Bubble Point Research Articles

Cell viability assessment associated with a contact of gas bubbles produced by femtosecond laser breakdown in cell culture media

High intensity near infrared femtosecond laser is a promising tool for three-dimensional processing of biological materials. During the processing of cells and tissues, long lasting gas bubbles randomly appeared around the laser focal point, however physicochemical and mechanical effects of the gas bubbles has not been emphasized. This paper presents characteristic behaviors of the gas bubbles and their contact effects on cell viability. High-speed imaging of the gas bubble formation with various additives in physiological medium confirms that the gas bubble consists of dissolved air, and amphipathic proteins stabilize the bubble surface. This surface protective layer inhibits interactions of gas bubbles and cell membranes. Consequently, the gas bubble contact does not cause critical effects on cell viability. On the other hands, burst of gas bubbles stimulated by an impact of femtosecond laser induced cavitation can lead to liquid jet flow that might cause serious mechanical damages on cells. These results provide insights for the parameter of biological tissue processing with intense fs laser pulses.

Effect of Some Chloride Salts on Swelling Properties of Expansive Soil

This paper aims to provide a proposed correlation for Sudanese crude oil in order to estimate solution gas oil- ratio directly without depending on laboratory measurements.There are many correlations that were utilized for a number of international crude oils. However, because the components of crude differ from region to region, it is difficult to use any specified correlation for different regions and that is simply because each region has its own properties. The core hypothesis of this paper is to find that there is a correlation between the solution gas- oil ratios as a function of the physical properties of the critical temperature, critical pressure, normal boiling temperature, bubble point pressure and gas specific gravity. In these the logarithmic regression method on Microsoft Excel Statistics Package programme used to find this correlation. The obtained results should that there are coefficients for correlation pilot. The correlations were tested using laboratory data in order to justify their accuracy and usefulness using statistical tools and graphics. The results obtained well agreed with laboratory results .The results were compared with other values obtained from international correlations which are used to calculate the solution gas oil ratio.The study indicates that this new correlation can predict well the solution gas oil ratio for Sudanese crude oil when compared to any other known correlations.

Solution Gas-Oil Ratios Correlation for Sudanese Crude Oil

This paper aims to provide a proposed correlation for Sudanese crude oil in order to estimate solution gas oil- ratio directly without depending on laboratory measurements.There are many correlations that were utilized for a number of international crude oils. However, because the components of crude differ from region to region, it is difficult to use any specified correlation for different regions and that is simply because each region has its own properties. The core hypothesis of this paper is to find that there is a correlation between the solution gas- oil ratios as a function of the physical properties of the critical temperature, critical pressure, normal boiling temperature, bubble point pressure and gas specific gravity. In these the logarithmic regression method on Microsoft Excel Statistics Package programme used to find this correlation. The obtained results should that there are coefficients for correlation pilot. The correlations were tested using laboratory data in order to justify their accuracy and usefulness using statistical tools and graphics. The results obtained well agreed with laboratory results .The results were compared with other values obtained from international correlations which are used to calculate the solution gas oil ratio.The study indicates that this new correlation can predict well the solution gas oil ratio for Sudanese crude oil when compared to any other known correlations.

Energy, exergy, exergoeconomic, economic, and environmental analyses and multiobjective optimization of a SCMR–ORC system with zeotropic mixtures

This paper proposes a SCMR–ORC system with zeotropic mixtures. Zeotropic mixtures are separated into two pure fluids in a partial condenser, the pure fluids recover condensation heat in a gas–liquid heat exchanger, and are then compressed, mixed, and recycled. Energy, exergy, exergoeconomic, economic, and environmental (5E) models based on the residual Helmholtz free energy are established to analyze the SCMR–ORC system performance, which is then compared with that of a SCR–ORC system with pure fluids. Multiobjective optimization is performed to obtain 3D Pareto frontiers, and TOPSIS is used to reveal the best performance. The results indicate that when the mass fraction of the low-boiling-point fluid (θ) is low, the SCMR–ORC system can reduce the condensation heat released and increase the condensation heat recovery, and its 5E performances are better than those of the SCR–ORC system. The exergy destruction sum of the partial condenser and gas–liquid heat exchanger can be reduced by 101.03 kW, and their capital cost rate can be saved by 34.89 $/h. The optimal bubble point evaporation temperature of three zeotropic mixtures is approximately 80 °C, their optimal outlet temperature at expander 1 is in the range of 42–45 °C, and their optimal θ is small.

