Petroleum Thermodynamics, Flow Assurance

Consortium Objectives

  • Establish a forum for active participation of oil companies for exchanging ideas, proposing problems and learning about the state-of-the-art technologies and tools in the area of petroleum thermodynamics and flow assurance.

  • Conduct fundamental and exploratory research for consortium members in the areas of petroleum thermodynamics and flow assurance to prove concepts and increase the general understanding of the phenomena associated to these areas of interest.

  • Develop experimental procedures and modeling tools for determining the behavior of crude oils, the occurrence and the magnitude of flow assurance problems and the most cost/effective solutions for mitigation of these problems.

  • Support the education and training of graduate students and employees of oil companies in the areas of petroleum thermodynamics and flow assurance.

Lead researchers

Francisco Vargas Picture

Francisco M. Vargas

Consortium Director
Assistant Professor
Chemical & Biomolecular Engineering

Areas of Expertise
Petroleum thermo-physical and rheological behavior, flow assurance and production chemistry

Walter G. Chapman

Walter G. Chapman

William W. Akers Chair Professor
Chemical & Biomolecular Engineering

Areas of Expertise
Molecular modeling of complex fluids, polymer systems, confined fluids and natural gas hydrates

Sibani Lisa Biswal Picture

Sibani Lisa Biswal

Associate Professor
Chemical & Biomolecular Engineering

Areas of Expertise
Soft matter, colloidal systems, surfactants and multiphase flow in microfluidic systems.

Research Topics

Gold members will influence the research direction of this consortium. The following are examples of research topics that can be executed with available infrastructure at Rice University:

  • Petroleum Phase Behavior
  • Thermo-physical and rheological properties of crude oils
  • Water content determination in hydrocarbons
  • Gas hydrate formation and inhibition
  • Prediction and mitigation of asphaltene precipitation and deposition
  • Development and testing of oilfield chemicals
  • Interactions between different flow assurance problems
  • Flow assurance problems in the near-wellbore region
  • Multiphase transport in micro-models (i.e. porous media and fractures)

Expected benefits for members

Both gold and silver members of this consortium will have access to:


  • State-of-the-art modeling and experimental methods for PVT and Flow Assurance applications
  • Our most advanced simulation tool for crude oil characterization, PVT and Flow Assurance modeling
  • Short online courses on PVT and Flow Assurance
  • Our scientific manuscripts before they are publically available
  • Dedicated website with FAQ, videos, and other relevant materials


Current infrastructure in the Petroleum Thermodynamics and Flow Assurance Laboratory (PTFA Lab):


  • Hirox KH-8700 3D Digital Microscope. Cross polarized light, 3D digital reconstruction of surfaces, up to 2500X magnification, light and bright fields (see Figure 1 for an example of microscopic analysis done on Edwards Brown rock).
  • Anton Paar Density meter 4500M + Anton Paar Refractometer Abbemat WR / Heated Auto-sampler, for ambient pressure and temperature range of ambient to 80 °C (ambient to 176 °F).
  • Anton Paar High Pressure and High Temperature Density meter to measure density at pressures up to 1,400 bar (20,300 psi) and temperatures from −10 up to 200 °C (14 up to 392 °F).
  • Shimadzu UV-VIS-NIR Spectrophotometer UV-3600 with T2X2 Dual Temp Controlled Cuvette Holder-UV-VIS to record sample absorbance in the wavelength range of 185 to 3300 nm and temperature range of −20 °C to 110 °C (−4 °F to 230° F).
  • Retsch Planetary Ball Mill PM 100 for grind sizes less than 1 mm (normal), 0.1 μm (colloidal).
  • Cryette WR (wide range) cryoscope for molecular weight determination of samples by depression of freezing point of solvents in the temperature range of −26 °C to 6 °C (−14.8 °F to 42.8 °F)
Hirox 3D surfaces microscopy

Figure 1.Digital reconstruction of the surface of a thin section of an Edwards Brown rock sample at 140x and 350x magnification, using the Hirox KH-8700 3D Digital Microscope. New algorithms for determination of surface roughness are being developed.

Besides the instruments currently available in the PTFA Lab, a number of instruments are also available on campus for determination of various properties of interest. For instance Biswal’s Lab has the following capabilities:

  • Interfacial shear rheometer
  • Brewster angle microscopy
  • Confocal Microscopy
  • High temperature flow imaging

Also equipment for fabrication of micro-channels and for determination of contact angle and wettability, interfacial tension, viscosity, and fluorescence intensity of samples are readily available. NMR, SEM, TEM, FTIR-Microscope, ICP-MS, XRD, and Zeta Potential Analyzer are also examples of instruments that are accessible on campus through the Shared Equipment Authority at Rice University.

