Structural uncertainties: Determination, management, and applications

Abstract

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.