Dissertations / Theses on the topic 'Surfactant/polymer flooding'

The aim of this thesis is to develop a robust parametric uncertainty quantification method and a decision making method for a chemical EOR process. The main motivation is that uncertainty is detrimental to the wide scale implementation of chemical EOR. Poor scale-up performance is not in line with the success in laboratory applications. Furthermore, economic uncertainty is also an important factor as low oil prices can deter EOR investment. As an example of chemical EOR we used Surfactant-polymer flooding due to its high potential and complexity. The approach was based on using Value of Flexibility evaluation in order to optimize the surfactant-polymer flooding in the presence of economic and technical uncertainty. This method was inspired by real options theory which provides a framework to value flexibility and captures the effect of uncertainty as the process evolves through time. By doing so, it provides the means to capitalize on the upside opportunities that these uncertainties present or to help mitigate worsening circumstances. In addition, it fulfils a secondary objective to develop a decision making process that combines both technical and economic uncertainty. The Least Squares Monte Carlo (LSM) method was chosen to value flexibility in surfactant-polymer flooding. The algorithm depends on two main components; the stochastic simulation of the input state variables and the dynamic programming approach that produce the optimal policy. The produced optimal policy represents the influence of uncertainty in the time series of the relevant input parameters. Different chemical related parameters were modelled stochastically such as surfactant and polymer adsorption rates and residual oil saturation. Static uncertainty in heterogeneity was incorporated using Gaussian and multiple-point statistics generated grids and dynamic uncertainty in heterogeneity was modelled using upscaling techniques. Economic uncertainties such as the oil price and surfactant and polymer cost were incorporated into the model as well. The results obtained for the initial case studies showed that the method produced higher value compared with static policy scenarios. It showed that by designing flexibility into the implementation of the surfactant-polymer flood, it is possible to create value in the presence of uncertainty. An attempt to enhance the performance of the LSM algorithm was introduced by using the probabilistic collocation method (PCM) to sample the distributions of the technical state input parameters more efficiently, requiring significantly less computational time compared to Monte Carlo sampling. The combined approach was then applied to more complex decisions to demonstrate its scalability. It was found that the LSM algorithm could value flexibility for surfactant-polymer flooding and that it introduces a new approach to highly uncertain problems. However, there are some limitations to the extendibility of the algorithm to more complex higher dimensional problems. The main limitation was observed when using a finer discretization of the decision space because it requires a significant increase in the number of stochastic realization for the results to converge, thus increasing the computational requirement significantly. The contributions of this thesis can be summarized into the following: an attempt to use real options theory to value flexibility in SP flooding processes, the development of an approximate dynamic programming approach to produce optimal policies, the robust quantification of parametric uncertainty for SP flooding using PCM and an attempt to improve the efficiency of the LSM method by coupling it with the PCM code in order to extend its applicability to more complex problems.

Thesis (MTech (Chemical Engineering))--Cape Peninsula University of Technology, 2016.
Due to the rising cost involve with bringing new fields on stream, of producing residual crude from matured fields, and the significant enhancement in oil recovery provided when compared to conventional water-flooding, increasing attention is being given to chemical flooding technologies. This is particular of interest in mature fields that had previously undergone water flooding. These methods entail injecting chemicals such as surfactant, alkali, and polymer often in mixture into reservoirs to improve oil recovery. In this study a sulfonated surfactant was produced from cheap waste vegetable oils and its performance was assessed in terms of thermal stability at reservoir conditions, adsorption on different reservoir materials, gas chromatography characterization and a limited interfacial tension measurement to evaluate its ability to improve the recovery of crude oil. Waste vegetable oils have great potential as a sustainable and low cost feedstock as well as its low toxicity.

