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Submitted by Fernanda Rodrigues de Lima (fernanda.rlima@ufpe.br) on 2018-10-05T22:32:21Z No. of bitstreams: 2 license_rdf: 811 bytes, checksum: e39d27027a6cc9cb039ad269a5db8e34 (MD5) DISSERTAÇÃO Luiz Hamilton Roberto da Silva.pdf: 3143342 bytes, checksum: 6d46e7ef9675c038bf4955aafdad3f5d (MD5) / Approved for entry into archive by Alice Araujo (alice.caraujo@ufpe.br) on 2018-11-14T21:49:58Z (GMT) No. of bitstreams: 2 license_rdf: 811 bytes, checksum: e39d27027a6cc9cb039ad269a5db8e34 (MD5) DISSERTAÇÃO Luiz Hamilton Roberto da Silva.pdf: 3143342 bytes, checksum: 6d46e7ef9675c038bf4955aafdad3f5d (MD5) / Made available in DSpace on 2018-11-14T21:49:58Z (GMT). No. of bitstreams: 2 license_rdf: 811 bytes, checksum: e39d27027a6cc9cb039ad269a5db8e34 (MD5) DISSERTAÇÃO Luiz Hamilton Roberto da Silva.pdf: 3143342 bytes, checksum: 6d46e7ef9675c038bf4955aafdad3f5d (MD5) Previous issue date: 2017-07-14 / SETEC / A análise do registro de eventos – conhecido como logs – em equipamentos e sistemas computacionais é útil para a identificação de atacantes, para delinear o modo de ataque e, também, para identificar quais são as falhas que foram exploradas. Há alguns trabalhos e pesquisas que demonstram a vantagem para uma política de segurança da informação em manter os logs de comunicação em redes e sistemas computacionais, focando nas trilhas para auditoria, que é um conjunto de ações onde se inclui: a coleta, o armazenamento e o tratamento dos logs de equipamentos, de aplicações e de sistemas operacionais, dentro de um sistema de computação. A auditoria de eventos atua na coleta de elementos que possam individualizar comportamentos perigosos de usuários, internos ou externos, ou eventos de sistema que possam vir a comprometer o uso aceitável dos recursos computacionais ou a quebra da tríade da segurança da informação: a confidencialidade, a integridade e a disponibilidade. Percebe-se que, dentro do modelo de política de segurança adotado nos centros de operação (datacenters) dos Institutos Federais de Educação, em sua imensa maioria, não utilizam o recurso de servidor de logs, ou tão somente atêm-se ao registro de eventos em seus sistemas e hosts, de forma individual e, sem o contexto da centralização e do tratamento dos registros dos eventos. A coleta dos logs, na modalidade loghost centralizado guarda, em um único repositório, os registros de eventos de diversos sistemas, equipamentos e serviços de rede, o que possibilitará uma análise do montante de logs adquiridos e a possibilidade de gerar trilhas de comportamento de usuários, além de permitir o cruzamento de informações conexas à autenticação de usuários. O recurso que permite a comunicação entre as aplicações, os sistemas operacionais e os equipamentos de rede, informando os eventos a serem registrados é o protocolo Syslog (system log), que é um padrão criado pela IETF para a transmissão de mensagens de log em redes IP. O objetivo maior deste trabalho é estabelecer um modelo para a análise e auditoria de logs, com o fim de identificar ações de usuários em uma rede com servidor de autenticação, aplicando a extração de informações úteis para o Gerenciamento da Segurança, elemento este levado a execução via o uso de scripts no formato PS1 (Windows PowerShell), atuando sobre os arquivos de logs dos Eventos de Segurança (Security.evtx) e gerando relatórios dos eventos relativos ao serviço de autenticação (Active Directory). Ressaltando que as funções implementadas pelos scripts não são disponibilizadas nativamente pelos sistemas Windows e, que o ferramental desenvolvido é de grande valor às atividades diárias do Administrador de Redes, concluindo-se que esta pesquisa apresenta um modelo de análise de logs para auditoria de registro de eventos. / The analysis of the events log - known as logs - in equipment and computer systems, is useful for the attackers’ identification, to delineate the attack way and also to identify which faults have been exploited. There are some papers and researches that demonstrate the advantage of an information security policy in maintaining communication logs in networks and computer systems, focusing on the audit trails, which is a set of actions, which includes: collection, storage and the treatment of equipment logs, applications, operating systems, within a computer system. The audit of events, acts in the collection of elements that can individualize users dangerous behaviors, internal or external, or system events that may compromise the acceptable use of computing resources or the breakdown of the triad of information security: confidentiality, integrity and availability. It´s noticed that, in the security policy model, adopted in the operation centers (datacenters) at the Federal Institutes of Education, in their vast majority, they do not use the log server resource, or only they attend the record of events, in their systems and hosts, individually and without the context of centralization and processing of event logs. The collection of logs, in the host-based mode, stores in a single repository, the event logs of various systems, equipment and network services, which will allow an analysis of the amount of logs acquired, the possibility of generating user behavior trails and, the crossing of information related to user authentication. The resource for communication between applications, operating systems and network equipment, informing the events to be registered is the Syslog protocol (system log), it’s a standard created by the IETF, for the transmission of log messages in IP networks. The main goal of this work is to establish a model for the analysis and audit of logs, in order to identify actions of users in a network with authentication server, applying the extraction of useful information to the Security Management, element this led to execution through the use of scripts in the PS1 (Windows PowerShell) format, by acting on the Security Event log files (Security.evtx) and generating reports of events related to the authentication service (Active Directory). Note that the functions implemented by the scripts are not made available natively by Windows systems, and that the tooling developed is of great value to the daily activities of the Network Manager, and it is concluded that this research presents a log analysis model for event log audit.