The effective refrigeration temperature zone expressed by partial molar enthalpy difference of each component in mixed-refrigerant Joule-Thomson refrigerators

Mixed-refrigerant Joule-Thomson refrigerators (MJTRs) are widely used in the fields of energy, chemical engineering and medical treatment. Mixed refrigerants generally employ a mixture of 4–8 components, which provide refrigeration effects in different temperature zones. It is essential to reveal the effective refrigeration temperature zones of different components for the selection of components and adjustment of their concentrations. In this study, the partial molar enthalpy difference is used to characterize the contribution of components to the isothermal throttling effect. The results show that there is an obvious peak in the graph of the contribution of each component to the isothermal throttling effect with temperature, whose height and width represent the refrigeration effect and the effective refrigeration temperature zone of the component, respectively. The temperature zone where the partial molar enthalpy difference of the component is greater than the isothermal throttling effect of the mixed refrigerant is defined as the effective refrigeration temperature zone. The effective refrigeration temperature zone of the component with highest boiling point lies between the high-pressure and low-pressure dew points, and that of the component with lowest boiling point lies between the high-pressure and low-pressure bubble points. Further, the other components provide the refrigeration effect in the temperature zone between low-pressure dew point and high-pressure bubble point, thereby playing the connecting role.

Investigation of non-equilibrium solvent exsolution dynamics and bubble formation and growth of a CO2/C3H8/heavy-oil system by micro-optical visualizations: Experimental and continuum-scale numerical studies

Non-equilibrium exsolution dynamics of a carbon dioxide/propane solvent mixture in heavy oil phase have been studied through a series of micro-optical visualization tests and continuum numerical simulations. The micro-optical visualization tests include bulk-phase Constant-Composition-Expansion (CCE) pressure depletion tests, and bubble-scale exsolution tests from nucleation sites. The CCE tests are aimed to investigate three main parameters of non-equilibrium exsolution dynamics, namely, the total gas phase volume ratio (Vg%), the relative volume of the solvent/heavy oil system (RV), and the solvent molar ratio in free gas phase (e.g., CO2 mol%). The experimental methodology has successfully validated the deviations of the targeting parameters between non-equilibrium and equilibrium state, providing a feasible way to characterize the definition of non-equilibrium. For bubble-scale exsolution tests, two operating schemes have been applied as continuous and segmental depletion. By capturing the growth of bubbles under different depletion schemes, logarithmic relationships have been found between kinetic reaction rate frequency factors (RRFs) of bubble growth and prevailing system pressure. A larger pressure differential from live oil saturation pressure yielded higher kinetic frequency factors. Through all tests, the pseudo-bubble point pressure (where the first batch of gas bubbles were observed) of the solvent/heavy oil system has been determined at ΔP =450∼550kPa from the live oil saturation pressure, which is consistent in terms of the values among different depletion schemes. This has indicated the experimental feasibility in determining the shifting/delay of the bubble point pressure. Numerically, a continuum numerical simulator has been developed to determine the relationship between RRFs and pressure by segmentally history matching Vg%, RV and CO2 mol% of the depletion tests. Similar to the experimental findings, the segmentally optimized RRFs have found to be in logarithmic relationships with pressure. This logarithmic relationship between RRFs and pressure have both been experimentally and numerically verified, and the feasibility of the logarithmic relationship developed from bubble exsolution to be implemented as numerical inputs in continuum reservoir simulation has been validated.

