The transport and fate of contaminants in fractured sedimentary rock aquifers depends strongly on the nature and distribution of the fracture network. The current standard practice of using only vertical coreholes to characterize bedrock aquifers can result in significantly biased data that is insufficient for fracture orientation analysis. This study involves the addition of two inclined coreholes to supplement existing data from eleven vertical coreholes at a contaminated site in Guelph, Ontario to reduce the effects of this bias. A suite of high-resolution, depth discrete data collection methods including core logging, borehole geophysics, and hydraulic testing were conducted to determine fracture orientation and spacing as well as hydraulic aperture distributions. The results of the orientation analysis demonstrate that the inclined coreholes were more effective at sampling high-angled fractures than the vertical coreholes and were necessary to identify all three of the dominant fracture sets on the site. The fracture network properties from this study can be used as input parameters for static and dynamic discrete fracture network models to assess current and future risks to municipal supply wells.

This dissertation aims to propose a new and practical method to obtain equivalent fracture network permeability (EFNP), which represents and replaces all the existing fractures located in each grid block for the reservoir simulation of naturally fractured reservoirs. To achieve this, first the relationship between different geometrical properties of fracture networks and their EFNP was studied. A MATLAB program was written to generate many different realizations of 2-D fracture networks by changing fracture length, density and also orientation. Next, twelve different 2-D fractal-statistical properties of the generated fracture networks were measured to quantify different characteristics. In addition to the 2-D fractal-statistical properties, readily available 1-D and 3-D data were also measured for the models showing variations of fracture properties in the Z-direction. The actual EFNP of each fracture network was then measured using commercial software called FRACA. The relationship between the 1-, 2- and 3-D data and EFNP was analyzed using multivariable regression analysis and based on these analyses, correlations with different number of variables were proposed to estimate EFNP. To improve the accuracy of the predicted EFNP values, an artificial neural network with the back-propagation algorithm was also developed. Then, using the experimental design technique, the impact of each fracture network parameter including fracture length, density, orientation and conductivity on EFNP was investigated. On the basis of the results and the analyses, the conditions to obtain EFNP for practical applications based on the available data (1-D well, 2-D outcrop, and 3-D welltest) were presented. This methodology was repeated for natural fracture patterns obtained mostly from the outcrops of different geothermal reservoirs. The validity of the equations was also tested against the real welltest data obtained from the fields. Finally, the concept of the percolation theory was used to determine whether each fracture network in the domain is percolating (permeable) and to quantify the fracture connectivity, which controls the EFNP. For each randomly generated fracture network, the relationship between the combined fractal-percolation properties and the EFNP values was investigated and correlations for predicting the EFNP were proposed. As before, the results were validated with a new set of fracture networks. / Petroleum Engineering

Neural networks (NNs) are widely used to investigate the relationship among variables in complex multivariate problems. In cases of limited data, the network behavior strongly depends on factors such as the choice of network activation function and network initial weights. In this study, I investigated the use of neural networks for multivariate analysis in the case of limited data. The analysis shows that special attention should be paid when building and using NNs in cases of limited data. The linear activation function at the output nodes outperforms the sigmoidal and Gaussian functions. I found that combining network predictions gives less biased predictions and allows for the assessment of the prediction variability. The NN results, along with conventional statistical analysis, were used to examine the effects of folding, bed thickness, structural position, and lithology on the fracture properties distributions in the Lisburne Formation, folded and exposed in the northeastern Brooks Range of Alaska. Fracture data from five folds, representing different degrees of folding, were analyzed. In addition, I modeled the fracture system using the discrete fracture network approach and investigated the effects of fracture properties on the flow conductance of the system. For the Lisburne data, two major fracture sets striking north/south and east/west were studied. Results of the NNs analysis suggest that fracture spacing in both sets is similar and weakly affected by folding and that stratigraphic position and lithology have a strong effect on fracture spacing. Folding, however, has a significant effect on fracture length. In open folds, fracture lengths in both sets have similar averages and variances. As the folds tighten, both the east/west and north/south fracture lengths increase by a factor of 2 or 3 and become more variable. In tight folds, fracture length in the north/south direction is significantly larger than in the east/west direction. The difference in length between the two fracture sets creates a strong anisotropy in the reservoir. Given the same fracture density in both sets, the set with the greater length plays an important role for fluid flow, not only for flow along its principal direction but also in the orthogonal direction.