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Predicting rock permeability from well logs in uncored wells is an important task in reservoir characterization. Due to the high costs of coring and laboratory analysis, typically cores are acquired in only a few wells. Since most wells are logged, the common practice is to estimate permeability from logs using correlation equations developed from limited core data. Most commonly, permeability is estimated from various well logs using statistical regression. For sandstones, often the logs of permeability can be correlated with porosity, but in carbonates the porosity permeability relationship tends to be much more complex and erratic. For this reason permeability prediction is a critical aspect of reservoir characterization in complex reservoirs such as carbonate reservoirs. In order to improve the permeability estimation in these reservoirs, several statistical regression techniques have already been tested in previous work to correlate permeability with different well logs. It has been shown that statistical regression for data correlation is quite promising in predicting complex reservoirs. But using all the possible well logs to predict permeability is not appropriate because the possibility of spurious correlation increases if you use more well logs. In statistics, variable selection is used to remove unnecessary independent variables and give a better prediction. So we apply variable selection to the permeability prediction procedures in order to further improve permeability estimation. We present three approaches to further improve reservoir permeability prediction based on well logs via data correlation and variable selection in this research. The first is a combination of stepwise algorithm with ACE technique. The second approach is the application of tree regression and cross-validation. The third is multivariate adaptive regression splines. Three methods are tested and compared at two complex carbonate reservoirs in west Texas: Salt Creek Field Unit (SCFU) and North Robertson Unit (NRU). The result of SCFU shows that permeability prediction is improved by applying variable selection to non-parametric regression ACE while tree regression is unable to predict permeability because it can not preserve the continuity of permeability. In NRU, none of these three methods can predict permeability accurately. This is due to the high complexity of NRU reservoir and measurement accuracy. In this reservoir, high permeability is discrete from low permeability, which makes prediction even more difficult. Permeability predictions based on well logs in complex carbonate reservoirs can be further improved by selecting appropriate well logs for data correlation. In comparing the relative predictive performance of the three regression methods, the stepwise with ACE method appears to outperform the other two methods.

