Well placement optimisation and risking using 3-D stochastic reservoir modelling techniques

The cost-effective development of small fields requires a thorough description and evaluation of the reservoir, with a strong focus on the estimation of associated uncertainty. This paper describes a new, integrated methodology for defining and risking optimum high-angle development wells as applied to a UKSNS basin-margin gas reservoir. Sequential Indicator Simulation (SIS) realisations of genetic unit distributions were generated for each target reservoir zone, conditioned with relevant geological data derived from the reservoir and the analogue outcrop. The models were 'pin-cushioned' with a large variety of well trajectories that varied in terms of inclination, azimuth, length and position within the zone. Genetic unit strings are then extracted from each well trajectory and analysed statistically, resulting in ranked well trajectories. This integrated approach produces ranked and risked well planning options, on which risk-conscious management decisions are readily made.