Paleokarst reservoirs consist of complex cave networks, which are formed by various mechanisms and associated collapsed cave facies. Traditionally, cave structures are defined using variogram-based methods in flow models and this description does not precisely represent the reservoir geology. Algorithms based on multiple-point statistics (MPS) are widely used in modeling complex geologic structures. Statistics required for these algorithms are inferred from gridded training images. However, structures like modern cave networks are represented by point data sets. Thus, it is not practical to apply rigid and gridded templates and training images for the simulation of such features. Therefore, a quantitative algorithm to characterize and model paleokarst reservoirs based on physical and geological attributes is needed. In this study, a unique non-gridded MPS analysis and pattern simulation algorithms are developed to infer statistics from modern cave networks and simulate distribution of cave structures in paleokarst reservoirs. Non-gridded MPS technique is practical by eliminating use of grids and gridding procedure, which is challenging to apply on cave network due to its complex structure. Statistics are calculated using commonly available cave networks, which are only represented by central line coordinates sampled along the accessible cave passages. Once the statistics are calibrated, a cave network is simulated by using a pattern simulation algorithm in which the simulation is conditioned to sparse data in the form of locations with cave facies or coordinates of cave structures. To get an accurate model for the spatial extent of the cave facies, an algorithm is also developed to simulate cave zone thickness while simulating the network. The proposed techniques are first implemented to represent connectivity statistics for synthetic data sets, which are used as point-set training images and are analogous to the data typically available for a cave network. Once the applicability of the algorithms is verified, non-gridded MPS analysis and pattern simulation are conducted for the Wind Cave located in South Dakota. The developed algorithms successfully characterize and model cave networks that can only be described by point sets. Subsequently, a cave network system is simulated for the Yates Field in West Texas which is a paleokarst reservoir. Well locations with cave facies and identified cave zone thickness values are used for conditioning the pattern simulation that utilizes the MP-histograms calibrated for Wind Cave. Then, the simulated cave network is implemented into flow simulation models to understand the effects of cave structures on fluid flow. Calibration of flow model against the primary production data is attempted to demonstrate that the pattern simulation algorithm yields detailed description of spatial distribution of cave facies. Moreover, impact of accurately representing network connectivity on flow responses is explored by a water injection case. Fluid flow responses are compared for models with cave networks that are constructed by non-gridded MPS and a traditional modeling workflow using sequential indicator simulation. Applications on the Yates Field show that the cave network and corresponding cave facies are successfully modeled by using the non-gridded MPS. Detailed description of cave facies in the reservoir yields accurate flow simulation results and better future predictions. / text

The effects of neutron displacement damage on materials are sensitive to neutron energy spectra. In controlled neutron damage experiments, a well characterized neutron flux spectrum is critical in determining the equivalent dose for displacement damage. Two techniques were used to characterize the neutron flux spectra in the University of Texas at Austin TRIGA research nuclear reactor. The first technique uses a standard method of measuring the reaction rates of two identical metal foils, one of which was irradiated in a Cd cover, the other of which was irradiated bare. Assuming an analytic form of the neutron spectrum the reaction rates were used to determine an approximate spectrum. The second technique uses the reaction rates measured from a set of activated metal foils along with two spectral unfolding techniques to approximate and then refine the neutron spectrum. A Matlab code was developed which fits radiative capture reaction rates to an approximate spectrum using a least squares approach. The result was used as an initial guess in a second Matlab code which refines the epithermal and fast energy ranges of the spectrum using reaction rates from threshold reactions. Errors in the reaction rates calculated from the resulting spectrum to the measured reaction rates were used to assess the accuracy of the final neutron spectrum. / text

This work focuses on device design and process integration of high-performance Ge-based devices for CMOS applications and beyond. Here we addressed several key challenges towards Ge-based devices, such as, poor passivation, underperformance of nMOSFETs, and incompatibility of fragile Ge wafers for mass production. We simultaneously addressed the issues of bulk Ge and passivation for pMOSFETs, by fabricating Si-capped epitaxial Ge:C(C<0.5%) devices. Carbon improves the crystalline quality of the channel, while Si capping prevents GeOx formation, creates a quantum well for holes and thus improves mobility. Temperature-dependent characterization of these devices suggests that Si cap thickness needs to be optimized to ensure highest mobility. We developed a simple approach to grow GeO₂ by rapid thermal oxidation, which provides improved passivation, especially for nMOSFETs. The MOSCAPs with GeO₂ passivation show ~10× lower Dit (~8×10¹¹ cm⁻²eV⁻¹) than that of the HF-last devices. The Ge (111) nMOSFETs with GeO₂ passivation show ~2× enhancement in mobility (~715 cm²V⁻¹s⁻¹ at peak) and ~1.6× enhancement in drive current over control Si (100) devices. For improved n⁺/p junctions, we proposed a simple technique of rapid thermal diffusion from "spin-on-dopants" to avoid implantation damage during junction formation. These junctions show a high ION/IOFF ratio (~10⁵⁻⁶) and an ideality factor of ~1.03, indicating a low defect density, whereas, ion-implanted junctions show higher Ioff (by ~1-2 orders) and a larger ideality factor (~1.45). Diffusion-doped and GeO₂-passivated Ge(100) nMOSFETs show a high ION/IOFF ratio (~10⁴⁻⁵) , a low SS (111 mV/decade), and a high [mu]eff (679 cm²V⁻¹s⁻¹ at peak). Moreover, diffusion-doped Ge (111) nMOSFETs show even higher [mu]eff (970 cm²V⁻¹s⁻¹ at peak) that surpasses the universal Si mobility at low Eeff. For Beyond CMOS devices, we investigated Mn-doped Ge:C-on-Si (100), a novel Si-compatible ferromagnetic semiconductor. The investigation suggests that the magnetic properties of these films depend strongly on crystalline structure and Mn concentration. On a different approach, we developed LaOx/SiOx barrier for Spin-diodes that reduces contact resistance by ~10⁴, compared to Al₂O₃ controls and hence is more conducive for spin injection. These ferromagnetic materials and devices can potentially be useful for novel spintronic devices. / text