Future infrastructure for the PTFA Lab:


  • Mettler Toledo High Pressure (HP) Differential Scanning Calorimeter (DSC) for thermal characterization of samples under precisely defined atmospheres at pressures of up to 100 bar (1,450 psi) as a function of temperature or time. Maximum operating temperature is 700 °C (1,292 °F).
  • Sanchez Technologies Asphaltene & Wax Automatic Instrument (AWAI 1000) for determination of asphaltene onset pressure (AOP), bubble point (BP) and wax appearance temperature (WAT). This instrument is equipped with an NIR spectrophotometer and a high pressure microscope with cross polarized light. Temperature range is −20 to 200 °C (−4 °F to 392 °F) and pressure range is ambient to 1,000 bar (14,500 psi).
  • Sanchez Technologies PVT System 400/1000 with full visibility for PVT studies of black oils and gas condensates. Cell volume of 400 mL, maximum operating pressure of 1,000 bar (14,500 psi) and temperature of 200 °C (392 °F).
  • Necessary instruments and accessories to perform full compositional analysis of gas and liquids, fluid recombination and restoration at reservoir conditions, gas-to-oil ratio determination, complete PVT studies including constant composition expansion, differential vaporization, separation tests, viscosity measurements, z-factor, bubble point and dew point, water content, among others.

Examples of research achievements and successful case studies

Modeling of petroleum phase behavior using the PC-SAFT Equation of State

We have successfully adapted the PC-SAFT equation of state (Gross & Sadowski, 2001; Chapman et al., 1988) for accurate prediction of the phase behavior of crude oils, including the precipitation of asphaltenes. The simulation parameters are fitted to compositional data, experimental values of stock-tank oil density, bubble pressure (BP) and asphaltene onset pressures (AOP) at certain composition. Figure 2 shows the simulation results for the blind prediction of asphaltene onset pressure (AOP) and bubble point for a light crude oil at different lean gas injection percentages. The simulation parameters are fitted to the 5% gas case and the asphaltene stability and bubble point are accurately predicted for 10, 15 and 30 % gas. Figures 3 and 4 show that the liquid density and gas-to-oil ratio, the isothermal compressibility and the gas composition during differential liberation experiments can be accurately predicted using this modeling method.

Hirox 3D surfaces microscopy

Figure 2. Accurate prediction of the asphaltene onset pressure (AOP) and bubble pressure (BP) for blends of light crude oil and lean hydrocarbon gas. The markers are experimental values of AOP and BP and the lines the simulation results using the PC-SAFT EOS.

Hirox 3D surfaces microscopy

Figure 3. Blind prediction of (a) liquid density and (b) gas-to-oil ratio (GOR) as a function of pressure for the same light crude oil, whose modeling results are shown in Figure 1. The markers are experimental data and the lines blind predictions from the PC-SAFT EOS.

Hirox 3D surfaces microscopy

Figure 4. Blind prediction of (a) isothermal compressibility, (b) mole fraction of methane in the gas phase and (c) mole fraction of nitrogen in the gas phase as a function of pressure for differential liberation experiments done on a light crude oil. The markers are experimental data and the lines represent the predictions from the PC-SAFT EOS.

An important application of our modeling methods based on the PC-SAFT equation of state is for the design of experiments and validation of experimental data. AOP and BP determinations done on bottom-hole samples are time consuming and represent a significant investment. Our simulation tool can assist in the design of such experiments to reduce the execution time and for validation of the results obtained. Figure 5 shows the results of a case study, in which simulation parameters were tuned to compositional data, STO density and bubble pressure of live oil and AOP data. The predictions of AOP and BP (blue lines and red lines, respectively) at 5% and 20% gas injection are acceptable. However, the results at 10% gas injection shows significant discrepancy between the model and the experiments. Repetition of this experiment led to experimental AOP and BP values that were consistent with the modeling predictions. Thus, this tool is very effective for quick data consistency validation.

Other potential applications for the PC-SAFT equation of state are for predicting the compositional grading of asphaltenes in the reservoir, reservoir connectivity, formation of tar-mats, effect of oil-base mud contamination on petroleum phase behavior and asphaltene stability and even for the calculation of derivative properties, such as heat capacity, speed of sound or the Joule-Thomson coefficient. Figure 6 shows the comparison of the modeling results using the Soave-Redlich-Kwong, the Peng-Robinson and the PC-SAFT equations of state with respect to experimental data for the Joule-Thomson coefficient, mJT, of n-decane as a function of pressure. The PC-SAFT equation of state has a clear superior performance in the prediction of this property in a wide range of temperatures (36 to 283 °C, 97 to 541 °F) and pressures (1 to 800 bar, 14.7 to 11,600 psi).

Hirox 3D surfaces microscopy

Figure 5. Validation of consistency of experimental data values for asphaltene onset pressure (AOP, blue line) and bubble pressure (BP, red line) using the PC-SAFT equation of state. Experimental values at 10% gas injection show discrepancies that may indicate potential experimental issues.

