• Alkali-surfactant-polymer (ASP) flooding - potential and simulation for Alaskan North Slope reservoir

      Ghorpade, Tejas S. (2014-09)
      Enhanced oil recovery (EOR) is essential to recover bypassed oil and improve recovery factor. Alkaline-surfactant-polymer (ASP) flooding is a chemical EOR method that can be used to recover heavy oil containing organic acids from sandstone formations. It involves injection of alkali to generate in situ surfactants, improve sweep efficiency, and reduce interfacial tension (IFT) between displacing and displaced phase, and injection of a polymer to improve mobility ratio; typically, it is followed by extended waterflooding. The concentration of alkali, surfactant, and polymer used in the process depends on oil type, salinity of solution, pressure, temperature of the reservoir, and injection water quality. This project evaluates the effect of waterflooding on recovery, calculates the recovery factor for ASP flooding, and optimum concentration of alkali, surfactant, and polymer for an Alaskan reservoir. Also, the effects of waterflooding and improvement with ASP flooding are evaluated and compared. Studies of these effects on oil recovery were analyzed with a Computer Modeling Group (CMG)-generated model for the Alaskan North Slope (ANS) reservoir. Based on a literature review and screening criteria, the Western North Slope (WNS) 1 reservoir was selected for the ASP process. A CMG - WinProp simulator was used to create a fluid model and regression was carried out with the help of actual field data. The CMG - WinProp model was prepared with a 5 spot well injection pattern using the CMG STARS simulator. Simulation runs conducted for primary and waterflooding processes showed that the recovery factor increased from 3% due to primary recovery to 45% due to waterflooding at 500 psi drawdown for 60 years with a constant producing gas oil ratio (GOR). ASP flooding was conducted to increase recovery further, and optimum ASP parameters were calculated for maximum recovery. Also, effect of alkali, surfactant and polymer on recovery was observed and compared with ASP flood. If proved effective, the use of ASP chemicals for ANS reservoirs to increase the recovery factor could replace current miscible gas injection with chemical EOR. It will help to develop chemical flooding processes for heavier crude oil produced in harsh environments and create new horizons for chemical industries in Alaska.
    • Alternative project delivery in rural Alaska: experiences, quality and claims

      Monta, Katrina L.; Pehrson, Gerald S.; Cryer, Matthew N. (2015-12)
      The popularity of alternative project delivery systems has expanded beyond the private sector and into the public sector. Alaska embodies unique challenges that may present obstacles while using alternative project delivery systems. This analysis will provide an understanding of alternative project delivery systems in Alaska and how local experiences, quality and claims are affected. Alaska's unique characteristics present both challenges and opportunities for implementing alternative project delivery systems. This report begins with a discussion of experiences from several rural Alaska projects, and how alternative project delivery systems can be utilized. Some impacts that alternative project delivery systems have on quality are then presented, including a perspective on quality and recommendations for achieving customer satisfaction. A treatment of construction claims is then provided, followed by conclusions and recommendations for stakeholders in selecting an appropriate project delivery system. Alternative project delivery systems were researched by means of scholarly literature reviews, professional interviews and seminars. The report of these findings is intended to provide owners and contractors with a concise presentation of the challenges and advantages for using alternative project delivery systems in Alaska.
    • Analysis and evaluation of fragment size distributions in rock blasting at the Erdenet Mine

      Dondov, Erdenebaatar; Дондов, Эрдэнэбаатар; Chen, Gang; Ghosh, Tathagata; Ganguli, Rajive (2015-08)
      Rock blasting is one of the most important operations in mining. It significantly affects the subsequent comminution processes and, therefore, is critical to successful mining productions. In this study, for the evaluation of the blasting performance at the Erdenet Mine, we analyzed rock fragment size distributions with the digital image processing method. The uniformities of rock fragments and the mean fragment sizes were determined and applied in the Kuz-Ram model. Statistical prediction models were also developed based on the field measured parameters. The results were compared with the Kuz-Ram model predictions and the digital image processing measurements. A total of twenty-eight images from eleven blasting patterns were processed, and rock size distributions were determined by Split-Desktop program in this study. Based on the rock mass and explosive properties and the blasting parameters, the rock fragment size distributions were also determined with the Kuz-Ram model and compared with the measurements by digital image processing. Furthermore, in order to improve the prediction of rock fragment size distributions at the mine, regression analyses were conducted and statistical models w ere developed for the estimation of the uniformity and characteristic size. The results indicated that there were discrepancies between the digital image measurements and those estimated by the Kuz-Ram model. The uniformity indices of image processing measurements varied from 0.76 to 1.90, while those estimate by the Kuz-Ram model were from 1.07 to 1.13. The mean fragment size of the Kuz-Ram model prediction was 97.59% greater than the mean fragment size of the image processing. The multivariate nonlinear regression analyses conducted in this study indicated that rock uniaxial compressive strength and elastic modulus, explosive energy input in the blasting, bench height to burden ratio and blast area per hole were significant predictor variables in determining the fragment characteristic size and the uniformity index. The regression models developed based on the above predictor variables showed much closer agreement with the measurements.
    • Analysis of cation-treated clay microstructure using zeta potential and x-ray diffraction