Cold pressurant gas bubble point experiments for coarse mesh screen channel liquid acquisition devices in liquid nitrogen

Screen channel liquid acquisition devices (LADs) will play a crucial role in future deep space travel. It is essential that vapor-free delivery of propellants during in-space transfer is ensured to maximize yield from storage tanks and prevent potential combustion instabilities. The screen channel LAD utilizes a fine screen wire mesh that can separate phases in a low Bond number (i.e. microgravity) environment using surface tension forces. This paper presents cryogenic liquid nitrogen (LN2) screen channel LAD bubble point experiments focused on coarser mesh screens. A total of 14 different screen types are tested across a range of cryogenic liquid temperatures near the screen (70.8 − 80.0 K) and dewar pressures (∼101.3 – 156.5 kPa or ∼0 – 8 psig) for two pressurization schemes (noncondensable gaseous helium and autogenous pressurization with gaseous nitrogen) to examine the effect of pressurant gas type on LAD performance. Cold pressurant gas bubble point test results for coarser meshes shown here agree almost perfectly with historical trends using fine mesh screens. Pressurization with a noncondensable generally leads to higher bubble point due to evaporative cooling at the LAD screen while pressurization with the vapor generally leads to degradation in performance due to condensation of the vapor and subsequent interfacial heating.

Laboratory and Theoretical investigations of Petroleum Reservoir Fluid Properties

Understanding the Pressure-Volume-Temperature (PVT) properties is very important to many kinds of petroleum determinations like calculations of reservoir fluid properties; expect the future performance, selection of enhanced oil recovery methods, and for production facilities design. Models for expecting reservoir fluid properties has been increased attention during last decade by knowing reservoir pressure and temperature, oil API gravity, and gas gravity. In general, PVT properties are obtained from laboratory experiments but in some cases In this study, complete PVT lab experiments were done and evaluated the most frequently used empirical black oil PVT correlations for application in the Middle East. Empirical PVT Correlations for the Middle East crude oil was compared as a function of commonly available PVT data. Correlations compared for: Bubble point pressure, solution gas oil ratio, oil formation volume factor, oil density, and oil viscosity. After evaluating the Empirical correlations, the crude sample was characterized using different EOS to arrive at one EOS model that accurately describes the PVT behavior of crude oil produced. The multi-sample characterization method is used to arrive at one consistent model for crude oil for the whole reservoir. The fluid sample is first analyzed for consistency to ensure that they are representative of oil produced, then it is used to obtain parameters for EOS model. The tuning procedure for the EOS is done systematically by matching the volumetric and phase behavior results with laboratory results. Results showed that some correlations give good results in PVT properties compared to the laboratory and can be used with Libyan oil, while some give a high percentage of error.

Estimation of the Bubble Point Pressure of Multicomponent Reservoir Hydrocarbon Fluids

This study developed a novel C-sharp (C#) programming language for the estimation of bubble point pressure (BPP) of various hydrocarbon mixtures at equilibrium state. The methodology was based on vapor–liquid equilibrium calculation using Peng Robinson equation of state implementation, thermodynamic equilibrium calculation and Newton-Raphson’s method for the successive substitution of the unknown variables. The equal fugacity constraint can be satisfied by obtaining the equilibrium which serves as a criterion for two or more phases to exist at equilibrium. The problem was resolved by searching for a pressure that will satisfy the two constraints. Complex calculation was performed by successively substituting the pressure value estimated by Newton–Raphson’s method at reservoir temperature until the two constraints were satisfied. The BPP values for the eight reservoir sample fluids were within the range of 29.32–308.00 atm with an absolute error deviation ranging from 0.00–4.27 and average percentage error of 0.54%. BPP values were obtained were within the reservoir temperature range of 328.15–398.71 K. This procedure is a potential approach for the estimation of BPP for hydrocarbon mixtures with defined fluid composition irrespective of their composition.

Explicit Neural Network-Based Models for Bubble Point Pressure and Formation Volume Factor Prediction

Explicit Neural Network-Based Models for Bubble Point Pressure and Formation Volume Factor Prediction

Experimental data and thermodynamic modeling of the CO2 + Acetone + Efavirenz system at high pressures

