Browsing by Subject "Shale Oil"
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Item Assessment of Eagle Ford Shale Oil and Gas Resources(2013-07-30) Gong, XinglaiThe Eagle Ford play in south Texas is currently one of the hottest plays in the United States. In 2012, the average Eagle Ford rig count (269 rigs) was 15% of the total US rig count. Assessment of the oil and gas resources and their associated uncertainties in the early stages is critical for optimal development. The objectives of my research were to develop a probabilistic methodology that can reliably quantify the reserves and resources uncertainties in unconventional oil and gas plays, and to assess Eagle Ford shale oil and gas reserves, contingent resources, and prospective resources. I first developed a Bayesian methodology to generate probabilistic decline curves using Markov Chain Monte Carlo (MCMC) that can quantify the reserves and resources uncertainties in unconventional oil and gas plays. I then divided the Eagle Ford play from the Sligo Shelf Margin to the San Macros Arch into 8 different production regions based on fluid type, performance and geology. I used a combination of the Duong model switching to the Arps model with b = 0.3 at the minimum decline rate to model the linear flow to boundary-dominated flow behavior often observed in shale plays. Cumulative production after 20 years predicted from Monte Carlo simulation combined with reservoir simulation was used as prior information in the Bayesian decline-curve methodology. Probabilistic type decline curves for oil and gas were then generated for all production regions. The wells were aggregated probabilistically within each production region and arithmetically between production regions. The total oil reserves and resources range from a P_(90) of 5.3 to P_(10) of 28.7 billion barrels of oil (BBO), with a P_(50) of 11.7 BBO; the total gas reserves and resources range from a P_(90) of 53.4 to P_(10) of 313.5 trillion cubic feet (TCF), with a P_(50) of 121.7 TCF. These reserves and resources estimates are much higher than the U.S. Energy Information Administration?s 2011 recoverable resource estimates of 3.35 BBO and 21 TCF. The results of this study provide a critical update on the reserves and resources estimates and their associated uncertainties for the Eagle Ford shale formation of South Texas.Item Bakken Shale Oil Production Trends(2012-07-16) Tran, TanAs the conventional reservoirs decrease in discovering, producing and reserving, unconventional reservoirs are more remarkable in terms of discovering, development and having more reserve. More fields have been discovered where Barnett Shale and Bakken Shale are the most recently unconventional reservoir examples. Shale reservoirs are typically considered self-sourcing and have very low permeability ranging from 10-100 nanodarcies. Over the past few decades, numerous research projects and developments have been studied, but it seems there is still some contention and misunderstanding surrounding shale reservoirs. One of the largest shale in the United State is the Bakken Shale play. This study will describe the primary geologic characteristics, field development history, reservoir properties,and especially production trends, over the Bakken Shale play. Data are available for over hundred wells from different companies. Most production data come from the Production Data Application (HDPI) database and in the format of monthly production for oil, water and gas. Additional 95 well data including daily production rate, completion, Pressure Volume Temperature (PVT), pressure data are given from companies who sponsor for this research study. This study finds that there are three Types of well production trends in the Bakken formation. Each decline curve characteristic has an important meaning to the production trend of the Bakken Shale play. In the Type I production trend, the reservoir pressure drops below bubble point pressure and gas releasingout of the solution. With the Type II production trend, oil flows linearly from the matrix into the fracture system, either natural fracture or hydraulic fracture. Reservoir pressure is higher than the bubble point pressure during the producing time and oil flows as a single phase throughout the production period of the well. A Type III production trend typically has scattering production data from wells with a different Type of trend. It is difficult to study this Type of behavior because of scattering data, which leads to erroneous interpretation for the analysis. These production Types, especially Types I and II will give a new type curve matches for shale oil wells above or below the bubble point.Item Fast Marching Method with Multiphase Flow and Compositional Effects(2014-08-06) Fujita, YusukeIn current petroleum industry, there is a lack of effective reservoir simulators for modeling shale and tight sand reservoirs. An unconventional resource modeling requires an accurate flow characterization of complex transport mechanisms caused by the interactions among fractures, inorganic matrices, and organic rocks. Pore size in shale and tight sand reservoirs typically ranges in nanometers, which results in ultralow permeability (nanodarcies) and a high capillary pressure in the confined space. In such extremely low permeability reservoirs, adsorption/desorption and diffusive flow processes play important roles for a fluid flow behavior in addition to heterogeneity-driven convective flow. In this study, the concept of ?Diffusive Time of Flight? (DTOF) is generalized for multiphase and multicomponent flow problems on the basis of the asymptotic theory. The proposed approach consists of two decoupled steps ? (1) calculation of well drainage volumes along a propagating ?peak? pressure front, and (2) numerical simulation based on the transformed 1-D coordinates. Geological heterogeneities distributed in 3-D space are integrated by tracking the propagation of ?peak? pressure front using a ?Fast Marching Method? (FMM), and subsequently, the drainage volumes are evaluated along the outwardly propagation contours. A DTOF-based numerical simulation is performed by treating a series of the DTOF as a spatial coordinate. This approach is analogous to streamline simulation, whereby a multidimensional simulation is transformed into 1-D coordinates resulting in substantial savings in computational time, thus allowing for high resolution simulation. However, instead of using a convective time of flight (CTOF), a diffusive time of flight is introduced in the modeling of a pressure front propagation. The overall workflow, which consist of the FMM and numerical simulation, is described in detail for single-phase, two-phase, blackoil, and compositional cases. The model validation is firstly performed on single-porosity systems with and without geological heterogeneity, then extended to multi-continuum domains including dual-porosity fractured reservoir and triple-continuum system. The large-scale unconventional models are finally demonstrated in consideration of the permeability correction for shale gas system and capillarity incorporation for confined phase behavior in multiphase shale oil system.