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Increasing confidence in full field modelling and water flood planning for a giant reservoir under primary depletion through Material Balance modelling
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Abstract<p>One of the principle inputs to project economics and all business decisions is a realistic production forecast and a practical and achievable development plan (i.e. waterflood). Particularly this becomes challenging in supergiant oil fields with medium to low lateral connectivity. The main objectives of the Production Forecast and feasibility study for water injection are:</p><p>1- Provide an overview of the total expected production profile, expected wells potential/spare capacity, water breakthrough timing and water cut development over time</p><p>2- Highlight the requirements to maintain performance, suggest the optimum development pattern</p><p>3- Increasing confidence in business decisions to develop the reservoir in question</p><p>The main tool used for these purposes is a sophisticated reservoir simulation software, namely CMG©, since it can predict reservoir behavior, honor physical constraints and capture the heterogeneity within the reservoir to accurately predict performance. However, the starting point for this kind of complicated studies needs to start from the basics, in order to understand the big picture and be able to plan properly for the scope to be delivered, hence, utilizing analytical tools like MBAL becomes quite necessary, if not crucial, to the success of full field modelling and choosing an optimum water flood pattern and design.</p><p>This paper covers the methodology for building the reservoir component utilizing a Material Balance model, of which the results will be used as an input to reservoir simulation to evaluate and accurately predict reservoir performance, which directly feeds into planning for water flooding projects and selection of an optimum flood pattern.</p><p>A Tank model was built at first to assess and understand the driving forces (energies) of the reservoir in question, utilizing pressure and production data from legacy wells, the prepared model is also supported by geological and petro physical studies to give representative results. Acquired Static Bottom Hole Pressures (SBHPs) in wells were used as anchor points for the tank pressure and to test the validity of the history match. Multiple analytical methods to QC the results and STOIIP volume were conducted, e.g. the Havlena-Odeh method.</p><p>This methodology has been tested successfully in the stated super giant oil field, in which the reservoir in question is a carbonate rock formation. An example of this is covered in the paper. It was concluded that utilizing a history matched and coherent MBAL model before conducting a detailed reservoir simulation study can save a lot of time and effort by providing guidance to the path which needs to be followed, and sheds light on the critical elements to be looked after. This has also helped to uncover the driving mechanisms and energies in the reservoir, hence allowing the engineer to plan for the necessary voidage replacement and water injection rates to sustain the reservoir pressure and pattern development. Another technical advantage of the described method is the higher sustainability of the model.</p><p>The suggested method, in combination with geological and petro physical information available, can be applied to majority of the reservoirs. This combination is paramount to ensure optimum time and planning that is followed for each reservoir development study that involves water flooding.</p>
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Energy Aware Scheme for Underwater Wireless Sensor Networks
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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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Publication Date
Sun Jun 12 2011
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Baghdad Science Journal
Java Applet Technology for Design Interference Optical Coating
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Java is a high-level , third generation programming language were introduced Javaoptics Open Source Physics (OSP) as a new simulation for design one of the most important interference optical coating called antireflection coating. It is recent developments in deign thin-film coatings. (OSP) shows multiple beam interferences from a parallel dielectric thin film and the evolution of reflection factors. It is simple to use and efficiently also can serve educational purposes. The obtained results have been compared with needle method

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Tue Mar 30 2021
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Computations for the special linear group (2, 49)
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An Efficient Method for Real Gas Pseudopressure Calculation
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Advanced Machine Learning Models for Banana Sweetness Classification
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It takes a lot of time to classify the banana slices by sweetness level using traditional methods. By assessing the quality of fruits more focus is placed on its sweetness as well as the color since they affect the taste. The reason for sorting banana slices by their sweetness is to estimate the ripeness of bananas using the sweetness and color values of the slices. This classifying system assists in establishing the degree of ripeness of bananas needed for processing and consumption. The purpose of this article is to compare the efficiency of the SVM-linear, SVM-polynomial, and LDA classification of the sweetness of banana slices by their LRV level. The result of the experiment showed that the highest accuracy of 96.66% was achieved by the

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Background: During Ramadan, Muslims fast throughout daylight hours. There is a direct link between fasting and increasing incidence of infections. Antibiotic usage for treatment of infections should be based on accurate diagnosis, with the correct dose and dosing regimen for the shortest period to avoid bacterial resistance. This study aimed to evaluate the practices of physicians in prescribing suitable antibiotics for fasting patients and the compliance of the patients in using such antibiotics at regular intervals. Materials and methods: An observational study was carried out during the middle 10 days of Ramadan 2014 in two pharmacies at Baghdad. A total of 34 prescriptions (Rx) for adults who suffered from infections were examined. For

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Publication Date
Sun Oct 29 2023
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Journal Of Al-qadisiyah For Computer Science And Mathematics
Optimization Techniques for Human Multi-Biometric Recognition System
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Researchers are increasingly using multimodal biometrics to strengthen the security of biometric applications. In this study, a strong multimodal human identification model was developed to address the growing problem of spoofing attacks in biometric security systems. Through the use of metaheuristic optimization methods, such as the Genetic Algorithm(GA), Ant Colony Optimization(ACO), and Particle Swarm Optimization (PSO) for feature selection, this unique model incorporates three biometric modalities: face, iris, and fingerprint. Image pre-processing, feature extraction, critical image feature selection, and multibiometric recognition are the four main steps in the workflow of the system. To determine its performance, the model wa

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Mon Mar 08 2021
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Shield Calculation Design for gamma-ray sterilzer plant
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The present calculation covers the building shield during irradiation process and under water storage of three milion curries Cobalt-60 radiation source the calculation results in design requirement of 8m depth of water in the source stoeage pool

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Publication Date
Thu Jun 16 2022
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Periodicals Of Engineering And Natural Sciences (pen)
Optimization algorithms for transportation problems with stochastic demand
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The purpose of this paper is to solve the stochastic demand for the unbalanced transport problem using heuristic algorithms to obtain the optimum solution, by minimizing the costs of transporting the gasoline product for the Oil Products Distribution Company of the Iraqi Ministry of Oil. The most important conclusions that were reached are the results prove the possibility of solving the random transportation problem when the demand is uncertain by the stochastic programming model. The most obvious finding to emerge from this work is that the genetic algorithm was able to address the problems of unbalanced transport, And the possibility of applying the model approved by the oil products distribution company in the Iraqi Ministry of Oil to m

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