Hirox 3D surfaces microscopy

Figure 6.Simulation of the Joule-Thomson coefficient for n-decane at (a) T = 36°C (97°F) and (b) T = 283°C (541°F) using PC-SAFT, PR and SRK equations of state. The data were taken from the NIST database (2013).

The PC-SAFT Equation of State has been proven to be successful in the prediction of petroleum phase behavior at reservoir conditions, including the precipitation of asphaltenes in a wide range of temperatures, pressures and compositions. The PC-SAFT equation of state is available in commercial software packages such as Infochem’s (KBC) Multiflash, VLXE, Calsep’s PVTsim and Aspen Plus. Nevertheless, the methodologies for parameter estimation vary greatly among the different commercial packages and this leads to significant differences in the predictions. Our methodology for parameter estimation that has been used to obtain the results shown in this document is only available in our own software that is currently being developed, which offers a user-friendly highly automated interface for quick and accurate calculations.


J. Gross & G. Sadowski. Ind. & Eng. Chem. Res. 2001, 40, 1244-1260   |  W.G. Chapman, K.E. Gubbins, G. Jackson, M. Radosz,  Ind. & Eng. Chem. Res. 1990, 29, 1709-1721    |   S. Punnapala & F.M. Vargas. Fuel, 2013,108, pp 417-429.   |   S.R Panuganti, F.M Vargas, D.L. Gonzalez, W.G Chapman. Fuel, 93, 2012, pp 658–669.   |  Abutaqiya, M. The Petroleum Institute, MSc Thesis 2013
F.M. Vargas, M. Garcia-Bermudes, M. Boggara, S. Punnapala, M. Abutaqiya, N. Mathew, S. Prasad, A. Khaleel, M. Al Rashed, H. Al Asafen, Offshore Technology Conference, OTC 25294, Houston, TX, May 2014.


Experimental investigation of the mechanisms by which asphaltenes precipitate and deposit

In a series of experiments we studied the reversibility of asphaltene precipitation and the morphology of the precipitate obtained. Fig. 7 shows that precipitation of asphaltenes upon addition of iso-octane is a reversible process after the iso-octane is evaporated from the sample. In Fig. 8a details of micro-structure of asphaltene aggregates are observed using Scanning Electron Microscopy. Asphaltene aggregates are porous materials formed by particles of fairly uniform size distribution (average diameter of about 350 nm in this case).  In Figs. 8b and c asphaltenes that were separated from oil by addition of n-heptane are dried at ambient temperature and 120°C (248°F), respectively, and put in contact with dead oil. Asphaltenes that were dried at ambient conditions are partially re-dissolved, but not the asphaltenes that were dried at high temperature. These observations suggest chemical and physical changes of the asphaltenes at elevated temperatures.  By combining the experimental observations, a conceptual mechanism for asphaltene precipitation, aggregation and aging is proposed, which is depicted in Figure 9. Asphaltene nano-aggregates, which are present even in good solvents (Mullins, 2010) upon precipitation form aggregates of less than 1 mm (which are not easily detected by commercial methods), and in turn further aggregate and eventually modify their structure to form solid-like materials.  Some steps are reversible (represented by double green arrows in Fig. 9). However, once a solid-like structure is formed re-dissolution is not easily achieved. Finally, Fig. 10a shows a graphical representation of the multi-step mechanism for asphaltene precipitation, aggregation and deposition in the wellbore. The multi-step process is partially confirmed experimentally according to Fig. 10b.   From this mechanism it is clear that asphaltene aggregation and deposition are two competing phenomena. Based on the mechanisms described in Figs. 9 and 10, novel asphaltene deposition inhibitors are being developed in our lab, which disrupt the aging process of asphaltene aggregates and help maintaining a soft asphaltene structure that is easier to re-dissolve and/or remove.

Hirox 3D surfaces microscopy

Figure 7. Microscopic observations of asphaltene precipitation reversibility under digital microscope using 100X of magnification. (a) Precipitation of asphaltene from stock tank oil upon addition of iso-octane; (b) Asphaltene precipitated phase upon outbound diffusion (from aggregates) and evaporation of iso-octane; (c) Asphaltenes being re-dissolved into the same oil from which they were precipitated.

Figure 8. (a) SEM micrograph of an asphaltene sample extracted from light dead oil (b) Asphaltene precipitated with n-heptane and dried at ambient temperature, then put in contact with the original oil. Partial re-dissolution is observed. (c) Asphaltene precipitated with n-heptane and dried at 120 °C, then put in contact with the original oil. No re-dissolution is observed and the appearance is of a solid structure.

