Gardiner Dam is located on the South Saskatchewan River approximately 100 km south of Saskatoon, SK. After the start of construction, the River Embankment experienced downstream movement in the shale portion of the foundation. Observed movements are occurring on a well-defined shear plane within the shale layer. This continuing foundation deformation raises concerns regarding the long-term stability of the structure and the effect of continuing deformation on the integrity of the embankment and ancillary works. The mechanism(s) responsible for the ongoing movements are not fully understood. As such, prediction of on-going deformation has had only a limited success. In the work presented in this dissertation, historic geotechnical instrumentation data was used to identify a potential mechanism of movement within the shale foundation. The potential mechanism thus identified can be briefly described as a combination of elastic deformation and consolidation within the shale. As the reservoir level rises, part of the increase in horizontal thrust is transferred to the shale. Since the shale is relatively stiff and has a low hydraulic conductivity, the increase in loading is; therefore, transferred to the porewater, resulting in generation of excess porewater pressures in shale. When the reservoir is high a portion of the excess porewater pressure dissipates. The observed horizontal movement along the shear zone is then developed from elastic deformation and horizontal consolidation of the shale from dissipation of excess porewater pressure. An analytical model was developed from the proposed conceptual model and had general success predicting the horizontal displacement based on the reservoir level and time period. However, the model was sensitive to the reservoir level and several variables within the shale including the hydraulic conductivity and porewater parameter B. Overall, the material variables such as hydraulic conductivity and B can be refined; however, without having an accurate reservoir prediction into the future, the ability for this model to predict the displacement in the foundation will be limited.

No description available.

Recent efforts to optimize oil recovery from Green River reservoirs, Uinta Basin, have stimulated the need for better understanding of the reservoir connectivity at the scale of the operational unit. This study focuses on Green River reservoirs in the Wells Draw study area where oil production response to implemented waterflood is poor and a better understanding of the reservoir connectivity is required to enhance future secondary oil recovery. Correlating the sand bodies between well locations in the area remains difficult at 40-acre well spacing. Thus, interwell connectivity of the reservoirs is uncertain. Understanding the reservoir connectivity in the Wells Draw study area requires integration of all static and dynamic data for generation of probabilistic models of the reservoir at the interwell locations. The objective of this study is two-fold. The first objective was to determine reservoir connectivity at the interwell scale in the Wells Draw study area. To achieve this goal, I used well log and perforation data in the Wells Draw study area to produce probabilistic models of net-porosity for four producing intervals: (1) Castle Peak, (2) Lower Douglas Creek, (3) Upper Douglas Creek, and (4) Garden Gulch. The second objective was to find readily applicable methods for determining interwell connectivity. To achieve this goal, I used sandstone net thickness and perforation data to evaluate interwell connectivity in the Wells Draw study area. This evaluation was done to: (1) assess and visualize connectivity, (2) provide an assessment of connectivity for validating / calibrating percolation and capacitance based methods, and (3) determine flow barriers for simulation. The probabilistic models encompass the four producing intervals with a gross thickness of 1,900 ft and enable simulation assessments of different development strategies for optimization of oil recovery in the Wells Draw study area. The method developed for determining interwell connectivity in Wells Draw study area is reliable and suited to the four producing intervals. Also, this study shows that the percolation based method is reliable for determining interwell connectivity in the four producing intervals.

In the coming decades, the world will require additional supplies of natural gas to meet the demand for energy. Tight gas reservoirs can be defined as reservoirs where the formation permeability is so low (< 0.1 md) that advanced stimulation technologies, such as large volume fracture treatments, are required before a reasonable profit can be made. Hydraulic fracturing is one of the best methods to stimulate a tight gas well. Most fracture treatments result in 3-6 fold increases in the productivity index. However, if one computes the effective fracture length of most wells, we usually find that the effective length is less than the designed propped fracture length. The “propped length” is the distance down the fracture from the wellbore where proppants have been placed at a high enough concentration to “prop open” the fracture. The “effective length” is the portion of the propped fracture that cleans up and allows gas flow from the reservoir into the fracture then down the fracture to the wellbore. Whenever the effective length is much shorter than the designed propped length, several reasons must be evaluated to determine what might have occurred. For example, the difference could be caused by one or more of the following issues: insufficient fracture fluid cleanup, proppant settling, proppant embedment, proppant crushing, or poor reservoir continuity. Although all these causes are possible, we believe that fracture fluid cleanup issues may be the most common reason the industry fails to achieve the designed propped fracture length in most cases. In this research, we have investigated fracture fluid cleanup problems and developed a better understanding of the issues involved which hopefully will lead to ways to improve cleanup. Fracture fluid cleanup is a complex problem, that can be influenced by many parameters such as the fluid system used, treatment design, flowback procedures, production strategy, and reservoir conditions. Residual polymer in the fracture can reduce the effective fracture permeability and porosity, reduce the effective fracture half-length, and limit the well productivity. Our ability to mathematically model the fundamental physical processes governing fluid recovery in hydraulic fractures in the past has been limited. In this research, fracture fluid damage mechanisms have been investigated, and mathematical models and computer codes have been developed to better characterize the cleanup process. The codes have been linked to a 3D, 3-phase simulator to model and quantify the fracture fluid cleanup process and its effect on long-term gas production performances. Then, a comprehensive systematic simulation study has been carried out by varying formation permeability, reservoir pressure, fracture length, fracture conductivity, yield stress, and pressure drawdown. On the basis of simulation results and analyses, new ways to improve fracture fluid cleanup have been provided. This new progress help engineers better understand fracture fluid cleanup, improve fracture treatment design, and increase gas recovery from tight sand reservoirs, which can be extremely important as more tight gas reservoirs are developed around the world.

