A multi-scenario geomechanical modeling approach is presented to investigate the potential mechanisms that lead to a series of well-deformation incidents in the deep overburden overlying a depleting and compacting chalk… Click to show full abstract
A multi-scenario geomechanical modeling approach is presented to investigate the potential mechanisms that lead to a series of well-deformation incidents in the deep overburden overlying a depleting and compacting chalk reservoir in the North Sea. Complementary to the commonly pursued approach of building a full-field geomechanical model presented in the companion paper of this special issue (Schutjens et al. in Compaction- and shear-induced well deformation in Tyra: geomechanics for impact on production, accepted by the ARMA 2018 special issue of Rock Mechanics and Rock Engineering, 2018), a suite of finite-element-based sector-scale ideal geomechanical models is developed based on data and evidence-driven scenarios that take into considerations fault population and juxtaposition, contrasting mechanical stratigraphy, intra-bedding contact conditions, and lateral persistence of thin stringer beds. The simulation results of extensive runs suggest that most of the geological faults in the overburden mudstones are stable under the pre-production stress state and remain largely inactive in the course of overburden deformation resulting from depletion of the underlying reservoir. Alternatively, the contrasting mechanical stratigraphy of the overburden, consisting of thick compliant mudstones and thin stiff carbonate stringers, facilitates “domino” or “bookshelf” style intra-bedded shear slippage in response to the developing dominant shear zone right above and around the periphery of the active compacting region. This multi-scenario approach provides new and accelerated insights into the diagnosis of compaction-induced well failure in the deep overburden and allows mapping of competing mechanisms potentially responsible for the problem. These new insights help to steer further modeling efforts and guides future data acquisitions.
               
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