Identification of a user’s actions while browsing the Internet is mostly achieved by instrumentation of the user’s browser or by obtaining server logs. In both cases this requires installation of software on multiple clients and/or servers in order to obtain sufficient data. However, by using network traffic, access to user generated traffic from multiple clients to multiple servers is possible. In this project a proxy server is used for recording network traffic and a user-action identification algorithm is proposed. The proposed algorithm includes various policies of analyzing network traffic in order to identify user actions. This project also presents an evaluation framework for the proposed policies, based on which the tradeoff of the various policies is revealed. Proxy servers are widely deployed by numerous organizations and often used for web mining, so with the work of this project user action recognition can be a new tool when considering web traffic evaluation.

Research has demonstrated the need for both teachers and students to find appropriate types of feedback for meaning-level (content) issues for English as a second langauge (ESL) writing (Kepner, 1991). The current study examines the use of a content revision log (where students monitor their revisions in such content issues as organization, paragraph development and use of topic sentences). Adding to the effect of applying the content revision log, the effect of holding conferences was also examined in the hope that referencing the content revision log during a conference session would bring the most positive results. There were three types of treatment, and the subjects included 3 teachers and 79 students. All of the student subjects' pre- and post- tests, the recorded numbers of content-based needed revisions on the content revision log, and both students and teachers' answers on an attitudes assessment survey were examined. The study found a significant effect on overall writing improvement for the combination of the content revision log and conference feedback compared to the use of the content revision log itself which in turn was better than the results found for the control group. The log + conference group demonstrated the greatest improvement for both types of data: the degree of progress between the pre- and post- tests and the decreasing rates of revision marks on the content revision log. In addition, the log + conferences group had greater numbers of more treatable content issue categories, followed by the log group, lastly the control group. Finally, the results of surveys reflect most students and teachers' preference toward the use of the log or conferences.

Identifying the location of sunken logs is a task of considerable interest in today?s world economy. The main motive of this work is to find and locate sunken cypress logs that were lost during the transit to a lumber mills. Underwater logging is possible because of the fact that many of the logs were barely affected by the decades of submersion. Cypress logs, the types of logs used in this research have a natural resistant to rotting. The other probability for the logs not being affected significantly, even staying in water for decades, is the high density of the growth rings. The quality of these sunken logs is far superior because of their high density in growth rings and they have a high economic value compared to present day logs. Sidescan sonar is proposed for the work of locating the sunken logs. Based on various research and studies, which involve several similar projects, sidescan sonar is proposed to locate and identify these sunken targets. These images that resemble a cylinder in some aspects can then be compared with a template for pattern matching. Any image size that is not matched with the acceptable size can be rejected. Using this template matching procedure, the size of the object is matched and the logs can be located and recovered. Based on various technical papers and studies involving similar projects, conclusions were drawn and future work has been suggested.

Multi-component induction resistivity and sonic measurements acquired in high-angle wells can be strongly influenced by shoulder-bed effects, anisotropy resulting from sand-shale laminations, and presence of mud-filtrate invasion. Understanding the corresponding biasing effects aids in the interpretation of resistivity and sonic measurements and subsequently leads to more accurate and reliable formation evaluation. This dissertation describes numerical simulation studies examining the effects on multi-component induction and sonic measurements in a variety of complex formation models. Subsequently, a joint inversion scheme is presented that combines resistivity and sonic measurements to estimate in situ petrophysical and elastic properties in the presence of mud-filtrate invasion. To facilitate the simulation study of multi-component induction logs, I develop a new finite-difference algorithm for the numerical simulation of frequency-domain electromagnetic borehole measurements. The algorithm~uses a coupled scalar-vector potential formulation for arbitrary three-dimensional inhomogeneous and electrically anisotropic media. Simulations show that shoulder-bed anisotropy: enhances shoulder-bed effects across sand layers; and impacts invasion sensitivities to significantly alter the assessment of invasion in terms of invaded- and virgin-zone resistivities, radial length, and front shape. For the simulation study of sonic logs, I develop a three-dimensional, finite-difference time-domain algorithm that models elastic wave propagation in a fluid-filled borehole. Simulations show that presence of anisotropy not only alters the degree of dispersion observed in flexural and Stoneley waves, but also alters their responses to invasion. In addition, presence of a dipping shoulder bed can significantly distort flexural dispersion, making it difficult to identify the low frequency asymptote corresponding to formation shear wave velocity. Lastly, I consider a radial one-dimensional model in the development of a joint resistivity and sonic inversion algorithm. This scheme simultaneously inverts array-induction apparent conductivities and sonic flexural and Stoneley dispersions for the rock's elastic moduli and water saturation in the presence of mud-filtrate invasion. Inversions are performed on numerically simulated data for a variety of models reflecting soft and hard rock formations with presence of water- and oil-based mud-filtrate invasion. Results show the estimated invasion profiles display excellent agreement with the true models, and the elastic moduli are estimated to within a few percent of the true values. / text