It is important to understand the fluid phase behavior of the systems containing CO2, acetone, and Efavirenz for processes that use supercritical fluids to produce micro and/or nanoparticles for drug encapsulation. Thus, the purpose of this work is to measure experimentally data on the phase transitions of CO2 + Efavirenz and CO2 + acetone + Efavirenz systems using the visual static synthetic method and a variable-volume cell integrated into the experimental equipment. The experimental settings for the binary system were: pressures up to 16 MPa, temperatures of 333.15, 338.15, and 343.15 K, and the global Efavirenz mole fraction from 4 × 10−5 up to 15 × 10−5. The experimental settings for the ternary system were: pressure up to 10 MPa, temperatures from 303.15 to 333.15 K, and the global CO2 mole fraction from 0.2 up to 0.9. For the binary systems, the observed phase transitions are solid–fluid transitions; for the ternary systems, the observed phase transitions are bubble point (BP) transitions. Thermodynamic simulations using the Group Contribution Volume-Translated Peng-Robinson (GC-VT-PR) and Perturbed Chain Statistical Associating Fluid Theory (PC-SAFT) equations of state (EoS) demonstrated a striking correlation with experimental data. The relative deviations from pressure and temperature corroborate the efficiency of the thermodynamic models used in this work.

High pressure phase behavior of ternary system (carbon dioxide + globalide + dichloromethane) at different dichloromethane to globalide mass ratios

Globalide is a 16-membered macrolactone, which contains a double bond, typically used in the fragrance industry, due to its musky odor. However, its application as a monomer for the synthesis of the polyester polyglobalide (PGl) is drawing attention of the scientific community, due to its biocompatible and non-toxic character, being a great candidate for biomedical applications. This kind of polymer are frequently synthesized using green solvents, and pressurized carbon dioxide is being reported as a suitable alternative in polymerization processes. In this work, we evaluate the phase behavior of the ternary system carbon dioxide (1) + globalide (2) + dichloromethane (3), at high pressures. Experimental measurements of the phase equilibrium of the system were carried out at the following dichloromethane/globalide mass ratios: 0.5:1, 1:1 and 2:1, in a range of temperatures varying from 313 to 343 K. Thermodynamic modeling of the experimental data was performed using Peng Robinson equation of state with van der Waals biparametric quadratic mixing rule (PR-vdW2). Phase transitions of vapor–liquid (bubble point), liquid–liquid and vapor–liquid–liquid types were observed. The system showed LCST behavior (Lower Critical Solution Temperature), whose temperature increase results in higher pressures necessary for complete solubilization of the system. Dichloromethane showed to be an effective co-solvent, reducing the pressure required for the solubilization of the system. PR-vdW2 equation satisfactorily represented the system, with acceptable deviations under the studied conditions.

The hard-core effect on PC-SAFT to model asphaltene precipitation in petroleum reservoir fluids

In this work, a hard-core version of the Perturbed Chain-Association Fluid Theory Equation of State (PC-SAFT EoS) is proposed and used to predict upper asphaltene onset pressures (AOPs), bubble points (BPs), and precipitated asphaltene amounts for eighteen real petroleum reservoir fluids around the world. As a result, for the same assumed asphaltene molecular weight (MW) value, this hard-core PC-SAFT model predicts lower AOPs than the other two PC-SAFT versions here tested, including the original version of PC-SAFT. The AOPs and precipitated asphaltene amounts are found to be directly related to the asphaltene MW values used for each PC-SAFT model. The hard-core PC-SAFT model here presented is the PC-SAFT version that requires the lowest asphaltene MWs and predicts the lowest precipitated asphaltene amounts for the eighteen fluids modeled.

Development of a new approach using an artificial neural network for estimating oil formation volume factor at bubble point pressure of Egyptian crude oil

Understanding the phase behavior and volumetric changes of reservoir fluids throughout the extent of reservoir lifetime are crucially required for effective-commercial oil recoveries. Ideally, reservoir fluid properties are experimentally measured by laboratory experiments known as PVT tests nonetheless, these tests are prohibitive, time-consuming, and required to restrict sampling and transporting procedures. For these discernible reasons, several modeling approaches have been developed. By reviewing the literature, one crucial obstacle that encounters field applicability of most extant models is the selection of input variables. Moreover, a great percentage of extant models employ the results of lengthy experimental tests such as differential gas solubility or even the sample’s chemical composition. Replicability of models’ results using different datasets is also one of the main challenges when employing AI models. Frequently, inadequate descriptions for AI models have been provided in many studies which limits their utility. The inadequate description includes the analysis of ANN model weights and biases besides, the final mathematical model. In this study, a rigorous ANN model with its mathematical model has been implemented to predict oil formation volume factors based on 600 compiled datasets from Egyptian oilfields.A detailed comparison between widely used empirical correlations and the proposed new ANN model is provided in this study. Statistical and graphical analysis depicted the outstanding performance of the new model with R2 = 0.974, ARE = −0.0017%, and AARE = 2.13%. The ANN model provides remarkable sustainable performance compared to local Egyptian empirical correlations and all the other global models.

