Browsing by Subject "Reservoir simulators"
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Item Development of an implicit full-tensor dual porosity compositional reservoir simulator(2008-12) Tarahhom, Farhad; Sepehrnoori, Kamy, 1951-A large percentage of oil and gas reservoirs in the most productive regions such as the Middle East, South America, and Southeast Asia are naturally fractured reservoirs (NFR). The major difference between conventional reservoirs and naturally fractured reservoirs is the discontinuity in media in fractured reservoir due to tectonic activities. These discontinuities cause remarkable difficulties in describing the petrophysical structures and the flow of fluids in the fractured reservoirs. Predicting fluid flow behavior in naturally fractured reservoirs is a challenging area in petroleum engineering. Two classes of models used to describe flow and transport phenomena in fracture reservoirs are discrete and continuum (i.e. dual porosity) models. The discrete model is appealing from a modeling point of view, but the huge computational demand and burden of porting the fractures into the computational grid are its shortcomings. The affect of natural fractures on the permeability anisotropy can be determined by considering distribution and orientation of fractures. Representative fracture permeability, which is a crucial step in the reservoir simulation study, must be calculated based on fracture characteristics. The diagonal representation of permeability, which is customarily used in a dual porosity model, is valid only for the cases where fractures are parallel to one of the principal axes. This assumption cannot adequately describe flow characteristics where there is variation in fracture spacing, length, and orientation. To overcome this shortcoming, the principle of the full permeability tensor in the discrete fracture network can be incorporated into the dual porosity model. Hence, the dual porosity model can retain the real fracture system characteristics. This study was designed to develop a novel approach to integrate dual porosity model and full permeability tensor representation in fractures. A fully implicit, parallel, compositional chemical dual porosity simulator for modeling naturally fractured reservoirs has been developed. The model is capable of simulating large-scale chemical flooding processes. Accurate representation of the fluid exchange between the matrix and fracture and precise representation of the fracture system as an equivalent porous media are the key parameters in utilizing of dual porosity models. The matrix blocks are discretized into both rectangular rings and vertical layers to offer a better resolution of transient flow. The developed model was successfully verified against a chemical flooding simulator called UTCHEM. Results show excellent agreements for a variety of flooding processes. The developed dual porosity model has further been improved by implementing a full permeability tensor representation of fractures. The full permeability feature in the fracture system of a dual porosity model adequately captures the system directionality and heterogeneity. At the same time, the powerful dual porosity concept is inherited. The implementation has been verified by studying water and chemical flooding in cylindrical and spherical reservoirs. It has also been verified against ECLIPSE and FracMan commercial simulators. This study leads to a conclusion that the full permeability tensor representation is essential to accurately simulate fluid flow in heterogeneous and anisotropic fracture systems.Item Modeling chemical EOR processes using IMPEC and fully IMPLICIT reservoir simulators(2009-08) Fathi Najafabadi, Nariman; Delshad, Mojdeh; Sepehrnoori, Kamy, 1951-As easy target reservoirs are depleted around the world, the need for intelligent enhanced oil recovery (EOR) methods increases. The first part of this work is focused on modeling aspects of novel chemical EOR methods for naturally fractured reservoirs (NFR) involving wettability modification towards more water wet conditions. The wettability of preferentially oil wet carbonates can be modified to more water wet conditions using alkali and/or surfactant solutions. This helps the oil production by increasing the rate of spontaneous imbibition of water from fractures into the matrix. This novel method cannot be successfully implemented in the field unless all of the mechanisms involved in this process are fully understood. A wettability alteration model is developed and implemented in the chemical flooding simulator, UTCHEM. A combination of laboratory experimental results and modeling is then used to understand the mechanisms involved in this process and their relative importance. The second part of this work is focused on modeling surfactant/polymer floods using a fully implicit scheme. A fully implicit chemical flooding module with comprehensive oil/brine/surfactant phase behavior is developed and implemented in general purpose adaptive simulator, GPAS. GPAS is a fully implicit, parallel EOS compositional reservoir simulator developed at The University of Texas at Austin. The developed chemical flooding module is then validated against UTCHEM.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.