The multiobjective genetic algorithm can be used to optimize two conflicting objectives, oil production and polymer utility factor in polymer flood design. This approach provides a set of optimal solutions which can be considered as trade-off curve (Pareto front) to maximize oil production while preserving polymer performance. Then an optimal polymer flood design can be considered from post-optimization analysis. A 2D synthetic example, and a 3D field-scale application, accounting for geologic uncertainty, showed that beyond the optimal design, a relatively minor increase in oil production requires much more polymer injection and the polymer utility factor increases substantially.

With the depletion of the existing reservoirs and the decline in oil discoveries during the last few decades, enhanced oil recovery (EOR) methods have gained a lot of attention. Among the various improved recovery methods, waterflooding is by far the most widely used. However, the presence of reservoir heterogeneity such as high permeability streaks often leads to premature breakthrough and poor sweep resulting in reduced oil recovery. This underscores the need for a prudent reservoir management, in terms of optimal production and injection rates, to maximize recovery. The increasing deployment of smart well completions and i-field has inspired many researchers to develop algorithms to optimize the production/injection rates along intervals of smart wells. However, the application of rate control for other EOR methods has been relatively few. This research aims to extend previous streamline-based rate optimization workflow to polymer flooding and CO2 flooding. The objective of the approach is to maximize sweep efficiency and minimize recycling of injected fluid (polymer/CO2) by delaying its breakthrough. This is achieved by equalizing the front arrival time at the producers using streamline time-of-flight. Arrival time is rescaled to allow for optimization after breakthrough of injected fluid. Additionally, we propose an accelerated production strategy to increase NPV over sweep efficiency maximization case. The optimization is performed under operational and facility constraints using a sequential quadratic programming approach. The geological uncertainty has been accounted via a stochastic optimization framework based on the combination of the expected value and variance of a performance measure from multiple realizations. Synthetic and field examples are used extensively to demonstrate the practical feasibility and robustness of our approach for application to EOR processes.

Reservoir pressure and solution gas can significantly alter the microemulsion phase behavior and the design of a surfactant-polymer flood. This dissertation shows how to predict changes in microemulsion phase behavior from dead oil at atmospheric pressure to live crude at reservoir pressure. Our method requires obtaining only a few glass pipette measurements of microemulsion phase behavior at atmospheric pressure. The key finding is that at reservoir pressure the optimum solubilization ratio and the logarithm of optimal salinity behave linearly with equivalent alkane carbon number (EACN). These trends are predicted from the experimental data at atmospheric pressure based on density calculations of pure components using the Peng-Robinson equation-of-state (PREOS). We show that predictions of the optimum conditions for live oil are in good agreement with the few experimental measurements that are available in the literature. We also present new measurements at atmospheric pressure to verify the established trends. The experiments show that while pressure induces a phase transition from upper microemulsion (Winsor Type II+) to lower microemulsion (Winsor Type II-), solution gas does the opposite. An increase in pressure decreases the optimum solubilization ratio and shifts the optimum salinity to a larger value. Adding methane to dead oil at constant pressure does the reverse. Thus, these effects are coupled and both must be taken into account. We show using a numerical simulator that these changes in the optimum conditions can impact oil recovery if not accounted for in the SP design. / text

Chemical enhanced oil recovery has regained its attention because of high oil price and the depletion of conventional oil reservoirs. This process is more complex than the primary and secondary recovery flooding and requires detailed engineering design for a successful field-scale application. An effective alkaline/co-solvent/polymer (ACP) formulation was developed and corefloods were performed for a cost efficient alternative to alkaline/surfactant/polymer floods by the research team at the department of Petroleum and Geosystems Engineering at The University of Texas at Austin. The alkali agent reacts with the acidic components of heavy oil (i.e. 170 cp in-situ viscosities) to form in-situ natural soap to significantly reduce the interfacial tension, which allows producing residual oil not contacted by waterflood or polymer flood alone. Polymer provides mobility control to drive chemical slug and oil bank. The cosolvent added to the chemical slug helps to improve the compatibility between in-situ soap and polymer and to reduce microemulsion viscosity. An impressive recovery of 70% of the waterflood residual oil saturation was achieved where the remaining oil saturation after the ACP flood was reduced to only 13.5%. The results were promising with very low chemical usage for injection. The UTCHEM chemical flooding reservoir simulator was used to model the coreflood experiments to obtain parameters for pilot scale simulations. Geological model was based on unconsolidated reservoir sand with multiple seven spot well patterns. However, facility capacity and field logistics, reservoir heterogeneity as well as mixing and dispersion effects might prevent coreflood design at laboratory from large scale implementation. Field-scale sensitivity studies were conducted to optimize the design under uncertainties. The influences of chemical mass, polymer pre-flush, well constraints, and well spacing on ultimate oil recovery were closely investigated. This research emphasized the importance of good mobility control on project economics. The in-situ soap generated from alkali-naphthenic acid reaction not only mobilizes residual oil to increase oil recovery, but also enhances water relative permeability and increases injectivity. It was also demonstrated that a closer well spacing significantly increases the oil recovery because of greater volumetric sweep efficiency. This thesis presents the simulation and modeling results of an ACP process for a viscous oil in high permeability sandstone reservoir at both coreflood and pilot scales. / text