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EVALUATION AND FIELD VERIFICATION OF STRENGTH AND STRUCTURAL IMPROVEMENT OF CHEMICALLY STABILIZED SUBGRADE SOIL (FHWA-OK-08-01 2195)
No full textOften subgrade soils exhibit properties, particularly strength and/or volume change properties that limit their performance as a support element for pavements. Typical problems include shrink-swell, settlement, collapse, erosion or simply insufficient strength. A common approach to subgrade soil support or stability problems involves chemical modification or stabilization with additives such as lime (hydrated or quick), fly ash (Class C from lignite coal), cement kiln dust (CKD) or Portland cement. Other additives are available, but this group constitutes the major products or by-products used on roadway construction in Oklahoma. The type and amount of chemical additive is dependent on the purpose or function of the treated material (i.e., improved physical properties or improved strength) and selection is based on accepted or standardized procedures. Questions then arise with regard to chemically treated subgrade soils about the rate of development and ultimate value of improvement. The purpose of this research is to develop relationships between rate of development and magnitude of strength (or physical property) improvement for chemically treated subgrade soils. The research project involved laboratory and field studies of the influence of cementitious additives on the strength and structural improvement of stabilized subgrade soils. Laboratory tests for measuring strength and structural improvement (e.g. UCS and MR) were conducted on field mixed treated soils and laboratory mixed treated and untreated soil samples. UCS and MR tests were conducted on samples varying curing time (field and laboratory mixed) and percent additive used (laboratory mixed). A series of field tests (Nuclear w-?, stiffness gauge, portable FWD, Dynamic Cone Pentrometer, and PANDA Pentrometer) were conducted at five field test sites on the untreated subgrade soils and on the treated subgrade soil with curing time as allowed by the construction schedule. The research project collected a large volume of both laboratory and field data which are summarized in the appendixes (5) to this report.Final Report October 2006-September 2008N
SERVICE-LIFE MODEL DESIGN OF UTAH FORGE ENHANCED GEOTHERMAL MULTI-STRING CASING SYSTEMS BASED ON HPHT OIL AND GAS PRACTICES
No full textGeothermal well design plays an essential role while the world tries to benefit from the 24/7 clean energy originating from the core of the Earth. FORGE EGS development at the Milford, Utah site is one of these initiatives where the subsurface temperatures can reach as high as 446℉. Although these temperatures do not necessarily impose severe steel failures as much as those observed in superhot developments, the typical well delivery cost of an EGS easily exceeds that of unconventional oil and gas wells. Ignoring that high upfront CAPEX (capital expenditure) is necessary for the EGS well completions, the arising problem is whether the casing strings of these wells will perform long with integrity or not, endangering the return on investment. Since there is no globally accepted geothermal well design standard, very careful design practices need to be adopted from the HPHT (high-pressure high-temperature) oil and gas experience to ensure the long-term well integrity and success of the EGS. This study used internationally accepted API TR 5C3 and one of the most well-known geothermal standards, NZS 2403, to perform a model geothermal well design. The information sourced from the NZS 2403 confirms that the triaxial casing design may be performed for the design of geothermal well casings. However, the design factors stated by the NZS 2403 were considered in the first step as a minimum acceptable.Since the geothermal wells have a late return on investment, it must be ensured that a quality wellbore design is achieved for long-term well integrity and production objectives. While there is no internationally agreed-upon design standard for geothermal wells, this study proposes a model design using both API TR 5C3 and NZS 2403. Typical oil and gas well designs disregard the thermal profiles where the bottomhole temperatures are small. However, more critical explorations and developments in the HPHT reservoirs mandate the usage of thermal profiles during critical operations to ensure that the designed casing strings will endure the loading. For this purpose, the actual data from the completed FORGE wells 16A and 16B were used to simulate the thermal and hydraulic profiles for drilling and completion operations. After obtaining the temperature and pressure profiles using WELLCATTM software, the load cases have been applied to the installed casing strings against their API and VME triaxial envelopes using the same software. It has been accurately checked if the installed casing strings pass the working stress design, with their strengths and weaknesses being highlighted. Throughout the design process, WellPlanTM software was used to