A great percentage of oil is observed to be left in the reservoir after the traditional primary and secondary recovery methods. This oil is described as immobile oil. Alkaline-Surfactants are chemicals used to reduce the interfacial tension between the involved fluids, while polymer is used in making the immobile oil mobile.Norne C-segment is in the decline stage and is facing considerable challenges regardingvolume of oil bye-passed due to water flooding. There is need for developing cost efficient enhanced oil recovery (EOR) methods that would be suitable for Norne fluid and rock properties and therefore improve sweep efficiency significantly. Based on literature and screening criteria, alkaline-surfactant-polymer can be used as an enhancing agent to produce extra oil and reduce water-cut significantly in the C-segment.The objective of this work is to evaluate the possibilities of using alkaline, surfactant and/or polymer to increase the oil recovery factor and prolong the production decline stage of Norne field. An initial study was conducted using heterogeneous synthetic models (with Norne Csegment fluids and rock properties) to assess the suitability of alkaline/surfactant/polymer (ASP) flooding. All the chemical cases simulated gave substantial incremental oil production and water-cut reduction. However, history matched Norne C-segment reservoir model was used to simulate alkalinesurfactant-polymer flooding using Eclipse 100. Appropriate chemical quantity for injection was ascertained by simulating several cases with different concentration, injection length and time of injection. Different sensitivity analyses were made and simulations revealed that the most effective method was not the most profitable. Having established most profitable method which was injecting ASP slug with a concentration of 7Kg/m3, 2Kg/m3 and 0.3Kg/m3 into C-3H (injector) for 4-years in a cyclic manner, an incremental recovery factor of 2.61% was recorded and Net Present Value (NPV) was calculated to be 1660 x103MNOK

This research is a simulation study to improve total oil production using ASP flooding method based on simulation model of Norne field C-segment. The black oil model was used for simulations. Remaining oil in the reservoir can be divided into two classes, firstly residual oil to the water flood and secondly oil bypassed by the water flood. Residual oil mainly contains capillary trapped oil. Water flooding only is not able to produce capillary trapped oil so that there is a need for additional technique and force to produce as much as residual oil. One way of recovering this capillary trapped oil is by adding chemicals such as surfactant and alkaline to the injected water. Surfactants are considered for enhanced oil recovery by reduction of oil–water interfacial tension (IFT). The crucial role of alkali in an alkaline surfactant process is to reduce adsorption of surfactant during displacement through the formation. Also alkali is beneficial for reduction of oil-water IFT by in situ generation of soap, which is an anionic surfactant. Generally alkali is injected with surfactant together. On the other hand, polymer is very effective addition by increasing water viscosity which controls water mobility thus improving the sweep efficiency.In the first place, ASP flooding was simulated and studied for one dimensional, two dimensional and three dimensional synthetic models. All these models were built based on C-segment rock properties and reservoir parameters. Based on test runs, well C-3H was selected and used as a main injector in order to execute chemical injection schemes in the C-segment. Five studies such as polymer flooding, surfactant flooding, surfactant-polymer flooding, alkaline-surfactant and alkaline-surfactant-polymer flooding were considered in the injection process and important results from simulator were analyzed and interpreted. Sensitivity analyses were done especially focusing on chemical solution concentration, injection rate and duration of injection time. The polymer flooding project in this study has shown a better outcome compared to water flooding project. Economically best ASP solution flooding case is the flooding with concentration of alkaline at1.5kg/m3, surfactant at 15kg/m3 and polymer at 0.35 kg/m3 injecting for 5 years. AS flooding case for 4 years with alkali concentration at 0.5kg/m3 and surfactant concentration at 25 kg/m3 gave highest NPV value. It was found that surfactant flooding has a promising effect and it is more profitable than polymer flooding for the C segment in terms of NPV. Economic sensitivity analysis (Spider diagram) for low case, base case and high case at different oil prices, chemicals prices, and discount rate were also presented. It was found that change in oil price has significant effect on NPV compared to other parameters while polymer price has the least effect on NPV for high and low cases.

