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.

As the development of shale resources continue to accelerate in the United States, improving the effectiveness and the cost efficiency of hydraulic fracturing completion is becoming increasingly important. For such improvement, it is necessary to investigate the effects of various design parameters and in-situ conditions on the resulting fracture dimensions and propagation patterns. In this thesis, a 3D geomechanical model was built using ABAQUS Standard to simulate the propagation of multiple competing fractures in a single fracture stage of a horizontal well. The reservoir was modeled as a porous elastic medium using C3D8RP pore pressure & stress elements. In addition, a vertical plane of COH3D8P pore pressure cohesive elements was inserted at each perforation cluster to model fracture propagation. Also, the flow distribution among perforation clusters was simulated using a parallel resistors model. The results suggested that the fracture spacing has the dominant impact on the number of propagated fractures. Even when all other conditions were favorable to fracture propagation, small fracture spacing reduced the number of propagated fractures. Similarly, in a given fracture stage, decreasing the number of perforation clusters abated inter-fracture stress interference, and increased the number of propagated fractures. Higher injection fluid viscosity significantly increased the fracture widths and slightly decreased the fracture lengths, but did not have any impact on the number of propagated fractures. Also, higher injection rates led to longer and wider fractures, and increased the number of propagated fractures. Therefore, a high injection fluid viscosity and a high injection rate should be used to promote fracture propagation. Lastly, higher Young's modulus of the target formation led to increased stress interference, and the resulting fractures were shorter and narrower. Therefore, if the Young’s modulus of a target formation is high, a wider fracture spacing should be considered. Through this study, a 3D geomechanical model was successfully formulated to simulate the propagation of multiple competing fractures. In addition, the effects of various hydraulic fracturing design parameters and in-situ conditions on the resulting fracture dimensions and propagation patterns were demonstrated. / text

Esta dissertação tem como objetivo apresentar uma estimativa preliminar do volume de recurso contingente não-convencionais de folhelhos oleígenos (oil shale) na Formação Tremembé através de métodos probabilísticos aplicados à informações compiladas de bibliografias existentes sobre a bacia. Como base para esta estimativa utilizou-se informações obtidas através de sísmica 2D, poços existentes na área e perfis geoquímicos. Através da interpretação dos mesmos foram gerados os valores de inputs para os parâmetros utilizados no cálculo, como: espessura econômica, densidade do minério e valor de Ensaio Fisher (Litros de óleo por tonelada de rocha). Para a análise foi construída uma planilha Excel no qual já descrito cada parâmetro do cálculo. Foi utilizado o software @Risk, da Palisade Inc., que é capaz de atribuir distribuições estatísticas a parâmetros utilizados no cálculo obtendo, a partir do método Monte Carlo, distribuições dos possíveis resultados. A metodologia apresentada se demonstra mais adequada ao caso em estudo que o método determinístico, devido a restrição e ausência da precisão dos dados o que aumentaria as incertezas e as chances de erro no cálculo do volume, podendo impossibilitar uma avaliação, no caso do segundo. A metodologia probabilística ao mesmo tempo em que permite uma avaliação preliminar na ausência de dados precisos, ela gera cenários probabilísticos de resultados, possibilitando a antecipação da tomada de decisões em um projeto, permitindo sua continuação ou abandono. / This paper aims to present a preliminary estimate of the volume of unconventional resource (oil shale) in Tremembé Formation, with probabilistic methods applied to previous studies in the basin. The estimate was based on 2D seismic, well and geochemical profiles. The interpretation of these values were generated for the input parameters used in the calculation, such as economic thickness, density and value of the Fisher Assay (liters of oil per tonne of rock). The analysis was done in Excel with a description of each parameter used. The plug-in software @ Risk (Palisade Inc.) was used, enabling statistical distributions and the use of Monte Carlo simulation in the estimate. The methodology proved to be more appropriate to the case study than to the deterministic method, due to restriction and lack of accurate data which would increase the uncertainties and the chances of error in calculating the volume, allowing a preliminary assessment generating distributions probabilistic results, enabling the anticipation of the decision-making process.

