In recent years, the petroleum industry achieved marked advances in the development of full 3D and 4D geomechanical models. If robust, these 3D/4D models provide the benefit for more accurate well and field development planning in structurally complex settings such as areas with significant topography or/and faulting, when substantial depletion is likely to cause changes in the in situ stress field accompanied by reservoir compaction and even surface subsidence, or due to the presence of salt diapirs or other frictionless bodies/layers with different material characteristics. In most cases, these 3D/4D geomechanical models also require advanced finite element modeling coupled with reservoir simulation. In these instances, in particular understanding the in situ stresses, pore pressure, and material properties and their variability (lateral, in depth as well as with time) is of critical importance to better evaluate and mitigate risk during the drilling, completion, and production phase of a field development.

However, not all fields require the finite-element approach. In this paper, we demonstrate how a 3D geomechanical model can be build in a structurally relatively straightforward setting based primarily on an existing structural model and augmented with well data under application of appropriate geostatistics techniques to map and interpolate rock properties (such as density, rock strength, internal friction, etc) along the structural grid directly linked to the field's stratigraphy. This type of 3D geomechanical model has a clear advantage over a 1D depth-stretched model by honoring structural and stratigraphic constraints. This is particular important when an operator plans to drill a high number of directional or even horizontal wells and needs to capture varying stresses, pore pressures, and rock properties on the field scale to optimize well integrity. At the same time, this geomechanical model also provides benefits over 3D numerical modes in terms of timing to build the model, cost, flexibility to update the model (with data from additional offset wells) and accessibility across disciplines in the asset team. For example, it is straightforward to export data along planned trajectories for conventional wellbore stability analyses.

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