Relative permeability upscaling for heterogeneous reservoir models

Detailed geological models usually contain multi-million grid cells, which makes the running of reservoir simulation difficult and time consuming. Therefore, reducing the number of grid cells, and in turn averaging reservoir properties within them, is desirable in order to make running simulations more feasible. Averaging reservoir properties within the coarse cells is usually referred to as upscaling, which can be achieved using different methods. Many upscaling techniques have been introduced in the literature. However, developing a practical and robust upscaling method has been a research topic for a long time. In this thesis, some of the upscaling methods, their application and limitations are presented. Special attention is given to two phase upscaling methods as they are within the scope of this project. Afterwards, a new two phase upscaling method, called Transmissibility Weighted Relative permeabilities (TWR), is proposed to upscale relative permeability curves in heterogeneous reservoirs. Also, a new method to generate well pseudos is introduced as a means of adjusting well results. The TWR method and the well pseudos were tested using synthetic 2D and 3D water flood models for different conditions in order to check the method’s performance. The results showed that the upscaled relative permeability curves (pseudo functions) succeeded in compensating for sub-grid heterogeneity and numerical dispersion so that the coarse models reproduced the fine models results. In order to make the use of the pseudo functions feasible in practice, a new method to group them, based on curve fitting of Chierici (1984) functional models, was introduced. Calculations of the TWR pseudos and the well pseudos were performed by writing C++ codes to do so. The grouping of the pseudos was accomplished using a non-linear regression solver

SOME ENVIRONMENTEAL FACTORS AFFECTING BROILER HOUSING IN WINTER SEASON

The main objective of this study was to study some environmental factors affecting broiler housing in winter season. The results showed that, temperature fluctuations between house ceiling and floor ranged between 0.4 to 5.93 ºC during the first two days of age. The average house temperature reduced gradually from 29.7 to 21.3 ºC. The indoor relative humidity ranged between 43.6 to 74.3 %. Specific heating power, specific fuel consumption and heating energy requirements ranged between 3850.2 W/ºC , 0.34 kg /h. ºC and 308.9 kJ/h. kg at the first week of age to 6213.4 W/ºC , 0.36 kg /h. ºC and 19.3 kJ/h. kg at the end of the life respectivel

Detection of Lying Electrical Vehicles in Charging Coordination Application Using Deep Learning

The simultaneous charging of many electric vehicles (EVs) stresses the distribution system and may cause grid instability in severe cases. The best way to avoid this problem is by charging coordination. The idea is that the EVs should report data (such as state-of-charge (SoC) of the battery) to run a mechanism to prioritize the charging requests and select the EVs that should charge during this time slot and defer other requests to future time slots. However, EVs may lie and send false data to receive high charging priority illegally. In this paper, we first study this attack to evaluate the gains of the lying EVs and how their behavior impacts the honest EVs and the performance of charging coordination mechanism. Our evaluations indicate that lying EVs have a greater chance to get charged comparing to honest EVs and they degrade the performance of the charging coordination mechanism. Then, an anomaly based detector that is using deep neural networks (DNN) is devised to identify the lying EVs. To do that, we first create an honest dataset for charging coordination application using real driving traces and information revealed by EV manufacturers, and then we also propose a number of attacks to create malicious data. We trained and evaluated two models, which are the multi-layer perceptron (MLP) and the gated recurrent unit (GRU) using this dataset and the GRU detector gives better results. Our evaluations indicate that our detector can detect lying EVs with high accuracy and low false positive rate

Microwave assisted synthesis of 2-amino-6-methoxy-4H-benzo[h]chromene derivatives

A convenient and efficient method using microwave assisted synthesis of 4H-benzo[h]chromenes (7 and 8), by the reaction of 4-methoxy-1-naphthol (1) with a mixture of aromatic aldehydes (2) and malononitrile (3) or ethyl cyanoacetate (5) and also, by the reaction of 4-methoxy-1-naphthol (1) with α-cyanocinnamonitriles (4) or ethyl α-cyanocinnamates (6) in ethanolic piperidine solution was examined. Structures of the newly synthesized compounds were established on the basis of spectral data, IR, 1H NMR, 13C NMR, 13C NMR-DEPT and MS data

Evaluation and implementation of an auto-encoder for compression of satellite images in the ScOSA project

The thesis evaluates the efficiency of various autoencoder neural networks for image compression regarding satellite imagery. The results highlight the evaluation and implementation of autoencoder architectures and the procedures required to deploy neural networks to reliable embedded devices. The developed autoencoders evaluated, targeting a ZYNQ 7020 FPGA (Field Programmable Gate Array) and a ZU7EV FPGA

Evaluation and implementation of an auto-encoder for compression of satellite images in the ScOSA project

The thesis evaluates the efficiency of various autoencoder neural networks for image compression regarding satellite imagery. The results highlight the evaluation and implementation of autoencoder architectures and the procedures required to deploy neural networks to reliable embedded devices. The developed autoencoders evaluated, targeting a ZYNQ 7020 FPGA (Field Programmable Gate Array) and a ZU7EV FPGA

Studies with aza-heterocyclic N-oxides: Synthesis of some new aromatic N-oxide derivatives

Benzofuroxan derivative (1a) reacts with the cyanoacetanilides (2a-d) to give the benzimidazole derivatives (3a-d). Benzofuroxan (1b) reacts with rhodanine derivatives (4a,b) in presence of sodium ethoxide to give the arylaminobenzoimidazole derivatives (6a,b); while the last reaction afforded the thiazolidinone derivatives (8a,b) and the o-benzoquinone dioxime derivatives (9a,b) when it was repeated in the presence of sodium acetate. Moreover, a series of quinoxalinyl 1,4-di-N-oxide derivatives were prepared starting from quinoxalin-1,4-di-N-oxide derivatives (10a-c). Plausible mechanisms to account for the formation of the products are discussed

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