The world needs energy – and over the short and medium term it is clear that much of our global energy consumption will come from fossil sources such as oil, gas and coal. With the current growing demand for oil led by major energy consuming countries such as China and India, securing new oil resources is a critical challenge for the oil industry. Each year, new production is needed to compensate the natural decline of existing wells, and the additional production required to satisfy the yearly demand for hydrocarbon energy that will represent approximately 9% of the worldwide total production. For this growth to be sustainable, a strong focus will have to be placed on finding new discoveries and/or optimizing oil production from current resources. The cost associated with the first option is significant. Therefore, reservoir management teams all over the world will have to cater for this demand mainly by maximizing hydrocarbon recovery factors through Enhanced Oil Recovery (EOR) processes. EOR consists of methods aimed at increasing ultimate oil recovery by injecting appropriate agents not normally present in the reservoir, such as chemicals, solvents, oxidizers and heat carriers in order to induce new mechanisms for displacing oil. Chemical flooding is one of the most promising and broadly applied EOR processes which have enjoyed significant research and pilot testing during the 1980s with a significant revival in recent years. However, its commercial implementation has been facing several technical, operational and economic challenges. Chemical flooding is further subdivided into polymer flooding, surfactant flooding, alkaline flooding, miscellar flooding, alkaline-surfactant-polymer (ASP) flooding. ASP flooding is a form of chemical enhanced oil recovery (EOR) that can allow operators to extend reservoir pool life and extract incremental reserves currently inaccessible by conventional EOR techniques such as waterflooding. Three chemical inject in the ASP process which is synergistic. In the ASP process, Surfactants are chemicals that used to reduce the interfacial tension between the involved fluids, making the immobile oil mobile. Alkali reduces adsorption of the surfactant on the rock surfaces and reacts with acids in the oil to create natural surfactant. Polymer improves the sweep efficiency. By simulating ASP flooding for several cases, with different chemical concentrations, injection length, time of injection, current well optimization and new well placement, this report suggests a number of good alternatives. Simulations showed that the most effective method was not the most profitable. From the simulation results and economic analysis, ASP flooding can be a good alternative for the Norne E-segment. But the margins are not significant, so fixed costs (such as equipment rental) will be of crucial importance.

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.

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.
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Alkaline/surfactant/polymer (ASP) flooding is of increasing interest and importance because of high oil prices and the need to increase oil production. The benefits of combining alkali with surfactant are well established. The alkali has very important benefits such as lowering interfacial tension and reducing adsorption of anionic surfactants that decrease costs and make ASP a very attractive enhanced oil recovery method provided the consumption is not too large and the alkali can be propagated at the same rate as a synthetic surfactant and polymer. However, the process is complex so it is important that new candidates for ASP be selected taking into account the numerous chemical reactions that occur in the reservoir. The reaction of acid and alkali to generate soap and its subsequent effect on phase behavior is the most crucial for crude oils containing naphthenic acids. Using numerical models, the process can be designed and optimized to ensure the proper propagation of alkali and effective soap and surfactant concentrations to promote low interfacial tension and a favorable salinity gradient. The first step in this investigation was to determine what geochemical reactions have the most impact on ASP flooding under different reservoir conditions and to quantify the consumption of alkali by different mechanisms. We describe the ASP module of UTCHEM simulator with particular attention to phase behavior and the effect of soap on optimum salinity and solubilization ratio. Several phase behavior measurements for a variety of surfactant formulations and crude oils were successfully modeled. The phase behavior results for sodium carbonate, blends of surfactants with an acidic crude oil followed the conventional Winsor phase transition with significant three-phase regions even at low surfactant concentrations. The solubilization data at different oil concentrations were successfully modeled using Hand's rule. Optimum salinity and solubilization ratio were correlated with soap mole fractions using mixing rules. New ASP corefloods were successfully modeled taking into account the aqueous reactions, alkali/rock interactions, and the phase behavior of soap and surfactant. These corefloods were performed in different sandstone cores with several chemical formulations, crude oils with a wide range of acid numbers, brine with a wide range of salinities, and a wide range of temperatures. 2D and 3D sector model ASP simulations were performed based on field data and design parameters obtained from coreflood history matches. The phenomena modeled included aqueous phase chemical reactions of the alkaline agent and consequent consumption of alkali, the in-situ generation of surfactant by reaction with the acid in the crude, surfactant/soap phase behavior, reduction of surfactant adsorption at high pH, cation exchange with clay, and the effect of co-solvent on phase behavior. Sensitivity simulations on chemical design parameters such as mass of surfactant and uncertain reservoir parameters such as kv/kh ratio were performed to provide insight as the importance of each of these variables in chemical oil recovery. Simulations with different permeability realizations provided the range for chemical oil recoveries. This study showed that it is very important to model both surface active components and their effect on phase behavior when doing mechanistic ASP simulations. The reactions between the alkali and the minerals in the formation depend very much on which alkali is used, the minerals in the formation, and the temperature. This research helped us increase our understanding on the process of ASP flooding. In general, these mechanistic simulations gave insights into the propagation of alkali, soap, and surfactant in the core and aid in future coreflood and field scale ASP designs.