obtain the kick tolerance and casing running results. Once the current design of the casing strings and their weaknesses have been identified, their wear tolerances and rates were identified using CasingWearTM software as the second step in the design. According to the simulation results, the intermediate casings of both wells may undergo a higher amount of wear due to the directional wellpath and critical drilling parameters. This study is also unique in a way that it differs from pre-construction well design analyses; it incorporates post-wear burst, collapse, and axial/triaxial ratings to identify the weak tubular intervals under critical load cases. In addition to the need for more elaborations on the thermal profiles, the wellhead movement and annular pressure build-up concepts are typically adopted in the HPHT wells. The good practices incorporating these aspects of HPHT well designs have been considered in this study. In the third step of the design, the results on the wellhead movement have been obtained using WELLCATTM software based on the actual and planned long-term well operations’ pressure and temperature profiles. The purpose of this step was to decide on the selection of the anchor casing. It was decided that the innermost casing of the injector wells should be chosen as the anchor casing. Along with this, it would be better if the intermediate casing of the producer wells is chosen as the anchor casing to reduce the wellhead growth. Based on casing design envelopes undergoing the simulated pressure and temperature profiles, it was identified that the surface casing strings of the FORGE Wells 16A and 16B are over-designed. These surface casings showed an over-design phenomenon even under post-wear conditions. While it is appreciated that a more conservative design was adopted, a thinner or a lower-grade casing for the surface intervals may be chosen if desired. The intermediate casing of these wells showed certain under-design conditions, especially post-wear. Based on the modifications of the applied design factors and discussions, further recommendations have been made to optimize the design, where applicable. It was identified that the production casing of the producer well 16B is also over-designed in a way that it contains a sacrificial thickness up to 18% (against API burst) to eliminate the well integrity issues for the long term, should uniform metal loss occur. Further discussions in terms of the estimated corrosion rates have been made (Appendix B), however, more detailed corrosion studies are recommended to be done for future studies. Some under-design aspects were identified for the innermost injection casing of the injector well 16A, particularly under long-term cold injection and cold shut-in conditions. This injection casing has certain weaknesses against the cyclic thermal loading and should not be allowed to heat up and cool down abruptly, and has no wear allowance
Partners and Neighbors: Reparative and Inclusive Description Projects and Partnerships at the University of Arkansas
No full textAcross the border from Oklahoma, Arkansas shares many stories, histories, and issues with our neighbors, including archival collections related to indigenous peoples, race riots, and other topics that have been represented in legacy archival description in ways that no longer meet the needs of our users or of the documented communities. In 2020, along with many other institutions, the University of Arkansas Special Collections began reparative description efforts to improve legacy finding aids, starting with professional development and education, moving onto a pilot project, and eventually establishing a commitment to ongoing work in this area. These efforts have also yielded dividends in inter-institutional collaborations, such as digital humanities projects where collections that have undergone reparative description are integrated with similar selections from other regional libraries, archives, and museums, including those that may not have had the resources to engage in reparative description work yet. Presenters will discuss the practical aspects of the work done so far, including the implementation of specific projects related to Japanese American incarceration during WWII, to enslaved persons, and to indigenous persons and nations; the development of policy frameworks; and assessment mechanisms used. We will also address adapting to the challenges of engaging in this essential work while situated in institutions or regions facing challenges to metadata justice efforts
APPLICATION OF POST-STACK SEISMIC ATTRIBUTES, WELL DYNAMIC DATA, AND MACHINE LEARNING FOR CARBONATE RESERVOIR FACIES AND PRODUCTIVITY PREDICTION FOR UPSTREAM OPTIMIZATION