Figure 9. Proposed multi-step mechanism for asphaltene precipitation, aggregation and aging. Reversible stages are represented by dual green arrows. The concept of nano-aggregate, along with the corresponding size is taken from the work of Mullins et al. (2010, 2012)

Figure 10. Left: Multi-step mechanism for asphaltene precipitation, aggregation and deposition. According to this mechanism asphaltene aggregation and deposition are two competing phenomena.
Top: Evolution of asphaltene aggregation at ambient conditions. Asphaltenes aggregates evolve forming more compact structures with time.

F.M. Vargas et al., OTC 25294. | O.C. Mullins. Energy & Fuels, 2010, 24, 2179–2207. | F.M. Vargas, J.L. Creek & W.G. Chapman, Energy & Fuels, 2010, 24 (4), 2294-2299

Effect of asphaltenes on viscosity of oils

A large body of the available viscosity data for asphaltene suspensions was reinterpreted in terms of the Krieger–Dougherty model. Based on the analysis carried out in this work, the following model is proposed for accurate estimation and correlation of the viscosity of asphaltene suspensions:

Fluorescence Deposit Asphaltene

where: ηr and η are the relative and intrinsic viscosities, respectively, and ϕ is the volume fraction of asphaltenes.

Plot Viscosity vs Asphaltene Volume Fraction

Ref: R. Pal & F.M. Vargas. Can. J. of Chem. Eng., 2013, 92, 573-577.

Prediction of the occurrence and the magnitude of asphaltene deposition in wellbores

Based on the conceptual mechanism described in Fig. 10, thermodynamic and transport equations have been developed and solved to predict the occurrence and the magnitude of asphaltene deposition in wellbores. This simulation tool has been successfully used to predict asphaltene deposit thickness as a function of well depth. The example shown below is for an oil well from the Marrat field in Kuwait.

Deposition Profile Simulation

Ref: A.S. Kurup, F.M. Vargas, J. Wang, J. Buckley, J.L. Creek, H.J. Subramani, and W.G. Chapman. Energy & Fuels, 2011, 25, 4506–4516.

Multiphase flow in porous media

Micro-models with various geometries, permeabilities and surface specifications can be created. These micro-models can mimic contrast of permeability and fractures in rocks. A special cell is currently being developed for high pressure experiments.

Asphaltene Deposition Porous Media

Surface alteration is possible and wettability can be studied via contact angle measurements.

Conctact angle
Fluorescence Deposit Asphaltene

Left: The mechanisms of asphaltene deposition in porous media can be studied using micro-models. Fluorescence of asphaltenes present in crude oil can be observed by using confocal microscopy. This technique is also useful to study remediation strategies for asphaltene deposition.

Ref: Y.J. Lin, F.M. Vargas & S.L. Biswal, in preparation.

Correlation and Prediction of Water Content in Alkanes Using a Molecular Theory

A predictive model has been developed for the saturated water concentration in n-alkanes based on a theoretical equation of state for the hydrocarbon rich phase and a water equation of state for the aqueous phase. Excellent qualitative and good quantitative agreement is exhibited without fitting a binary interaction parameter. The model is then extrapolated to predict water solubility in n-alkanes as a function of temperature, pressure, and carbon number for conditions where experimental data is of questionable validity or unavailable.

Plot Viscosity vs Asphaltene Volume Fraction

Ref:C.P. Emborsky, K.R. Cox, and W.G. Chapman. Ind. & Eng. Chem. Res. 2011, 50, 7791-7799   |  R.H. Olds, B. H. Sage & W. N. Lacey, Ind. Eng. Chem. 1942, 34, 1223.

Membership levels

Silver Membership

For smaller companies interested in keeping up with the dynamic research and continuous development of experimental methods and simulation tools in the areas of petroleum thermodynamics and flow assurance. Silver members receive:

  • Attendance to the annual meeting of the Consortium on Petroleum Thermodynamics and Flow Assurance at Rice University. At this technical meeting, graduate students, research associates and faculty affiliated to the consortium will present the progress on the research projects and receive feedback from the members.
  • Unlimited access to short online courses in the areas of petroleum thermodynamics and flow assurance.

Gold Membership

For larger corporations that want to steer the research direction of the consortium and lead the exploration of problems and proof of concepts and the development of state-of-the-art experimental techniques and modeling tools for petroleum phase behavior and flow assurance applications. Gold members receive all the benefits of silver members plus:


  • ONE short face-to-face course on petroleum phase behavior modeling or flow assurance related issues per year.

  • The opportunity to vote on the selection of projects and research direction of the consortium.

Contact Details

Francisco M. Vargas
CHBE Department
Rice University
6100 Main St, MS-362
Houston, TX, USA 77005

Abercrombie Lab, B228
George R. Brown Hall
E110 and E125

Tel:   +1 (713) 348-2384

Email: vargas(at)


Go to Top