Structural uncertainties have a direct impact in exploration, development, and production, and in drilling decisions. In this paper, we present an approach for determining and handling structural uncertainties. We first examine the magnitude of the different sources of uncertainty, and explain how to estimate their direction and correlation length. This task requires a huge geophysical input. This information is then used in a general scheme to generate multiple realizations of the structural model consistent with structural uncertainties. The technique is based on geostatistical concepts. Finally, we illustrate the application of this scheme in examples relevant for exploration, development and production, and drilling. The structural model is described as a set of horizons represented by triangulated surfaces cut by faults. The relationships between horizons and faults are expressed as a set of constraints. On a horizon, each source of uncertainty (typically migration, picking, and time‐to‐depth conversion) is described as a field of vectors with its magnitude, direction, and correlation length expressed in terms of a variogram. A special fault object has been developed to aid in discribing the faults as probabilistic objects in a very simple way. Once all sources of uncertainty have been quantified many equiprobable realizations of the structural model are generated. For this, we use a special implementation of the probability field technique adapted to triangulated surfaces that handles correlation between horizons. At each realization, faults and horizons are moved in three dimensions according to uncertainties. Links between faults and horizons are maintained. Such complex 3‐D modeling can only be achieved in the frame of a geomodeler. Finally, we propose three types of applications requiring structural uncertainty determination:rock volume distribution, well trajectory optimization and risk analysis, and the use of structural uncertainty as a parameter for history matching. Our scheme generates many equiprobable realizations of the structural model provided that each source of uncertainty has been described in terms of magnitude direction and correlation length. These realizations may then be used to quantify risk in exploration development and drilling.

Modelling faults from seismic data for a 3D depth model is a difficult task because of the multiple sources of uncertainty. The uncertainty may be attributed to migration velocities, picking of faults and organization of the fault network in 3D. Faults are generally not migrated from time to depth domain like horizons are, but modelled in the depth domain from the depth migrated horizons. For this reason, a new data structure has been designed that is targeted for fault modelling. Taking uncertainties into account, this structure allows for rapid modelling of faults from depth migrated horizons. The input data and the parameterization of the new data structure will be described. Following this, a way to incorporate uncertainties during the interpretation process is proposed and a description of different stochastic methods used to compute new shapes and locations inside a given uncertainty volume will be made. Finally, the method and the results obtained will be described while studying uncertainties on more complex fault networks. The influence of fault uncertainties on the reservoir volumetric estimates will be shown as one possible result of the simulation process.

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Uncertainty studies become increasingly important as reservoir complexity increases. Although such studies are commonly a key factor in oil and gas exploration, projects are commonly restricted to simulation of facies and petrophysical properties. The structure of the reservoir itself is commonly considered to be a deterministic parameter, and yet it may contain uncertainty that has a major impact on the reserve estimations. A new methodology based on the P-field technique and focusing on reservoir geometry uncertainty is proposed to tackle this problem. With this method, not only horizon but also fault geometries are simulated around a given reference model. Because simulating fault geometries is more difficult than simulating horizon geometries, a new data structure has been designed to produce efficient computation of geometries. The simulation method tries to preserve the initial geometry at best. It may affect the location, dip, and shape in map view of all faults or any combination of these three basic modifications. Then, for each fault network realization, several horizon geometry simulations may be performed. The modeling and simulation system keep the geological model consistent after each simulation loop, allowing volumetric studies to proceed in a consistent fashion.