No full textEven almost 20 years after the discovery of the prolific pre-salt oil province in SE Brazil offshore, seismic characterization of these complex reservoirs is still a challenging task. In the oil and gas fields, where dozens of wells are available, the seismic inversion-based workflows are proven to be the best for reservoir characterization. However, in exploratory stage areas the reduced number of wells makes seismic inversion non-viable. As a result, solely seismic amplitude-based workflows are strongly affected by ambiguity pitfalls, which delay the appraisal phase, postpone commercial production, and, thus, erode the economic value of the project. As a solution, I propose a machine learning approach that leverages the big amount of dynamic reservoir data in a known field (Mero field in Santos Basin) and easy-to-obtain post-sack 3D seismic attributes, which are common to both production and exploration areas and are available as soon as the seismic processing is done, without requiring wells for calibration like seismic inversion does. Well dynamic data, mainly drill stem tests, are the most reliable information on reservoir productivity before the commercial production and are available during the upstream phase. In this sense, my doctoral research was structured in three main projects: the first one (Chapter 2) on qualitative reservoir modelling using post-stack seismic attributes and unsupervised learning techniques. I used combinations of ten different seismic attributes (interval velocity, amplitude versus offset, complex traces, geometric and voxel-based texture) as inputs for self-organizing maps, generative topographic mapping and k-means clustering algorithms for seismic facies discrimination in the Barra Velha reservoir of the Mero field. The seismic facies models were validated using information from 13 wells which were not used for any training. The best models were obtained with self-organizing maps. The second project (Chapter 3) is on quantitative interpretation using the same attributes and drill stem test data to train supervised learning algorithms for prediction of reservoir productivity of the Barra Velha carbonates in the Mero field. I tested classic supervised learning algorithms (shallow learning) of random forest, support vector machines and K-nearest neighbors for supervised regression of flow capacity and productivity index. I also tested a deep learning algorithm (multi-layer perceptron) to compare its cost-effectiveness to the shallow learning algorithms. For the validation of my predictive models, I used information from 20 blind test wells. The best results were obtained with random forest regression of flow capacity (85% blind test performance). In the third project, I studied how transfer learning techniques can leverage the machine learning training using Mero field data to accurately predict reservoir facies and productivity in other seismic surveys 200 km distant from Mero field: the Bacalhau and Lapa fields, which have production data to validate my predictive models. Using self-organizing maps and random forest algorithms trained with Mero field data, I could accurately predict (80% average performance) the facies distribution and flow capacity values observed in the blind test wells in Bacalhau and Lapa fields. Transfer learning using Mero training proved effective for reservoir de-risking and upstream optimization even when working with multiple seismic surveys. As I used post-stack seismic attributes, well test productivity, and injectivity data from subsurface reservoirs to train our models, this approach can be used in any kind of project such as CCUS, geothermal, and hydrogen storage projects in the context of the energy transition
REGIONAL STRATIGRAPHY AND DEPOSITIONAL CHARACTERISTICS OF THE PENNSYLVANIAN PRUE SANDSTONE, LINCOLN COUNTY, OKLAHOMA
No full textThe Pennsylvanian Prue Sandstone in northeastern Oklahoma represents fluvial and deltaic deposits that formed across a gently dipping shelf margin. The Prue Sandstone is predominantly well-sorted, fine to medium-grain sandstones that are light grey to tan in color within a stratigraphic interval of sandstone and shale. To evaluate the Prue Sandstone regional stratigraphy and depositional characteristics for the 990 mi2 (1593 km2) study area of Lincoln County, Oklahoma, cross sections and subsurface maps were generated to illustrate the spatial variability of the Prue Sandstone. Raster logs from 1724 wells were used for subsurface correlation and to generate geological maps. LAS logs from 95 wells were used to generate a 3D lithology model. Two wells totaling 126 ft (38.4 m) of Prue Sandstone core spanning the selected interval were examined, along with the petrographic analysis of ten thin sections. Subsurface maps combined with well-log signatures, core descriptions, and literature review were used to further define the Prue Sandstone depositional environment, stratigraphy, and reservoir characteristics. The Prue Sandstone is bounded at the top by the Excello Shale and at the base by the Verdigris Limestone. The Excello and Verdigris are easily recognized on well-logs and form excellent stratigraphic markers given their lateral continuity. Iron Post Coal and Breezy Hill Limestone deposits are observed intermittently throughout the study area. Top and base Prue Sandstone structure maps illustrate the gradual southwesterly dip across the study area. Isopach and net sandstone maps reveal thickness trends that are oriented from