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Due to capillary pressure, reservoir heterogeneity, oil mobility, and lack of reservoir energy, typically more than 50 % of the original oil in place is left in the reservoir after primary and secondary recovery oil production. With relatively easy-to-get conventional oil resources diminishing and the price of oil hovering around triple digits, enhanced oil recovery methods, such as polymer flooding, have become very attractive ways to recover oil effectively from existing reservoirs. Enhanced oil recovery methods can be categorized into three categories: water or chemical based, gas based, and thermal based. This thesis will focus on the chemical injection of surfactants, alkali, and polymer of the water based methods. Surfactants are used to alter the interfacial tension of the aqueous and oleic phases in order to facility oil production. Alkali chemicals are used to create surfactants by reacting with acidic oil. And polymer is used to reduce injection water mobility to effectively displace the contacted oil in heterogeneous reservoirs by improving the volumetric and displacement sweep efficiencies. This research presents several laboratory results of polymer and alkali/surfactant/polymer core floods performed in the Center for Petroleum and Geosystems Engineering laboratories. Properties of polymer and surfactant phase behavior were measured and modeled and each coreflood was history matched with UTCHEM, a three-dimensional chemical flooding simulator. The coreflood results and the history matched model parameters were then upscaled to a pilot case for viscous oil in offshore environment with four wells in a line drive pattern. The potential of polymer flooding was investigated and several sensitivity cases were performed to evaluate the effect of various physical property parameters on oil recovery. Water salinity and hardness (i.e. amount of calcium and magnesium) has detrimental effects on polymer viscosity and its stability. The potential benefits of low salinity water injection by desalinization of seawater for polymer flood projects have been discussed in recent publications. The effect of low salinity polymer flood was also investigated. A series of sensitivity studies on well pattern and well spacing is carried out to investigate the impact on recovery factor and recovery time.
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Accurate simulation of chemical flooding requires a detailed understanding of numerous complex mechanisms and model parameters where grid size has a substantial impact upon results. In this research we show the effect of grid size on parameters such as phase behavior, interfacial tension, surfactant dilution and salinity gradient for chemical flooding of a very heterogeneous oil reservoir. The effective propagation of the surfactant slug in the reservoir is of paramount importance and the salinity gradient is a key factor in ensuring the process effectiveness. The larger the grid block size, the greater the surfactant dilution, which in turn erroneously reduces the effectiveness of the process indicated with low simulated oil recoveries. We show that the salinity gradient is not adequately captured by coarse grid simulations of heterogeneous reservoirs and this leads to performance predictions with lower recovery compared to fine grid simulations. Due to the highly coupled, nonlinear interactions of the many chemical and physical processes involved in chemical flooding, it is better to use fine-grid simulations rather than coarse grids with upscaled physical properties whenever feasible. However, the upscaling methodology for chemical flooding presented in this work accounts approximately for some of the more important effects, as demonstrated by comparison of fine grid and coarse grid results and is very different than the way other enhanced oil recovery methods are upscaled. This is a step towards making better performance predictions of chemical flooding for large field projects where it is not currently feasible to perform the large number of simulations required to properly consider different designs, optimization, risk and uncertainty using fine-grid simulations.
