Abstract
AbstractIn the early stages of field development, there are many uncertainties and the current trend is to generate coarse-scale models so that many simulations can be run rapidly in order to determine the main sensitivities in a model. However, at a later stage, more data are available and there is less uncertainty in the model, so a more detailed modelling approach is desirable. In this paper, we discuss two modelling procedures which are suitable for different stages of the life of a field, and address the problem of upscaling at each stage. First, we consider a novel approach for generating coarse-scale models for evaluating uncertainty. When there is a large amount of uncertainty, the generation of fine-scale models is too time-consuming, and upscaling them by large factors may produce large errors. We demonstrate an alternative approach for modelling at a coarse scale, while preserving the heterogeneity of the fine-scale distribution, in such a way as to reproduce the fine-scale flow results. Secondly, we focus on more detailed geological models, generated at a later stage of field development. These models may comprise millions of grid cells, and may be highly heterogeneous. Such models require upscaling, but traditional methods may be very inaccurate. We have developed a method for upscaling using well-drive boundary conditions. Tests of this method show that it can reliably reproduce the fine-scale recovery in a range of models.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.