northeast to southwest and are consistent with a sediment source from the northeast. In central Lincoln County, interval thickness increases toward the southeast and ranges from 20 – 160 ft (6.1 – 48.8 m) across the county. Prue net sandstone thickness ranges from 0 – 116 ft (35.4 m) and displays similar trends as the isopach. Porosity ranges from 0 – 0.24 within the main depositional trend. By incorporating core, log-signature analysis, and subsurface maps, three key environments are interpreted: fluvial channels, distributary channels, and floodplain environments. Fluvial and distributary channel fill are both characterized by well-sorted, medium to fine-grain sandstones. Using gamma-ray logs, fluvial channels were distinguished from distributaries by their blocky sandstone appearance. Distributary channel signatures displayed stacking, thinner sandstone packages, and an increased amount of interbedded shale. Interpreted floodplain deposits are predominantly shale with a non-distinct or serrated well-log signature. Lithology proportion maps indicate a central-southeastern trend of sandstone deposition with isolated pockets of coal occurring intermittently throughout the study area. Modeled sandstone trends are representative of fluvial and distributary channel-fill deposits. Channel geometry and heterogeneity affect vertical sandstone variability, while changes in the depositional environment are the primary control for spatial variability
Micro and Macro Habitability Factors Associated with Resident Well-Being in Affordable Housing
No full textThis study investigates the relationship between the habitability of affordable housing and the perceived well-being of low-income households in Oklahoma. While extensive research has explored the impact of housing on people's health, there is a significant gap in understanding how comprehensive design aspects of affordable habitability influence residents’ satisfaction and quality of life. Employing a multi-scale approach, this research analyzes habitability features at both a micro-level – unit features (e.g., typology, affordability, and tenure) and interior design parameters (e.g., spatial adequacy, design/functionality, and indoor environmental quality) – and macro-level – neighborhood characteristics (e.g., amenities and accessibility). This research also compares single-family and middle-housing options to provide affordable, satisfying, and equitable living solutions suited to each typology.Data was gathered through physical and online surveys from 215 residents with experience living in affordable housing in Oklahoma, including middle-housing residents (n = 50) and single-family home residents (n = 165). A mixed-methods approach was used, combining quantitative correlation analysis and qualitative thematic analysis. Correlation analysis revealed significant relationships between residents’ well-being and various habitability features, including unit features (single-family housing r = .562, ***p < 0.001, middle housing r = .698, ***p < 0.001), interior design parameters (single-family housing r = .764, ***p < 0.001, middle housing r = .859, ***p < 0.001) and neighborhood characteristics (single-family housing r = .599, ***p < 0.001, middle housing r = .495, ***p < 0.001). Comparison analysis revealed that unit features and interior design parameters exhibited stronger correlations with well-being among middle-housing residents than among single-family housing residents. Meanwhile, neighborhood characteristics were more relevant to the well-being of single-family home residents than those in middle housing. Additionally, thematic analysis identified key themes that enriched and contextualized the quantitative findings. This investigation offers user-oriented design strategies for designers to enhance habitability and improve the well-being of residents in affordable housing. The design recommendations emphasize residents’ satisfaction, equity perception, and quality of life while also considering aspects such as privacy, place attachment, safety, social interaction, and sense of community
Social Media Marketing: Linguistics & Technology
No full textThis dissertation, structured as three essays, explores various aspects of modern linguistics and technology with regards to social media marketing through various methods and original datasets. The first essay introduces the linguistic framework of animacy into marketing to explore how brands are perceived as “living” entities by consumers. A novel method for measuring animacy through computational linguistics is developed and demonstrated on a dataset of branded social media posts. The second essay explores the concept of brand activism through the framework of ego involvement, and how consumers engage with brands on social media. This is explored using both social media data and a survey instrument. The third essay returns to the concept of animacy, this time looking at how consumers react to AI generated content on social media. Like the second essay, this is explored through both social media data and a survey. This research aims to advance the understanding of the role linguistics play in several critically relevant areas of marketing science