This dissertation presents a series of studies relating to kinetics and kinematics of inter-layer dielectric and metal chemical mechanical planarization processes. These are also evaluated with the purposes of minimizing environmental and cost of ownership impact.The first study is performed to obtain the real-time substrate temperature during the polishing process and is specifically intended to understand the temperature distribution across the polishing wafer during the chemical mechanical planarization process. Later, this technique is implemented to study the effect of slurry injection position for optimum slurry usage. It is known that the performance of chemical mechanical planarization depends significantly on the polishing pad and the kinematics involved in the process. Variations in pad material and pad grooving type as well as pressure and sliding velocity can affect polishing performance. One study in this dissertation investigates thermoset and thermoplastic pad materials with different grooving methods and patterns. The study is conducted on multiple pressure and sliding velocity variations to understand the characteristic of each pad. The analysis method elaborated in this study can be applied generically.A subsequent study focuses in a slurry characterization technique. Slurry, a critical component in chemical mechanical planarization, is typically a water-based dispersion of fine abrasive particles with various additives to control material removal rate and microscratches. Simultaneous turbidity and low angle light scattering methods under well-defined mixing conditions are shown to quantify the stability of abrasive particle from aggregations. Further contribution of this dissertation involves studies related to the spectral analysis of raw shear force and down force data obtained during chemical mechanical planarization. These studies implemented Fast Fourier Transforms to convert force data from time to frequency domain. A study is performed to detect the presence of larger, defect-causing particles during polishing. In a further application on diamond disc conditioning work is performed to achieve optimum break-in time and an optimum conditioning duty cycle. Studies on spectral analysis are also extended to planarization of shallow trench isolation pattern wafers to monitor the polishing progress in real-time.

This work details an investigation into the production of porous shape memory alloys (SMAs) via hot isostatic press (HIP) from prealloyed powders. HIPing is one of three main methods for producing porous SMAs, the other two are conventional sintering and selfpropagating hightemperature synthesis (SHS). Conventional sintering is characterized by its long processing time at near atmospheric pressure and samples made this way are limited in porosity range. The SHS method consists of preloading a chamber with elemental powders and then initiating an explosion at one end, which then propagates through the material in a very short time. HIPing provides a compromise between the two methods, requiring approximately 5 hours per cycle while operating in a very controlled environment. The HIPing method gives fine control of both temperature and pressure during the run which allows for the production of samples with varying porosity as well as for finetuning of the process for other characteristics. By starting with prealloyed powder, this study seeks to avoid the drawbacks while retaining the benefits of HIPing with elemental powders. In an extension of previous work with elemental powders, this study will apply the HIP method to a compact of prealloyed powders. It is hoped that the use of these powders will limit the formation of alternate phases as well as reducing oxidation formed during preparation. In addition, the nearspherical shape of the powders will encourage an even pore distribution. Processing techniques will be presented as well as a detailed investigation of the thermal and mechanical properties of the resulting material.

