As energy supplies from known resources are declining, the development of new energy sources is mandatory. One reasonable source is natural gas from unconventional resources. This study focus on three types of unconventional gas resources: coalbeds, tight sands, and shales. Whereas these resources are abundant, they have largely been overlooked and understudied, especially outside of North America. New technologies, including those needed to unlock unconventional gas (UCG) resources, have been acknowledged to be the most significant factor in increasing natural gas supply in the United States. This study evaluates advances in critical technology that will most likely increase supply the most. Advanced technology is one of the main drivers in increasing unconventional natural gas production, as observed in the United States, Canada, and Australia. 3D seismic, horizontal drilling, multilateral completion, water and gel based fracturing, coiled tubing rig, enhanced recovery, and produced water treatments are current important technologies critical in developing unconventional gas resources. More advanced technologies with significant impacts are expected to be available in the next decades. Fit-to-purpose technology reduces the cost to recover gas from unconventional resources. The better the unconventional gas resources are characterized, the better we can tailor specific technology to recover the gas, and less cost are needed. Analogy assumption is a good start in deciding which critical technology to be transferred to undeveloped unconventional reservoirs. If the key properties of two unconventional gas basins or formations are more or less similar, it is expected that the impact of certain technology applied in one basin or formation will resemble the impact to the other basin or formation.

As energy supplies from known resources are declining, the development of new energy sources is mandatory. One reasonable source is natural gas from unconventional resources. This study focus on three types of unconventional gas resources: coalbeds, tight sands, and shales. Whereas these resources are abundant, they have largely been overlooked and understudied, especially outside of North America. New technologies, including those needed to unlock unconventional gas (UCG) resources, have been acknowledged to be the most significant factor in increasing natural gas supply in the United States. This study evaluates advances in critical technology that will most likely increase supply the most. Advanced technology is one of the main drivers in increasing unconventional natural gas production, as observed in the United States, Canada, and Australia. 3D seismic, horizontal drilling, multilateral completion, water and gel based fracturing, coiled tubing rig, enhanced recovery, and produced water treatments are current important technologies critical in developing unconventional gas resources. More advanced technologies with significant impacts are expected to be available in the next decades. Fit-to-purpose technology reduces the cost to recover gas from unconventional resources. The better the unconventional gas resources are characterized, the better we can tailor specific technology to recover the gas, and less cost are needed. Analogy assumption is a good start in deciding which critical technology to be transferred to undeveloped unconventional reservoirs. If the key properties of two unconventional gas basins or formations are more or less similar, it is expected that the impact of certain technology applied in one basin or formation will resemble the impact to the other basin or formation.

Since the 1970s, various private and governmental agencies have conducted studies to assess potential unconventional gas resources, particularly those resources contained in tight sands, fractured shales, and coal beds. The US Geological Survey (USGS) has assessed the amount of unconventional gas resources in North America, and its estimates are used by other government agencies as the basis for their resource estimates. While the USGS employs a probabilistic methodology, it is apparent from the resulting narrow ranges that the methodology underestimates the uncertainty of these undiscovered, untested, potential resources, which in turn limits the reliability and usefulness of the assessments. The objective of this research is to develop an improved methodology to assess potential unconventional gas resources that better accounts for the uncertainty in these resources. This study investigates the causes of the narrow ranges generated by the USGS analyticprobabilistic methodology used to prepare the 1995 national oil and gas assessment and the 2000 NOGA series, and presents an improved methodology to assess potential unconventional gas resources. The new model improves upon the USGS method by using a stochastic approach, which includes correlation between the input variables and Monte Carlo simulation, representing a more versatile and robust methodology than the USGS analytic-probabilistic methodology. The improved methodology is applied to the assessment of potential unconventional gas resources in the Uinta-Piceance province of Utah and Colorado, and compared to results of the evaluation performed by the USGS in 2002. Comparison of the results validates the means and standard deviations produced by the USGS methodology, but shows that the probability distributions generated are rather different and, that the USGS distributions are not skewed to right, as expected for a natural resource. This study indicates that the unrealistic shape and width of the resulting USGS probability distributions are not caused by the analytic equations or lack of correlation between input parameters, but rather the use of narrow triangular probability distributions as input variables. Adoption of the improved methodology, along with a careful examination and revision of input probability distributions, will allow a more realistic assessment of the uncertainty surrounding potential unconventional gas resources.

