Browsing by Subject "reservoir simulation"
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Item A numerical sensitivity analysis of streamline simulation(Texas A&M University, 2005-02-17) Chaban Habib, Fady RubenNowadays, field development strategy has become increasingly dependent on the results of reservoir simulation models. Reservoir studies demand fast and efficient results to make investment decisions that require a reasonable trade off between accuracy and simulation time. One of the suitable options to fulfill this requirement is streamline reservoir simulation technology, which has become very popular in the last few years. Streamline (SL) simulation provides an attractive alternative to conventional reservoir simulation because SL offers high computational efficiency and minimizes numerical diffusion and grid orientation effects. However, streamline methods have weaknesses incorporating complex physical processes and can also suffer numerical accuracy problems. The main objective of this research is to evaluate the numerical accuracy of the latest SL technology, and examine the influence of different factors that may impact the solution of SL simulation models. An extensive number of numerical experiments based on sensitivity analysis were performed to determine the effects of various influential elements on the stability and results of the solution. Those experiments were applied to various models to identify the impact of factors such as mobility ratios, mapping of saturation methods, number of streamlines, time step sizes, and gravity effects. This study provides a detailed investigation of some fundamental issues that are currently unresolved in streamline simulation.Item Analytical Estimation of CO2 Storage Capacity in Depleted Oil and Gas Reservoirs Based on Thermodynamic State Functions(2012-02-14) Valbuena Olivares, ErnestoNumerical simulation has been used, as common practice, to estimate the CO2 storage capacity of depleted reservoirs. However, this method is time consuming, expensive and requires detailed input data. This investigation proposes an analytical method to estimate the ultimate CO2 storage in depleted oil and gas reservoirs by implementing a volume constrained thermodynamic equation of state (EOS) using the reservoir?s average pressure and fluid composition. This method was implemented in an algorithm which allows fast and accurate estimations of final storage, which can be used to select target storage reservoirs, and design the injection scheme and surface facilities. Impurities such as nitrogen and carbon monoxide, usually contained in power plant flue gases, are considered in the injection stream and can be handled correctly in the proposed algorithm by using their thermodynamic properties into the EOS. Results from analytical method presented excellent agreement with those from reservoir simulation. Ultimate CO2 storage capacity was predicted with an average difference of 1.3%, molar basis, between analytical and numerical methods; average oil, gas, and water saturations were also matched. Additionally, the analytical algorithm performed several orders of magnitude faster than numerical simulation, with an average of 5 seconds per run.Item Flood control reservoir operations for conditions of limited storage capacity(Texas A&M University, 2005-02-17) Rivera Ramirez, Hector DavidThe main objective of this research is to devise a risk-based methodology for developing emergency operation schedules (EOS). EOS are decision tools that provide guidance to reservoir operators in charge of making real-time release decisions during major flood events. A computer program named REOS was created to perform the computations to develop risk-based EOS. The computational algorithm in REOS is divided in three major components: (1) synthetic streamflow generation, (2) mass balance computations, and (3) frequency analysis. The methodology computes the required releases to limit storage to the capacity available based on the probabilistic properties of future flows, conditional to current streamflow conditions. The final product is a series of alternative risk-based EOS in which releases, specified as a function of reservoir storage level, current and past inflows, and time of year, are associated with a certain risk of failing to attain the emergency operations objectives. The assumption is that once emergency operations are triggered by a flood event, the risk associated with a particular EOS reflects the probability of exceeding a pre-established critical storage level given that the same EOS is followed throughout the event. This provides reservoir operators with a mechanism for evaluating the tradeoffs and potential consequences of release decisions. The methodology was applied and tested using the Addicks and Barker Reservoir system in Houston, TX as a case study. Upstream flooding is also a major concern for these reservoirs. Modifications to the current emergency policies that would allow emergency releases based on the probability of upstream flooding are evaluated. Riskbased EOS were tested through a series of flood control simulations. The simulations were performed using the HEC-ResSim reservoir simulation model. Rainfall data recorded from Tropical Storm Allison was transposed over the Addicks and Barker watersheds to compute hypothetical hydrographs using HEC-HMS. Repeated runs of the HEC-ResSim model were made using different flooding and residual storage scenarios