Projects – University of Copenhagen


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(]
GEUS [contact: Flemming Jørgensen (]
Dept. of Geosciences, Aarhus University [contact: Niels Bøie Christensen (]
University of Cagliary [contact: Giulio Vignoli (]
USGS, Denver, [contact: Burke J. Minsley (]

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 (]

PLANNING [2017-2019]

Increasingly large amounts of data has been, are continuously being, collected that refer to the subsurface. This is data of very different origin, sensitive to different parts of the subsurface. It is a major challenge to make use of all this available data to take informed decisions about the subsurface, both because of the amount and complexity of available data. The major goal in this project is to make use of Machine Learning to help manage and utilize the large amount of data, such that decision can be made faster and with higher accuracy than possible today.
This is an Industrial Post Doc funded by Innovation Fund Denmark

Collaborators and contact:
PostDoc Mats Lundh Gulbrandsen (

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 (]

OPTION [2014-2019] Optimizing oil production by novel technology integration

Horizontal wells have already dramatically improved the productivity and reduced the cost of oil and gas fields. The objective of this project is to bring the technology to the next level by providing tools for predicting and performing optimal control of the flow between the wells and the reservoir. To reach the production optimum from the long horizontal wells, each segment has to be controlled to ensure uniform depletion and prevent loss of reserves by premature water or gas breakthrough.

The solid Earth Geophysics group at NBI contributes to the OPTION project though development of stochastic reservoir models. Uncertainty analysis of reservoir models from geological, geophysical and production data is currently based on summary evaluations and physically inconsistent error propagation methods. Statistical predictions about reservoirs are mostly based on: 1) large geological data bases, or 2) subjective expert assessments of geophysical and geological data. These limitations may have significant consequences for the appraisal of the reservoir, and a miscalculation of these factors may seriously reduce the quality of production scenario evaluations. The aim of the NBI group is to develop an uncertainty evaluation system based on a consistent, probabilistic approach to geophysical/geostatistical inversion and flow data analysis.

Collaborators and contact:
Niels Bohr Institute, University of Copenhagen, DTU Chemistry, DTU Mech. Eng., DTU Compute, Lloyd’s Register Consulting, Welltec A/S.
[contact: Klaus Mosegaard (]

PSPA [2015-2018] Probabilistic Seismic Prospect Assessment

Funded by Innovation Fund Denmark

Over the last 5-10 years the oil price has fallen significantly. At the same time expenses related to exploration of new oil researches has increased. This pose a challenge. The goal of the PSPA project is to develop a software that can be a useful tool to transform the very large amounts of available (typical seismic) data into a decision tool. This can be used to example to reduce the risk of starting for expensive drilling in a wrong locations.

In the research project knowledge about geophysical analysis (inversion) from the Solid Earth Physics group at the Niels Bohr Institute, will be combined with Q-eye Labs' unique data analysis and self developed inversion software software. The resulting software and methodology will be tested out example form the oil-industry.

Collaborators and contact:
Niels Bohr Institute, University of Copenhagen [contact: Thomas Mejer Hansen(]
Qeye [contact: Anders Bruun (]