Fluid flow mechanisms in a large naturally fractured heterogeneous carbonate reservoir were investigated in this manuscript. A very thin layer with high permeability that produces the majority of production from specific wells and is deemed the Super-K Zone was investigated. It is known that these zones are connected to naturally occurring fractures. Fluid flow in naturally fractured reservoirs is a very difficult mechanism to understand. To accomplish this mission, the Super-K Zone and fractures were treated as two systems. Reservoir management practices and decisions should be very carefully reviewed and executed in this dual continuum reservoir based on the results of this work. Studying this dual media flow behavior is vital for better future completion strategies and for enhanced reservoir management decisions. The reservoir geology, Super-K identification and natural fractures literature were reviewed. To understand how fluid flows in such a dual continuum reservoir, a dual permeability simulation model has been studied. Some geological and production iv data were used; however, due to unavailability of some critical values of the natural fractures, the model was assumed hypothetical. A reasonable history match was achieved and was set as a basis of the reservoir model. Several sensitivity studies were run to understand fluid flow behavior and prediction runs were executed to help make completion recommendations for future wells based on the results obtained. Conclusions and recommended completions were highlighted at the end of this research. It was realized that the natural fractures are the main source of premature water breakthrough, and the Super-K acts as a secondary cause of water channeling to the wellbore.

The goal of any data assimilation or history matching algorithm is to enable better reservoir management decisions through the construction of reliable reservoir performance models and the assessment of the underlying uncertainties. A considerable body of research work and enhanced computational capabilities have led to an increased application of robust and efficient history matching algorithms to condition reservoir models to dynamic data. Moreover, there has been a shift towards generating multiple plausible reservoir models in recognition of the significance of the associated uncertainties. This provides for uncertainty analysis in reservoir performance forecasts, enabling better management decisions for reservoir development. Additionally, the increased deployment of permanent well sensors and downhole monitors has led to an increasing interest in maintaining 'live' models that are current and consistent with historical observations. One such data assimilation approach that has gained popularity in the recent past is the Ensemble Kalman Filter (EnKF) (Evensen 2003). It is a Monte Carlo approach to generate a suite of plausible subsurface models conditioned to previously obtained measurements. One advantage of the EnKF is its ability to integrate different types of data at different scales thereby allowing for a framework where all available dynamic data is simultaneously or sequentially utilized to improve estimates of the reservoir model parameters. Of particular interest is the use of partitioning tracer data to infer the location and distribution of target un-swept oil. Due to the difficulty in differentiating the relative effects of spatial variations in fractional flow and fluid saturations and partitioning coefficients on the tracer response, interpretation of partitioning tracer responses is particularly challenging in the presence of mobile oil saturations. The purpose of this research is to improve the performance of the EnKF in parameter estimation for reservoir characterization studies without the use of a large ensemble size so as to keep the algorithm efficient and computationally inexpensive for large, field-scale models. To achieve this, we propose the use of streamline-derived information to mitigate problems associated with the use of the EnKF with small sample sizes and non-linear dynamics in non-Gaussian settings. Following this, we present the application of the EnKF for interpretation of partitioning tracer tests specifically to obtain improved estimates of the spatial distribution of target oil.

Unconventional reservoir systems can best be described as petroleum (oil and/or gas) accumulations which are difficult to be characterized and produced by conventional technologies. In this work we present the development of a systematic procedure to evaluate well performance in unconventional (i.e., low to ultra-low permeability) reservoir systems. The specific tasks achieved in this work include the following: ● Integrated Diagnostics and Analysis of Production Data in Unconventional Reservoirs: We identify the challenges and common pitfalls of production analysis and provide guidelines for the analysis of production data. We provide a comprehensive workflow which consists of model-based production analysis (i.e., rate-transient or model matching approaches) complemented by traditional decline curve analysis to estimate reserves in unconventional reservoirs. In particular, we use analytical solutions (e.g., elliptical flow, horizontal well with multiple fractures solution, etc.) which are applicable to wells produced in unconventional reservoirs. ● Deconvolution: We propose to use deconvolution to identify the correlation between pressure and rate data. For our purposes we modify the B-spline deconvolution algorithm to obtain the constantpressure rate solution using cumulative production and bottomhole pressure data in real time domain. It is shown that constant-pressure rate and constant-rate pressure solutions obtained by deconvolution could identify the correlation between measured rate and pressure data when used in conjunction. ● Series of Rate-Time Relations: We develop three new main rate-time relations and five supplementary rate-time relations which utilize power-law, hyperbolic, stretched exponential, and exponential components to properly model the behavior of a given set of rate-time data. These relations are well-suited for the estimation of ultimate recovery as well as for extrapolating production into the future. While our proposed models can be used for any system, we provide application almost exclusively for wells completed in unconventional reservoirs as a means of providing estimates of time-dependent reserves. We attempt to correlate the rate-time relation model parameters versus model-based production analysis results. As example applications, we present a variety of field examples using production data acquired from tight gas, shale gas reservoir systems.