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Chemical Enhanced Oil Recovery methods have been growing in popularity as a result of the depletion of conventional oil reservoirs and high oil prices. These processes are significantly more complex when compared to waterflooding and require detailed engineering design before field-scale implementation. Coreflood experiments that have been performed on reservoir rock are invaluable for obtaining parameters that can be used for field-scale flooding simulations. However, the design used in these floods may not always scale to the field due to heterogeneities, chemical retention, mixing and dispersion effects. Reservoir simulators can be used to identify an optimum design that accounts for these effects but uncertainties in reservoir properties can still cause poor project results if it not properly accounted for. Different reservoirs will be investigated in this study, including more unconventional applications of chemical flooding such as a 3md high-temperature, carbonate reservoir and a heterogeneous sandstone reservoir with very high initial oil saturation. The goal of the research presented here is to investigate the impact that select reservoir uncertainties can have on the success of the pilot and to propose methods to reduce the sensitivity to these parameters. This research highlights the importance of good mobility control in all the case studies, which is shown to have a significant impact on the economics of the project. It was also demonstrated that a slug design with good mobility control is less sensitive to uncertainties in the relative permeability parameters. The research also demonstrates that for a low-permeability reservoir, surfactant propagation can have a significant impact on the economics of a Surfactant-Polymer Flood. In addition to mobilizing residual oil and increasing oil recovery, the surfactant enhances the relative permeability and this has a significant impact on increasing the injectivity and reducing the project life. Injecting a high concentration of surfactant also makes the design less sensitive to uncertainties in adsorption. Finally, it was demonstrated that for a heterogeneous reservoir with high initial oil saturation, optimizing the salinity gradient will significantly increase the oil recovery and will also make the process less sensitive to uncertainties in the cation exchange capacity.
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Studying chemical enhanced oil recovery (EOR) in a high-temperature/high-salinity (HT/HS) reservoir will help expand the application of chemical EOR to more challenging environments. Until recently, chemical EOR was not recommended at reservoirs that contain high concentrations of divalent cations without the need to recondition the reservoir by flooding it with less saline/ less hardness brines. This strategy was found ineffective in preparing the reservoir for chemical flooding. Surfactants used for chemical flooding operating in high temperatures tend to precipitate when exposed to high concentrations of divalent cations and will partition to the oil phase at high salinities. In this study amphoteric surfactant was used to replace the traditionally used anionic surfactants. Amphoteric surfactants show higher multivalent cations tolerance with better thermal stability. A modified amphoteric surfactant with lower adsorption properties was evaluated for oil recovery. Organic alkali was used to eliminate the water softening process when preparing the chemical solution and reduce potential scale problems caused by precipitation due to incompatibility between chemical slug containing alkali and formation brine. Using organic alkali helped in minimizing softening required when preparing an alkali-surfactant-polymer (ASP) solution using seawater. Solution prepared with organic alkali showed the least injectivity decline when compared to traditional alkalis (NaOH and Na2CO3) and sodium metaborate. Adding organic alkali helped further reduce IFT values when added to surfactant solution. Amphoteric surfactant was found to produce low IFT values at low concentrations and can operate at high salinity / high hardness conditions. When mixed with polymer it improved the viscosity of the surfactant-polymer (SP) solution when prepared in high salinity mixing water (6% NaCl). When prepared in seawater and tested in reservoir temperature (95°C) no reduction in viscosity was found. Unlike the anionic surfactant that causes reduction in viscosity of the SP solution at reservoir temperature. This will not require increasing the polymer concentration in the chemical slug. Unlike the case when anionic surfactant was used and more polymer need to be added to compensate the reduction in viscosity. Berea sandstone cores show lower recovery compared to dolomite cores. It was also found that Berea cores were more sensitive to polymer concentration and type and injectivity decline can be a serious issue during chemical and polymer injection. Dolomite did not show injectivity decline during chemical and polymer flooding and was not sensitive to the polymer concentration when a polymer with low molecular weight was used. CT scan was employed to study the displacement of oil during ASP, SP, polymer and surfactant flooding. The formation and propagation oil bank was observed during these core flood experiments. ASP and SP flooding showed the highest recovery, and formation and propagation of oil bank was clearer in these experiments compared to surfactant flooding. It was found that in Berea sandstone with a permeability range of 50 to 80 md that the recovery and fluid flow was through some dominating and some smaller channels. This explained the deviation from piston-like displacement, where a sharp change in saturation in part of the flood related to the dominated channels and tapered front with late arrival when oil is recovered from the smaller channels. It was concluded that the recovery in the case of sandstone was dominated by the fluid flow and chemical propagation in the porous media not by the effectiveness of the chemical slug to lower the IFT between the displacing fluid and oil.