      Guo, Rui; Darrow, Margaret .; Metz, Paul A.; Trainor, Thomas P. (2018-12)
      Unfrozen water within cation-treated, fine-grained frozen soils is a key element in cold regions engineering, and is heavily influenced by the surface charge of the soil's clay component. This study investigated the effects of the surface charge of cation-treated clay soils by measuring the zeta potential as a function of temperature, and measuring changes in the micro-structure of frozen cation-treated clays using the x-ray diffraction (XRD) method. I tested five treatments (untreated, and Ca²⁺, Mg²⁺, Na⁺, and K⁺ treatments) of six soils (montmorillonite, kaolinite, illite, illite-smectite, chlorite, and Copper River soil). The zeta potential demonstrated a negative relationship with temperature change for both above-freezing and sub-freezing conditions (-1 to 20 °C). Temperature had a greater effect on the monovalent-treated soils that contain smectite minerals, which included montmorillonite, illite-smectite, and the Copper River soil. Monovalent cation-treated soils demonstrated large negative trends and more negative zeta potential, whereas divalent cation-treated soils demonstrated less negative trends that were less dependent on temperature. The cation treatment will affect the Debye-length, also affecting the zeta potential and arrangement of clay particles. More negative zeta potential (i.e., soil dominated by monovalent cations) will lead to a dispersed structure, whereas less negative zeta potential (i.e., soil dominated by divalent cations) will lead to a flocculated structure. XRD research indicated that the montmorillonite samples demonstrated decreased dspacing compared with the International Center for Diffraction Data (ICDD) standard. The K⁺- treated montmorillonite, untreated montmorillonite, and untreated illite-smectite samples demonstrated donut-shaped pole figure results, which may indicate that the results are an artifact of sample preparation rather than a reflection of the cation effects on the structure of the clay. Improved could be made in sample preparation to eliminate ice lens formation during freezing, which may improve the success with the XRD method. Scanning electron microscopy (SEM) should be used to observe the frozen clays, especially montmorillonite, illite-smectite, and the Copper River soil, as it may reveal the internal geometry of voids and the possible relationship between ice and the clay structure, increasing our understanding of the clay structure at the microaggregate scale.
    • Analysis of ground source heat pumps in sub-Arctic conditions

      Bishop, Stephen; Peterson, Rorik; Daanen, Ronald; Shur, Yuri (2014-05)
      The Purpose of this project is to investigate the factors involved in the application of a ground source heat pump in subarctic conditions. This project originated with the construction of a ground source heat pump (GSHP) built at Cold Climate Housing Research Center's (CCHRC) Research Testing Facility. The GSHP built by CCHRC is an experiment to test the viability of a GSHP with different surface coverings. Specifically, this project will focus on different soil and atmospheric properties to gauge their effect on a GSHP in sub-arctic conditions. The project is primarily broken into 3 main sections which test in simulation: the effects of soil and atmospheric properties on heat flow into soil, the effects of these properties on a hypothetical GSHP and applying this to a simulation of CCHRC's GSHP. Additionally, some mitigation efforts were attem pted in simulation to improve the viability of the GSHP built by CCHRC.
    • Analysis of IPR curves in North Slope horizontal producers supported by waterflood and water alternating gas EOR processes

      Abel, Alan; Awoleke, Obadare; Zhang, Yin; Dandekar, Abhijit (2019-05)
      The shape and behavior of IPR curves in waterflooded reservoirs has not previously been defined despite their common use for optimization activities in such systems. This work begins to define the behavior of IPR curves in both water flood and water‐alternating‐gas EOR systems using a fine scale model of the Alpine A‐sand. The behavior of IPRs is extended to 3 additional reservoir systems with differing mobility ratios. Traditionally derived (Vogel, Fetkovich) IPR curves are found to be poor representations of well performance and are shown to lead to non‐optimal gas lift allocations in compression limited production networks. Additionally, the seemingly trivial solution to gas lift optimization in an unconstrained system is shown to be more complex than simply minimizing the bottom hole pressure of the producing well; maximized economic value is achieved at FBHPs greater than zero psi.
    • Analysis of steel-reinforced concrete-filled steel tube columns (CFT) under axial compression and moment

      Li, Fei (2015)
      This study presents an investigation into the behavior of steel-reinforced concrete filled steel tubular columns (CFT) using the finite element software ABAQUS. The steel tube provides lateral confinement to the concrete core which results in an increased concrete compressive strength and deformation capacity. The concrete infill, in return, prevents the inward local buckling within steel tubes. The axial load bearing capacity of CFT is thus higher than the summation of axial load-bearing capacities of the concrete core and the hollow steel tube. The axial force P and moment M interaction diagram is generated.
    • Applied machine learning using twitter sentiment and time series data for stock market forecasting

      McKenna, Jacob; Hartman, Chris; Genetti, Jon; Metzgar, Jonathan (2020-05)
      This paper presents an approach to determine stock prices using Twitter sentiment. Due to the highly stochastic nature of the stock market, it is difficult to determine a model that accurately predicts prices. In Twitter Mood Predicts the Stock Market by Bollen, capturing tweets and classifying each tweet’s mood was useful in predicting the Dow Industrial Jones Average (DJIA). Accurately predicting a movement quantitatively is profitable. We present a method that captures sentiment from Twitter with mentions of specific companies to predict their price for the following day.
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