Geomechanical modelling and simulation are introduced to accurately determine the combined effects of hydrocarbon production and changes in rock properties due to geomechanical effects. The reservoir geomechanical model is concerned with stress-related issues and rock failure in compression, shear, and tension induced by reservoir pore pressure changes due to reservoir depletion. In this paper, a rock mechanical model is constructed in geomechanical mode, and reservoir geomechanics simulations are run for a carbonate gas reservoir. The study begins with assessment of the data, construction of 1D rock mechanical models along the well trajectory, the generation of a 3D mechanical earth model, and running a 4D geomechanical simulation using a two-way coupling simulation method, followed by results analysis. A dual porosity/permeability model is coupled with a 3D geomechanical model, and iterative two-way coupling simulation is performed to understand the changes in effective stress dynamics with the decrease in reservoir pressure due to production, and therefore to identify the changes in dual-continuum media conductivity to fluid flow and field ultimate recovery. The results of analysis show an observed effect on reservoir flow behaviour of a 4% decrease in gas ultimate recovery and considerable changes in matrix contribution and fracture properties, with the geomechanical effects on the matrix visibly decreasing the gas production potential, and the effect on the natural fracture contribution is limited on gas inflow. Generally, this could be due to slip flow of gas at the media walls of micro-extension fractures, and the flow contribution and fracture conductivity is quite sufficient for the volume that the matrixes feed the fractures. Also, the geomechanical simulation results show the stability of existing faults, emphasizing that the loading on the fault is too low to induce fault slip to create fracturing, and enhanced permeability provides efficient conduit for reservoir fluid flow in reservoirs characterized by natural fractures.
Ischemic stroke is a significant cause of morbidity and mortality worldwide. Autophagy, a process of intracellular degradation, has been shown to play a crucial role in the pathogenesis of ischemic stroke. Long non-coding RNAs (lncRNAs) have emerged as essential regulators of autophagy in various diseases, including ischemic stroke. Recent studies have identified several lncRNAs that modulate autophagy in ischemic stroke, including MALAT1, MIAT, SNHG12, H19, AC136007. 2, C2dat2, MEG3, KCNQ1OT1, SNHG3, and RMRP. These lncRNAs regulate autophagy by interacting with key proteins involved in the autophagic process, such as Beclin-1, ATG7, and LC3. Understanding the role of lncRNAs in regulating auto
تقدم هذه الدراسة وصفا للطريقة المستخدمة في تحضير الكربون المنشط (AC)من بقايا الشاي. تم دراسة الخواص الفيزيائية والكيميائية وكفاءة الامتزاز للكربون المنشط المحضر. تم إنتاج الكربون المنشط (AC) على مرحلتين: الاولى التنشيط باستخدام حامض الفوسفوريك (H3PO4) والثانية الكربنة عند درجة حرارة 450 درجة مئوية. استخدم الكربون المنشط لغرض امتصاص العقار الدوائي السيبروفلوكساسين(CIP) . تمت دراسة عدة عوامل تشغيلية بدرجة حرار
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The present investigation aimed to formulate a liquid self-microemulsifying drug delivery system (SMEDDS) of tacrolimus to enhance its oral bioavailability by improving its dispersibility and dissolution rate. Four liquid SMEDDS were prepared using maisine CC as oil phase, labrasol ALF as surfactant and transcutol HP as co-surfactant based on the solubility studies of tacrolimus in these components. The phase behavior of the components and the area of microemulsion were evaluated using pseudoternary phase diagrams. The formulations were also assessed for thermodynamic stability, robustness to dilution, self-emulsification time, drug content, globule size and polydispersity index. The prepared SMEDDS formulations exhibi
... Show MoreThe risk of breast cancer development is believed to be attributed to the alterations of a number of key biological components. Within this context, elevated levels of some chemokines that act as growth factors and can promote cancer development. The current study was designed to evaluate CXCL3 (a chemokine C-X-C Motif Ligand 3) and leptin (a peptide hormone synthesized by adipose tissue with cytokine activity) serum of Iraqi breast cancer patients in comparison to healthy controls. A total of 90 participants consisted of 60 patients diagnosed with breast cancer and 30 healthy women as control group were enrolled into this case-control study. Venous blood samples were collected from all participants to evaluate CXCL3 and leptin serum levels
... Show MoreAir pollution is very important topic for those interested in studying the environment because of its importance and the damage caused by it to human, animal and plant life. This research addresses the concept of air pollution, its causes, and its danger, and sheds light on the influence of climate elements on environmental pollution and the effect of temperature, rain, humidity, wind direction and speed, and atmospheric pressure on the increase or decrease of air pollution. This research discusses the sources of air pollution, including natural ones, including dust, smoke resulting from fires, erupting volcanoes, and others, including those resulting from human uses such as the use of fuel and others. The research addressed the dam
... Show MoreNumeral recognition is considered an essential preliminary step for optical character recognition, document understanding, and others. Although several handwritten numeral recognition algorithms have been proposed so far, achieving adequate recognition accuracy and execution time remain challenging to date. In particular, recognition accuracy depends on the features extraction mechanism. As such, a fast and robust numeral recognition method is essential, which meets the desired accuracy by extracting the features efficiently while maintaining fast implementation time. Furthermore, to date most of the existing studies are focused on evaluating their methods based on clean environments, thus limiting understanding of their potential a
... Show MoreStatistical learning theory serves as the foundational bedrock of Machine learning (ML), which in turn represents the backbone of artificial intelligence, ushering in innovative solutions for real-world challenges. Its origins can be linked to the point where statistics and the field of computing meet, evolving into a distinct scientific discipline. Machine learning can be distinguished by its fundamental branches, encompassing supervised learning, unsupervised learning, semi-supervised learning, and reinforcement learning. Within this tapestry, supervised learning takes center stage, divided in two fundamental forms: classification and regression. Regression is tailored for continuous outcomes, while classification specializes in c
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