This study aims to investigate the effect of elastic properties of viscoelastic polymer solutions on the microscopic sweep efficiency in enhanced oil recovery (EOR) operations. The effect of elasticity was studied as isolated from the shear viscosity effect using polymer blends with identical shear viscosity behavior but different elastic characteristics. Oil displacement results were compared and the individual effect of elasticity on the sweep efficiency was investigated. A detailed rheological characterization of the polymer solutions was done to measure their viscoelastic properties. A series of polymer flooding experiments were performed using a radial core holder. Results of the experiments indicated that the sweep efficiency of a polymeric fluid could be effectively improved by adjusting the molecular weight distribution (MWD) of the solution at constant shear viscosity and polymer concentration. An attempt was made to find a rheological parameter of polymer solutions that correlates better with the resultant oil recovery. / Petroleum Engineering

Waterflooding has been used for many decades as a way of recovering oil from petroleum reservoirs. Historically the salinity of the injection water has not been regarded as a key variable in determining the amount of oil recovered. In recent years, however, evidence of increased oil recovery by injection of low salinity water has been observed in laboratories and fields. The technique is getting wider attention in the oil industry because it is more cost-effective than other EOR techniques. The present work demonstrates the synergy of low salinity water flooding and polymer flooding in the laboratory scale. The use of low salinity polymer solution in polymer flooding has significant benefits because considerably lower amount of polymer is required to make the solution of a target viscosity. Low salinity polymer flooding can also increase oil recovery by lowering residual oil saturation and achieve faster oil recovery by improving sweep efficiency. Several coreflood experiments were conducted to study the efficiency of low salinity water flooding and low salinity polymer flooding in mixed-wet Berea sandstone cores. All the core samples were aged with a crude oil at 90oC for 30-60 days before the tests. All the polymer floods were conducted in the tertiary mode. A synthetic formation brine (33,800 ppm) was chosen for high salinity water and a NaCl brine (1,000 ppm) for low salinity water. Medium molecular weight HPAM polymer, FlopaamTM 3330S was used due to the low/moderate permeability of the Berea sandstone cores used in this study. Coreflood tests indicate that injection of low salinity polymer solution reduces residual oil saturation by 5-10% over that of the high salinity waterflood. A part of the residual saturation reduction is due to low salinity and this reduction is achieved in less pore volumes of injection in the presence of polymers. Effluent ion analysis from both low salinity water flooding and low salinity polymer flooding showed a slight increase in divalent cation concentrations after the polymer breakthrough. Cation bridging may play a role in oil wettability and low salinity injection desorbs some of these cations. / text

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With the depletion of oil reserves and increase in oil price, the enhanced oil recovery methods such as polymer flooding to increase oil production from water flooded fields are becoming more attractive. Effective design of these processes is challenging because the polymer chemistry has a strong effect on reaction and fluid rheology, which in turn has a strong effect on fluid transport. We have implemented a well-established polymer model within the Implicit Parallel Accurate Reservoir Simulator (IPARS), which enables parallel simulation of non-Newtonian fluid flow through porous media. The following properties of polymer solution are modeled in this work: 1) polymer adsorption; 2) polymer viscosity as a function of salinity, hardness, polymer concentration, and shear rate; 3) permeability reduction; 4) inaccessible pore volume. IPARS enables field-scale polymer flooding simulation with its parallel computation capability. In this thesis, several numerical examples are presented. The result of polymer module is verified by UTCHEM, a three-dimensional chemical flood simulator developed at the University of Texas at Austin. The parallel capability is also tested. The influence of different shear rate calculations is investigated in homogeneous and heterogeneous reservoirs. We observed that the wellbore velocity calculation instead of Darcy velocity reduces the grid effect for coarse mesh. We noted that the injection bottom hole pressure is very sensitive to the shear rate calculation. However, cumulative oil recovery and overall oil saturation appear to not be sensitive to grid and shear rate calculation for same reservoir. There are two models to model the ground water infiltration in vadose zone. One is Richard’s Equation (RE) model. And the other is two-phase flow model. In this work, we compare the two-phase model with an RE model to ascertain, under common scenarios such as infiltration or injection of water into initially dry soils, the similarities and differences in solutions behaviors, the ability of each model to simulate such infiltration processes under realistic scenarios, and to investigate the numerical efficiencies and difficulties which arise in these models. Six different data sets were assembled as benchmark infiltration problems in the unsaturated zone. The comparison shows that two-phase model holds for general porous media and is not limited by several assumptions that must be made for the RE formulation, while RE is applicable only for shallow regions (vadose) that are only several meters in depth and a fully saturated bottom boundary condition must be assumed. / text

