High-pressure shear viscosity measurements of polymer/supercritical fluid systems are numerous, but most involve pressure-gradient equipment such as a capillary or slit die with pressure drops exceeding 10%. Pressure change across the measurement region introduces some errors when quantifying the effect of blowing agents and other diluents on viscosity. This source of errors was removed by using a static-pressure, Couette rheometer. The viscosity of polystyrene (PS)/carbon dioxide (CO 2 ) was measured from 140 to 180 °C and from 3 to 6 wt % CO 2 . The effect of pressure on diluent-free PS viscosity was required to calculate the CO 2 concentration shift factor. Thus, viscosities at both atmospheric and elevated pressure (via helium, an insoluble gas) were measured using the same equipment and method. The Fillers-Moonan-Tschoegl (FMT) model was overdefined for obtaining free volume parameters, but it was a helpful correlation tool to obtain the pressure effect on viscosity. Pressure and concentration shift factors obtained from the experiments were compared with empirical free-volume plasticization models, one based on glass transition temperature, the other on P-V-T behavior. Unfortunately, neither model demonstrated quantitative agreement with the experimental data within the 3-6 wt % CO 2 range examined. The WLF-Chow model, based on T g data, fared better than the P-V-T-based model.

In this work, a new methodology is developed that describes the viscoelastic scaling of a polymerphysical foaming agent (PFA) solution in a detailed and internally consistent manner. The approach is new in that while previous researchers have largely focused on scaling down experimentally obtained high pressure polymer-PFA solution viscosity data onto a master curve for the viscosity of the undiluted polymer melt at a reference temperature and atmospheric pressure, we have generated the shear viscosity data required for our simulations by systematically scaling up the viscosity values obtained from measurements on a pure polymer melt to the desired temperature, pressure, and concentration values characterizing the flow. Simulations have been run for the flow of a polymer-PFA solution through an extrusion foaming die with an abrupt axisymmetric contraction and good qualitative agreement is obtained with experimental pressure drop measurements obtained previously in our laboratory. The pressure drop rates and temperature rise rates have been estimated at the surface of incipient nucleation. Because of the short residence times in the die for the microcellular foaming process, approximating the flow through the die as a single phase flow in our simulations still gives useful insights into the dynamics of the flow.

In the continuous production of microcellular thermoplastic foam, a polymer-physical foaming agent (PFA) solution is subjected to a rapid pressure drop through an extrusion foaming die. Simulations were run for the flow of a polymer-PFA solution through an extrusion foaming die with an abrupt axisymmetric contraction. The pressure drops across the die obtained through the simulations showed good qualitative agreement with experimental pressure drop measurements on the foaming extrusion die obtained in our laboratory. Field values of pressure, temperature, and velocity were obtained at each point in the foaming die. Once the values of pressure and temperature were obtained along each point in the foaming die, classical nucleation theory for bubble nucleation was invoked to predict the local bubble nucleation rate downstream of the saturation surface. The hydrodynamic constraints to the nucleation rate were calculated by using a modified form of the classical nucleation theory that accounted for the diffusional and viscosity constraints to the rate of homogeneous nucleation. The capillarity approximation was found not to be valid for bubble nucleation of CO 2 in polymers; a correction accounting for the curvature dependence of surface tension was applied to get nonzero nucleation rates for the system to reconcile theoretically predicted rates with experimental observations.

The acetaldehyde (AA) generation behavior of poly(ethylene terephthalate) (PET) has been investigated in terms of its relationship to changes in various processing conditions. A single‐cavity injection‐molding machine was used to prepare preforms in order to relate changes in barrel temperature, screw shear rate, back pressure, cooling time and total residence time to levels of AA generated during processing. Within the temperature range 280–300 °C, a 10 °C rise in processing temperature causes AA production to double. Shear rate increases from 20 to 40 m min−1 result in 13–21 % increases in AA generation at temperatures from 300 to 280 °C. Increased back pressures from 0 to 200 bar result in AA concentration increases of about 1.2 ppm for each 50 bar pressure increase. The majority of this change is caused by increased polymer residence time. Longer cooling times also increase overall cycle times and result in higher levels of AA generation, at the rate of almost 7 ppm per additional minute at 290 °C processing conditions. Apparent activation energies of 167 kJ mol−1 were calculated for samples prepared at various shear rates. These results are in agreement with literature values obtained under conditions of static mixing and indicate that shear rate and plastication do not significantly affect reaction mechanisms for AA generation. Copyright © 2005 Society of Chemical Industry

This paper focuses on a chemical EOR feasibility study for Raudhatain Zubair (RAZU) reservoir in North Kuwait. The study describes a methodical approach to enable pilot location selection, and a fit-for-purpose modeling strategy to guide the Alkaline Surfactant Polymer (ASP) pilot design decisions. The objective of the pilot is to test in the field that ASP chemicals could mobilize remaining oil and drive it to the producers, where it is captured, produced and separated at the surface. A detailed study was conducted that focused first on mapping out the distribution of remaining oil in the Raudhatain Zubair (RAZU) sandstone reservoir, defining the subsurface uncertainties and identifying key decisions that needed to be addressed for the pilot design. Thereafter, a fit-for-purpose probabilistic dynamic model using a range of inputs based on available rock and fluid field data and ASP parameters from an in-house global Chemical EOR database was built. This model was used to predict the range of production outcomes and aid with pilot design decisions. Based on the stated objective of the pilot, an inverted 5-spot pilot pattern was chosen and a representative area was identified that spanned a reasonable average of field properties. An uncertainty analysis on the pilot pattern revealed that the residual oil saturation to both water and chemical and the remaining oil saturation at the commencement of pilot are the largest uncertainties governing the incremental oil recovery from ASP over water flood. Another significant uncertainty was the presence of an aquifer and the influence of active injectors near the pilot area. Depending on the aquifer strength and heterogeneity of the reservoir, fluid drift and can sweep the chemical slug away from the intended target region of the 5 spot pattern. On the design side, the chosen surfactant concentration in ASP slug, which affects the residual oil saturation to chemical, can result in lower than optimal oil recovery if surfactant losses (via adsorption or chemical consumption) are not adequately managed. Other important decisions are injection rate and pattern size since they affect the incremental recovery due to different swept pore volumes in the pilot pattern. Moreover, the model helped in steering important decisions for the pilot – e.g optimum time to switch to ASP injection after water flood. ASP sector models frequently suffer from being overly complex since they are not tailored to address practical questions that drive key pilot decisions in a timely manner. The unique practical modeling approach presented here focuses on identifying critical uncertainties and pilot design parameters while circumventing the need of detailed laboratory data and a full field model history match.