Modeling and simulation of fluid flow in subsurface fractured systems has been steadily a popular topic in petroleum industry. The huge potential hydrocarbon reserve in naturally and hydraulically fractured reservoirs has been a major stimulant for developments in this field. Although several models have found limited applications in studying fractured reservoirs, still more comprehensive models are required to be applied for practical purposes. A recently developed Embedded Discrete Fracture Model (EDFM) incorporates the advantages of two of the well-known approaches, the dual continuum and the discrete fracture models, to investigate more complex fracture geometries. In EDFM, each fracture is embedded inside the matrix grid and is discretized by the cell boundaries. This approach introduces a robust methodology to represent the fracture planes explicitly in the computational domain. As part of this research, the EDFM was implemented in two of The University of Texas in-house reservoir simulators, UTCOMP and UTGEL. The modified reservoir simulators are capable of modeling and simulation of a broad range of reservoir engineering applications in naturally and hydraulically fractured reservoirs. To validate this work, comparisons were made against a fine-grid simulation and a semi-analytical solution. Also, the results were compared for more complicated fracture geometries with the results obtained from EDFM implementation in the GPAS reservoir simulator. In all the examples, good agreements were observed. To further illustrate the application and capabilities of UTCOMP- and UTGEL-EDFM, a few case studies were presented. First, a synthetic reservoir model with a network of fractures was considered to study the impact of well placement. It was shown that considering the configuration of background fracture networks can significantly improve the well placement design and also maximize the oil recovery. Then, the capillary imbibition effect was investigated for the same reservoir models to display its effect on incremental oil recovery. Furthermore, UTCOMP-EDFM was applied for hydraulic fracturing design where the performances of a simple and a complex fracture networks were evaluated in reservoirs with different rock matrix permeabilities. Accordingly, it was shown that a complex network is an ideal design for a very low permeability reservoir, while a simple network results in higher recovery when the reservoir permeability is moderate. Finally, UTGEL-EDFM was employed to optimize a conformance control process. Different injection timings and different gel concentrations were selected for water-flooding processes and their impact on oil recovery was evaluated henceforth. / text

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No description available.

Today everyone seems to agree that ultra-low permeability and shale reservoirs have become the potentials to transform North America's oil and gas industry to a new phase. Unfortunately, transient flow is of long duration (perhaps life of the well) in ultra-low permeability reservoirs, and traditional decline curve analysis (DCA) models can lead to significantly over-optimistic production forecasts without additional safeguards. Stretched Exponential decline model (SEDM) gives considerably more stabilized production forecast than traditional DCA models and in this work it is shown that it produces unchanging EUR forecasts after only two-three years of production data are available in selected reservoirs, notably the Barnett Shale. For an individual well, the SEDM model parameters, can be determined by the method of least squares in various ways, but the inherent nonlinear character of the least squares problem cannot be bypassed. To assure a unique solution to the parameter estimation problem, this work suggests a physics-based regularization approach, based on critical velocity concept. Applied to selected Barnett Shale gas wells, the suggested method leads to reliable and consistent EURs. To further understand the interaction of the different fracture properties on reservoir response and production decline curve behavior, a series of Discrete Fracture Network (DFN) simulations were performed. Results show that at least a 3-layer model is required to reproduce the decline behavior as captured in the published SEDM parameters for Barnett Shale. Further, DFN modeling implies a large number of parameters like fracture density and fracture length are in such a way that their effect can be compensated by the other one. The results of DFN modeling of several Barnett Shale horizontal wells, with numerous fracture stages, showed a very good agreement with the estimated SEDM model for the same wells. Estimation of P90 reserves that meet SEC criteria is required by law for all companies that raise capital in the United States. Estimation of P50 and P10 reserves that meet SPE/WPC/AAPG/SPEE Petroleum Resources Management System (PRMS) criteria is important for internal resource inventories for most companies. In this work a systematic methodology was developed to quantify the range of uncertainty in production forecast using SEDM. This methodology can be used as a probabilistic tool to quantify P90, P50, and P10 reserves and hence might provide one possible way to satisfy the various legal and technical-society-suggested criteria.

