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.

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The improvement of the success of the well drilling is an important task during the development of hydrocarbon reservoirs, and the use of three dimension mechanical earth model (MEM) is key to predict the behavior of drilled well and to prevent damaging the well. The MEM encapsulates several information related to pore pressure, mechanical properties of the reservoir rock, the geometry of the reservoir limits and the overburden and the stress regime. Various workflows were proposed to build and update the MEM. However, those approaches do not incorporate the complexity of the carbonate rocks. In fact, the carbonate rocks, hold heterogeneous pore systems that impact the rock strength and the pore pressure behavior. The heterogeneity of the pore systems is due to the specificity of the deposition process of the carbonate rocks, mainly composed of fauna and or flora, and the rate of diagenesis.In this paper, we propose a workflow that improves the modeling of the mechanical properties for carbonate reservoirs. This workflow starts by reconciling data at different scales, diagenesis rate at thin-section scale, scratch and laboratory strength tests at plug scale, electrical logs at well scale, and three dimension sedimentology and seismic volumes at reservoir scale. The second step is to establish the relationship between the mechanical properties, the pore pressure, the seismic attributes, the sedimentology and the rate of diagenesis. The last step allows interpolating and assessing the uncertainty of the mechanical properties and pore pressure in the three dimension reservoir model.The workflow was applied to an off-shore carbonate field in South-America. It showed that there is a strong relationship between the type of fauna and flora, composing the carbonate rock, and the rock strength and pore pressure. The three dimension mechanical model, at hundred meter horizontal resolution and one foot vertical resolution, allowed to quantify the risk associated with the drilling of the previously planned wells, to improve the location for future drilling wells and to optimize the drilling parameters such as mud weight.

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