  A key part of planning CO2 storage sites is to devise a monitoring strategy.
The aim of this strategy is to fulfill the requirements of legislations and
lower cost of the operation by avoiding operational problems. If CCS is going
to be a widespread technology to deliver energy without CO2 emissions,
cost-efficient monitoring programs will be a key to reduce the storage costs. A
simulation framework, previously used to estimate flow parameters at Sleipner
Layer 9 [1], is here extended and employed to identify how the number of
measurements can be reduced without significantly reducing the obtained
information. The main part of the methodology is based on well-proven, stable
and robust, simulation technology together with adjoint-based sensitivities and
data mining techniques using singular value decomposition (SVD). In particular
we combine the simulation framework with time-dependent (seismic) measurements
of the migrating plume. We also study how uplift data and gravitational data
give complementary information.
  We apply this methodology to the Sleipner project, which provides the most
extensive data for CO2 storage to date. For this study we utilize a
vertical-equilibrium (VE) flow model for computational efficiency as
implemented in the open-source software MRST-co2lab.
  However, our methodology for deriving efficient monitoring schemes is not
restricted to VE-type flow models, and at the end, we discuss how the
methodology can be used in the context of full 3D simulations.
