Why the uncertainty in your structural model really does matter.
The course is as applicable to interpreters, and reservoir modellers as it is asset evaluation manager who need awareness of confidence in the output.
Duration
Learning Level
With the advent of extensive 3D data it is all too easy to determine top reservoir horizon from well picks, autopick and generate a structure map. Once generated this is then used in the first instance to generate a prospect and then subsequently as the input into reservoir modelling. Despite being fundamental in volumetric determination and prediction of fluid migration, the uncertainty, and inaccuracy, in this structure map is often under estimated.
Recent advances of automated fault picking in part reduces the time taken to generate structure maps and corresponding fault networks, which can reduce this uncertainty, but all interpretation still needs to be QC’d and be sensible. Critically, these advances still require the interpreter to understand both fault behaviour and impact on reservoir distribution and integrity.
The central theme of this event is construction of robust structural models and develop an understanding and appreciation of the uncertainties within them and how to evaluate multiple scenarios.
The course content is organised around the following:
The scope of the course is 4 days, or flexed to suit the client’s requirement. The primary course will provide an overview across all tectonic settings and include both 2D and 3D data types with applicability at prospect and reservoir scales. The course can be more specifically tailored for extensional or contractional systems, and prospect generation or reservoir modelling.
PhD
20+ years – geoscience
Douglas develops and runs courses in the Reservoir and Open Air series. He has a career background at Conoco-Phillips, Chevron, BHP, Saudi Aramco and TectonKnow. Douglas has published over 60 scientific articles and papers and is an invited committee member, GCSSPEM Roberts meeting (2021); Invited member for AAPG International Research Committee (2017-present).