to compare regulation of the floods under alternative operating policies. An alternative application of the risk-based EOS in which their associated risk was used to help quantify the actual probability of upstream flooding in Addicks and Barker was also presented.Item Optimizing Development Strategies to Increase Reserves in Unconventional Gas Reservoirs(2011-10-21) Turkarslan, GulcanThe 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.Item Reservoir Simulation Used to Plan Diatomite Developement in Mountainous Region(2012-10-19) Powell, RichardIn Santa Barbara County, Santa Maria Pacific (an exploration and production company) is expanding their cyclic steam project in a diatomite reservoir. The hilly or mountainous topography and cut and fill restrictions have interfered with the company's ideal development plan. The steep hillsides prevent well pad development for about 22 vertical well locations in the 110 well expansion plan. Conventional production performs poorly in the area because the combination of relatively low permeability (1-10 md) and high viscosity (~220 cp) at the reservoir temperature. Cyclic steam injection has been widely used in diatomite reservoirs to take advantage of the diatomite rocks unique properties and lower the viscosity of the oil. Some companies used deviated wells for cyclic steam injection, but Santa Maria Pacific prefers the use only vertical wells for the expansion. Currently, the inability to create well pads above 22 vertical well target locations will result in an estimated $60,000,000 of lost revenue over a five year period. The target locations could be developed with unstimulated deviated or horizontal wells, but expected well rates and expenses have not been estimated. In this work, I use a thermal reservoir simulator to estimate production based on five potential development cases. The first case represents no development other than the cyclic wells. This case is used to calibrate the model based on the pilot program performance and serves as a reference point for the other cases. Two of the cases simulate a deviated well with and without artificial lift next to a cyclic well, and the final two cases simulate a horizontal well segment with and without artificial lift next to a cyclic well. The deviated well with artificial lift results in the highest NPV and profit after five years. The well experienced pressure support from the neighboring cyclic well and performed better with the cyclic well than without it. Adding 22 deviated wells with artificial lift will increase the project's net profit by an estimated $7,326,000 and NPV by $2,838,000 after five years.Item Rigorous Simulation Model of Kerogen Pyrolysis for the In-situ Upgrading of Oil Shales(2014-10-09) Lee, Kyung JaeOil shale is a vast, yet untapped energy source, and the pyrolysis of kerogen in the oil shales releases recoverable hydrocarbons. In this dissertation, we investigate how to increase process efficiency and decrease the costs of in-situ upgrading process for kerogen pyrolysis, which is applicable to the majority of the oil shales. In-situ upgrading processes include (a) Shell In-situ Conversion Process (ICP), (b) ExxonMobil Electrofrac, and (c) Texas A&M (TAMU) Steamfrac. We evaluate these three processes in realistic scenarios using our newly developed multi-phase, multi-component, nonisothermal simulator. Kerogen pyrolysis is represented by 6 kinetic reactions resulting in 10 components and 4 phases. Expanding TAMU Flow and Transport Simulator (FTSim), we develop a fully functional capability that describes the kerogen pyrolysis and the accompanying system changes. The simulator describes the coupled process of mass transport and heat flow through porous and fractured media, and accurately accounts for phase equilibria and transitions. It provides a powerful tool to evaluate the efficiency and the productivity of the in-situ upgrading processes. We validate our simulator by reproducing the field production data of the Shell ICP implemented in Green River Formation. We conduct the sensitivity analyses of the presence and absence of pre-existing fracture system, oil shale grade, permeability of the fracture network, and thermal conductivity of the formation. Validated model has the oil shale grade of 25 gal/ton, fracture domain permeability of 150 md, and formation thermal conductivity of 2.0 W/m-K. In the application cases, we analyze the significant factors affecting each process. In the Shell ICP, the ExxonMobil Electrofrac, and the TAMU Steamfrac, we study the effects of heater temperature, electrical conductivities of injection material, and steam injection strategy, respectively. We find that the best case of the Shell ICP showed the highest energy efficiency of 144 %. The best cases of the ExxonMobil Electrofrac and the TAMU Steamfrac show the energy efficiency of 74.1 %, and 54.1 %, respectively. We obtain positive Net Present Value (NPV) in the TAMU Steamfrac by much less number of wells than the Shell ICP and the ExxonMobil Electrofrac, though it has the lowest energy efficiency.Item Study of Flow Regimes in Multiply-Fractured Horizontal Wells in Tight Gas and Shale Gas Reservoir Systems(2010-07-14) Freeman, Craig M.Various analytical, semi-analytical, and empirical models have been proposed to characterize rate and pressure behavior as a function of time in tight/shale gas systems featuring a horizontal well with multiple hydraulic fractures. Despite a small