The depletion of oil reserves and higher oil prices has made chemical enhanced oil recovery (EOR) methods more attractive in recent years. Because of geological heterogeneity, unfavorable mobility ratio, and capillary forces, conventional oil recovery (including water flooding) leaves behind much oil in reservoir, often as much as 70% OOIP (original oil in place). Surfactant/polymer flooding targets these bypassed oil left after waterflood by reducing water mobility and oil/water interfacial tension. The complexity and uncertainty of reservoir characterization make the design and implementation of a robust and effective surfactant/polymer flooding to be quite challenging. Accurate numerical simulation prior to the field surfactant/polymer flooding is essential for a successful design and implementation of surfactant/polymer flooding. A recently developed unified polymer viscosity model was implemented into our existing polymer module within our in-house reservoir simulator, the Implicit Parallel Accurate Reservoir Simulator (IPARS). The new viscosity model is capable of simulating not only the Newtonian and shear-thinning rheology of polymer solution but also the shear-thickening behavior, which may occur near the wellbore with high injection rates when high molecular weight Partially Hydrolyzed Acrylamide (HPAM) polymers are injected. We have added a full capability of surfactant/polymer flooding to TRCHEM module of IPARS using a simplified but mechanistic and user-friendly approach for modeling surfactant/water/oil phase behavior. The features of surfactant module include: 1) surfactant component transport in porous media; 2) surfactant adsorption on the rock; 3) surfactant/oil/water phase behavior transitioned with salinity of Type II(-), Type III, and Type II(+) phase behaviors; 4) compositional microemulsion phase viscosity correlation and 5) relative permeabilities based on the trapping number. With the parallel capability of IPARS, commercial scale simulation of surfactant/polymer flooding becomes practical and affordable. Several numerical examples are presented in this dissertation. The results of surfactant/polymer flood are verified by comparing with the results obtained from UTCHEM, a three-dimensional chemical flood simulator developed at the University of Texas at Austin. The parallel capability and scalability are also demonstrated. / text

This thesis presents a framework for history matching and model calibration of surfactant-polymer (SP) flooding. At first, a high-fidelity mechanistic SP flood model is constructed by performing extensive lab-scale experiments on Berea cores. Then, incorporating Sobol based sensitivity analysis, polynomial chaos expansion based surrogate modelling (PCE-proxy) and Genetic algorithm based inverse optimization, an optimized model parameter set is determined by minimizing the miss-fit between PCE-proxy response and experimental observations for quantities of interests such as cumulative oil recovery and pressure profile. The epistemic uncertainty in PCE-proxy is quantified using a Gaussian regression process called Kriging. The framework is then extended to Bayesian calibration where the posterior of model parameters is inferred by directly sampling from it using Markov chain Monte Carlo (MCMC). Finally, a stochastic multi-objective optimization problem is posed under uncertainties in model parameters and oil price which is solved using a variant of Bayesian global optimization routine. <br>

Many attempts have been made to control water conformance. It is very costly to produce, treat and dispose of water, and produced water represents the largest waste stream associated with oil and gas production. The production of large amounts of water results in: (a) the need for more complex water?oil separation; (b) corrosion of wellbore and other equipment; (c) a rapid decline in hydrocarbon production rate and ultimate recovery; and (d) consequently, premature abandonment of a well or field, leaving considerable hydrocarbons unproduced. Sometimes water production results from heterogeneities in the horizontal direction, which leads to uneven movement of the flood front and subsequent early breakthrough of water from high permeability layers. This problem is exacerbated if there is (vertical) hydraulic communication between layers so that crossflow can occur. One of the novel technologies in chemical enhanced oil recovery (EOR) is a gel type called deep diverting gel (DDG), which describes material that functions by plugging thief zones deep from the well where they were being injected. To evaluate the performance of this new treatment method, we will (1) model the treatment methods, (2) conduct economic analysis, and (3) compare different EOR methods. We have conducted relevant literature review about the development, design, modeling and economics of the enhanced oil recovery methods. Schlumberger's Eclipse simulator software has been used for modeling purposes. Modeling runs have demonstrated that placement of a DDG in a high permeability zone provided a blockage that diverted water into lower permeability areas, thus increasing the sweep of target zones. Research results demonstrated that, although higher recovery can be achieved with a polymer flood, the combination of delayed production response and large polymer amounts cause such projects to be less economically favorable than deep gel placement treatments. From results of several sensitivity runs, it can be concluded that plug size and oil viscosity are two determining factors in the efficiency of DDG treatments. For the assumed case, economic analysis demonstrated that DDG has the most positive net present value (NPV), with polymer flooding second and simply continuing the waterflood to its economic limit the least positive NPV.

