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. Structural uncertainty is a key parameter affecting theaccuracy of the information contained in static and dynamic reservoirmodels. However, quantifying and assessing its real impact on reservoirproperty distribution, in-place volume estimates and dynamic simulation hasalways been a challenge. Due to the limitation of the existing workflows andtime constraints, the exploration of all potential geological configurationsmatching the interpreted data has been limited to a small number ofscenarios, making the future field development decisions uncertain. We present a case study in the Lubina and Montanazo mature oil fields(Western Mediterranean) in which the structural uncertainty in the seismicinterpretation of faults and horizons has been captured using modernreservoir modeling workflows. We model the fault and horizon uncertainty bymeans of two workflows: the manually interpreted and the constantuncertainty cases. In the manually interpreted case, the zones of ambiguityin the position of horizons and faults are defined as locally varyingenvelopes around the best interpretation, whose dimensions mainly varyaccording to the frequency content of the seismic data, lateral variationsof amplitudes along reflectors, and how the reflectors terminate aroundfaults when fault reflections are not present in the seismic image. In theconstant case, the envelope dimensions are kept constant for each horizonand each fault. Both faults and horizons are simulated within theirrespective uncertainty envelopes as provided to the user. In allsimulations, conditioning to available well data is ensured. Stochasticsimulation was used to obtain 200 realizations for each uncertainty modelingworkflow. The realizations were compared in terms of gross rock volumesabove the oil–water contact considering three scenarios at the depths of thecontact. The results show that capturing the structural uncertainty in the picking ofhorizons and faults in seismic data has a relevant impact on the volumeestimation. The models predict percentage differences in the mean gross rockvolume with respect to best-estimate interpretation up to 7 % higher and12 % lower (P10 and P90). The manually interpreted uncertainty workflowreports narrower gross rock volume predictions and more consistent resultsfrom the simulated structural models than the constant case. This work hasalso revealed that, for the Lubina and Montanazo fields, the faultuncertainty associated with the major faults that bound thereservoir laterally strongly affects the gross rock volume predicted. The multiplerealizations obtained are geologically consistent with the available data, and their differences in geometry and dimensions of the reservoir allow usto improve the understanding of the reservoir structure. The uncertainty modeling workflows applied are easy to design and allow us toupdate the models when required. This work demonstrates that knowledge ofthe data and the sources of uncertainty is important to set up the workflowscorrectly. Further studies can combine other sources of uncertainty in themodeling process to improve the risk assessment.

Quantifying the impact of the structural uncertainty on the gross rock volume in the Lubina and Montanazo oil fields (Western Mediterranean)