The map of permeability distribution in the reservoirs is considered one of the most essential steps of the geologic model building due to its governing the fluid flow through the reservoir which makes it the most influential parameter on the history matching than other parameters. For that, it is the most petrophysical properties that are tuned during the history matching. Unfortunately, the prediction of the relationship between static petrophysics (porosity) and dynamic petrophysics (permeability) from conventional wells logs has a sophisticated problem to solve by conventional statistical methods for heterogeneous formations. For that, this paper examines the ability and performance of the artificial intelligence method in permeability prediction and compared its results with the flow zone indicator methods for a carbonate heterogeneous Iraqi formation. The methodology of the research can be Summarized by permeability was estimated by using two methods: Flow zone indicator and Artificial intelligence, two reservoir models are built, where the difference between them is in permeability method estimation, and the simulation run will be conducted on both of the models, and the permeability estimation methods will be examined by comparing their effect on the model history matching. The results showed that the model with permeability predicted by using artificial intelligence matched the observed data for different reservoir responses more accurately than the model with permeability predicted by the flow zone indicator method. That conclusion is represented by good matching between observed data and simulated results for all reservoir responses such for the artificial intelligence model than the flow zone indicator model.
The study (Quality in the Industrial Products Designs and its Reflection on Achieving Competitive Advantage) focused on developing the products in a way that satisfies human desires through the impact of technology on products design systems and performance enhancement. The study question is: how to effectively achieve quality in industrial products designs that influences competitiveness? The aim of the research is to show the design contexts for the product and its reflection on competitiveness. The study is limited to (LG) products in 2017-2018. The results and conclusions reached at by the researcher are included in the study.
The sample models adopted contexts, forms and relational relations transcending traditional contex
In this paper, the concept of normalized duality mapping has introduced in real convex modular spaces. Then, some of its properties have shown which allow dealing with results related to the concept of uniformly smooth convex real modular spaces. For multivalued mappings defined on these spaces, the convergence of a two-step type iterative sequence to a fixed point is proved
Contents IJPAM: Volume 116, No. 3 (2017)
Arthropod-borne infections, known as vector-borne diseases, are a significant threat to both humans and animals. These diseases are transmitted to humans and animals through the bites of infected arthropods. In the last half century, there have been a number of unexpected viral outbreaks in Middle Eastern countries. Recently, Iraq has witnessed an outbreak of the Crimean-Congo Hemorrhagic Fever virus with high morbidity and mortality rates in humans. However, very little is known about the prevalence and distribution of CCHFV in Iraq, and therefore, it is impossible to quantify the risk of infection. CCHFV is transmitted to humans through the bite of infected ticks. However, transmission can also occur through contact with the blood or ti
... Show MoreLet h is Γ−(λ,δ) – derivation on prime Γ−near-ring G and K be a nonzero semi-group ideal of G and δ(K) = K, then the purpose of this paper is to prove the following :- (a) If λ is onto on G, λ(K) = K, λ(0) = 0 and h acts like Γ−hom. or acts like anti–Γ−hom. on K, then h(K) = {0}.(b) If h + h is an additive on K, then (G, +) is abelian.
One of the most common metabolic illnesses in the world is diabetes mellitus. This metabolic disease is responsible for a large percentage of the burden of kidney damage and dysfunction. The goal of this study was to look into the renal function of diabetic patients using metformin monotherapy who came to Mosul's Al-Wafaa diabetes care and research facility. During the period 1 January 2021 to 30 April 2021, 47 patients with T2DM (age 50.48 7.74 years) were enrolled in this case-control study. These patients' results were compared to a control group of 47 seemingly healthy people (age 45.89 9.06 years). All participants' demographic and medical histories were acquired through the delivery of a questionnaire. Blood samples were collected
... Show MoreIn the current worldwide health crisis produced by coronavirus disease (COVID-19), researchers and medical specialists began looking for new ways to tackle the epidemic. According to recent studies, Machine Learning (ML) has been effectively deployed in the health sector. Medical imaging sources (radiography and computed tomography) have aided in the development of artificial intelligence(AI) strategies to tackle the coronavirus outbreak. As a result, a classical machine learning approach for coronavirus detection from Computerized Tomography (CT) images was developed. In this study, the convolutional neural network (CNN) model for feature extraction and support vector machine (SVM) for the classification of axial
... Show MoreIn this paper, a new class of non-convex functions called semi strongly (
Strengthening of the existing structures is an important task that civil engineers continuously face. Compression members, especially columns, being the most important members of any structure, are the most important members to strengthen if the need ever arise. The method of strengthening compression members by direct wrapping by Carbon Fiber Reinforced Polymer (CFRP) was adopted in this research. Since the concrete material is a heterogeneous and complex in behavior, thus, the behavior of the confined compression members subjected to uniaxial stress is investigated by finite element (FE) models created using Abaqus CAE 2017 software. The aim of this research is to study experimentally and numerically, the beha
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