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In this paper, we present workflows, key relationships and results of multiple stochastic fault seal analyses conducted on geocellular geological or (static) reservoir grids. Ranges of uncertainties are computed from new and published datasets for the different input relationships (e.g. throw, VShale to VClay, fault clay prediction, fault rock clay content to permeability); these are used as input into stochastic modelling processes and the impact of each is assessed. The power of stochastic modelling to focus interpretation and risking effort is reviewed. Reducing the uncertainty distributions from the published data ranges has a massive impact on the range of predicted fault seal properties. Halving the uncertainties associated with the computation of the transmissibility multiplier, for instance, reduces this range from 7 to 1–1.5 orders of magnitude of the base-case value (no uncertainty). Importantly, when combined together, the median predictions from each individual parameter do not lead to the median value for the final prediction; average relationships combined together will not therefore produce the average final prediction. This is a powerful result for two reasons: first, current geological modelling packages use global trends to define fault properties and so are likely to predict spurious results; and secondly, reducing the uncertainty on specific relationships by around 50% is an achievable goal. Locally calibrated datasets and relationships (field-specific) based on carefully characterized samples should allow for this improvement in prediction accuracy. This paper presents a review of fault seal techniques, published data and the potential pitfalls associated with the analyses.

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