Large-Scale Knowledge Synthesis and Complex Information Retrieval from Biomedical Documents

Recent advances in the healthcare industry have led to an abundance of unstructured data, making it challenging to perform tasks such as efficient and accurate information retrieval at scale. Our work offers an all-in-one scalable solution for extracting and exploring complex information from large-scale research documents, which would otherwise be tedious. First, we briefly explain our knowledge synthesis process to extract helpful information from unstructured text data of research documents. Then, on top of the knowledge extracted from the documents, we perform complex information retrieval using three major components- Paragraph Retrieval, Triplet Retrieval from Knowledge Graphs, and Complex Question Answering (QA). These components combine lexical and semantic-based methods to retrieve paragraphs and triplets and perform faceted refinement for filtering these search results. The complexity of biomedical queries and documents necessitates using a QA system capable of handling queries more complex than factoid queries, which we evaluate qualitatively on the COVID-19 Open Research Dataset (CORD-19) to demonstrate the effectiveness and value-add

Doctor of Philosophy

dissertationNumerical simulation of the geometrically complex fractured reservoirs has been a major engineering challenge. The deficiencies of continuum models are often addressed using the discrete fracture network (DFN) models which represent the complex fracture geometry explicitly. The primary goal in this dissertation is to explore ways of applying the DFN methodology to solve a variety of multiphase problems in oil reservoir simulation. Three-dimensional, three-phase simulators using the control-volume finiteelement scheme were used. After completing validation and fracture-property sensitivity studies, the limitation of employing the often-used Oda homogenization method was shown followed by the development of a simpler geometric scheme. The important question of oil recovery from basement reservoirs (Type I) composed of fractures of various sizes was examined in detail. Oil recovery and breakthrough behavior of this system comprised of seismic and subseismic features were investigated for different oil distributions, permeability values, levels of heterogeneity and rate. In general having more oil distributed in smaller systems led to lower recovery and quicker breakthrough. Lower permeabilities in the subseismic features also led to lower recovery. The recovery at given pore volume of water injected was rate dependent in all of the scenarios explored, with the lower rate production leading to about 5% higher oil in place recovery. This phenomenon was consistent when viewed from the point of view of gravity number for each displacement. The mechanism of gravity-dominated oil recovery in two-phase applications was explored, and a "critical rate" concept for obtaining higher recoveries in gravity-dominated flow was developed A multiscale upscaling exercise was performed to match the oil recovery performance from a structured fault zone using a single feature with different sets of relative permeability curves. The effectiveness of using DFN simulations for reservoirs containing matrix and fractures (Type II) was shown using two different systems. It was shown that placing wells either in the fault zone or in the matrix can have significant impact on recovery and breakthrough behavior. It was also demonstrated that fracture networks bring apparent anisotropy, and water-flooding from one direction or the other may affect oil recovery. Fractured reservoir simulation is high-performance computing - data and file management, computation, visualization, etc. are integral components of this exercise. A workflow to facilitate creation of fracture networks, gridding and simulation, and visualization was developed. A fully integrated two-dimensional graphical user interface (java-based) was also built

Ontology based data warehousing for mining of heterogeneous and multidimensional data sources

Heterogeneous and multidimensional big-data sources are virtually prevalent in all business environments. System and data analysts are unable to fast-track and access big-data sources. A robust and versatile data warehousing system is developed, integrating domain ontologies from multidimensional data sources. For example, petroleum digital ecosystems and digital oil field solutions, derived from big-data petroleum (information) systems, are in increasing demand in multibillion dollar resource businesses worldwide. This work is recognized by Industrial Electronic Society of IEEE and appeared in more than 50 international conference proceedings and journals

Multidimensional computation and visualisation for marine controlled source electromagnetic methods

The controlled source electromagnetic method is improving the search for oil and gas in marine settings and is becoming an integral component of many exploration toolkits. While the level of detail and benefit obtained from recorded electromagnetic data sets is limited to the tools available, interpretation is fundamentally restricted by non-unique and equivalent solutions. I create the tools necessary to rapidly compute and visualise multi-dimensional electromagnetic fields generated for a variety of controlled source electromagnetic surveys. This thesis is divided into two parts: the creation of an electromagnetic software framework and the electromagnetic research applications.The creation of a new electromagnetic software framework is covered in Part I. Steps to create and test a modern electromagnetic data structure, three-dimensional visualisation and interactive graphical user interface from the ground up are presented. Bringing together several computer science disciplines ranging from parallel computing, networking and computer human interaction to three-dimensional visualisation, a package specifically tailored to marine controlled source electromagnetic compuation is formed. The electromagnetic framework is comprised of approximately 100,000 lines of new Java code and several third party libraries, which provides low-level graphical, network and execution cross-platform functionality. The software provides a generic framework to integrate most computational engines and algorithms into the coherent global electromagnetic package enabling the interactive forward modelling, inversion and visualisation of electromagnetic data.Part II is comprised of several research applications utilising the developed electromagnetic software framework. Cloud computing and streamline visualisation are covered. These topics are covered to solve several problems in modern controlled source electromagnetic methods. Large 3D electromagnetic modelling and inversion may require days or even weeks to be performed on a single-threaded personal computers. A massively parallelised electromagnetic forward modelling and inversion methods can dramatically was created to improve computational time. The developed ’macro’ parallelisation method facilitated the reduction in computational time by several orders of magnitude with relatively little additional effort and without modification of the internal electromagnetic algorithm. The air wave is a significant component of marine controlled source electromagnetic surveys however there is controversy and confusion over its defintion. The airwave has been described as a reflected, refracted, direct or diffusing wave, which has lead to confusion over its physical reality

