|ISBN / DOI:||10.3997/1365-2397.2017019|
|Link to publication:|
This paper describes a statistical method for determining the probability for hydrocarbon detection by Controlled Source Electromagnetic (CSEM) data. The method can be used to quantitatively estimate the reliability and predictability of CSEM results and the validity of a CSEM interpretation over a specific target with given geological parameters (e.g. porosity and clay content). Wells and case studies from the Norwegian Barents Sea are used to highlight how the uncertainty of the geological model affects CSEM interpretation.
All types of geoscientific applications face challenges on how to handle uncertainties; CSEM sensitivity studies are no different. The proposed method constrains the uncertainties by first establishing a statistical resistivity model containing expected resistivity and other geological parameters, then running Monte Carlo simulations to generate target specific sensitivity plots. Finally, the reservoir properties, e.g. porosity and clay content, can be varied to quantitatively establish if CSEM can detect a potential hydrocarbon column.
The most important aspect of this method is that the CSEM integration and interpretation is now strongly controlled by the geoscientist, who must provide the expected reservoir parameters and their uncertainties for each target or case study under evaluation.