Review of statistical probabilities from technologies used for pre-drill hydrocarbon prediction
Kim Gunn Maver
Journal name: First Break
Issue: Vol 37, No 6, June 2019 pp. 67 - 73
Special topic: Embracing Change - Creativity for the Future
Info: Article, PDF ( 5Mb )
Price: € 30
To correctly rank prospects to make appropriate drill or drop decisions in hydrocarbon exploration, and to avoid personal biases, detailed processes have been developed. One systematic approach to pre-drill predict the outcome of a well is calculation of Geological Chance Of Success (GCOS) of mobile hydrocarbons, which is done by multiplying the fractions representing the likelihood of each of the parameters: Structure, Reservoir, Retention, and Charge. Commercial chance of success is estimated by linking GCOS with the chance of the well eventually being completed and is therefore lower (AAPG Wiki, 2019). Each GCOS parameter is well understood and described. The explorationist’s assessment and input is based on past drilling experience, analogue field studies, well cores, and outcrops. In addition acquired data from different technologies can be used to describe an undrilled prospect to assess both reservoir properties and hydrocarbon presence. This paper provides an overview of technologies, which can provide data input to determine each of the parameters in the GCOS calculation and are supported by statistical probabilities derived from their historical track record.