Browsing by Subject "Oil reservoirs"
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Item Experimental study of microemulsion characterization and optimization in enhanced oil recovery : a design approach for reservoirs with high salinity and hardness(2007-12) Flaaten, Adam Knut; Nguyen, Quoc P.; Pope, G.A.The objective of this research was to develop a systematic laboratory approach, and design a high performance chemical flood for a problematic reservoir with formation brine having high salinity and hardness. Aqueous and microemulsion phase behavior tests have previously been shown to be a rapid, inexpensive and highly effective means to select the best chemicals and minimize the need for relatively expensive core flood tests. Phase behavior tests were therefore done with various combinations of surfactants, co-solvents and alkali for several crude oils and reservoir conditions, including the problematic reservoir of interest for design. Extensive phase behavior testing identified performance trends of chemicals at different concentrations, which could be interpolated for optimization. The trends were ultimately used to develop an approach to design potential chemical flood formulations for the problematic reservoir of interest. Using this approach, several formulations were designed showing good performance in phase behavior testing. One of the formulations was then validated in a core flood experiment to give nearly 100% oil recovery with very low surfactant adsorption. The chemical flood design used a salinity gradient that was robust enough with withstand the sharp salinity contrast of the formation brine and surfactant slug at the displacement front. Salinity analysis of core flood effluent showed how Type III microemulsion conditions were targeted to most effectively mobilize residual oil.Item Numerical simulation of ph-sensitive polymer injection as a conformance control method(2007-05) Benson, Ian Phillip, 1978-; Sharma, Mukul M.; Bryant, Steven L.; Huh, ChunPolymers such as polyacrylic acid hydrogel are microgel solutions that exhibit large viscosity changes as their pH increases above a critical value. The Huh-Choi-Sharma rheological model developed previously for pH-sensitive polymer was successfully implemented in the commercial GEM-GHG reservoir simulator and tested. With the simulator’s ability to model geochemical reactions and to predict fluid pH, the polymer viscosity model allowed estimation of polymer solution viscosity based on the pH, ionic strength, shear rate and polymer concentration of an aqueous solution. Simulations of linear and radial geometry floods were carried out to test the effectiveness of using high-viscosity fluids and pH-sensitive polymers as an in-depth conformance control method in oil reservoirs.Item Reservoir characterization and sequence stratigraphy of Permian San Andres platform carbonates, Fullerton Field, Permian Basin, West Texas(2010-05) Helbert, Dana Kristin; Kerans, C. (Charles), 1954-; Ruppel, Stephen C.; Fisher, William L.The San Andres Formation (Permian, Guadalupian) is the most prolific oil reservoir in the Permian basin. However, despite more than 60 years of production, an estimated 70% of the original oil in place remains. Recovery of this huge resource requires a better understanding of facies and reservoir framework, which, in turn, must be accomplished using a rock-based reservoir characterization process. This high resolution correlation method is essential for understanding the complex heterogeneities found in shallow water platform carbonates. Steps in the construction of a rock-based reservoir model in the Fullerton San Andres Unit (FSAU) included (1) defining depositional facies and primary facies groups; (2) creating an outcrop depositional model; (3) integrating facies descriptions with gamma-ray and porosity log data; (3) defining field-wide high frequency sequences based on wireline logs and cycle stacking patterns; (4) developing a sequence-based reservoir framework and 3-dimensional reservoir architecture; (5) defining porosity and permeability relationships for facies groups based on rock fabric characteristics. In Fullerton Field, the San Andres Formation comprises high frequency cycles of upward shoaling shallow-marine carbonates. Studies of nine cores (1730 ft) in FSAU reveal four peritidal and five shallow subtidal depositional facies based on texture, fossil assemblages, and sedimentary structures. Peritidal facies are dominantly laminated carbonate mudstones, interpreted as deposited on an intermittently exposed tidal flat. Shallow subtidal facies are peloid and mollusk dominated wackestones and packstones, interpreted as deposited in a shallow protected lagoon. Cycle stacking patterns indicate four complete upward shallowing high frequency sequences. Comparison of high frequency sequences between cored wells shows a high degree of similarity in the overall generalized vertical sequence, especially in the proportions of peritidal and subtidal components within each sequence. Three-dimensional reservoir characterization, using 132 gamma ray and porosity logs, reveals that depositional sequences are largely flat-lying with local topographic variation identified as the fundamental influence on lateral facies distribution within the reservoir section. Integration of core and petrophysical data from surrounding fields places FSAU in the larger sequence stratigraphic framework of the Central Basin Platform. The regional depositional sequence formed a series of depositional environments ranging from intermittently exposed to open marine. San Andres facies developed during south-easterly progradation of shallow water tidal flat and sabkha sediments over a deeper open marine shelf.Item The use of capacitance-resistance models to optimize injection allocation and well location in water floods(2009-08) Weber, Daniel Brent; Edgar, Thomas F.; Lake, Larry W.Reservoir management strategies traditionally attempt to combine and balance complex geophysical, petrophysical, thermodynamic and economic factors to determine an optimal method to recover hydrocarbons from a given reservoir. Reservoir simulators have traditionally been too large and run times too long to allow for rigorous solution in conjunction with an optimization algorithm. It has also proven very difficult to marry an optimizer with the large set of nonlinear partial differential equations required for accurate reservoir simulation. A simple capacitance-resistance model (CRM) that characterizes the connectivity between injection and production wells can determine an injection scheme maximizes the value of the reservoir asset. Model parameters are identified using linear and nonlinear regression. The model is then used together with a nonlinear optimization algorithm to compute a set of future injection rates which maximize discounted net profit. This research demonstrates that this simple dynamic model provides an excellent match to historic data. Based on three case studies examining actual reservoirs, the optimal injection schemes based on the capacitance-resistive model yield a predicted increase in hydrocarbon recovery of up to 60% over the extrapolated exponential historic decline. An advantage of using a simple model is its ability to describe large reservoirs in a straightforward way with computation times that are short to moderate. However, applying the CRM to large reservoirs with many wells presents several new challenges. Reservoirs with hundreds of wells have longer production histories – new wells are created, wells are shut in for varying periods of time and production wells are converted to injection wells. Additionally, ensuring that the production data to which the CRM is fit are free from contamination or corruption is important. Several modeling techniques and heuristics are presented that provide a simple, accurate reservoir model that can be used to optimize the value of the reservoir over future time periods. In addition to optimizing reservoir performance by allocating injection, this research presents a few methods that use the CRM to find optimal well locations for new injectors. These algorithms are still in their infancy and represent the best ideas for future research.