Modeling of changing pressure, temperature, and density profiles in a wellbore as a function of time is crucial for design and analysis of pressure-transient tests (particularly when data are gathered above perforations), real-time management of annular-pressure buildup (ABP) and identifying potential flow-assurance issues. Other applications of this modeling approach include improving design of production tubulars and artificial-lift systems and gathering pressure data for continuous reservoir management. This work presents a transient wellbore model coupled with a semianalytic temperature model for computing wellbore-fluid-temperature profile in flowing and shut-in wells. The accuracy of the analytic heat-transfer calculations improved with a variable-formation temperature model and a newly developed numerical-differentiation scheme. Surrounding formation temperature is updated in every timestep up to a user specified distance to account for changes in heat-transfer rate between the hotter wellbore fluid and the cooler formation. Matrix operations are not required for energy calculations because of the semianalytic formulation. This efficient coupling with the semianalytic heat-transfer model increased the computational speed significantly. Either an analytic or a numeric reservoir model can be coupled with the transient wellbore model for rapid computations of pressure, temperature, and velocity. The wellbore simulator is used for modeling a multirate test from a deep offshore well. Thermal distortion and its effects on pressure data is studied using the calibrated model, resulting in development of correlations for optimum gauge location in both oil and gas wells. Finally, predictive capabilities of the wellbore model are tested on multiple onshore wells experiencing annular-pressure buildup problems. Modeling results compare quite well with the field data and also with the state-of-the-art commercial wellbore simulator.

Modeling of changing pressure, temperature, and density profiles in a wellbore as a function of time is crucial for design and analysis of pressure-transient tests (particularly when data are gathered above perforations), real-time management of annular-pressure buildup (ABP) and identifying potential flow-assurance issues. Other applications of this modeling approach include improving design of production tubulars and artificial-lift systems and gathering pressure data for continuous reservoir management. This work presents a transient wellbore model coupled with a semianalytic temperature model for computing wellbore-fluid-temperature profile in flowing and shut-in wells. The accuracy of the analytic heat-transfer calculations improved with a variable-formation temperature model and a newly developed numerical-differentiation scheme. Surrounding formation temperature is updated in every timestep up to a user specified distance to account for changes in heat-transfer rate between the hotter wellbore fluid and the cooler formation. Matrix operations are not required for energy calculations because of the semianalytic formulation. This efficient coupling with the semianalytic heat-transfer model increased the computational speed significantly. Either an analytic or a numeric reservoir model can be coupled with the transient wellbore model for rapid computations of pressure, temperature, and velocity. The wellbore simulator is used for modeling a multirate test from a deep offshore well. Thermal distortion and its effects on pressure data is studied using the calibrated model, resulting in development of correlations for optimum gauge location in both oil and gas wells. Finally, predictive capabilities of the wellbore model are tested on multiple onshore wells experiencing annular-pressure buildup problems. Modeling results compare quite well with the field data and also with the state-of-the-art commercial wellbore simulator.

When approximating heat transfer through a streambed, an understanding of the thermal properties of the sediments is essential (e.g., thermal conductivity, specific heat capacity, and density). Even though considerable research has been completed in this field, little has been done to establish appropriate standard data collection approaches or to compare modeling methods for approximating these properties. Three mixture models were selected for comparison against each other and against a bed conduction model (SEDMOD). Typical data collection approaches were implemented for use in the mixture models while numerous data collection approaches were employed for use within SEDMOD. Sediment samples were taken from the streambed to estimate the necessary parameters for the mixture models (e.g., sediment volume, density, porosity, etc.) and to identify the minerals present. To yield more accurate estimates of the thermal properties from SEDMOD, methods of obtaining sediment temperature profiles representing the influences of conduction only were developed through the use of a steel cylinder and different capping materials (e.g., using geo-fabric or aluminum). In comparison to laboratory measurements of the thermal properties, it was found that the mixture model that provided the best estimates of the thermal properties was a volume weighted average. The method that best isolated conductive heating from advective heating was the steel cylinder with an aluminum cap. Using this data to calibrate SEDMOD yielded thermal diffusivity values most similar to the laboratory measurements. Due to its ability to estimate both thermal diffusivity and reproduce sediment temperature profiles, SEDMOD is recommended in combination with the aluminum isolation technique.

