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

Abstract

Structural uncertainty is a key parameter affecting the accuracy of the information contained in static and dynamicreservoirmodels.However,quantifyingandassessingitsrealimpactonreservoirpropertydistribution,in-place volume estimates and dynamic simulation has always been a challenge. Due to the limitation of the existing workflows and time constraints, the exploration of all potential geological configurations matching the interpreted data has been limited to a small number of scenarios, making the future field development decisions uncertain. WepresentacasestudyintheLubinaandMontanazomature oil fields (Western Mediterranean) in which the structural uncertainty in the seismic interpretation of faults and horizons has been captured using modern reservoir modeling workflows. We model the fault and horizon uncertainty by means of two workflows: the manually interpreted and the constant uncertainty cases. In the manually interpreted case, the zones of ambiguity in the position of horizons and faults are defined as locally varying envelopes around the bestinterpretation,whosedimensionsmainlyvaryaccording to the frequency content of the seismic data, lateral variations of amplitudes along reflectors, and how the reflectors terminatearoundfaultswhenfaultreflectionsarenotpresent in the seismic image. In the constant case, the envelope dimensions are kept constant for each horizon and each fault. Bothfaultsandhorizonsaresimulatedwithintheirrespective uncertainty envelopes as provided to the user. In all simulations,conditioningtoavailablewelldataisensured.Stochastic simulation was used to obtain 200 realizations for each uncertainty modeling workflow. The realizations were compared in terms of gross rock volumes above the oil-water contact considering three scenarios at the depths of the contact. The results show that capturing the structural uncertainty inthepickingofhorizonsandfaultsinseismicdatahasarelevant impact on the volume estimation. The models predict percentage differences in the mean gross rock volume with respect to best-estimate interpretation up to 7% higher and 12% lower (P10 and P90). The manually interpreted uncertainty workflow reports narrower gross rock volume predictions and more consistent results from the simulated structural models than the constant case. This work has also revealed that, for the Lubina and Montanazo fields, the fault uncertainty associated with the major faults that bound the reservoirlaterallystronglyaffectsthegrossrockvolumepredicted. The multiple realizations obtained are geologically consistentwiththeavailabledata,andtheirdifferencesingeometry and dimensions of the reservoir allow us to improve the understanding of the reservoir structure. The uncertainty modeling workflows applied are easy to design and allow us to update the models when required. This work demonstrates that knowledge of the data and the sources of uncertainty is important to set up the workflows correctly. Further studies can combine other sources of uncertainty in the modeling process to improve the risk assessment.