number of analytical models and published numerical studies there is currently little consensus regarding the large-scale flow behavior over time in such systems. The purpose of this work is to construct a fit-for-purpose numerical simulator which will account for a variety of production features pertinent to these systems, and to use this model to study the effects of various parameters on flow behavior. Specific features examined in this work include hydraulically fractured horizontal wells, multiple porosity and permeability fields, desorption, and micro-scale flow effects. The theoretical basis of the model is described in Chapter I, along with a validation of the model. We employ the numerical simulator to examine various tight gas and shale gas systems and to illustrate and define the various flow regimes which progressively occur over time. We visualize the flow regimes using both specialized plots of rate and pressure functions, as well as high-resolution maps of pressure distributions. The results of this study are described in Chapter II. We use pressure maps to illustrate the initial linear flow into the hydraulic fractures in a tight gas system, transitioning to compound formation linear flow, and then into elliptical flow. We show that flow behavior is dominated by the fracture configuration due to the extremely low permeability of shale. We also explore the possible effect of microscale flow effects on gas effective permeability and subsequent gas species fractionation. We examine the interaction of sorptive diffusion and Knudsen diffusion. We show that microscale porous media can result in a compositional shift in produced gas concentration without the presence of adsorbed gas. The development and implementation of the micro-flow model is documented in Chapter III. This work expands our understanding of flow behavior in tight gas and shale gas systems, where such an understanding may ultimately be used to estimate reservoir properties and reserves in these types of reservoirs.Item The effects of incorporating dynamic data on estimates of uncertainty(Texas A&M University, 2004-09-30) Mulla, Shahebaz HisamuddinPetroleum exploration and development are capital intensive and smart economic decisions that need to be made to profitably extract oil and gas from the reservoirs. Accurate quantification of uncertainty in production forecasts will help in assessing risk and making good economic decisions. This study investigates the effect of combining dynamic data with the uncertainty in static data to see the effect on estimates of uncertainty in production forecasting. Fifty permeability realizations were generated for a reservoir in west Texas from available petrophysical data. We quantified the uncertainty in the production forecasts using a likelihood weighting method and an automatic history matching technique combined with linear uncertainty analysis. The results were compared with the uncertainty predicted using only static data. We also investigated approaches for best selecting a smaller number of models from a larger set of realizations to be history matched for quantification of uncertainty. We found that incorporating dynamic data in a reservoir model will result in lower estimates of uncertainty than considering only static data. However, incorporation of dynamic data does not guarantee that the forecasted ranges will encompass the true value. Reliability of the forecasted ranges depends on the method employed. When sampling multiple realizations of static data for history matching to quantify uncertainty, a sampling over the entire range of realization likelihoods shows larger confidence intervals and is more likely to encompass the true value for predicted fluid recoveries, as compared to selecting the best models.Item The Optimization of Well Spacing in a Coalbed Methane Reservoir(2012-02-14) Sinurat, Pahala DominicusNumerical reservoir simulation has been used to describe mechanism of methane gas desorption process, diffusion process, and fluid flow in a coalbed methane reservoir. The reservoir simulation model reflects the response of a reservoir system and the relationship among coalbed methane reservoir properties, operation procedures, and gas production. This work presents a procedure to select the optimum well spacing scenario by using a reservoir simulation. This work uses a two-phase compositional simulator with a dual porosity model to investigate well-spacing effects on coalbed methane production performance and methane recovery. Because of reservoir parameters uncertainty, a sensitivity and parametric study are required to investigate the effects of parameter variability on coalbed methane reservoir production performance and methane recovery. This thesis includes a reservoir parameter screening procedures based on a sensitivity and parametric study. Considering the tremendous amounts of simulation runs required, this work uses a regression analysis to replace the numerical simulation model for each wellspacing scenario. A Monte Carlo simulation has been applied to present the probability function. Incorporated with the Monte Carlo simulation approach, this thesis proposes a well-spacing study procedure to determine the optimum coalbed methane development scenario. The study workflow is applied in a North America basin resulting in distinct Net Present Value predictions between each well-spacing design and an optimum range of well-spacing for a particular basin area.