NUMERICAL MODELING OF HYDRAULIC FRACTURING IN SHALE OIL FORMATION

Shale oil reservoir is one of the modern studies that oil and gas industries have started to concern about it. Although its permeability is very low, shale oil reservoirs can be produced by using many techniques such as hydraulic fracturing method. Since the shale oil reservoir is much complicated, it is challenging to study hydraulic fracturing in this reservoir. Among the literature review, basic theories of hydraulic fracturing technique, how the process is performed, equipment used, and some fracture geometry models, will be discussed. There are several computer software programs that have been established to help petroleum engineers and planners to model hydraulic fracturing. These programs use numerical methods to model fracture propagation through the targeted formation. The user of this model will insert the necessary input parameters to that model. Eventually, the final output of these models will be the fracture geometry which is mainly the width and length of the fracture. The aim of this study is to analyze the two dimensional models which are Perkins-Kern-Nordgen, PKN and Geertsma de-Klerk, KGD fracture propagation models to obtain the geometry of the fracture based on the rock data as well as fracture treatment data. The realization of this project will intensify the knowledge and it will help in the future researches of hydraulic fracturing for shale oil reservoir

Fast power network detection of topology change locations using PMU measurements

System monitoring and contingency analysis are crucial functions in power control centers. In order to perform these analyses, a complete model of the power network is needed. Moreover, to account for system configuration dynamics, this model must be continuously updated for the purpose of on-line analysis. Several topology processing schemes have been developed in the literature to accomplish this task. The majority of these schemes process breaker statuses to detect changes in system topology. Transformer tap positions as well as statuses of capacitor and reactor bank switches must also be included in the process. This results in a complicated topology processing scheme. In this work, a simple and quick method for on-line detection and identification of system topology changes is introduced. This method is based on representing line outages with fictitious nodal power injections. The injections are calculated using system states obtained from phasor measurement units (PMUs). This scheme can be applied on reduced systems where parts of the network are not covered by PMU measurements. The scheme was tested during different outage events in the IEEE39-bus system. The obtained results validated the algorithm’s ability to detect and identify line outage events effectively and efficiently

REGION-BASED ADAPTIVE DISTRIBUTED VIDEO CODING CODEC

The recently developed Distributed Video Coding (DVC) is typically suitable for the applications where the conventional video coding is not feasible because of its inherent high-complexity encoding. Examples include video surveillance usmg wireless/wired video sensor network and applications using mobile cameras etc. With DVC, the complexity is shifted from the encoder to the decoder. The practical application of DVC is referred to as Wyner-Ziv video coding (WZ) where an estimate of the original frame called "side information" is generated using motion compensation at the decoder. The compression is achieved by sending only that extra information that is needed to correct this estimation. An error-correcting code is used with the assumption that the estimate is a noisy version of the original frame and the rate needed is certain amount of the parity bits. The side information is assumed to have become available at the decoder through a virtual channel. Due to the limitation of compensation method, the predicted frame, or the side information, is expected to have varying degrees of success. These limitations stem from locationspecific non-stationary estimation noise. In order to avoid these, the conventional video coders, like MPEG, make use of frame partitioning to allocate optimum coder for each partition and hence achieve better rate-distortion performance. The same, however, has not been used in DVC as it increases the encoder complexity. This work proposes partitioning the considered frame into many coding units (region) where each unit is encoded differently. This partitioning is, however, done at the decoder while generating the side-information and the region map is sent over to encoder at very little rate penalty. The partitioning allows allocation of appropriate DVC coding parameters (virtual channel, rate, and quantizer) to each region. The resulting regions map is compressed by employing quadtree algorithm and communicated to the encoder via the feedback channel. The rate control in DVC is performed by channel coding techniques (turbo codes, LDPC, etc.). The performance of the channel code depends heavily on the accuracy of virtual channel model that models estimation error for each region. In this work, a turbo code has been used and an adaptive WZ DVC is designed both in transform domain and in pixel domain. The transform domain WZ video coding (TDWZ) has distinct superior performance as compared to the normal Pixel Domain Wyner-Ziv (PDWZ), since it exploits the ' spatial redundancy during the encoding. The performance evaluations show that the proposed system is superior to the existing distributed video coding solutions. Although the, proposed system requires extra bits representing the "regions map" to be transmitted, fuut still the rate gain is noticeable and it outperforms the state-of-the-art frame based DVC by 0.6-1.9 dB. The feedback channel (FC) has the role to adapt the bit rate to the changing ' statistics between the side infonmation and the frame to be encoded. In the unidirectional scenario, the encoder must perform the rate control. To correctly estimate the rate, the encoder must calculate typical side information. However, the rate cannot be exactly calculated at the encoder, instead it can only be estimated. This work also prbposes a feedback-free region-based adaptive DVC solution in pixel domain based on machine learning approach to estimate the side information. Although the performance evaluations show rate-penalty but it is acceptable considering the simplicity of the proposed algorithm. vii