Hydro-meteorological risk assessment methods and management by nature-based solutions

Hydro-meteorological risk (HMR) management involves a range of methods, such as monitoring of uncertain climate, planning and prevention by technical countermeasures, risk assessment, preparedness for risk by early-warnings, spreading knowledge and awareness, response and recovery. To execute HMR management by risk assessment, many models and tools, ranging from conceptual to sophisticated/numerical methods are currently in use. However, there is still a gap in systematically classifying and documenting them in the field of disaster risk management. This paper discusses various methods used for HMR assessment and its management via potential nature-based solutions (NBS), which are actually lessons learnt from nature. We focused on three hydro-meteorological hazards (HMHs), floods, droughts and heatwaves, and their management by relevant NBS. Different methodologies related to the chosen HMHs are considered with respect to exposure, vulnerability and adaptation interaction of the elements at risk. Two widely used methods for flood risk assessment are fuzzy logic (e.g. fuzzy analytic hierarchy process) and probabilistic methodology (e.g. univariate and multivariate probability distributions). Different kinds of indices have been described in the literature to define drought risk, depending upon the type of drought and the purpose of evaluation. For heatwave risk estimation, mapping of the vulnerable property and population-based on geographical information system is a widely used methodology in addition to a number of computational, mathematical and statistical methods, such as principal component analysis, extreme value theorem, functional data analysis, the Ornstein–Uhlenbeck process and meta-analysis. NBS (blue, green and hybrid infrastructures) are promoted for HMR management. For example, marshes and wetlands in place of dams for flood and drought risk reduction, and green infrastructure for urban cooling and combating heatwaves, are potential NBS. More research is needed into risk assessment and management through NBS, to enhance its wider significance for sustainable living, building adaptations and resilience

Doctor of Philosophy

dissertationThe outstanding surge in hydrocarbon production from unconventional reservoirs is unprecedented. Profitable oil prices and new technologies have untapped massive oil and gas resources in recent years. However, the correct exploitation of these resources has been dampened by the lack of understanding of these systems. Research efforts to understand and properly assess unconventional resources have exploded in the literature. In this research work, a series of advancements in reservoir production analysis, simulation modeling, and simulation development are made. A semi-analytical method based on conventional material balance was developed to approximate reservoir pressure distributions and permeability. One of the strengths of this method is that it only requires limited information to be viable. Reservoirs with dry gas and/or high gas oil ratios are handled with an additional average pressure correction factor that takes gas compressibility into account. Hence, this method can be used for any type of fluid and fluid flow as long as the correct material balance formulation and surrogate curves are employed. Verification of the method is made through comparison with synthetic data and a field case study. Furthermore, a standardized simplification workflow for hydraulically stimulated reservoirs was introduced. The aim of this workflow is to guide the engineer when developing a simplified reservoir simulation model with multiple wells and fractures. Simplified models have been around for a long time in the literature, however, their applicability to field-scale projects is very limited. Models that result from the application of this workflow are shown to retain the low simulation run-times characteristic of popular single-fracture models. In addition, fluid rate results from the proposed workflow models are in good agreement with results from full-scale simulation models. This is not the case for the single-fracture model which loses accuracy as the complexity of the project grows. Lastly, a new discrete fracture model formulation is implemented in a control-volume finite element simulator. This new fracture model provides fractures with their own control volumes and gives them freedom to be placed anywhere in the matrix domain. Verification of this implementation is made through comparison with analytical expressions and other well-established simulators

Assessment of Natural Stream Sites for Hydroelectric Dams in the Pacific Northwest Region

This pilot study presents a methodology for modeling project characteristics using a development model of a stream obstructing dam. The model is applied to all individual stream reaches in hydrologic region 17, which encompasses nearly all of Idaho, Oregon, and Washington. Project site characteristics produced by the modeling technique include: capacity potential, principal dam dimensions, number of required auxiliary dams, total extent of the constructed impoundment boundary, and the surface area of the resulting reservoir. Aggregated capacity potential values for the region are presented in capacity categories including total, that at existing dams, within federal and environmentally sensitive exclusion zones, and the balance which is consider available for greenfield development within the limits of the study. Distributions of site characteristics for small hydropower sites are presented and discussed. These sites are screened to identify candidate small hydropower sites and distributions of the site characteristics of this site population are presented and discussed. Recommendations are made for upgrading the methodology and extensions to make the results more accessible and available on a larger scale