Modelling in-situ upgrading of heavy oil using operator splitting method

The in-situ upgrading (ISU) of bitumen and oil shale is a very challenging process to model numerically because of the large number of components that need to be modelled using a system of equations that are both highly non-linear and strongly coupled. Operator splitting methods are one way of potentially improving computational performance. Each numerical operator in a process is modelled separately, allowing the best solution method to be used for the given numerical operator. A significant drawback to the approach is that decoupling the governing equations introduces an additional source of numerical error, known as the splitting error. The best splitting method for modelling a given process minimises the splitting error whilst improving computational performance compared to a fully implicit approach. Although operator splitting has been widely used for the modelling of reactive-transport problems, it has not yet been applied to the modelling of ISU. One reason is that it is not clear which operator splitting technique to use. Numerous such techniques are described in the literature and each leads to a different splitting error. While this error has been extensively analysed for linear operators for a wide range of methods, the results cannot be extended to general non-linear systems. It is therefore not clear which of these techniques is most appropriate for the modelling of ISU. In this paper, we investigate the application of various operator splitting techniques to the modelling of the ISU of bitumen and oil shale. The techniques were tested on a simplified model of the physical system in which a solid or heavy liquid component is decomposed by pyrolysis into lighter liquid and gas components. The operator splitting techniques examined include the sequential split operator (SSO), the Strang-Marchuk split operator (SMSO) and the iterative split operator (ISO). They were evaluated on various test cases by considering the evolution of the discretization error as a function of the time-step size compared with the results obtained from a fully implicit simulation. We observed that the error was least for a splitting scheme where the thermal conduction was performed first, followed by the chemical reaction step and finally the heat and mass convection operator (SSO-CKA). This method was then applied to a more realistic model of the ISU of bitumen with multiple components, and we were able to obtain a speed-up of between 3 and 5.     

Sekundäre Umlagerung Pflanzlicher Mikrofossilien in klastischen Sedimenten

Ohne Zusammenfassung     

On the relationship between cloud–radiation interaction, atmospheric stability and Atlantic tropical cyclones in a variable-resolution climate model

We compare two 28-year simulations performed with two versions of the Global Environmental Multiscale model run in variable-resolution mode. The two versions differ only by small differences in their radiation scheme. The most significant modification introduced is a reduction in the ice effective radius, which is observed to increase absorption of upwelling infrared radiation and increase temperature in the upper troposphere. The resulting change in vertical lapse rate is then observed to drive a resolution-dependent response of convection, which in turn modifies the zonal circulation and induces significant changes in simulated Atlantic tropical cyclone activity. The resulting change in vertical lapse rate and its implication in the context of anthropogenic climate change are discussed.     

The Phase A study of the ESA M4 mission candidate ARIEL

ARIEL, the Atmospheric Remote sensing Infrared Exoplanet Large survey, is one of the three M-class mission candidates competing for the M4 launch slot within the Cosmic Vision science programme of the European Space Agency (ESA). As such, ARIEL has been the subject of a Phase A study that involved European industry, research institutes and universities from ESA member states. This study is now completed and the M4 down-selection is expected to be concluded in November 2017. ARIEL is a concept for a dedicated mission to measure the chemical composition and structure of hundreds of exoplanet atmospheres using the technique of transit spectroscopy. ARIEL targets extend from gas giants (Jupiter or Neptune-like) to super-Earths in the very hot to warm zones of F to M-type host stars, opening up the way to large-scale, comparative planetology that would place our own Solar System in the context of other planetary systems in the Milky Way. A technical and programmatic review of the ARIEL mission was performed between February and May 2017, with the objective of assessing the readiness of the mission to progress to the Phase B1 study. No critical issues were identified and the mission was deemed technically feasible within the M4 programmatic boundary conditions. In this paper we give an overview of the final mission concept for ARIEL as of the end of the Phase A study, from scientific, technical and operational perspectives.