Abstract Providing that a primary and reliable record of the magnetic field and its reference in a deformed area exists, the incorporation of palaeomagnetic constraints in restoration methods reduces uncertainty of rotation because such constraints can be applied both before and after deformation. In this paper, we utilize palaeomagnetic data to improve an unfolding algorithm based on the parameterization of the surface using isometric constraints. This method is more robust than others based on piecewise restoration of a triangulated surface, which are dependent on the meshing and, especially, on the pin-element. A disadvantage of this approach is that parametric restoration is sensitive to the initial solution, which hampers results for complex non-coaxial or non-cylindrical structures. We show that the use of palaeomagnetism as the initial gradient of one of the parameters improves the results of the method. We use analogue models to test the method because the expected restoration result can be stated, since the initial surface is known. We study the restoration sensitivity to surface meshing and the initial palaeomagnetic orientation. All in all, the use of palaeomagnetic vectors in the studied analogue models achieves the best restoration results. The implementation of palaeomagnetic vectors is crucial to obtain reliable 3D restorations of complex structures.

Abstract The stochastic stratigraphic well correlation method considers the stratigraphic correlation of well data as a set of possible models to sample and manage uncertainty in subsurface studies. This method was applied to the Malampaya buildup (a well documented offshore gas field located NW of the Palawan Island, Philippines), aged upper Eocene to lower Miocene. Previous studies highlight that rock petrophysical properties are mainly controlled by diagenesis. Correlation rules are thus developed in order to adapt the stochastic stratigraphic well correlation method to the study of diagenetic units. These rules are based on wireline log shape and diagenetic units types. Four stratigraphic correlation models are generated using the proposed correlation method: a deterministic one corresponding to the most probable model considering only well data and three stochastic ones. These correlation models are bound with geostatistical methods to build static reservoir models. Synthetic seismic profiles are computed from facies models conditioned to acoustic impedance models. It leads to comparable seismic amplitude images, highlighting the importance of considering several well correlation models for one given seismic survey. Stochastic stratigraphic correlations are shown to have a first-order impact on reservoir unit characterization, rock volumes and fluid flow response on the reservoir model.