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Research Area: Improved recovery

Enhanced oil recovery with CO2 based nanofluid: A Multiscale modelling scheme for Nanoparticle interaction with liquid CO2

Project Number: 6368
Project Duration: 01.01.18 - 31.12.20

Project manager: Afrooz Barnoush, NTNU

Division Head: Kent Holing

Technical contact person, Statoil: Bamshad Nazarin

Objective

Residual oil saturation not accessible to primary and secondary recovery can be recovered using Enhanced Oil Recovery (EOR) methods. Water-Alternating-Gas (WAG) technique involving gas (e.g., CO2) injection to increase displacement efficiency followed by water injection to increase sweep efficiency is an emerging EOR method that has attracted significant attention. This technique has high microscopic sweep efficiency; however, it suffers from poorer macroscopic sweep efficiency (e.g., channeling, gravity instability) due to the large density difference and also adverse mobility ratio between displacing fluid (CO2) and displaced fluid (oil).

An increase in CO2 viscosity which results in lower CO2 mobility could reduce problems with poor macroscopic sweep efficiency. Therefore, design of an economic CO2 thickener remains an extremely relevant research topic for CO2-EOR. Besides their high cost, efficiency of thickeners such as polymer, foam and gel are not satisfactory due to long-term stability which is difficult to maintain. The use of nanoparticles instead of surfactant to stabilize CO2 by forming a nanofluid may overcome the long-term instability and surfactant adsorption loss and high cost issues that affect efficiency of CO2-EOR processes.

The objective is to develop a new method for thickening of CO2 using nanoparticle and forming a CO2 based nanofluid which can improve volumetric sweep efficiency compared to conventional CO2-EOR method. In this project, we use ab initio - quantum mechanics guided nanoparticle selection combined with atomistic simulation for optimization of the size and shape of the nanoparticles. We study the interaction of CO2 molecules with different nanoparticles by solving the quantum mechanics equations of the electronic structure that so called ab initio calculations. This reveals the most promising compositions for the nanoparticles to make the CO2 based nanofluid. Atomistic simulations of liquid CO2 interaction with nanoparticles (i.e., most promising compositions) perform using Molecular Dynamics (MD) and Dissipative Particle Dynamics (DPD) methods to optimize the size and shape of the nanoparticles. The results attained apply for reservoir-scale modeling to better understanding of the performance of the CO2 based nanofluid at larger-scale of a reservoir.

Obligatorisk!

PostDoc: Rasoul Khaledialidusti

E-mail: rasoul.khaledialidusti@ntnu.no
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