A Comparison between the Perturbed-Chain Statistical Associating Fluid Theory Equation of State and Machine Learning Modeling Approaches in Asphaltene Onset Pressure and Bubble Point Pressure Prediction during Gas Injection.

Predicting asphaltene onset pressure (AOP) and bubble point pressure (Pb) is essential for optimization of gas injection for enhanced oil recovery. Pressure-Volume-Temperature or PVT studies along with equations of state (EoSs) are widely used to predict AOP and Pb. However, PVT experiments are costly and time-consuming. The perturbed-chain statistical associating fluid theory or PC-SAFT is a sophisticated EoS used for prediction of the AOP and Pb. However, this method is computationally complex and has high data requirements. Hence, developing precise and reliable smart models for prediction of the AOP and Pb is inevitable. In this paper, we used machine learning (ML) methods to develop predictive tools for the estimation of the AOP and Pb using experimental data (AOP data set: 170 samples; Pb data set: 146 samples). Extra trees (ET), support vector machine (SVM), decision tree, and k-nearest neighbors ML methods were used. Reservoir temperature, reservoir pressure, SARA fraction, API gravity, gas–oil ratio, fluid molecular weight, monophasic composition, and composition of gas injection are considered as input data. The ET (R2: 0.793, RMSE: 7.5) and the SVM models (R2: 0.988, RMSE: 0.76) attained more reliable results for estimation of the AOP and Pb, respectively. Generally, the accuracy of the PC-SAFT model is higher than that of the AI/ML models. However, our results confirm that the AI/ML approach is an acceptable alternative for the PC-SAFT model when we face lack of data and/or complex mathematical equations. The developed smart models are accurate and fast and produce reliable results with lower data requirements.

A reservoir bubble point pressure prediction model using the Adaptive Neuro-Fuzzy Inference System (ANFIS) technique with trend analysis.

The bubble point pressure (Pb) could be obtained from pressure-volume-temperature (PVT) measurements; nonetheless, these measurements have drawbacks such as time, cost, and difficulties associated with conducting experiments at high-pressure-high-temperature conditions. Therefore, numerous attempts have been made using several approaches (such as regressions and machine learning) to accurately develop models for predicting the Pb. However, some previous models did not study the trend analysis to prove the correct relationships between inputs and outputs to show the proper physical behavior. Thus, this study aims to build a robust and more accurate model to predict the Pb using the adaptive neuro-fuzzy inference system (ANFIS) and trend analysis approaches for the first time. More than 700 global datasets have been used to develop and validate the model to robustly and accurately predict the Pb. The proposed ANFIS model is compared with 21 existing models using statistical error analysis such as correlation coefficient (R), standard deviation (SD), average absolute percentage relative error (AAPRE), average percentage relative error (APRE), and root mean square error (RMSE). The ANFIS model shows the proper relationships between independent and dependent parameters that indicate the correct physical behavior. The ANFIS model outperformed all 21 models with the highest R of 0.994 and the lowest AAPRE, APRE, SD, and RMSE of 6.38%, -0.99%, 0.074 psi, and 9.73 psi, respectively, as the first rank model. The second rank model has the R, AAPRE, APRE, SD, and RMSE of 0.9724, 9%, -1.58%, 0.095 psi, and 13.04 psi, respectively. It is concluded that the proposed ANFIS model is validated to follow the correct physical behavior with higher accuracy than all studied models.

