A New Method to Characterize the Size and Shape Dynamics of Asphaltene Deposition Process in CO2 Miscible Flooding

Abstract

The use of miscible solvents in Improved Oil Recovery (IOR) processes requires knowledge of how the solvent will behave over all mixing ratios of oil and solvent. In particular it is important to know: (i) at what solvent concentration the asphaltenes start to precipitate, and (ii) what conditions will cause the particles to flocculate and eventually deposit in the reservoir pore network. In order to study this process we have developed a new method of describing the process of asphaltene precipitation/flocculation/deposition under typical reservoir conditions. This method uses image analysis to convert the information obtained from a typical sequence of images obtained from a dynamic high pressure mixing system acquired using a Micro-Visual cell and special optics. These images are analyzed and a single number per image is computed. This number is defined as the “Particle Growth Factor” (PGF), which is a compound number that includes information about the size of the particles, the number of particles and their shape. This new approach shows how PGF increases with respect to solvent concentration. If we use a suitable non-linear model to fit PGF with respect to concentration, we can use the characteristics of the function to predict the onset of precipitation, the point of maximum flocculation, and when deposition is at its maximum. We can then produce a least squares correlation, which relates the concentration of asphaltene precipitation onset to both pressure and temperature, using a 3D polynomial surface. In the field, this information can then be used to predict production/injection performance and different operational problems related to asphaltene deposition in CO2 miscible injection and also CO2 sequestration process in a depleted oil reservoir.