During the past decade, the worldwide demand for energy has continued to increase at a rapid rate. Natural gas has emerged as a primary source of US energy. The technically recoverable natural gas resources in the United States have increased from approximately 1,400 trillion cubic feet (Tcf) to approximately 2,100 trillion cubic feet (Tcf) in 2010. The recent declines in gas prices have created short-term uncertainties and increased the risk of developing natural gas fields, rendering a substantial portion of this resource uneconomical at current gas prices. This research quantifies the impact of changes in finding and development costs (FandDC), lease operating expenses (LOE), and gas prices, in the estimation of the economically recoverable gas for unconventional plays. To develop our methodology, we have performed an extensive economic analysis using data from the Barnett Shale, as a representative case study. We have used the cumulative distribution function (CDF) of the values of the Estimated Ultimate Recovery (EUR) for all the wells in a given gas play, to determine the values of the P10 (10th percentile), P50 (50th percentile), and P90 (90th percentile) from the CDF. We then use these probability values to calculate the technically recoverable resource (TRR) for the play, and determine the economically recoverable resource (ERR) as a function of FandDC, LOE, and gas price. Our selected investment hurdle for a development project is a 20 percent rate of return and a payout of 5 years or less. Using our methodology, we have developed software to solve the problem. For the Barnett Shale data, at a FandDC of 3 Million dollars, we have found that 90 percent of the Barnet shale gas is economically recoverable at a gas price of 46 dollars/Mcf, 50 percent of the Barnet shale gas is economically recoverable at a gas price of 9.2 dollars/Mcf, and 10 percent of the Barnet shale gas is economically recoverable at a gas price of 5.2 dollars/Mcf. The developed methodology and software can be used to analyze other unconventional gas plays to reduce short-term uncertainties and determine the values of FandDC and gas prices that are required to recover economically a certain percentage of TRR.

Time-rate analysis and time-rate-pressure analysis methods are available to estimate reserves and study flow performance of wells in unconventional gas reservoirs. However, these tools are often incorrectly used or the analysis can become difficult because of the complex nature of the reservoir system. Conventional methods (e.g., Arps' time-rate relations) are often used incorrectly to estimate reserves from such reservoirs. It was only recently that a serious study was conducted to outline the limitations of these relations and to set guidelines for their correct application. New time-rate relations, particularly the Duong and logistic growth model, were introduced to estimate reserves and forecast production from unconventional reservoirs. These new models are being used with limited understanding of their characteristics and limitations. Moreover, well performance analyses using analytical/semi-analytical solutions (time-rate-pressure) are often complicated from non-uniqueness that arises when estimating well/formation properties. In this work, we present a detailed study of the Duong model and logistic growth model to investigate the behaviors and limitations of these models when analyzing production data from unconventional reservoirs. We consider production data generated from numerical simulation cases and data obtained from unconventional gas reservoirs to study the quality of match to specific flow regimes and compare accuracy of the reserve estimates. We use the power-law exponential model (PLE), which has been shown to model transient, transition and boundary-dominated flow regimes reliably, as a benchmark to study performance of Duong and logistic growth models. Moreover, we use the "continuous EUR" approach to compare these models during reserve estimation. Finally, we develop four new time-rate relations, based on characteristics of the time-rate data on diagnostic plots. Using diagnostic plots we show that the new time-rate relations provide a quality match to the production data across all flow regimes, leading to a reliable reserve estimate. In a preliminary study, we integrated time-rate model parameters with fundamental reservoir properties (i.e., fracture conductivity (Fc) and 30 year EUR (EUR30yr)), by studying 15 numerical simulation cases to yield parametric correlations. We have demonstrated a methodology to integrate time-rate model parameters and reservoir properties. This method avoids the non-uniqueness issues often associated with model-based production data analysis. This study provides theoretical basis for further demonstration of the methodology using field cases.