Localizing Resilience: Fiscal Decentralization and Implication on Disaster Risk Reduction Outcomes in Kenya
No full textFiscal decentralization has been widely advocated as a policy reform aimed at improving public service delivery, including Disaster Risk Reduction(DRR) outcomes, by shifting fiscal decision-making powers to subnational governments. However, there is a paucity of empirical studies that provide conclusive evidence on its implications on disaster risk reduction. This dissertation empirically examines the impact of fiscal decentralization on DRR outcomes in Kenya through a mixed-methods approach, combining survey data and semi-structured interviews with officials from county and national governments, NGOs, and international organizations across five selected counties in Kenya. Specifically, this dissertation explores how revenue and expenditure assignments, citizen engagement, and intergovernmental coordination influence DRR outcomes. Additionally, it assesses the moderating role of information transparency and investigates whether urbanization acts as a facilitating or constraining factor. The regression results reveal a positive and statistically significant relationship between revenue and expenditure assignments, citizen engagement, and intergovernmental coordination with disaster risk reduction outcomes, and they are consistent with findings from previous country-specific studies. These findings have important theoretical and policy implications and provide insights into how fiscal decentralization can enhance disaster risk reduction efforts in Kenya’s fiscally decentralized governance system
A mechanistic understanding of Desulfovibrio vulgaris Hildenborough biofilm formation and the genetic requirements for survival in coculture with Clostridium acetobutylicum
No full textSulfate-reducing bacteria impact the world through the biofilms they form in environmental and industrial systems, and through the interspecies connections made with other bacteria. The biofilms formed by sulfate-reducing bacteria cost the United States alone hundreds of millions of dollars annually due to microbiologically influenced corrosion and the biofouling of petroleum fuels. The biofilms formed by sulfate-reducing bacteria and association-dependent interactions with other bacteria have also been used in the generation of clean energy, using biological batteries and the generation of hydrogen, respectively. The consequences of sulfate-reducing bacterial biofilms and interspecies associations have been previously characterized; however, the mechanisms and genetic requirements for biofilm formation and for direct intercellular connections have not been determined. Here, this work describes the role of two surface proteins from Desulfovibrio vulgaris Hildenborough in biofilm formation and surface attachment, and the genetic requirements that allow for the survival of this bacterium in cocultures with the solventogen Clostridium acetobutylicum ATCC 824. Through proteomic analyses and microscopy, this work identified the proteomic changes to biofilm composition in protein deletion mutants, and the roles of the adhesins in surface attachment and cell aggregation. Coculture studies with gene deletion mutants and transcriptomic analyses identified the importance of flagella and tryptophan biosynthesis in the survival of D. vulgaris in cocultures with C. acetobutylicum. This work furthers the understanding of biofilm adhesins of D. vulgaris, the potential function of homologous proteins in other species, and the genetic requirements for coculture survivability in obligate commensal conditions
Utilizing Auxetic Materials in Responsive Facades for Optimal Daylighting in the Office Building
No full textThe purpose of this thesis is to explore the integration of auxetic materials into responsive façades for optimizing daylighting and visual comfort in office buildings. By using their negative Poisson's ratio (NPR), auxetic structures passively adapt to solar exposure by expanding perpendicularly to applied forces, enabling dynamic shading without mechanical systems. Through parametric modeling, 36 façade configurations were generated and structurally validated using Karamba3D. Climate-based simulations (Honeybee/Ladybug) evaluated performance using three metrics: Useful Daylight Illuminance (UDI): % of time illuminance stays within 300–3000 lux (optimal range), Spatial Daylight Autonomy (sDA): % of floor area receiving ≥300 lux for ≥50% of occupied hours, and Daylight Glare Probability (DGP): % of time glare remains <0.45 (acceptable comfort). The 4×6 panel configuration at 90° actuation (Scenario 24) achieved the best balance: 79% UDI (daylight availability), 61.36% sDA (spatial coverage), and 93.71% glare comfort (6.6% improvement over the unshaded baseline). These results validate auxetic façades as a passive, energy-efficient solution that simultaneously enhances daylight sufficiency (meeting LEED standards) and visual comfort, advancing sustainable building envelope design