Recently, oil prices and oil demand are rising and are projected to continue to rise over the long term. These trends create great potential for enhanced oil recovery methods that could improve the recovery efficiency of reservoirs all over the world. The greatest challenges for enhanced oil recovery involve the technical uncertainty with design and performance, and the high financial risk. Pilot tests can help mitigate the risk associated with such projects; however, there is a question about the value of information from the tests. Decision support can provide information about the value of an enhanced oil recovery project, which can assist with alleviating financial risk and create more potential opportunities for the technology. The first objective of this study is to create a new simplified method for modeling oil production histories of enhanced oil recovery methods. The method is designed to satisfy three criteria: 1) it allows for quick simulations based on only a few physically meaningful input parameters; 2) it can create almost any potential type of realistic production history that may be realized during a project; and 3) it applies to all nonthermal enhanced oil recovery methods, including surfactant-polymer, alkali-surfactant polymer, and CO₂ floods. The developed method is capable of creating realistic curves with only four unique parameters. The second objective is to evaluate the predictive method against data from pilot and field scale projects. The evaluations demonstrate that the method can fit most realistic production histories as well as provided ranges for the input parameters. A sensitivity analysis is also performed to assist with determining how all of the parameters involved with the predictive method and the economic model influence the forecasted value for a project. The analysis suggests that the price of oil, change in oil saturation, and the size of the reservoir are the most influential parameters. The final objective is to establish a method for a decision analysis that determines the value of information of a pilot for enhanced oil recovery. The analysis uses the predictive method and economic model for determining economic utilities for every potential outcome. It uses a decision-based method to ensure that the non-informative prior probability distributions have an unbiased, consistent, and rational starting point. A simple example demonstrating the process is discussed and it is used to show that a pilot test provides some valuable information when there is minimal prior information. For future work it is recommended that more evaluations are performed, the decision analysis is expanded to include more input parameters, and a rational and logical method is developed for determining likelihood functions from existing information.
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The overall objective of this research was to gain an insight into the challenges encountered during chemical flooding under high hardness conditions. Different aspects of this problem were studied using a combination of laboratory experiments and simulation studies. Chemical Flooding is an important Enhanced Oil Recovery process. One of the major components of the operational expenses of any chemical flooding project, especially Alkali Surfactant Polymer (ASP) flooding is the cost of softening the injection brine to prevent the precipitation of the carbonates of the calcium and magnesium ions which are invariably present in the formation brine. Novel hardness tolerant alkalis like sodium metaborate have been shown to perform well with brines of high salinity and hardness, thereby eliminating the need to soften the injection brine. The first part of this research was aimed at designing an optimal chemical flooding formulation for a reservoir having hard formation brine. Sodium metaborate was used as the alkali in the formulation with the hard brine. Under the experimental conditions, sodium metaborate was found to be inadequate in preventing precipitation in the ASP slug. Factors affecting the ability of sodium metaborate to sequester divalent ions, including its potential limitations under the experimental conditions were studied. The second part of this research studied the factors affecting the ability of novel alkali and chelating agents like sodium metaborate and tetrasodium EDTA to sequester divalent ions. Recent studies have shown that both these chemicals showed good performance in sequestering divalent ions under high hardness conditions. A study of the geochemical species in solution under different conditions was done using the computer program PHREEQC. Sensitivity studies about the effect of the presence of different solution species on the performance of these alkalis were done. The third part of this research focused on field scale mechanistic simulation studies of geochemical scaling during ASP flooding. This is one of the major challenges faced by the oil and gas industry and has been found to occur when sodium carbonate is used as the alkali and the formation brine present in situ has a sufficiently high hardness content. The multicomponent and multiphase compositional chemical flooding simulator, UTCHEM was used to determine the quantity and composition of the scales formed in the reservoir as well as the injection and production wells. Reactions occurring between the injected fluids, in situ fluids and the reservoir rocks were taken into consideration for this study. Sensitivity studies of the effect of key reservoir and process parameters like the physical dispersion and the alkali concentration on the extent of scaling were also done as a part of this study.
