OMNICS

Observing, Modelling & Predicting in situ Petrophysical Parameter Evolution in Geologic Carbon Storage System (OMNICS)
MSCA Fellow: Y. Yang
Advisor: S.L.S. Stipp
Host: NanoGeoScience Research Section, University of Copenhagen
European Commission Horizon 2020, Marie Skłodowska-Curie Individual Fellowships (IF-EF), Project ID: 653241. http://cordis.europa.eu/project/rcn/194840_en.html

A picture is a key to understanding. Scientific breakthroughs often build upon the successful visualisation of objects invisible to the human eye. – Citation, Nobel Prize in Chemistry 2017

Geologic carbon storage (GCS) is an important means to arrest global warming by reducing atmospheric CO2 emission. A central goal of GCS-associated research is to understand and predict the structure evolution of CO2-bearing geologic formations. This knowledge will ultimately pave the way for GCS implementation with maximum efficiency and safety. Although high-impact scientific research has been performed on carbon mineralisation in the field, direct observation of porous structure evolution stemming from CO2-fluid-rock interactions can be conducted in the laboratory in a more reproducible manner, making them more amenable to sensitivity analysis. Despite this, capturing a nonlinear, dynamic process with high fidelity and upscaling the results from lab to field remain key challenges. Very recently, the vastly expanding field of X-ray imaging with supercomputing has offered new, attractive solutions to these problems. OMNICS aims to explore the possibility of combining X-ray computerised tomography (XCT) with mathematical modelling to tackle some of the most challenging problems in GCS. In OMNICS, we do three things:

I. SEEING – We develop instrumentation for in situ XCT to observe microstructure evolution of natural porous media. For example, we build mini Hassler core holders with which we record chalk disintegration in a reactive flow field without interfering with the process (FOV 1 x 2 mm2):

We can even trace the migration of CO2 and experience what it “sees” as it journeys through the porous architecture:

II. UNDERSTANDING – We use reactive transport models to assemble knowledge. We put the kinetics of water-rock interactions into physically realistic pore scale geometries and treat a GCS formation as a dynamic, ever-evolving system:

Our modelling ability allows us to conduct numerical experiments without permanently destroying precious geologic samples and to unveil, with well-defined initial and boundary conditions, microscopic nonlinear phenomena  (e.g., momentary recession of acidic reactant):

III. PREDICTING – We build mathematical models to upscale results from lab to field and to predict if the effects of microscopic heterogeneities are encoded in the macroscopic behaviors of a GCS system.

The self-organisation of a GCS formation is among the most exciting research topics in Earth Sciences. After injection, CO2 acidifies formation water and dissolves minerals. The reactive fluid flows toward the more permeable region, dissolving minerals there and making it even more permeable. A positive feedback loop forms spontaneously , leading to flow channelization. This phenomenon is similar to the “Mathew Effect” in sociology, where an economic inequality leads to “the rich get richer and the poor get poorer”. In this analogue, CO2 is the “fortune” and the inherent petrophysical and chemical heterogeneities in natural porous materials are the inequalities. During this dynamic process, certain microstructural features may grow into hydrological properties that ultimately determine the entire flow field. In OMINICS, we create various models to study the development of flow networks in GCS and relate the networks’ topological and statistical features to their capacity of dissipating anthropogenic CO2. Here is an example of network development for those very, very patient viewers:

OMNICS was launched on March 10, 2016. Its progress updates have been delivered through eight talks at international conferences, including three invited talks. The final results will be disseminated through a series of seven peer reviewed Open Access publications upon the project closure in March, 2018.