Solid Earth Physics and Computational Geoscience

Probabilistic approach for risk assessment of CO₂ Storage

One of the possible post-production utilization of abandoned hydrocarbon fields in the North Sea fields is to use them as reservoirs for CO₂ storage. There are several advantages in doing so: the reservoirs are already discovered and the wells needed to access them are in place.

However, CO₂ storage requires a careful risk assessment, based on integrated data analysis where all uncertainties are correctly balanced. In an ideal approach, the analysis must evaluate risks related to capture, transport and storage, the associated CO₂ migration mechanisms and pathways, as well as effects on atmosphere, soil, groundwater, and surface water. Each component in this chain of investigations must be based on all available data for the considered CO₂ storage scenario, and the best possible probabilistic model for data uncertainties.

Current methods try to reach these ideal goals, but have severe limitations in the analysis of reservoir properties. Probabilistic analysis of geoscientific data and production data is not based on physically correct error propagation methods. Instead, statistical predictions about the reservoir are only based on (1) large geological data bases, or (2) subjective expert assessments of geophysical and geological data. Prediction models about the overburden are nearly non-existing. These limitations may have significant consequences for the appraisal of possible caprock failures, releases through induced or existing faults, displacement into non-target formations, or well leakage. Furthermore, a miscalculation of these factors may have a dramatic consequence on the evaluation of migration scenarios and their short and long-term consequences.

The aim of this pilot project is to investigate and describe how a risk analysis system based on a consistent, probabilistic approach to geophysical/geostatistical inversion and flow data analysis can be developed.

RESPROB [2018-2021] Probabilistic Geomodelling of Groundwater Resources

funded by Free Research Council (Technology and Production)

Groundwater mapping in Denmark is internationally acknowledged and regarded as a benchmark approach. Massive amounts of data (well logs, geophysical, geo- and hydrological data) have been collected. Today these data are combined in a deterministic sequential workflow, where, typically, a single final model represents all available information. While successful, this workflow has some limitations: There is no way to ensure the final model consistency with all information at hand, and there is no way to ensure correct uncertainty quantification. The main goal of RESPROB is to develop a probabilistic data integration workflow that allows consistent integration of well-log, geophysical and geological data. The resulting probabilistic geomodel should be efficient tool for end-users for informed, data-driven, decision making and for risk assessment.

A PhD position (located at Niels Bohr Institute) and a PostDoc position (GEUS/University of Aarhus) will be offered as part of the project.

Collaborators and contact:
Niels Bohr Institute, University of Copenhagen [contact: Thomas Mejer Hansen(tmeha@nbi.ku.dk)]
GEUS [contact: Flemming Jørgensen (flj@geus.dk)]
Dept. of Geosciences, Aarhus University [contact: Niels Bøie Christensen (nbc@geo.au.dk)]
University of Cagliary [contact: Giulio Vignoli (gv@unica.it)]
USGS, Denver, [contact: Burke J. Minsley (bminsley@usgs.com)]

LOCRETA [2018-2020] Seismic modelling and optimal inversion

With this initiative we strive to improve seismic imaging of key features, which are determining for the reservoir properties of the lower Cretaceous sediment package, i.e. characteristic, alternating (cyclic?) lithologies as well as faults and fractures. We employ forward full-waveform modelling for improved understanding of origin and characterization of seismic arrivals occurring from such key features, and we build full-waveform inversion (FWI) schemes aimed particularly at resolution of such elements. The FWI schemes will be constrained by geological and rock physical prior knowledge (including results from other work packages of this proposal) and special emphasis will be on formulating the inversion schemes in a geostatistical framework, which provides realistic distributions and uncertainties of key seismic and/or rock physical parameters. We draw on existing collaboration with international leading experts in this research field.

Collaborators and contact:
Niels Bohr Institute, University of Copenhagen, Department of Geosciences and Natural Resource Management (IGN), University of Copenhagen. Geological Survey of Denmark And Greenland (GEUS), DTU Civil Engineering
[contact: Klaus Mosegaard (mosegaard@nbi.ku.dk)]

Outcrop Analog Studies of Chalk [2017-2020]

The goal is to build reservoir models spanning heterogeneities from millimeters to hundreds of meters, thereby providing a link between structural and depositional elements of widely different scales. In a cross-disciplinary effort, we combine geological, geophysical and geostatistical methods to identify different length-scale regimes. Statistical models will be developed for each regime and combined to one multiscale model to be compared with North Sea data sets. Geostatistical models provide not only spatial estimates of rock properties with uncertainties and correlations, they also provide a framework for consistent updating of existing reservoir models with new information, as well as the necessary information needed to upscale a reservoir model to coarser grids to facilitate reservoir simulations.

Collaborators and contact:
Niels Bohr Institute, University of Copenhagen, Natural History Museum of Denmark, University of Copenhagen, Department of Geosciences and Natural Resource Management (IGN), University of Copenhagen.
[contact: Klaus Mosegaard (mosegaard@nbi.ku.dk)]