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Browsing by Author "McWhorter, David, committee member"

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    Direct measurement of LNAPL flow in porous media using tracer dilution techniques
    (Colorado State University. Libraries, 2004) Taylor, Geoffrey Ryan, author; Sale, Thomas, advisor; McWhorter, David, committee member; Warner, James, committee member
    Petroleum liquids, commonly referred to as LNAPL's, have become a basic building block of modem society. Used as fuels, lubricants, solvents and chemical feed stocks, petroleum liquids have brought many conveniences to our lives. However, a small fraction of these liquids have been inadvertently released into the subsurface forming contiguous bodies of separate phase liquids. Resolving how to manage these releases hinges largely on the rate at which these bodies are moving. To that end, a number of techniques have been developed in an effort to measure the migration, or flow rate, of LNAPL in the subsurface. Many of the current methods require challenging and costly indirect measurements to estimate this migration. The purpose of this thesis is to explore a promising new method that directly measures the flow rate of LNAPL's, a method that builds on the tracer dilution technique used to measure the flow of groundwater. Traditional tracer dilution techniques measures the dilution of a tracer, placed into a well, to determine the flow rate of water through the well. The flow rate through the well is then used to calculate the flow rate of groundwater. The same theory applies to LNAPL's flowing through a well. Determining the potential of the tracer dilution technique to measure LNAPL flow through a well requires investigating the mathematics governing the tracer dilution technique. A first order dilution equation was adapted for LNAPL. A method to analyze the results in a dimensionless format was also developed because it provides a technique to determine when the data conforms to the assumptions of the dilution equation. The mathematics necessary to convert the flow rate of LNAPL through a well into common measures is also derived. Laboratory studies were conducted to verify the mathematics and to determine the applicability of the tracer dilution technique to measure LNAPL flow. At first, small scale experiments were used to visualize the dilution process and develop the technology necessary to conduct tracer dilution tests in LNAPL. A fluorescent dye, BSL 715, was selected as a tracer. A spectrometer and computer were used to measure and log the fluorescent intensity, which is a measure of the tracer concentration. A device to mix the tracer in the well without causing adverse dilution was also developed. A large tank study explored the tracer dilution technique using a typical range of LNAPL thicknesses and flow rates. The flow rates varied from 7.2 m3/m/yr to 0.035 m3/m/yr and the LNAPL thicknesses varied from 9cm to 24cm. The results of the large tank study demonstrated that the tracer dilution technique is an accurate and reliable method to measure the migration of petroleum liquids in the subsurface. The measured error tends to increase at lower flow rates but is insensitive to the LNAPL thickness. The results of the large tank study led to a field test at the former ChevronTexaco Refinery in Casper, WY. The tracer dilution method was deployed in two locations. The first location was near an active recovery well where the flow rate was expected to be high. The second test was conducted in a quiescent area where the flow rate was low. The first test, near the recovery well, measured a flow rate of 0.1 m3/m/yr to 0.3 m3/m/yr. The second test, in a quiescent area, indicated a flow rate of less then 0.005 m3/m/yr. In addition, opportunities for improving sensitivity and increasing the usefulness of the method were discovered. In all, the experiments have shown the tracer dilution technique to be an effective method to directly measure the in situ migration of petroleum liquids in the subsurface.
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    Optimal design of groundwater quality monitoring networks
    (Colorado State University. Libraries, 1992) Farr, Anne McCormack, author; Ward, Robert C., advisor; McWhorter, David, committee member; Salas, Jose, committee member; Bell, Harry, committee member
    This research focuses on the optimal design of groundwater quality monitoring networks. The optimization technique developed allows for incorporation of both the model structure, data error, and model parameter uncertainty into the monitoring network design, with concurrent determination of sampling frequency and well locations. Particular emphasis has been placed on the use of stochastic models to describe groundwater quality data in order to incorporate both the deterministic and random behavior of groundwater quality in the model evaluation and monitoring network design processes. A protocol is developed for the evaluation of model applicability and the design of monitoring networks. This protocol was developed based on the results of a simulation study, with the developed protocol tested against field data; The simulation study provided a method of evaluating the performance of various model applicability tests and monitoring network designs against a known correct model. The performance of the protocol could therefore be evaluated for correct models with different magnitudes and types of error (additive and multiplicative normal and lognormal errors were considered), as well as for incorrect models with different magnitudes and types of error. The results of this research strengthen the importance of a detailed statistical evaluation of model applicability prior to the use of a model as a tool for describing groundwater quality behavior or prior to the design of monitoring networks. The model applicability evaluation should include the use of a variety of statistical tests to assess model applicability, and more importantly, should include the evaluation of the behavior of statistical tests compared to the theoretical expected behavior of the statistical tests for a correct model under conditions of varying sampling frequency, record length, and sampling density. In addition, the optimal monitoring network was found to be highly dependent on the sampling locations used to fit the model and to the monitoring locations identified to be considered for inclusion in the monitoring network.