Pore network modelling of wettability effects on waterflood oil recovery from Agbada sandstone formation in the Niger Delta, Nigeria

A thesis Submitted to the School of Chemical and Metallurgical Engineering, Faculty of Engineering and the Built Environment, University of the Witwatersrand, Johannesburg, in fulfillment of the requirements for the degree of Doctor of Philosophy Johannesburg, 2016Wettability of a porous reservoir rock is an important factor that affects oil recovery during waterflooding. It is recognized as being important for multiphase properties. Understanding the variation of these properties in the field, due to wettability trends and different pore structures, is very critical for designing efficient and reliable processes and projects for enhanced hydrocarbon recovery. After primary drainage the reservoir wettability changes: if it was oil-wet initially, it gradually changes to water-wet during waterflooding. This change in reservoir wettability towards water-wet will reduce the residual oil saturation and improve the oil displacement efficiency. However, knowledge of the constitutive relationship between the pore scale descriptors of transport in the porous system is required to adequately describe wettability trend and its impact on oil recovery, particularly during waterflooding. In this work, the petrophysical properties that define fluid flow in the Agbada, Nigeria sandstone reservoir were determined using conventional experimental and x-ray CT scanning methods. Experimentally measured average porosity is 0.28, average permeability is 1699 mD, while the initial and irreducible water saturation is 0.22. Permeability in the x, y and z directions, ranging from 50 to 200 mD, were calculated from the pore network extracted from the Agbada sandstone rock. Results obtained from the Amott-Harvey wettability measurement method indicate that the reservoir is strongly water-wet, with Amott-Harvey index of about 0.9. The cross-over between the water and oil relative permeabilities occurred at saturations of the samples above 0.5, giving an indication of strong water-wetness. The work summarizes the mechanism of wettability alteration and characterizes the performance of the reservoir during waterflooding from injecting water, and relates the residual oil saturation, relative permeability and volumes of water injected to wettability and its effects on oil recovery. Waterflood oil recovery is computed using the Buckley-Leverett method based on the reservoir rock and fluid properties. Computed waterflood oil recovery using this method was about 60% of the oil initially in place. Plots of spontaneous imbibition rate show that the injection rate for optimal oil recovery is 40 bbls of injected water per day. At this rate, both the mobility and shock front mobility ratios are less than 1, leading to a stable flood front and absence of viscous fingering. Waterflooding is by far the most widely applied method of improved oil recovery over the years with good results in conventional and unconventional (tight oil) reservoirs It is relatively simple and cost effective: abundance and availability of water. Waterflood oil recovery factor is affected by internal and external factors. The placement of the injection and production wells, for example, impacts on the effectiveness of the waterflooding process. I considered the placement of the wells in a five-spot pattern as elements of an unbounded double periodic array of wells and assumed the reservoir to be homogeneous, infinite and isotropic, with constant porosity and permeability. Both fluids are treated as having slight but constant compressibility and their flow governed by Darcy’s law. The average pressure in the reservoir satisfies quasi-static flow or diffusion equation. I then assumed piston-like displacement of oil by injected water that takes account of viscosity diffence between both fluids and proposed a model based on the theory of elliptic functions, in particular Weierstrass p-functions functions. Oil-water contact movement, dimensionless time for water breakthrough at the production well, areal sweep and average reservoir pressures were modeled. The model was tested using Wolfram Mathematica 10 software and the results are promising. The thesis has therefore established that the Agbada sandstone reservoir is strongly water-wet and that waterflooding is a viable option for enhanced oil recovery from the reservoir.MT201

Pegmatite productive terrains in the Variscan Granite hosts from Northern and Central Portugal

The detection of suboutcropping pegmatite deposits in regions recognizably fertile regarding the occurrence of pegmatites depends upon the optimization of conceptual models which support the interpretation of the regional distribution of pegmatites and the structure of their assemblies. In intra-granitic context is at concern the more conventional cartographic expression of pegmatites in connection with the structuring of granitic cupolas. The establishment of occurrence situations linked to certain lithological units or structural alignments is a pathway for the delimitation of productive research areas. Some productivity situations deduced from geological mapping include: accommodation in preferred structural directions, proximity to mixing-mingling corridors, certain petrographic structuring units that reflect irregularities in terms of flow and fractionation processes, and trends of hydrothermal and supergene alteration of host granitic masses. The detection of these aspects, to regard as exploration guides, can avail itself of remote sensing, as they represent contrasting chromatic lithotypes with sufficient surface continuity.(undefined

