Abstract

The cost-effective development of small fields requires a thorough description of the reservoir with a strong focus on the estimation of uncertainty. In this example, 3-D reservoir models are used to define and risk optimum well trajectories in a complex, mixed fluvio-aeolian gas reservoir. Emphasis is placed on the definition and quantification of those geological factors that affect the integrity of the hybrid stochastic-deterministic reservoir model. Sequential Indicator Simulation (SIS) models conditioned to well data were constructed for target zones. Construction of geologically realistic models required identification of genetic units, an understanding of their spatial distribution and assignation of appropriate dimensions. These objectives were achieved by an integration of probe-permeametry and sedimentology data on reservoir core, and the derivation of relevant genetic unit architectures from analogous sequences at outcrop. Assignation of appropriate sizes depends on the similarity between the outcrop analogue and the subsurface reservoir. Similarity was assessed by comparison of facies types, their proportions, the vertical association of facies, types of fluvio-aeolian interaction, the size of depositional systems and general depositional environment. Outcrop data were compared to reservoir observations and sub-sampled to eliminate unrepresentative elements. The SIS models generated with this data were [open quote]pin-cushioned[close quote] with over 100,000more » numerical [open quotes]wells[close quotes] of varying azimuth, length, inclination and elevation. Much improved decision support was provided through a statistical definition of the [open quote]optimum[close quote] well trajectory.« less

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