Structural geometries, faults and their movement histories, together with the petrophysical properties of flow units, are some of the major controls on hydrocarbon migration pathways within sedimentary basins. Currently, structural restoration, fault-seal analysis and hydrocarbon migration are treated as separate approaches to investigating basin geohistory and petroleum systems. Each of these separate modelling approaches in their own fields is advanced and sophisticated but they are not compatible with each other. Lack of integration produces incorrect palaeogeometries in basin models and inaccurate migration pathways.
A combined structural restoration and fault-seal analysis technique, integrated with fast hydrocarbon migration pathway modelling code based on invasion percolation (IP) methods, is described. These modelling methods are used to develop a 4D basin modelling workflow in which evolving basin geohistories and geometries form an integral part of the analysis of hydrocarbon migration and trapping. By combining structural restoration and 3D fault-seal analysis it is possible to investigate the evolution of structurally complex traps through time. Integration of these techniques with a numerically fast migration pathway modelling technique allows hydrocarbon migration pathways and accumulations to be modelled through the evolution of the basin with time. Additionally, the effects of uncertainties in structural geometry, fault seal or any of the model input parameters can be explored using a risk-driven approach to modelling.
These methods are demonstrated using synthetic, computer generated, 3D models and a well-constrained model of the Moab Fault, Utah, USA. Comparison of modelled structural geometries, fault-seal properties and predicted trapped hydrocarbons with outcrop data is used to validate the integrated modelling approach. The validated techniques are then applied to a seismically derived, 3D model from the southern North Sea, UK, to demonstrate how an integrated, risk-driven approach to modelling allows the effects of uncertainties in the distribution of hydrocarbon accumulations to be investigated.