AAPG Middle East Region GTW, Regional Variations in Charge Systems and the Impact on Hydrocarbon Fluid Properties in Exploration

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Thermal History of Sedimentary Basins – Best Practices Towards a Consistent Heat Flow Model Through Geological Time


The primary objective in Petroleum systems modeling is the reconstruction of the thermal history of the petroleum systems elements. The thermal history is the basis of almost all calculated processes from hydrocarbon generation, migration, accumulation and preservation. Over the recent past, our understanding of lithospheric processes and most importantly, of the present-day structures we made. Together with advanced tools available we can utilize this knowledge and reconstruct a geologically consistent temperature history that allows us to reduce the uncertainties and improve the predictability of petroleum systems models. This paper will illustrate best practices to define a consistent geological model input that delivers a fit for purpose thermal history that not only calibrates to measured thermal indicators, but also to the fundamental geological constraints such as present day lithospheric structures and observed lithospheric processes. Basin forming mechanisms and present day lithospheric structures are key parameters to consider. Based on additional process information we can reconstruct the lithospheric evolution of a basin. The heat flow into the sediments can then be calculated through geological time based on the resulting lithospheric model and the sedimentary blanketing effect. We present several case studies to illustrate the recommended workflows and discuss limitations and uncertainties. We present how geological observations can be used to calibrate numerical models and test sensitivities on the petroleum systems under consideration. All case studies clearly show that the understanding of the present-day lithosphere geometry is the key to a consistent and therefore predictive thermal history, delivering a solid petroleum systems analysis that gives operators more confidence in utilizing the predictions for prospect assessment workflows.