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Chemical EOR processes such as polymer flooding and surfactant polymer flooding must be designed and implemented in an economically attractive manner to be perceived as viable oil recovery options. The primary expenses associated with these processes are chemical costs which are predominantly controlled by the crude oil properties of a reservoir. Crude oil viscosity dictates polymer concentration requirements for mobility control and can also negatively affect the rheological properties of a microemulsion when surfactant polymer flooding. High microemulsion viscosity can be reduced with the introduction of an alcohol co-solvent into the surfactant formulation, but this increases the cost of the formulation. Experimental research done as part of this study combined the process of hot water injection with ASP flooding as a solution to reduce both crude oil viscosity and microemulsion viscosity. The results of this investigation revealed that when action was taken to reduce microemulsion viscosity, residual oil recoveries were greater than 90%. Hot water flooding lowered required polymer concentrations by reducing oil viscosity and lowered microemulsion viscosity without co-solvent. Laboratory testing of viscous microemulsions in core floods proved to compromise surfactant performance and oil recovery by causing high surfactant retention, high pressure gradients that would be unsustainable in the field, high required polymer concentrations to maintain favorable mobility during chemical flooding, reduced sweep efficiency and stagnation of microemulsions due to high viscosity from flowing at low shear rates. Rough scale-up chemical cost estimations were performed using core flood performance data. Without reducing microemulsion viscosity, field chemical costs were as high as 26.15 dollars per incremental barrel of oil. The introduction of co-solvent reduced chemical costs to as low as 22.01 dollars per incremental barrel of oil. This reduction in cost is the combined result of increasing residual oil recovery and the added cost of an alcohol co-solvent. Heating the reservoir by hot water flooding resulted in combined chemical and heating costs of 13.94 dollars per incremental barrel of oil. The significant drop in cost when using hot water is due to increased residual oil recovery, reduction in polymer concentrations from reduced oil viscosity and reduction of microemulsion viscosity at a fraction of the cost of co-solvent.
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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.
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Understanding flow and transport in porous media is critical as it plays a central role in many biological, natural, and industrial processes. Such processes are not limited to one length or time scale; they occur over a wide span of scales from micron to Kilometers and microseconds to years. While field-scale simulation relies on a continuum description of the flow and transport, one must take into account transport processes occurring on much smaller scales. In doing so, pore-scale modeling is a powerful tool for shedding light on processes at small length and time scales.

In this work, we look into the multi-phase flow and transport through porous media at two different scales, namely pore- and Darcy scales. First, using direct numerical simulations, we study pore-scale Eulerian and Lagrangian statistics. We study the evolution of Lagrangian velocities for uniform injection of particles and numerically verify their relationship with the Eulerian velocity field. We show that for three porous media velocity, probability distributions change over a range of porosities from an exponential distribution to a Gaussian distribution. We thus model this behavior by using a power-exponential function and show that it can accurately represent the velocity distributions. Finally, using fully resolved velocity field and pore-geometry, we show that despite the randomness in the flow and pore space distributions, their two-point correlation functions decay extremely similarly.