Borehole imaging is one of the fastest and most precise methods for collecting subsurface data that provides high resolution information on layering, texture and dips, permitting a core-like description of the subsurface. Although the range of information recoverable from this technology is widely acknowledged, image logs are still used in a strictly qualitative manner. Interpreting image logs manually is cumbersome, time consuming and is subjective based on the experience of the interpreter. This thesis outlines new methods that automate image log interpretation and extract subsurface lithofacies information in a quantitative manner. We developed two methodologies based on advanced image analysis techniques successfully employed in remote sensing and medical imaging. The first one is a pixelbased pattern recognition technique applying textural analysis to quantify image textural properties. These properties together with standard logs and core-derived lithofacies information are used to train a back propagation Neural Network. In principle the trained and tested Neural Network is applicable for automated borehole image interpretation from similar geological settings. However, this pixel-based approach fails to make use explicitly of the spatial characteristics of a high resolution image. TAT second methodology is introduced which groups identical neighbouring pixels into objects. The resultant spectrally and spatially consistent objects are then related to geologically meaningful groups such as lithofacies by employing fuzzy classifiers. This method showed better results and is applied to outcrop photos, core photos and image logs, including a ‘difficult’ data set from a deviated well. The latter image log did not distinguish some of the conductive and resistive regions, as observed from standard logs and core photos. This is overcome by marking bed boundaries using standard logs. Bed orientations were estimated using an automated sinusoid fitting algorithm within a formal uncertainty framework in order to distinguish dipping beds and horizontal stratification. Integration of these derived logs in the methodology yields a complete automated lithofacies identification, even from the difficult dataset. The results were validated through the interpretation of cored intervals by a geologist. This is a supervised classification method which incorporates the expertise of one or several geologists, and hence includes human logic, reasoning, and current knowledge of the field heterogeneity. By including multiple geologists in the training, the results become less dependent on each individual’s subjectivity and prior experience. The method is also easily adaptable to other geological settings. In addition, it is applicable to several kinds of borehole images, for example wireline electrical borehole wall images, core photographs, and logging-while-drilling (LWD) images. Thus, the theme of this dissertation is the development of methodologies which makes image log interpretation simpler, faster, less subjective, and efficient such that it can be applied to large quantities of data.

Redwood (Sequoia sempervirens (D. Don) Endl.) has been identified as a species with considerable potential for plantation forestry in New Zealand. Investment decisions in high value alternate species must be based on accurate wood quality and value predictions. There is an opportunity to extend non-destructive evaluation tools available to redwood growers, and to present the outputs of the growth model by log products and sawn timber. A redwood pruned buttlog sawing simulator has been developed however the simulator had not been tested with real data. Twelve redwood trees from Mangatu estate were selected for a sawing study; these logs were reconstructed and run through the sawing simulator. Computerised log processing was used to produce simulated pruned log sawing outturn from the redwood Buttlog Sawing Simulator, and results were compared to real results from a sawing study. The objective of the study was therefore to determine how well the simulator matched volume and grade out-turn from twelve logs. This study found the many inconsistencies between simulated data and real data; particularly related to log size. While this study was unsuccessful in validation of the redwood sawing simulator, it provides initial insight into the simulators strengths and short comings.