The Internet of Everything

In the era before IoT, the world wide web, internet, web 2.0 and social media made people’s lives comfortable by providing web services and enabling access personal data irrespective of their location. Further, to save time and improve efficiency, there is a need for machine to machine communication, automation, smart computing and ubiquitous access to personal devices. This need gave birth to the phenomenon of Internet of Things (IoT) and further to the concept of Internet of Everything (IoE)

Novel Approaches to the Representation and Analysis of 3D Segmented Anatomical Districts

Nowadays, image processing and 3D shape analysis are an integral part of clinical practice and have the potentiality to support clinicians with advanced analysis and visualization techniques. Both approaches provide visual and quantitative information to medical practitioners, even if from different points of view. Indeed, shape analysis is aimed at studying the morphology of anatomical structures, while image processing is focused more on the tissue or functional information provided by the pixels/voxels intensities levels. Despite the progress obtained by research in both fields, a junction between these two complementary worlds is missing. When working with 3D models analyzing shape features, the information of the volume surrounding the structure is lost, since a segmentation process is needed to obtain the 3D shape model; however, the 3D nature of the anatomical structure is represented explicitly. With volume images, instead, the tissue information related to the imaged volume is the core of the analysis, while the shape and morphology of the structure are just implicitly represented, thus not clear enough. The aim of this Thesis work is the integration of these two approaches in order to increase the amount of information available for physicians, allowing a more accurate analysis of each patient. An augmented visualization tool able to provide information on both the anatomical structure shape and the surrounding volume through a hybrid representation, could reduce the gap between the two approaches and provide a more complete anatomical rendering of the subject. To this end, given a segmented anatomical district, we propose a novel mapping of volumetric data onto the segmented surface. The grey-levels of the image voxels are mapped through a volume-surface correspondence map, which defines a grey-level texture on the segmented surface. The resulting texture mapping is coherent to the local morphology of the segmented anatomical structure and provides an enhanced visual representation of the anatomical district. The integration of volume-based and surface-based information in a unique 3D representation also supports the identification and characterization of morphological landmarks and pathology evaluations. The main research contributions of the Ph.D. activities and Thesis are: \u2022 the development of a novel integration algorithm that combines surface-based (segmented 3D anatomical structure meshes) and volume-based (MRI volumes) information. The integration supports different criteria for the grey-levels mapping onto the segmented surface; \u2022 the development of methodological approaches for using the grey-levels mapping together with morphological analysis. The final goal is to solve problems in real clinical tasks, such as the identification of (patient-specific) ligament insertion sites on bones from segmented MR images, the characterization of the local morphology of bones/tissues, the early diagnosis, classification, and monitoring of muscle-skeletal pathologies; \u2022 the analysis of segmentation procedures, with a focus on the tissue classification process, in order to reduce operator dependency and to overcome the absence of a real gold standard for the evaluation of automatic segmentations; \u2022 the evaluation and comparison of (unsupervised) segmentation methods, finalized to define a novel segmentation method for low-field MR images, and for the local correction/improvement of a given segmentation. The proposed method is simple but effectively integrates information derived from medical image analysis and 3D shape analysis. Moreover, the algorithm is general enough to be applied to different anatomical districts independently of the segmentation method, imaging techniques (such as CT), or image resolution. The volume information can be integrated easily in different shape analysis applications, taking into consideration not only the morphology of the input shape but also the real context in which it is inserted, to solve clinical tasks. The results obtained by this combined analysis have been evaluated through statistical analysis

Security techniques for sensor systems and the Internet of Things

Sensor systems are becoming pervasive in many domains, and are recently being generalized by the Internet of Things (IoT). This wide deployment, however, presents significant security issues. We develop security techniques for sensor systems and IoT, addressing all security management phases. Prior to deployment, the nodes need to be hardened. We develop nesCheck, a novel approach that combines static analysis and dynamic checking to efficiently enforce memory safety on TinyOS applications. As security guarantees come at a cost, determining which resources to protect becomes important. Our solution, OptAll, leverages game-theoretic techniques to determine the optimal allocation of security resources in IoT networks, taking into account fixed and variable costs, criticality of different portions of the network, and risk metrics related to a specified security goal. Monitoring IoT devices and sensors during operation is necessary to detect incidents. We design Kalis, a knowledge-driven intrusion detection technique for IoT that does not target a single protocol or application, and adapts the detection strategy to the network features. As the scale of IoT makes the devices good targets for botnets, we design Heimdall, a whitelist-based anomaly detection technique for detecting and protecting against IoT-based denial of service attacks. Once our monitoring tools detect an attack, determining its actual cause is crucial to an effective reaction. We design a fine-grained analysis tool for sensor networks that leverages resident packet parameters to determine whether a packet loss attack is node- or link-related and, in the second case, locate the attack source. Moreover, we design a statistical model for determining optimal system thresholds by exploiting packet parameters variances. With our techniques\u27 diagnosis information, we develop Kinesis, a security incident response system for sensor networks designed to recover from attacks without significant interruption, dynamically selecting response actions while being lightweight in communication and energy overhead

