CO2 Storage in the North Sea: Quantification of Uncertainties and Error Reduction (CONQUER)
Project period2015 – 2018
One of the goals of carbon capture and storage is to efficiently and safely store large amounts of CO2 in subsurface formations, with no leakage to groundwater resources, and with minimum leakage to the atmosphere. When simulations are used to inform the decisions on where to store CO2, limited understanding of the underlying physics and lack of data will be a big problem. These uncertainties in input parameters will lead to uncertainty in the transport of CO2 in the reservoir over the centuries. In addition, there may also be risk for leakage through fractures caused by high pressure as a result of excessive injection of CO2.
Storage facilities are very expensive, and uncertainty quantification is a key technology for realizing large-scale CO2 storage and minimizing unnecessary costs due to uninformed decisions. The bottleneck is the lack of reliable tools for quantifying uncertainty due to limited data.
In this project simulation tools for uncertainty quantification are being developed.
We focus on three key processes that may lead to storage constraints:
• Pressure buildup during injection
• Long-term migration of CO2
• Leakage through the caprock overlying the formation
We devise a model based on interconnected modules, each consisting of a tailored numerical method for one of the problems (pressure problem, transport problem and geomechanics model).
Due to the prohibitive numerical cost of a direct implementation (complex physics and many sources
of uncertainty), we use reduced order models and simplified physics. The expected outcome is a set
of open-source simulation tools where the errors from lack of data, inaccurately represented physics and numerical effects are systematically treated within a unified framework.
A mathematical framework has been developed for simulating uncertain transport of CO2 after injection into a reservoir. The effect of uncertain physical parameters can be simulated to demonstrate the effect on the long-term CO2 plume propagation. The mathematical methods developed involve tools to identify different solution regions in high-dimensional stochastic space, and tools to compute highly nonlinear solutions that vary in stochastic space. The results extend previous work in the field and have been published in Transport in Porous Media. Extensions to more complex physics (dissolution effects) and heterogeneous domains is in progress.
Joint work with the international partners on efficient representation of uncertain pressure fields has been initiated. Low-rank methods for big matrices have previously been used to make blurred images more clear. We have implemented related methods on pressure problems with uncertain permeability fields. The methods show potential for more robust simulation of uncertain pressure in cases of heterogeneous reservoirs with noisy and few measurements, which is typically the case in CO2 storage reservoirs.
A reduced-dimensional model for coupled two-phase flow and geomechanical deformation within the context of CO2 storage has been derived. Dimension reduction is essential to make stochastic simulations meaningful, otherwise the task requires too much computing time. The reduced-order model simplifies the complex flow and interaction within thin storage units, while retaining the full-dimensional poroelastic equations for the overburden and underburden.
A matlab simulation tool for poro-mechanics, compatible with the Matlab Reservoir Simulaiton Toolbox developed by Sintef, has been released as open source (see https://github.com/keileg/fvbiot). This methodology forms the basis for stochastic simulations in WP3; extensions of the tools will be released as the project progresses.
When storing large quantities of carbon dioxide in groundwater aquifers, the capacity will generally be limited by pressure build-up in the aquifer. In certain cases, the pressure build-up can be reduced because of leakage of formation water through the reservoir cap rock. This reduction in pressure build-up is very uncertain, as it is partly determined by the properties of the reservoir where very few measurements exist. We have conducted an analysis of leakage through the caprock and determined a threshold for when leakage can be neglected. Furthermore, we have derived a method that facilitates calculation of the pressure build-up when leakage must be considered. In this method the leakage is calculated through a convolution instead of an extension of the computational grid of the reservoir.