The project was launched in 2015, with the ambitious perspective to significantly contribute to the improvement of current oil reservoir characterization methods by developing a novel Electromagnetic (EM) Tomography survey technique that exploits novel magnetic nanoparticles (MNPs) as contrast nanoagents to unveil long-distance reservoir architecture. In this context, the MNPs are injected into the subsurface in the form of colloidal magnetic fluids and their flow paths during flooding are monitored via advanced logging Electromagnetic (EM) Methods. Specifically, the propagation of the magnetic nanofluid modifies the local magnetic permeability of the formation; this in turn modifies propagation and reception of low frequency electromagnetic waves that can be detected with a system of electromagnetic antennas. The reconstruction of the position of the magnetic nanoparticles in the subsurface is realized by using advanced post-processing methods (software), based on inversion algorithms.
The research was implemented through the collaboration of the ssNMR group with a Consortium of international Academic partners and was funded by the Abu Dhabi National Oil Company (ADNOC). The project expired on December 31, 2018. The major scientific highlights accomplished within the framework of this research are outlined in the following:
(i) the construction of a prototype EMT system able to provide detailed mapping of the magnetic nanoparticle dispersions at laboratory scale. The developed EMT device was tested at 1.6 m and gave experimental results in excellent agreement with the theoretical predictions of the COMSOL Multiphysics® software. In addition, theoretical COMSOL simulations performed at 1.5m, 100m and 1km demonstrated that the results remain invariant with scaling up.
(ii) Development of 2D Inversion Algorithms to “invert” electromagnetic data, in order to acquire the position of the MNPs dispersion in the reservoir. The resolution and precision of the inversion image (location of the slug) is by far higher than most existing algorithms. The algorithm possesses exceptional ability to precisely monitor in addition to the spatial distribution also the propagation of corresponding magnetic disturbances and is also applicable on conductivity data from conventional EM logging tools. The methodology is potentially patentable. On November 7, 2018, an official proof of concept demonstration of the prototype EMT system's operation was performed with great success at the premises of Khalifa University (Sas Al Nakhl Campus) Abu Dhabi, UAE and was attended by collaborators from Khalifa University, KBSI and NCSRD and two senior executives from the ADNOC project committee.
