Abrupt perturbations of the global carbon cycle during the early Eocene are associated with rapid global warming events, which are analogous in many ways to present greenhouse warming. Mammal dwarfing has been observed, along with other changes in community structure, during the largest of these ancient global warming events, known as the Paleocene-Eocene Thermal Maximum [PETM; ~56 million years ago (Ma)]. We show that mammalian dwarfing accompanied the subsequent, smaller-magnitude warming event known as Eocene Thermal Maximum 2 [ETM2 (~53 Ma)]. Statistically significant decrease in body size during ETM2 is observed in two of four taxonomic groups analyzed in this study and is most clearly observed in early equids (horses). During ETM2, the best-sampled lineage of equids decreased in size by ~14%, as opposed to ~30% during the PETM. Thus, dwarfing appears to be a common evolutionary response of some mammals during past global warming events, and the extent of dwarfing seems related to the magnitude of the event.

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We have developed a new finite element - finite volume based simulation approach to study flow and transport processes at sub-grid scales, i.e. at scales below the typical size of a reservoir simulation grid block, using real 3D geometries in carbonate reservoirs. We complement the simulations by high-resolution X-Ray CT experiments which provide us with the 3D structures, allow us to visualise flow processes at the core-scale in real time, and help us to compare the observed processes to numerical simulations to validate and verify the latter. We use this combined numerical-experimental approach to analyse the fundamental processes controlling fluid flow in carbonates at sub-grid scales. Results can be incorporated in existing reservoir simulation workflows to increase the confidence in reservoir performance forecasting. We show applications related to fractured carbonate reservoirs and enhanced oil recovery processes due to injection of low-salinity fluids and hot water.@en

We have been able to solve a reservoir simulation problem which was previously thought of as intractable: We simulated multiphase displacement, including viscous, capillary, and gravitational forces, for highly resolved and geologically realistic models of naturally fractured reservoirs (NFR) at the sector, i.e. kilometre, scale with very reasonable runtime. This has been possible because we used massive parallelisation and hierarchical solvers in conjunction with a new discrete fracture and matrix modelling (DFM) technique that is based on mixed-dimensional unstructured hybrid-element discretisations. High-resolution DFM simulations are important to resolve the non-linear coupling of small scale capillary - viscous and large scale gravitational - viscous processes adequately for sector scale NFR. Cross-scale process coupling in NFR controls oil recovery and NFR often exhibit power-law fracture length distributions, i.e. they do not possess an REV, and highly permeable fractures can extend over the full hydrocarbon column height. As a consequence, emergent displacement patterns have been observed which are difficult to quantify using traditional means of upscaling. However, such patterns could now be used as benchmarks to reach a better consensus on the correctness of promising new upscaling techniques. The parallel DFM technologies presented here allow us to to obtain these results much more efficiently and hence explore the parameter space in greater detail. We observed a linear scaling behaviour for up to 64 processes and a significant decrease in runtime when applying our parallel DFM approach to three highly refined NFR simulations. These contain thousands of fractures, up to 5 million elements, and have local grid-refinements below 1 m for model dimensions between I and 10 kilometres. We achieved this excellent speedup because we reduced inter-processor communication by minimising the overlap between individual domains and decreased idle time of individual processors by distributing the number of unknowns equally among the processors.@en