The ever increasing energy demand brings about widespread interest to rapidly, profitably and efficiently develop unconventional resources, among which tight gas sands hold a significant portion. However, optimization of development strategies in tight gas fields is challenging, not only because of the wide range of depositional environments and large variability in reservoir properties, but also because the evaluation often has to deal with a multitude of wells, limited reservoir information, and time and budget constraints. Unfortunately, classical full-scale reservoir evaluation cannot be routinely employed by small- to medium-sized operators, given its timeconsuming and expensive nature. In addition, the full-scale evaluation is generally built on deterministic principles and produces a single realization of the reservoir, despite the significant uncertainty faced by operators. This work addresses the need for rapid and cost-efficient technologies to help operators determine optimal well spacing in highly uncertain and risky unconventional gas reservoirs. To achieve the research objectives, an integrated reservoir and decision modeling tool that fully incorporates uncertainty was developed. Monte Carlo simulation was used with a fast, approximate reservoir simulation model to match and predict production performance in unconventional gas reservoirs. Simulation results were then fit with decline curves to enable direct integration of the reservoir model into a Bayesian decision model. These integrated tools were applied to the tight gas assets of Unconventional Gas Resources Inc. in the Berland River area, Alberta, Canada.

With the rapidly increasing demand for energy and the increasing prices for oil and gas, the role of unconventional gas reservoirs (UGRs) as energy sources is becoming more important throughout the world. Because of high risks and uncertainties associated with UGRs, their profitable development requires experts to be involved in the most critical development stages, such as drilling, completion, stimulation, and production. However, many companies operating UGRs lack this expertise. The advisory system we developed will help them make efficient decisions by providing insight from analogous basins that can be applied to the wells drilled in target basins. In North America, UGRs have been in development for more than 50 years. The petroleum literature has thousands of papers describing best practices in management of these resources. If we can define the characteristics of the target basin anywhere in the world and find an analogous basin in North America, we should be able to study the best practices in the analogous basin or formation and provide the best practices to the operators. In this research, we have built an advisory system that we call the Unconventional Gas Reservoir (UGR) Advisor. UGR Advisor incorporates three major modules: BASIN, PRISE and Drilling & Completion (D&C) Advisor. BASIN is used to identify the reference basin and formations in North America that are the best analogs to the target basin or formation. With these data, PRISE is used to estimate the technically recoverable gas volume in the target basin. Finally, by analogy with data from the reference formation, we use D&C Advisor to find the best practice for drilling and producing the target reservoir. To create this module, we reviewed the literature and interviewed experts to gather the information required to determine best completion and stimulation practices as a function of reservoir properties. We used these best practices to build decision trees that allow the user to take an elementary data set and end up with a decision that honors the best practices. From the decision trees, we developed simple computer algorithms that streamline the process.

Various models featuring horizontal wells with multiple induced fractures have been proposed to characterize flow behavior over time in tight gas and shale gas systems. Currently, there is little consensus regarding the effects of non-ideal fracture geometries and coupled primary-secondary fracture interactions on reservoir performance in these unconventional gas reservoirs. This thesis provides a grid construction tool to generate high-resolution unstructured meshes using Voronoi grids, which provides the flexibility required to accurately represent complex geologic domains and fractures in three dimensions. Using these Voronoi grids, the interaction between propped hydraulic fractures and secondary "stress-release" fractures were evaluated. Additionally, various primary fracture configurations were examined, where the fractures may be non-planar or non-orthogonal. For this study, a numerical model was developed to assess the potential performance of tight gas and shale gas reservoirs. These simulations utilized up to a half-million grid-blocks and consider a period of up to 3,000 years in some cases. The aim is to provide very high-definition reference numerical solutions that will exhibit virtually all flow regimes we can expect in these unconventional gas reservoirs. The simulation results are analyzed to identify production signatures and flow regimes using diagnostic plots, and these interpretations are confirmed using pressure maps where useful. The coupled primary-secondary fracture systems with the largest fracture surface areas are shown to give the highest production in the traditional "linear flow" regime (which occurs for very high conductivity vertical fracture cases). The non-ideal hydraulic fracture geometries are shown to yield progressively lower production as the angularity of these fractures increases. Hence, to design optimum fracture completions, we should endeavor to keep the fractures as orthogonal to the horizontal well as possible. This work expands the current understanding of flow behavior in fractured tight-gas and shale-gas systems and may be used to optimize fracture and completion design, to validate analytical models and to facilitate more accurate reserves estimation.