Optimizing well spacing in unconventional gas reservoirs is difficult due to complex heterogeneity, large variability and uncertainty in reservoir properties, and lack of data that increase the production uncertainty. Previous methods are either suboptimal because they do not consider subsurface uncertainty (e.g., statistical moving-window methods) or they are too time-consuming and expensive for many operators (e.g., integrated reservoir characterization and simulation studies). This research has focused on developing and extending a new technology for determining optimal well spacing in tight gas reservoirs that maximize profitability. To achieve the research objectives, an integrated multi-well reservoir and decision model that fully incorporates uncertainty was developed. The reservoir model is based on reservoir simulation technology coupled with geostatistical and Monte Carlo methods to predict production performance in unconventional gas reservoirs as a function of well spacing and different development scenarios. The variability in discounted cumulative production was used for direct integration of the reservoir model with a Bayesian decision model (developed by other members of the research team) that determines the optimal well spacing and hence the optimal development strategy. The integrated model includes two development stages with a varying Stage-1 time span. The integrated tools were applied to an illustrative example in Deep Basin (Gething D) tight gas sands in Alberta, Canada, to determine optimal development strategies. The results showed that a Stage-1 length of 1 year starting at 160-acre spacing with no further downspacing is the optimal development policy. It also showed that extending the duration of Stage 1 beyond one year does not represent an economic benefit. These results are specific to the Berland River (Gething) area and should not be generalized to other unconventional gas reservoirs. However, the proposed technology provides insight into both the value of information and the ability to incorporate learning in a dynamic development strategy. The new technology is expected to help operators determine the combination of primary and secondary development policies early in the reservoir life that profitably maximize production and minimize the number of uneconomical wells. I anticipate that this methodology will be applicable to other tight and shale gas reservoirs.

Unconventional resources will play an important role in filling the gap between supply and demand for future world energy. In North America, the impact of unconventional resources on energy supplies is growing continuously. However, around the world they have yet to serve as a major contributor to the energy supply, partly due to the scarcity of information about the exploration and development technologies required to produce them. Basin analogy can be used to estimate the undiscovered petroleum potential in a target basin by finding a geological analog that has been explored enough that its resource potential is fully understood. In 2006, Singh developed a basin analog system BASIN (Basin Analog Systems INvestigation) in detail that could rapidly and consistently identify analogous reference basins for a target basin. My research focused on continuing that work, comprehensively improving the basin analog system in four areas: the basin analog method; the database; the software functionality; and the validation methods. The updated system compares basins in terms of probability distributions of geological parameters. It compensates for data that are sparse or that do not represent basin-level geological parameters, and it expands the system's ability to compare widely varying quantitative parameters. Because the updated BASIN database contains more geologic and petroleum systems information on reference (existing) basins, it identifies analog basins more accurately and efficiently. The updated BASIN software was developed by using component-based design and data visualization techniques that help users better manage large volumes of information to understand various data objects and their complicated relationships among various data objects. Validation of the improved BASIN software confirms its accuracy: if a basin selected as the target basin appears in the reference basin list with other basins, the target basin is 100% analogous only to itself. Furthermore, when a target basin is analyzed by both BASIN and PRISE (Petroleum Resources Investigation and Summary Evaluation) software, results of the improved BASIN closely matched the PRISE results, which provides important support for using BASIN and PRISE together to quantitatively estimate the resource potential in frontier basins.

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.

Hydraulic fracturing is an important stimulation method for producing unconventional gas reserves. Natural fractures are present in many low-permeability gas environments and often provide important production pathways for natural gas. The production benefit from natural fractures can be immense, but it is difficult to quantify. The Mesaverde Group in the Piceance Basin in Colorado is a gas producing reservoir that has low matrix permeability but is also highly naturally fractured. Wells in the Piceance Basin are hydraulically fractured, so the production enhancements due to natural fracturing and hydraulic fracturing are difficult to decouple. In this thesis, dipole sonic logs were used to quantify geomechanical properties by combining stress equations with critically-stressed faulting theory. The properties derived from this log-based evaluation were used to numerically model hydraulic fracture treatments that had previously been pumped in the basin. The results from these hydraulic fracture models, in addition to the log-derived reservoir properties were used to develop reservoir models. Several methods for simulating the reservoir were compared and evaluated, including layer cake models, geostatistical models, and models simulating the fracture treatment using water injection. The results from the reservoir models were compared to actual production data to quantify the effect of both hydraulic fractures and natural fractures on production. This modeling also provided a framework upon which completion techniques were economically evaluated. / text