Next, we extend our previous study to investigate the effect of viscoelastic fluids on particle dispersion, velocity distributions, and flow resistance in porous media. We show that long-term particle dispersion could not be modulated by using viscoelastic fluids in random porous media. However, flow resistance compared to the Newtonian case goes through three distinct regions depending on the strength of fluid elasticity. We also show that when elastic effects are strong, flow thickens and strongly fluctuates even in the absence of inertial forces.

Next, we focused our attention on flow and transport at the Darcy scale. In particular, we study a tertiary improved oil recovery technique called surfactant-polymer flooding. In this work, which has been done in collaboration with Purdue enhanced oil recovery lab, we aim at modeling coreflood experiments using 1D numerical simulations. To do so, we propose a framework in which various experiments need to be done to quantity surfactant phase behavior, polymer rheology, polymer effects on rock permeability, dispersion, and etc. Then, via a sensitivity study, we further reduce the parameter space of the problem to facilitate the model calibration process. Finally, we propose a multi-stage calibration algorithm in which two critically important parameters, namely peak pressure drop, and cumulative oil recovery factor, are matched with experimental data. To show the predictive capabilities of our framework, we numerically simulate two additional coreflood experiments and show good agreement with experimental data for both of our quantities of interest.

Lastly, we study the unstable displacement of non-aqueous phase liquids (e.g., oil) via a finite-size injection of surfactant-polymer slug in a 2-D domain with homogeneous and heterogeneous permeability fields. Unstable displacement could be detrimental to surfactant-polymer flood and thus is critically important to design it in a way that a piston-like displacement is achieved for maximum recovery. We study the effects of mobility ratio, finite-size length of surfactant-polymer slug, and heterogeneity on the effectiveness of such process by looking into recovery rate and breakthrough and removal times.

Hybrid gas/chemical Enhanced Oil Recovery (EOR) methods are such novel techniques to increase oil production and oil recovery efficiency. Gas flooding using carbon dioxide, nitrogen, flue gas, and enriched natural gas produce more oil from the reservoirs by channeling gas into previously by-passed areas. Surfactant flooding can recover trapped oil by reducing the interfacial tension between oil and water phases. Hybrid gas/chemical EOR methods benefit from using both chemical and gas flooding. In hybrid gas/chemical EOR processes, surfactant solution is injected with gas during low-tension-gas or foam flooding. Polymer solution can also be injected alternatively with gas to improve the gas volumetric sweep efficiency. Most fundamentally, wide applications of hybrid gas/chemical processes are limited due to uncertainties in reservoir characterization and heterogeneity, due to the lack of understanding of the process and consequently lack of a predictive reservoir simulator to mechanistically model the process. Without a reliable simulator, built on mechanisms determined in the laboratory, promising field candidates cannot be identified in advance nor can process performance be optimized. In this research, UTCHEM was modified to model four-phase water, oil, microemulsion, and gas phases to simulate and interpret chemical EOR processes including free and/or solution gas. We coupled the black-oil model for water/oil/gas equilibrium with microemulsion phase behavior model through a new approach. Four-phase fluid properties, relative permeability, and capillary pressure were developed and implemented. The mass conservation equation was solved for total volumetric concentration of each component at standard conditions and pressure equation was derived for both saturated and undersaturated PVT conditions. To model foam flow in porous media, comprehensive research was performed comparing capabilities and limitations of implicit texture (IT) and population-balance (PB) foam models. Dimensionless foam bubble density was defined in IT models to derive explicitly the foam-coalescence-rate function in these models. Results showed that each of the IT models examined was equivalent to the LE formulation of a population-balance model with a lamella-destruction function that increased abruptly in the vicinity of the limiting capillary pressure, as in current population-balance models. Foam models were incorporated in UTCHEM to model low-tension-gas and foam flow processes in laboratory and field scales. The modified UTCEM reservoir simulator was used to history match published low-tension-gas and foam coreflood experiments. The simulations were also extended to model and evaluate hybrid gas/chemical EOR methods in field scales. Simulation results indicated a well-designed low-tension-gas flooding has the potential to recover the trapped oil where foam provides mobility control during surfactant and surfactant-alkaline flooding in reservoirs with very low permeability.
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