One of the issues with multilateral wells is determining the contribution of each lateral to the total production that is measured at the surface. Also, if water is detected at the surface or if the multilateral well performance declines, then it is difficult to identify which lateral or laterals are causing the production decline. One way to estimate the contribution from each lateral is to run production Logging Tools (PLT). Unfortunately, PLT jobs are expensive, time-consuming, labor-intensive and involve operational risks. An alternative way to measure the production from each lateral is to use Distributed Temperature Sensing (DTS) technology. Recent advances in DTS technology enable measuring the temperature profile in horizontal wells with high precision and resolution. The changes in the temperature profile are successfully used to calculate the production profile in horizontal wells. In this research, we develop a computer program that uses a multilateral well model to calculate the pressure and temperature profile in the motherbore. The results help understand the temperature and pressure behaviors in multilateral wells that are crucial in designing and optimizing DTS installations. Also, this model can be coupled with an inversion model that can use the measured temperature and pressure profile to calculate the production from each lateral. Our model shows that changing the permeability or the water cut produced from one lateral results in a clear signature in the motherbore temperature profile that can be measured with DTS technology. However, varying the length of one of the lateral did not seem to impact the temperature profile in the motherbore. For future work, this research recommends developing a numerical reservoir model that would enable studying the effect of lateral inference and reservoir heterogeneity. Also recommended is developing an inversion model that can be used to validate our model using field data.

The late Permian Queen Formation (115 m thick) is a succession of mixed clastics, carbonates and evaporites deposited in the northeastern margin of Central Basin Platform of the Permian Basin, west Texas, USA. Depositional facies, stacking patterns of cyclic facies associations and statistical correlation of rock property variations define geologic controls on reservoir rock properties. Textural, compositional, petrophysical and diagenetic variations within lithofacies exhibit systematic changes with stratigraphic position, which can be related to base level changes that were controlled by high-frequency, low-amplitude, sea level fluctuations during a greenhouse period. Ten lithofacies record variations in clastic input, shallow marine carbonate production, and evaporate precipitation in sabhkas and salinas. Four different types of lithofacies associations define: (1) transgressive deltaic deposits; (2) upward-shallowing evaporite and carbonate tidal-flat deposits; (3) transgressive beach ridge and sand flat deposits; and (4) upward-shallowing evaporite salina-sabhka deposits. Stacking patterns of lithofacies associations define sixteen depositional cycles that can be grouped into eight cycle sets. Cycle sets in turn are grouped to define two high-frequency sequences. Sequence 1 progresses from fluvial to carbonate tidal flat cycles. Sequence 2 consists of salina-dominated upward-shoaling cycles. Lateral continuity of cycles indicates restricted sedimentation on low-accommodation inner platform areas updip of prograding highstand platform-margin carbonate buildups, and a long-term trend of accommodation decrease. The Queen Formation contains two reservoir types; (1) siliciclastic reservoirs capped by evaporites and (2) layer-cake carbonate reservoirs. Of the four reservoir zones identified, R11 in lowstand fluvial-deltaic deposits has relatively little cement and the best reservoir characters.

Water availability has been of great concern in the State of Texas and many other places worldwide. During 1997-2003, pursuant to the 1997 Senate Bill 1, the Texas Commission on Environmental Quality (TCEQ), its partner agencies, and contractors developed a Water Availability Modeling (WAM) System based on the Water Rights Analysis Package (WRAP) model, developed at Texas A&M University. WAM has been widely applied in the State of Texas and because of its convenience, applications, and capabilities, it is planned to be implemented in other States and Countries. This thesis addresses different aspects of WAM, including conditional reliability modeling, firm yield analysis following classic and recently developed methodologies, evaluating the impact of different considerations on reliability analyses, simplification of complex WAM datasets and the display of WRAP results into ArcMap. Conditional reliability modeling evaluates short term diversion/storage reliabilities based on an initial storage level. WRAP-CON has been evaluated and improved, in addition a new modeling methodology has been developed, in which probabilities of occurrence for each hydrologic sequence is based on the relationship between storage and future flows. Recently developed WRAP capabilities have been evaluated, providing users new tools and increased flexibility. Some of these improvements are firm yield analysis, cycling and dual simulation. In addition to improved software, guidelines have also been developed, including a set to simplify extremely large WAM datasets, while maintaining the effect of all the other water rights in a basin.