Meren field, located offshore Niger Delta, is one of the most prolific oil-producing fields in the Niger Delta. The upper Miocene D-07, D-08 and E-01 oil sands comprise a series of stacked hydrocarbon reservoirs in Block 2 of Meren field. These reservoir sandstones were deposited in offshore to upper shoreface environments. Seven depositional facies were identified in the studied interval, each with distinct lithology, sedimentary structures, trace fossils, and wire-line log character. The dominant lithofacies are (1) locally calcite-cemented highly-bioturbated, fine-grained sandstones, (middle to lower shoreface facies); (2) cross-bedded, fine- to medium-grained well-sorted sandstones (upper shoreface facies); (3) horizontal to sub-horizontal laminated, very-fine- to fine-grained sandstone (delta front facies); (4) massive very-fine- to fine-grained poorly-sorted sandstone (delta front facies); (5) muddy silt- to fine-grained wavy-bedded sandstone (lower shoreface facies); (6) very-fine- to fine-grained sandy mudstone (lower shoreface facies); and (7) massive, silty shales (offshore marine facies). Lithofacies have distinct mean petrophysical properties, although there is overlap in the range of values. The highest quality reservoir deposits are cross-bedded sands that were deposited in high-energy upper shoreface environments. Calcite cements in lower shoreface facies significantly reduce porosity and permeability. Integration of core and wire-line log data allowed porosity and permeability to be empirically determined from bulk density. The derived equation indicated that bulk density values could predict 80% of the variance in core porosity and permeability values. Three parasequence sets were interpreted, including one lower progradational and two upper retrogradational parasequence sets. The progradational parasequence set consists of upward-coarsening delta front to upper shoreface facies, whereas the upward-fining retrogradational parasequence sets are composed of middle to lower shoreface deposits overlain by offshore marine shales. The limited amount of core data and the relatively small area of investigation place serious constraints on stratigraphic interpretations. Two possible sequence stratigraphic interpretations are presented. The first interpretation suggests the deposits comprise a highstand systems tract overlain by a transgressive systems tract. A lowstand systems tract is restricted to an incised valley fill at the southeastern end of the study area. The alternate interpretation suggests the deposits comprise a falling stage systems tract overlain by transgressive systems tract.

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In this work, we present a new method for seismic waveform characterization, which is aimed at extracting detailed litho-stratigraphical information from seismic data. We attempt to estimate the lithological attributes from seismic data according to our parametric representation of stratigraphical horizons, where the parameter values provide us with a direct link to nature of lithological transitions. We test our method on a seismic dataset with a strong diagenetic transition (opal-A to opal-CT transition). Given some information from cutting samples of well, we use a percolation-based model to construct the elastic profile of lithological transitions. Our goal is to match parametric representation for the diagenetic transition in both real data and synthetic data given by these elastic profiles. This match may be interpreted as a well-seismic tie, which reveals lithological information about stratigraphical horizons.

Modern storage systems are complex. Simple direct-attached storage devices are giving way to storage systems that are flexible, network-attached, consolidated and virtualized. Today, storage systems have their own administrators, who use specialized tools and expertise to configure and manage storage resources. As a result, database administrators are no longer in direct control of the design and configuration of their database systems' underlying storage resources. This introduces problems because database physical design and storage configuration are closely related tasks, and the separation makes it more difficult to achieve a good end-to-end design. For instance, the performance of a database system depends strongly on the storage layout of database objects, such as tables and indexes, and the separation makes it hard to design a storage layout that is tuned to the I/O workload generated by the database system. In this thesis we address this problem and attempt to close the information gap between database and storage tiers by addressing the problem of predicting the storage (I/O) workload that will be generated by a database management system. Specifically, we show how to translate a database workload description, together with a database physical design, into a characterization of the I/O workload that will result. Such a characterization can directly be used by a storage configuration tool and thus enables effective end-to-end design and configuration spanning both the database and storage tiers. We then introduce our storage layout optimization tool, which leverages such workload characterizations to generate an optimized layout for a given set of database objects. We formulate the layout problem as a non-linear programming (NLP) problem and use the I/O characterization as input to an NLP solver. We have incorporated our I/O estimation technique into the PostgreSQL database management system and our layout optimization technique into a database layout advisor. We present an empirical assessment of the cost of both tools as well as the efficacy and accuracy of their results.

A modern approach to the treatment of localized disease involves the use of advanced polymeric or ceramic implant materials for controlled-rate drug delivery. These implants are dynamic systems that maintain drug concentrations within the optimal therapeutic window via complex hydration, swelling, and degradation processes. To optimize the performance of these materials, however, requires a fundamental understanding of the mechanisms that govern drug release. Magnetic resonance imaging (MRI) provides a means of non-invasively characterizing the microstructure and transport properties in this type of material, and has proven to be an invaluable tool for their advancement. Calcium polyphosphate (CPP) is a biomaterial that has shown promise as a degradable matrix for drug delivery and bone defect repair. Release rates are potentially governed by hydrogelation, swelling, and polymer chain scission. CPP bioceramics have previously been studied using models for drug elution, but these tend to be simplistic and unable to explain the many interrelated mechanisms. Structural analysis techniques have also been applied, but these tend to be inherently destructive and unable to characterize the material in situ. With the aim of characterizing degradation/drug release mechanisms, a non-invasive approach based on MRI was developed and optimized for imaging two existing types of CPP device. Techniques included mapping of the T1 and T2 relaxation times and the apparent diffusion coefficient (ADC), which together provide sensitivity to local fluid transport parameters. The non-destructive nature of MRI permitted longitudinal observation, and structural degradation effects were investigated by correlation with concurrent drug elution measurements. Temporal variation in the release mechanisms was treated by analyzing elution in stages. Large variation between samples was found, but on average, drug elution that was controlled by a structural-relaxation mechanism appeared correlated with the gradual formation of a highly-mobile ``free'' water component within the disk. Other characteristics, such as swelling rate, did not appear to correlate with drug release at all. While the data did not implicate a singular, governing scheme for drug release from CPP bioceramics, the approach did yield an assessment of the relative importance of the various contributing mechanisms.