Multi Agent Systems

Research on multi-agent systems is enlarging our future technical capabilities as humans and as an intelligent society. During recent years many effective applications have been implemented and are part of our daily life. These applications have agent-based models and methods as an important ingredient. Markets, finance world, robotics, medical technology, social negotiation, video games, big-data science, etc. are some of the branches where the knowledge gained through multi-agent simulations is necessary and where new software engineering tools are continuously created and tested in order to reach an effective technology transfer to impact our lives. This book brings together researchers working in several fields that cover the techniques, the challenges and the applications of multi-agent systems in a wide variety of aspects related to learning algorithms for different devices such as vehicles, robots and drones, computational optimization to reach a more efficient energy distribution in power grids and the use of social networks and decision strategies applied to the smart learning and education environments in emergent countries. We hope that this book can be useful and become a guide or reference to an audience interested in the developments and applications of multi-agent systems

Three-dimensional modeling of natural heterogeneous objects

En la medicina y otros campos relacionados cuando se va a estudiar un objeto natural, se toman imágenes de tomografía computarizada a través de varios cortes paralelos. Estos cortes se apilan en datos de volumen y se reconstruyen en modelos computacionales con el fin de estudiar la estructura de dicho objeto. Para construir con éxito modelos tridimensionales es importante la identificación y extracción precisa de todas las regiones que comprenden el objeto heterogéneo natural. Sin embargo, la construcción de modelos tridimensionales por medio del computador a partir de imágenes médicas sigue siendo un problema difícil y plantea dos problemas relacionados con las inexactitudes que surgen de, y son inherentes al proceso de adquisición de datos. El primer problema es la aparición de artefactos que distorsionan el límite entre las regiones. Este es un problema común en la generación de mallas a partir de imágenes médicas, también conocido como efecto de escalón. El segundo problema es la extracción de mallas suaves 3D que se ajustan a los límites de las región que conforman los objetos heterogéneos naturales descritos en las imágenes médicas. Para resolver estos problemas, se propone el método CAREM y el método RAM. El énfasis de esta investigación está puesto en la exactitud y fidelidad a la forma de las regiones necesaria en las aplicaciones biomédicas. Todas las regiones representadas de forma implícita que componen el objeto heterogéneo natural se utilizan para generar mallas adaptadas a los requisitos de los métodos de elementos finitos a través de un enfoque de modelado de ingeniería reversa, por lo tanto, estas regiones se consideran como un todo en lugar de piezas aisladas ensambladas.In medicine and other related fields when a natural object is going to be studied, computed tomography images are taken through several parallel slices. These slices are then stacked in volume data and reconstructed into 3D computer models. In order to successfully build 3D computer models of natural heterogeneous objects, accurate identification and extraction of all regions comprising the natural heterogeneous object is important. However, building 3D computer models of natural heterogeneous objects from medical images is still a challenging problem, and poses two issues related to the inaccuracies which arise from and are inherent to the data acquisition process. The first issue is the appearance of aliasing artifacts in the boundary between regions, a common issue in mesh generation from medical images, also known as stair-stepped artifacts. The second issue is the extraction of smooth 3D multi-region meshes that conform to the region boundaries of natural heterogeneous objects described in the medical images. To solve these issues, the CAREM method and the RAM method are proposed. The emphasis of this research is placed on accuracy and shape fidelity needed for biomedical applications. All implicitly represented regions composing the natural heterogeneous object are used to generate meshes adapted to the requirements of finite element methods through a reverse engineering modeling approach, thus these regions are considered as whole rather than loosely assembled parts.Doctor en IngenieríaDoctorad

The Internet of Everything

In the era before IoT, the world wide web, internet, web 2.0 and social media made people’s lives comfortable by providing web services and enabling access personal data irrespective of their location. Further, to save time and improve efficiency, there is a need for machine to machine communication, automation, smart computing and ubiquitous access to personal devices. This need gave birth to the phenomenon of Internet of Things (IoT) and further to the concept of Internet of Everything (IoE)