Water temperature directly affects biological and chemical processes of fresh water ecosystems. Elevated instream temperatures are commonplace in the Virgin River of southwestern Utah during summer due to a hot desert climate and high water demands that result in low stream flows. This is of concern since the Virgin River is home to two endangered species, the Virgin River Chub (Gila seminuda) and Woundfin (Plagopterus argentissimus). Efforts to model instream temperatures within the Virgin River have been undertaken to help mitigate elevated instream temperatures including the development of a two-zone temperature and solute (TZTS) model. This model was developed to approximate the dominant processes that influence instream temperatures and used both temperature and solute data in parameter estimation. Past model applications highlighted two concerns: (1) how to confidently estimate the high number of parameters and (2) whether Rhodamine WT (RhWT) could be used as a conservative solute tracer within the Virgin River. To begin addressing these issues, spatially representative data were collected to facilitate the physical estimation of two previously calibrated parameters: total average channel width (BTOT) and the fraction of channel width associated with dead zones (β). Methods for analyzing multispectral and thermal infrared imagery were developed to provide estimates of these parameters at different resolutions. Three different TZTS model calibration cases were then evaluated to determine how decreasing the calibrated parameters and increasing the resolution and frequency at which these parameters are estimated improved model predictions and/or decreased parameter uncertainty. While temperature predictions did not change significantly in each of the calibrations, parameter uncertainty was reduced. The concern regarding the use of RhWT resulted in a series of studies to quantify the potential losses of RhWT within this system. A batch sorption study resulted in distribution coefficient values lower than those found in literature. A photodegradation study suggested possible photolysis; however, a dual tracer study conducted within the Virgin River comparing Br- (conservative tracer) with RhWT confirmed that there was insignificant RhWT loss within this system.

Limnologists and stream ecologists acknowledge the fundamental importance of temperature for regulating many ecological, biological, chemical, and physical processes. I investigated how water temperatures were affected by hydrologic linkages between streams and lakes at various positions along surface water networks throughout several headwater basins in the Sawtooth and White Cloud Mountains of Idaho (USA). Temperatures of streams and lakes were measured for up to 27 months in seven 6 – 41 km2 watersheds, with a range of lake influence. When they were ice-free, warming in lakes resulted in dramatically warmer temperatures at lake outflows compared to inflow streams (midsummer average 6.4°C warming, but as much as 12.5°C). Temperatures cooled as water traveled downstream from lakes, as rapidly as 9°C km-1. Longitudinal stream cooling was usually not strong enough, however, to reduce temperatures to baseline conditions. In early spring, lakes had the opposite effect on streams, as they released water from beneath the ice at near 0°C. Early spring stream water warmed as it flowed downstream from lakes, influenced by additional groundwater inflows. In addition to lakes, other watershed characteristics influenced temperatures, though effects differed seasonally. Multiple regression analyses indicated that lake size, distance from nearest upstream lake, and stream shading were most important in explaining stream temperatures, but the relative importance of each variable changed seasonally.

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The valuation of weather derivatives is greatly dependent on accurate modeling and forecasting of the underlying temperature indices. The complexity and uncertainty in such modeling has led to several temperature processes being developed for the Monte Carlo simulation of daily average temperatures. In this report, we aim to compare the results of two recently developed models by Gyamerah et al. (2018) and Evarest, Berntsson, Singull, and Yang (2018). The paper gives a thorough introduction to option theory, Lévy and Wiener processes, and generalized hyperbolic distributions frequently used in temperature modeling. Implementations of maximum likelihood estimation and the expectation-maximization algorithm with Kim's smoothed transition probabilities are used to fit the Lévy process distributions and both models' parameters, respectively. Later, the use of both models is considered for the pricing of European HDD and CDD options by Monte Carlo simulation. The evaluation shows a tendency toward the shifted temperature regime over the base regime, in contrast to the two articles, when evaluated for three data sets. Simulation is successfully demonstrated for the model of Evarest, however Gyamerah's model was unable to be replicated. This is concluded to be due to the two articles containing several incorrect derivations, why the thesis is left unanswered and the articles' conclusions are questioned. We end by proposing further validation of the two models and summarize the alterations required for a correct implementation.