Numerical modeling of fluid flow and dissolved species transport in the subsurface is a challenging task, given variability and measurement uncertainty in the physical properties of the rock, the complexities of multi-fluid interaction, and limited computational resources. Nonetheless, this thesis seeks to expand our modeling capabilities in the context of contaminant hydrogeology. We describe the numerical simulator CompFlow Bio and use it to model invasion of a nonaqueous phase liquid (NAPL) contaminant through the vadose zone and below the water table in a fractured porous rock. CompFlow Bio is a three-phase, multicomponent, deterministic numerical model for fluid flow and dissolved species transport; it includes capillary pressure and equilibrium partitioning relationships. We have augmented the model to include randomly generated, axis-aligned, discrete fracture networks (DFNs). The DFN is coupled with the porous medium (PM) to form a single continuum. The domain is discretized using a finite-volume scheme in an unstructured mesh of rectilinear control volumes (CVs). Herein we present the governing equations, unstructured mesh creation scheme, algebraic development of fracture intersection CV elimination, and coupling of PM CVs over a fracture plane to permit asperity contact bridged flow. We include: small scale two-phase water-air and NAPL-water simulations to validate the practice of intersection CV elimination; small scale simulations with water-air, NAPL-water, and NAPL-water-air systems in a grid refinement exercise and to demonstrate the effect of asperity contact bridged flow; intermediate scale 3D simulations of NAPL invading the saturated zone, based on the Smithville, Ontario, site; intermediate scale 2D and 3D simulations of NAPL invading the vadose zone and saturated zone with transient recharge, based on the Santa Susana Field Laboratory site, California. Our findings indicate that: the formulation provides a practical and satisfactory way of modeling three-phase flow in discretely fractured porous rock; numerical error caused by spatial discretization manifests itself as several biases in physical flow processes; that asperity contact is important in establishing target water saturation conditions in the vadose zone; and simulation results are sensitive to relative permeability-saturation-capillary pressure relationships. We suggest a number of enhancements to CompFlow Bio to overcome certain computational limitations.

Prediction of groundwater inflow into rock tunnels is one of the essential tasks of tunnel engineering. Currently, most of the methods used in the industry are typically based on continuum models, whether analytical, semi-empirical, or numerical. As a consequence, a regular flow along the tunnel is commonly predicted. There are also some discrete fracture network methods based on a discontinous model, which typically yield regular flow or random flow along the tunnel. However, it was observed that, in hard rock tunnels, flow usually concentrates in some areas, and much of the tunnel is dry. The reason is that, in hard rock, most of the water flows in rock fractures and fractures typically occur in a clustered pattern rather than in a regular or random pattern. A new method is developed in this work, which can model the fracture clustering and reproduce the flow concentration. After elaborate literature review, a new algorithm is developed to simulate fractures with clustering properties by using geostatistics. Then, a discrete fracture network is built and simplified. In order to solve the flow problem in the discrete fracture network, an existing analytical-numercial method is improved. Two case studies illustrate the procedure of fracture simulation. Several ideal tunnel cases and one real tunnel project are used to validate the flow analysis. It is found that fracture clustering can be modeled and flow concentration can be reproduced by using the proposed technique. / text

Numerical modeling of fluid flow and dissolved species transport in the subsurface is a challenging task, given variability and measurement uncertainty in the physical properties of the rock, the complexities of multi-fluid interaction, and limited computational resources. Nonetheless, this thesis seeks to expand our modeling capabilities in the context of contaminant hydrogeology. We describe the numerical simulator CompFlow Bio and use it to model invasion of a nonaqueous phase liquid (NAPL) contaminant through the vadose zone and below the water table in a fractured porous rock. CompFlow Bio is a three-phase, multicomponent, deterministic numerical model for fluid flow and dissolved species transport; it includes capillary pressure and equilibrium partitioning relationships. We have augmented the model to include randomly generated, axis-aligned, discrete fracture networks (DFNs). The DFN is coupled with the porous medium (PM) to form a single continuum. The domain is discretized using a finite-volume scheme in an unstructured mesh of rectilinear control volumes (CVs). Herein we present the governing equations, unstructured mesh creation scheme, algebraic development of fracture intersection CV elimination, and coupling of PM CVs over a fracture plane to permit asperity contact bridged flow. We include: small scale two-phase water-air and NAPL-water simulations to validate the practice of intersection CV elimination; small scale simulations with water-air, NAPL-water, and NAPL-water-air systems in a grid refinement exercise and to demonstrate the effect of asperity contact bridged flow; intermediate scale 3D simulations of NAPL invading the saturated zone, based on the Smithville, Ontario, site; intermediate scale 2D and 3D simulations of NAPL invading the vadose zone and saturated zone with transient recharge, based on the Santa Susana Field Laboratory site, California. Our findings indicate that: the formulation provides a practical and satisfactory way of modeling three-phase flow in discretely fractured porous rock; numerical error caused by spatial discretization manifests itself as several biases in physical flow processes; that asperity contact is important in establishing target water saturation conditions in the vadose zone; and simulation results are sensitive to relative permeability-saturation-capillary pressure relationships. We suggest a number of enhancements to CompFlow Bio to overcome certain computational limitations.