The Unconventional Resource Plays consisting of the lowest tier of resources (large volumes and most difficult to develop) have been the main focus of US domestic activity during recent times. Horizontal well drilling and hydraulic fracturing completion technology have been primarily responsible for this paradigm shift. The concept of drainage volume is being examined using pressure diffusion along streamlines. We use diffusive time of flight to optimize the number of hydraulic fracture stages in horizontal well application for Tight Gas reservoirs. Numerous field case histories are available in literature for optimizing number of hydraulic fracture stages, although the conclusions are case specific. In contrast, a general method is being presented that can be used to augment field experiments necessary to optimize the number of hydraulic fracture stages. The optimization results for the tight gas example are in line with the results from economic analysis. The fluid flow simulation for Naturally Fractured Reservoirs (NFR) is performed by Dual-Permeability or Dual-Porosity formulations. Microseismic data from Barnett Shale well is used to characterize the hydraulic fracture geometry. Sensitivity analysis, uncertainty assessment, manual & computer assisted history matching are integrated to develop a comprehensive workflow for building reliable reservoir simulation models. We demonstrate that incorporating proper physics of flow is the first step in building reliable reservoir simulation models. Lack of proper physics often leads to unreasonable reservoir parameter estimates. The workflow demonstrates reduced non-uniqueness for the inverse history matching problem. The behavior of near-critical fluids in Liquid Rich Shale plays defies the production behavior observed in conventional reservoir systems. In conventional reservoirs an increased gas-oil ratio is observed as flowing bottom-hole pressure is less than the saturation pressure. The production behavior is examined by building a compositional simulation model on an Eagle Ford well. Extremely high pressure drop along the multiple transverse hydraulic fractures and high critical gas saturation are responsible for this production behavior. Integrating pore-scale flow modeling (such as Lattice Boltzmann) to the field-scale reservoir simulation may enable quantifying the effects of high capillary pressure and phase behavior alteration due to confinement in the nano-pore system.

Esta dissertação tem como objetivo apresentar uma estimativa preliminar do volume de recurso contingente não-convencionais de folhelhos oleígenos (oil shale) na Formação Tremembé através de métodos probabilísticos aplicados à informações compiladas de bibliografias existentes sobre a bacia. Como base para esta estimativa utilizou-se informações obtidas através de sísmica 2D, poços existentes na área e perfis geoquímicos. Através da interpretação dos mesmos foram gerados os valores de inputs para os parâmetros utilizados no cálculo, como: espessura econômica, densidade do minério e valor de Ensaio Fisher (Litros de óleo por tonelada de rocha). Para a análise foi construída uma planilha Excel no qual já descrito cada parâmetro do cálculo. Foi utilizado o software @Risk, da Palisade Inc., que é capaz de atribuir distribuições estatísticas a parâmetros utilizados no cálculo obtendo, a partir do método Monte Carlo, distribuições dos possíveis resultados. A metodologia apresentada se demonstra mais adequada ao caso em estudo que o método determinístico, devido a restrição e ausência da precisão dos dados o que aumentaria as incertezas e as chances de erro no cálculo do volume, podendo impossibilitar uma avaliação, no caso do segundo. A metodologia probabilística ao mesmo tempo em que permite uma avaliação preliminar na ausência de dados precisos, ela gera cenários probabilísticos de resultados, possibilitando a antecipação da tomada de decisões em um projeto, permitindo sua continuação ou abandono. / This paper aims to present a preliminary estimate of the volume of unconventional resource (oil shale) in Tremembé Formation, with probabilistic methods applied to previous studies in the basin. The estimate was based on 2D seismic, well and geochemical profiles. The interpretation of these values were generated for the input parameters used in the calculation, such as economic thickness, density and value of the Fisher Assay (liters of oil per tonne of rock). The analysis was done in Excel with a description of each parameter used. The plug-in software @ Risk (Palisade Inc.) was used, enabling statistical distributions and the use of Monte Carlo simulation in the estimate. The methodology proved to be more appropriate to the case study than to the deterministic method, due to restriction and lack of accurate data which would increase the uncertainties and the chances of error in calculating the volume, allowing a preliminary assessment generating distributions probabilistic results, enabling the anticipation of the decision-making process.