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.
Twelve species from Brassicaceae family were studied using two different molecular techniques: RAPD and ISSR; both of these techniques were used to detect some molecular markers associated with the genotype identification. RAPD results, from using five random primers, revealed 241 amplified fragments, 62 of them were polymorphic (26%).
ISSR results showed that out of seven primers, three (ISSR3, UBC807, UBC811) could not amplify the genomic DNA; other primers revealed 183 amplified fragments, 36 of them were polymorphic (20%). The similarity evidence and dendrogram for the genetic distances of the incorporation between the two techniques showed that the highest similarity was 0.897 between the va
... Show MoreBackground: Opportunistic viral infections make an important threat to renal transplantation recipients (RTRs), and with the use of more intense newly-developed immunosuppressive drugs; the risk of renal allograft loss due to reactivation of these viruses has increased considerably. At the top priority of these viruses lie BK polyomavirus (BKV) and human cytomegalovirus (CMV). Reactivation of these viruses in these chronically immunosuppressed RTRs can lead to renal impairment and subsequently allograft loss, unless early detected and properly treated. Objectives: The study aimed to detect and quantify plasma viral load of BKV and CMV in RTRs using quantitative real time PCR (qRT-PCR), in order to study the prevalence of these two viruses i
... Show MoreTo identify and explore the factors nurses perceive as influencing their knowledge acquisition in relation to diabetes care and its management in Saudi Arabia.
Diabetes continues to pose major healthcare challenges despite advances in diabetes management. Nurses have a crucial role in diabetes care, but diabetes knowledge deficits deter effective collaboration with other healthcare providers in educating patients about diabetes self‐management.
An exploratory descriptive qualitative design.
Coumarin is a natural substance isolated from different plants. It belonges to a group of benzobyrones which consists of a benzene ring joined to a pyrone nucleus. In the present research, a new series of coumarin derivatives were formed. Compound (1) (7-hydroxy-4-methyl Coumarin) was converted into 4-methylquinolin-2(H) derivative (2) by reaction with acetamide, and then reaction of (2) with thiosemicarbazide in ethanol leads to the synthesize of hydrazincarbothioamide derivative (3).The reaction of (3) with ethylchloroacetate in presence of sodium acetate leads to closure ring to get [(1-(5-oxo-2-thioxoimidazolidin-1-ylimino) ethyl)]quinolin-2(1H)-one (4). Mannich bases were prepared through the reaction of (4) with primary
... Show MoreBackground: Breast cancer is the most common cancer in Iraq and the United Kingdom. While the disease is frequently diagnosed among middleaged Iraqi women at advanced stages accounting for the second cause of cancer-related deaths, breast cancer often affects elderly British women yielding the highest survival of all registered malignancies in the UK. Objective: To compare the clinical and pathological profiles of breast cancer among Iraqi and British women; correlating age at diagnosis with the tumor characteristics, receptor-defined biomarkers and phenotype patterns. Methods: This comparative retrospective study included the clinical and pathological characteristics of (1,940) consecutive female patients who were diagnosed with invasive b
... Show MoreLung cancer is one of the most serious and prevalent diseases, causing many deaths each year. Though CT scan images are mostly used in the diagnosis of cancer, the assessment of scans is an error-prone and time-consuming task. Machine learning and AI-based models can identify and classify types of lung cancer quite accurately, which helps in the early-stage detection of lung cancer that can increase the survival rate. In this paper, Convolutional Neural Network is used to classify Adenocarcinoma, squamous cell carcinoma and normal case CT scan images from the Chest CT Scan Images Dataset using different combinations of hidden layers and parameters in CNN models. The proposed model was trained on 1000 CT Scan Images of cancerous and non-c
... Show MoreA simple low-cost approach at various exposure times was utilized to generate cold plasma in the aim to fabricate AuNPs. UV-Visible spectra and X-ray diffraction were used to characterize the nanoparticles (XRD). Surface Plasmon resonance was observed in the synthesized AuNPs at 530, 540, and 533 nm. For all samples, the patterns of XRD show very intensive peaks implying the fcc crystalline structure of AuNPs. The average crystallite size of AuNPs is ranging between 20-30 nm. The observation of morphology by FESEM revealed the spherical formation of AuNPs. Doses of 100 and 200 ppm of AuNPs were adapted to investigate their effect on the blood-mixture with and without a 20-second of cold plasma exposure. The WBC components in the blood
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