On the phase behaviour of the CO2 + N2O4 system at low temperatures

• VLE data for CO 2 + NO 2 /N 2 O 4 at 253 to 303 K using a static-synthetic apparatus. • Experimental data compared to the Peng–Robinson (PR) with classic mixing rules. • Melting points of N 2 O 4 in CO 2 were measured. • Models used to predict the phase diagram of the binary system. Carbon dioxide capture transportation and storage is one of the technologies that can be employed to reduce CO 2 emissions from power plants. Unfortunately, in the post combustion capture process, CO 2 is not pure and contains impurities like SO 2 , NO x , N 2 , O 2 and Ar for example. In this paper, Vapour-Liquid-Equilibrium (VLE) of a binary system composed of CO 2 and N 2 O 4 /NO 2 have been investigated. The equipment used is based on the “static-synthetic” method with a variable cell to determine the bubble pressure or saturated pressure of the system. The setup was used to obtain bubble point data at four isotherms (253.43, 273.43, 293.43, 303.43) K and pressures up to 7.3 MPa. The accuracies of the measured temperature and pressure were estimated to be 0.03 K and 0.12 kPa, respectively. The Peng–Robinson equation of state (PR78 EoS) is used to represent the isothermal P, x data.

Phase Behavior in Nanopores and Its Indication for Cyclic Gas Injection in a Volatile Oil Reservoir from Duvernay Shale

Abstract Duvernay shale spans over 6 million acres with a total resource of 440 billion barrels’ oil equivalent in the Western Canada Sedimentary Basin (WCSB). The oil recovery factors typically decrease with the decreasing of gas-oil ratio (GOR) in oil window of Duvernay shale. The volatile oil recovery factors are typically 5–10%. Enhanced oil recovery technologies should be applied to improve the economics of the reservoirs. In this paper, the volatile oil from the Duvernay shale was taken as an example for phase behavior study. We analyzed the nanopore confinement on phase behavior and physical properties of Duvernay shale oil. The shift of critical properties was quantified within nanopores. With the confinement of nanopores, the viscosity, density, and bubble point pressure of the oil decrease with the shrinking of the pore size. Minimum miscibility pressure (MMP) was calculated for different injected gases. The MMP from high to low is N2>CH4>lean gas>rich gas>CO2. In the case of injecting the same gas component, the MMP decreases as the pore size decreases. The wellhead rich gas is suggested to be the main gas source for gas injection in Duvernay shale. The formation pressure should be rapidly increased to the MMP and maintained close to it, which would help to improve the effect of gas injection and enhance shale oil recovery. This paper can provide critical insights for the research of shale oil gas injection for enhanced oil recovery.

Gas Hydrate in Oil-Dominant Systems: A Review.

Gas hydrate risks minimization in deepsea hydrocarbon flowlines, especially in high water to oil ratios, and is critical for the oil and gas flow assurance industry. Although there are several reviews on gas hydrate mitigation in gas-dominated systems, limited reviews have been dedicated to the understanding and mechanism of hydrate formation and mitigation in oil-dominated systems. Hence, this review article discusses and summarizes the prior studies on the hydrate formation behavior and mitigation in oil-dominated multiphase systems. The factors (such as oil volume or water cut, bubble point, and hydrate formers) that affect hydrate formation in oil systems are also discussed in detail. Furthermore, insight into the hydrate mitigation and mechanism in oil systems is also presented in this review. Also, a detailed table on the various studied hydrate tests in oil systems, including the experimental methods, inhibitor type, conventions, and testing conditions, is provided in this work. The findings presented in this work are relevant for developing the best solution to manage hydrate formation in oil-dominated systems for the oil and gas industry.

Development of a Downhole Measurement System for Phase Behavior of Reservoir Crude Oils and Retrograde Condensates

This article reviews the scientific findings that were integrated into a downhole prototype to measure hydrocarbon phase behavior. While laboratory measurements of bubble point pressure (Pb), asphaltene onset pressure (AOP), and dewpoint pressure (Pd) are well established and have been extensively studied, such measurements of reservoir crude oils are novel downhole due to their operational, hydraulic, and interpretational complexities. Furthermore, such laboratory measurements typically take several hours to complete and can only be carried out by skilled personnel. For the downhole measurement, novel science and understanding were developed to reduce the measurement time to minutes and to automate the workflow. This article reviews the science and technology that enabled these downhole measurements to be made rapidly and provides field examples of how sampling is optimized and quality is validated in real time.