A Gas Kick Model that Uses the Thermodynamic Approach to Account for Gas Solubility in Synthetic-based Mud

This paper presents a rigorous, mechanistic model for simulating a gas kick, that uses the thermodynamic approach to account for gas solubility. This thermodynamic solubility model uses the pressure and temperature data from the kick simulations and estimates the mole fraction of various gas components in the liquid phase. We validated these gas solubility results using Aspen HYSYS, a commercial chemical process simulation software. The thermodynamic solubility model presented in this paper assumes a pure-methane kick and applies the concepts of phase-equilibrium and fugacity to estimate the amount of dissolved gas in the drilling fluid. Application of fugacity equilibrium between the gas and liquid phases, in conjunction with the Peng-Robinson equation, gives the liquid phase mole fraction of methane. The analytical kick model uses the Hasan-Kabir two-phase flow modeling approach to describes the changes in pressure during kick migration, at various points in the annulus. Since the expansion of the gas bubbles depends on the variation in pressure, these studies also lead to pit gain estimates. A comparison between our model results and HYSYS values for methane liquid-phase mole fraction showed a maximum 8% deviation with complete agreement on bubble point (Pb) pressure and location estimates. Similarly, our model calculated the solution gas-oil ratio (Rs), with a maximum divergence of 3% from HYSYS estimates. From the comparison studies with other empirical Bo & Rs correlations, we note that the estimates of our model agreed best with those of O’Bryan’s (O'Bryan 1988) correlations. Many numerical kick simulators exist today, but they are notoriously time-consuming, limiting their on-field utility. Our kick simulator’s simplicity makes it potentially useful for on-field well control decisions. Most of these existing numerical simulators ignore the effects of kick solubility in synthetic-based muds. In the few models that do not ignore solubility, the approach to accounting for gas solubility and mud swelling is empirical, limiting their usage under conditions beyond the range of the source data used in developing these correlations. The mud swelling calculation approach we developed does not have these pressure and temperature range limitations.

Test Method for the Solubility Model of Physical Blowing Agent of Self-Expanding Polymer

This paper aims to present a solubility model of physical blowing agent (PBA) for a kind of commonly used self-expanding polymer on engineering. The self-expanding polymer contains Component A (isocyanate) and Component B (polyhydric alcohol, PBA, water, and catalyst). Component B grout of the polymer, which contains PBA, was heated to measure its temperature and volume variations. Based on the principle of mass conservation and Clapeyron equation, the solubility curve of PBA with respect to temperature was calculated. The solubility curve was then applied to simulate the foaming process. A two-component polymer grout foaming experiment was then carried out to verify the applicability of the measured solubility curve. The simulated changes of temperature and density with respect to time of polymer grout were analyzed and compared with experimental results. The error of both sets of curves is within 5%, which shows a good agreement among them and proves the feasibility of the solubility model. This study provides a relatively complete test and verification process for the solubility model of PBA, which lays a theoretical foundation for both the polymer grouting diffusion mechanism and engineering application.

Predicting Low Toxicity and Scalable Solvent Systems for High Speed Roll-to-Roll Perovskite Manufacturing

This manuscript introduces solvent toxicity in solar perovskite ink chemistries as a major technoeconomic limitation for the growth of the technology. More specifically, the capital and operational cost of handling such toxic chemicals to maintain a safe working environment can lead to significant added costs. As all record power conversion efficiency devices to date have been solution processed, this represents a major challenge for the perovskite optoelectronic field and of printed electronics as a whole. Knowing this limitation, we propose that solvent selections for ink chemistries should be more quantitative and focus on lowering toxicity. To this end, we show that a Hansen solubility model is effective in predicting ink systems using lower toxicity solvents. We also show that inks formed from this method are applicable for high-speed slot-die coating, limiting the need for long anneal times. These methods and results demonstrate a useful framework for quantitatively engineering solvent systems with reduced toxicity while simultaneously maintaining and surpassing performance. It therefore provides a pathway and major step forward towards the commercialization of solution coated perovskite technologies.

Suitable CO2 Solubility Models for Determination of the CO2 Removal Performance of Oxygenators

CO2 removal via membrane oxygenators during lung protective ventilation has become a reliable clinical technique. For further optimization of oxygenators, accurate prediction of the CO2 removal rate is necessary. It can either be determined by measuring the CO2 content in the exhaust gas of the oxygenator (sweep flow-based) or using blood gas analyzer data and a CO2 solubility model (blood-based). In this study, we determined the CO2 removal rate of a prototype oxygenator utilizing both methods in in vitro trials with bovine and in vivo trials with porcine blood. While the sweep flow-based method is reliably accurate, the blood-based method depends on the accuracy of the solubility model. In this work, we quantified performances of four different solubility models by calculating the deviation of the CO2 removal rates determined by both methods. Obtained data suggest that the simplest model (Loeppky) performs better than the more complex ones (May, Siggaard-Anderson, and Zierenberg). The models of May, Siggaard-Anderson, and Zierenberg show a significantly better performance for in vitro bovine blood data than for in vivo porcine blood data. Furthermore, the suitability of the Loeppky model parameters for bovine blood (in vitro) and porcine blood (in vivo) is evaluated.

Predicting Low Toxicity and Scalable Solvent Systems for High Speed Roll-to-Roll Perovskite Manufacturing

This manuscript introduces solvent toxicity in solar perovskite ink chemistries as a major technoeconomic limitation for the growth of the technology. More specifically, the capital and operational cost of handling such toxic chemicals to maintain a safe working environment can lead to significant added costs. As all record power conversion efficiency devices to date have been solution processed, this represents a major challenge for the perovskite optoelectronic field and of printed electronics as a whole. Knowing this limitation, we propose that solvent selections for ink chemistries should be more quantitative and focus on lowering toxicity. To this end, we show that a Hansen solubility model is effective in predicting ink systems using lower toxicity solvents. We also show that inks formed from this method are applicable for high-speed slot-die coating, limiting the need for long anneal times. These methods and results demonstrate a useful framework for quantitatively engineering solvent systems with reduced toxicity while simultaneously maintaining and surpassing performance. It therefore provides a pathway and major step forward towards the commercialization of solution coated perovskite technologies.