Oil and gas production of tight chalk reservoirs frequently rely on the presence of natural fractures, which increases the effective permeability of the reservoirs. Fracture characterization is therefore imperative in optimizing production schemes and obtaining economically viable recovery factors. Subsurface fracture characterization is often deemed challenging as the available data is typically of varying age and quality, and represents different scales. We have developed an integrated workflow for fracture characterization in chalk to address these challenges. The workflow is based on data from borehole images, cores and seismic. These data are typically available for most chalk (and hydrocarbon) fields. The interpreted borehole image dataset contains over 17 000 manual dip picks, ensuring a statistically viable base. A total of 150 m of core is available from 3 wells. The applied 3D seismic cube covers an 8 × 5 km hydrocarbon chalk field in the Danish North Sea.

In this workflow, the scale-gap between the data sets is bridged by the introduction of two ant-tracked attribute volumes, which display structural trends below the resolution of amplitude seismic. Further insight into the intricacy of subsurface fracture systems is obtained from fracture density logs, which provide an opportunity to study spatial distribution of fractures as well as a qualitative measure of fracture clustering. Cumulative density distribution plots and calculation of the variation coefficient of fracture spacing provide a more quantitative analysis of the fracture distribution.

The workflow, presented here in a step-by-step manner, is a general approach applied to data from the Kraka Field of the Danish North Sea. In the Kraka Field, the usage of this integrated approach shows that the fracture pattern in this region is more complex than previously suggested; probably controlled by the regional maximum horizontal stress and salt movements.