No abstract

Summary The main objective of history matching is to improve reservoir representation in order to obtain reliable predictions of production rate and thus optimise future field developments. Standard history matching techniques are composed of a fixed geological model with global modifications and local adjustments. The limitations with this methodology are clear: local adjustments are not always geologically realistic, static uncertainties are not taken into account and only a limited number of models are used for prediction. In order to solve this problem, a probabilistic approach is presented using uncertainty quantification throughout the history matching process. This paper describes the process of geological and reservoir uncertainty quantification and ranking, and focuses on specific examples. The result of implementing such a workflow leads to reservoir models which honour the production history of the modelled field. To achieve a history match, the workflow should consist of the following steps:Probabilistic multi-realizations of the reservoir model taking into account static uncertainty using JACTATM;Calculation of the impact of static uncertainties on the history match by means of reservoir simulation;Calculation of the impact of dynamic uncertainty on the history match using experimental designs;Evaluation of the relative importance of uncertain static and dynamic parameters;‘Hybrid’ geostatistical simulations;Calculation of the impact of the dynamic reservoir parameters on the history match using an experimental design technique;Adjustment of dynamic parameters to obtain a final history match. This workflow provides the industry with the long-awaited possibility of addressing subsurface uncertainties in a systematic and objective manner. The history matching process shifts from deterministic to probabilistic and results in a more realistic reservoir model which can further be used for true risk assessment prediction. The workflow proposed increases the chance of attaint the history match. Combining the structural, geological and dynamic uncertainties, covers the whole uncertainty domain, resulting in a multiple history matched reservoir models, which could be used for forecast calculation with more confidence.