Adaptive Linear System Identification over Simulated Wireless Environment

Wireless technologies have become one of the basic industrial pillars, whereas system identification represents an important tool in many practical engineering circumstances and thus sooner or later both wireless technologies and system identification should be linked together in sense of having an identifier that is able to reliably identify a system over wireless links. It is well known that wireless links are considered as unreliable medium and therefore the loss of the system observations across them is unavoidable. The system observations represent the main element in the identification process since the identifier relies only on these observations in order to identify the underlying function of the system as they are the only information available to tell about the system dynamics, for this reason vast amount of literature in the context of system identification is written about the way the excitation signal is chosen to force the system to show its dynamic and also about the way the sampling process is carried out to obtain informative observations in order to construct a satisfactory model for the system. This shows that the random loss of these observations (which are vital and core element of identification process) might deter the system modeling process. Experience shows that well sampled observations over regular intervals during observations loss could not guarantee a satisfactory model for the system. This thesis looks into the concepts of system identification and the behavior of the identifier components when placing wireless links between the system and the identifier. The thesis investigates the possibility of performing system identification over wireless network for both on-line and off-line system identification approaches. This research work studies the effects of observations loss on the performance of the learning algorithms and it focuses only on first order autoregressive with exogenous input (ARX) model structure adopted on linear network. The work looks thoroughly on three forms of instantaneous learning algorithms which are: first order algorithms (e.g. least mean square (LMS)), second order algorithms (e.g. recursive least squares (RLS)) and finally high order or sliding window (SW) algorithms (e.g. moving average (MA))

On Endogenous Growth: The Implications of Environmental Externalities

This paper uses an endogenous growth model to examine the interaction between trade, economic growth, and the environment. We find that whether trade enhances or retards growth depends on the relation between factor intensities of exportable, importable, and R&D and the relative abundance of the factor R&D uses more intensively. Depending on the intertemporal elasticity of substitution, the long-run rate of economic growth changes with environmental externalities. Concerns about the environment can explain a significant part of cross-country difference in growth rates. For the empirically reported range of the elasticity of intertemporal substitution, countries which care more about the environment grow faster. The effects of trade on the environment and welfare depend on the elasticities of supply for the two traded goods, the terms of trade effect on growth, and pollution intensities. The decentralized and Pareto optimal growth rates are, in general, different. The market growth rate is bigger than the optimal rate the larger the degree of monopoly power in the innovation sector and the stronger the effects of environmental externalities. The policy implications of this divergence are discussed. We also consider numerical exercises to broaden the insights from the analytical results and allow for incorporating pollution abatementEnvironmental Economics and Policy, F11, O31, O41, Q20,

Environment in Three Classes of Endogenous Growth Models

The implications of environmental externalities are studied within three classes of endogenous growth models viz. the linear technology models, the human capital models, and the R&D and innovation models. The long-run rate of economic growth changes when environmental extemalities are introduced; the direction of change depends on the severity of extemalities and the intertemporal elasticity of substitution. The presence of environmental externalities cause the decentralized growth rate to diverge from the efficient rate. Which rate is bigger than the other depends, among other things, on the valuation of consumption relative to environmental quality. Several policy changes to align the two paths are discussed. The models are calibrated to U.S. data.Environmental Economics and Policy, International Development,