The performance of Enhanced Oil Recovery (EOR) processes is adversely affected by the heterogeneous distribution of flow properties of the rock. The effects of heterogeneity are further highlighted when the mobility ratio between the displacing and the displaced fluids is unfavorable. Polymer flooding aims to mitigate this by controlling the mobility ratio resulting in an increase in the volumetric swept efficiency. However, the design of the polymer injection process has to take into account the uncertainty due to a limited knowledge of the heterogeneous properties of the reservoir. Numerical reservoir models equipped with the most updated, yet uncertain information about the reservoir should be employed to optimize the operational settings. Consequently, the optimal settings are uncertain and should be revised as the model is updated. In this report, a feedback-control scheme is proposed with a model updating step that conditions prior reservoir models to newly obtained dynamic data, and this followed by an optimization step that adjusts well control settings to maximize (or minimize) an objective function. An illustration of the implementation of the proposed closed-loop scheme is presented through an example where the rate settings of a well affected by water coning are adjusted as the reservoir models are updated. The revised control settings yield an increase in the final value of the objective function. Finally, a fast analog of a polymer flooding displacement that traces the movement of random particles from injectors to producers following probability rules that reflect the physics of the actual displacement is presented. The algorithm was calibrated against the full-physics simulation results from UTCHEM, the compositional chemical flow simulator developed at The University of Texas at Austin. This algorithm can be used for a rapid estimation of basic responses such as breakthrough time or recovery factor and to provide a simplified characterization the reservoir heterogeneity. This report is presented to fulfill the requirements to obtain the degree of Master of Science in Engineering under fast track option. It summarizes the research proposal presented for my doctorate studies that are currently ongoing. / text

Polymer flooding is economically successful in reservoirs where the water flood mobility ratio is high, and/or the reservoir heterogeneity is adverse, because of the improved sweep resulting from the mobility-controlled oil displacement. The performance of a polymer flood can be further improved if the process is dynamically controlled using updated reservoir models and a closed-loop production optimization scheme is implemented. However, the formulation of an optimal production strategy is based on uncertain production forecasts resulting from uncertainty in spatial representation of reservoir heterogeneity, geologic scenarios, inaccurate modeling, scaling, just to cite a few factors. Assessing the uncertainty in reservoir modeling and transferring it to uncertainty in production forecasts is crucial for efficiently controlling the process. This dissertation presents a feedback control framework that (1) assesses uncertainty in reservoir modeling and production forecasts, (2) updates the prior uncertainty in reservoir models by integrating continuously monitored production data, and (3) formulates optimal injection/production rates for the updated reservoir models. This approach focuses on assessing uncertainty in reservoir modeling and production forecasts originated mainly by uncertain geologic scenarios and spatial variations of reservoir properties (heterogeneity). This uncertainty is mapped in a metric space created by comparing multiple reservoir models and measuring differences in effective heterogeneity related to well connectivity and well responses characteristic of polymer flooding. Continuously monitored production data is used to refine the uncertainty map using a Bayesian inversion algorithm. In contrast to classical approach of history matching by model perturbation, a model selection problem is implemented where highly probable reservoir models are selected to represent the posterior uncertainty in production forecasts. The model selection procedure yields the posterior uncertainty associated with the reservoir model. The production optimization problem is solved using the posterior models and a proxy model of polymer flooding to rapidly evaluate the objective function and response surfaces to represent the relationship between well controls and an economic objective function. The value of the feedback control framework is demonstrated with two examples of polymer flooding where the economic performance was maximized. / text

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