paper proposes a new unsupervised model to detect KCN, based on adapted flower pollination algorithm (FPA) and the k-means algorithm. We will evaluate the proposed models using corneal data collected from 5430 eyes at different stages of KCN severity (1520 healthy, 331 KCN1, 1319 KCN2, 1699 KCN3 a
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The swarm intelligence and evolutionary methods are commonly utilized by researchers in solving the difficult combinatorial and Non-Deterministic Polynomial (NP) problems. The N-Queen problem can be defined as a combinatorial problem that became intractable for the large ‘n’ values and, thereby, it is placed in the NP class of problems. In the present study, a solution is suggested for the N-Queen problem, on the basis of the Meerkat Clan Algorithm (MCA). The problem of n-Queen can be mainly defined as one of the generalized 8-Queen problem forms, for which the aim is placing 8 queens in a way that none of the queens has the ability of killing the others with the use of the standard moves of the chess queen. The Meerkat Clan environm
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The usage of remote sensing techniques in managing and monitoring the environmental areas is increasing due to the improvement of the sensors used in the observation satellites around the earth. Resolution merge process is used to combine high resolution one band image with another one that have low resolution multi bands image to produce one image that is high in both spatial and spectral resolution. In this work different merging methods were tested to evaluate their enhancement capabilities to extract different environmental areas; Principle component analysis (PCA), Brovey, modified (Intensity, Hue ,Saturation) method and High Pass Filter methods were tested and subjected to visual and statistical comparison for evaluation. Both visu
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A total of 243 serum samples were tested for the presence of
Chlamydia antibodies by ind irect immunofluorescent antibody test.Ninety
nine females were suffering from abortions, 64 were infertile and other 80 were none aborted women. The incidence of Ch lamydia were (15%,
9.4%) and (3.8%) in abortion, infertile and non aborted group,
respecti vely. The results also showed a difference in prevalence rate between the age groups. The highest incidence was found in the age group 20-39 &
... Show MoreIn this work , a hybrid scheme tor Arabic speech for the recognition
of the speaker verification is presented . The scheme is hybrid as utilizes the traditional digi tal signal processi ng and neural network . Kohonen neural network has been used as a recognizer tor speaker verification after extract spectral features from an acoustic signal by Fast Fourier Transformation Algorithm(FFT) .
The system was im plemented using a PENTIUM processor , I000
MHZ compatible and MS-dos 6.2 .
We study one example of hyperbolic problems it's Initial-boundary string problem with two ends. In fact we look for the solution in weak sense in some sobolev spaces. Also we use energy technic with Galerkin's method to study some properties for our problem as existence and uniqueness
This work presents an approach to deal with modelling a decision support system framework to introduce an application for decisions in medical knowledge system analysis. First aid is extremely important worldwide and, hence, a decision support framework, know as First Aid Decision Support System (FADSS), was designed and implemented to access experimental cases exerting danger to the general population, offering advanced conditions for testing abilities in research and arranging an emergency treatment through the graphical user interface (UI). The design of first aid treatment in FADSS depends on the general cases in first aid. We presented a strategy to manage first aid treatment by modelling an application (FADSS) that assists pe
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The development of wireless sensor networks (WSNs) in the underwater environment leads to underwater WSN (UWSN). It has severe impact over the research field due to its extensive and real-time applications. However effective execution of underwater WSNs undergoes several problems. The main concern in the UWSN is sensor nodes’ energy depletion issue. Energy saving and maintaining quality of service (QoS) becomes highly essential for UWASN because of necessity of QoS application and confined sensor nodes (SNs). To overcome this problem, numerous prevailing methods like adaptive data forwarding techniques, QoS-based congestion control approaches, and various methods have been devised with maximum throughput and minimum network lifesp
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The development of wireless sensor networks (WSNs) in the underwater environment leads to underwater WSN (UWSN). It has severe impact over the research field due to its extensive and real-time applications. However effective execution of underwater WSNs undergoes several problems. The main concern in the UWSN is sensor nodes’ energy depletion issue. Energy saving and maintaining quality of service (QoS) becomes highly essential for UWASN because of necessity of QoS application and confined sensor nodes (SNs). To overcome this problem, numerous prevailing methods like adaptive data forwarding techniques, QoS-based congestion control approaches, and various methods have been devised with maximum throughput and minimum network lifesp
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