Hydrocarbon reservoir models have a high degree of uncertainty regarding their reservoir geometry and structure. A range of conceptual models should therefore be generated to explore how first-order uncertainties impact fluids-in-place, reservoir dynamics, and development decisions. However, it is very time consuming to generate and explore a large number of conceptual models using conventional reservoir modelling and simulation workflows. Key reservoir concepts are therefore often locked in early and are difficult to change later. To overcome this challenge, the Rapid Reservoir Modelling (RRM) software has been developed to prototype reservoir models across scales and test their dynamic behaviour. RRM complements existing workflows in that conceptual models can be prototyped, explored, compared, and ranked rapidly prior to detailed reservoir modelling. Reservoir geology is sketched in 2D with geological operators and translated in real-time into geologically correct 3D models. Flow diagnostics provide quantitative information for these reservoir model prototypes about their static and dynamic behaviours. Numerical well testing (NWT) is implemented to further interrogate the reservoir model. The combination of surface-based reservoir modelling with geological operators, flow diagnostics and NWT on unstructured grids enable, for the first time, rapid prototyping of reservoir geologies with real-time feedback on fluid flow behaviour.
|Publication status||Published - 3 Sep 2018|
|Event||16th European Conference on the Mathematics of Oil Recovery 2018 - Barcelona, Spain|
Duration: 3 Sep 2018 → 6 Sep 2018
|Conference||16th European Conference on the Mathematics of Oil Recovery 2018|
|Abbreviated title||ECMOR 2018|
|Period||3/09/18 → 6/09/18|
Zhang, Z., Geiger, S., Rood, M., Jacquemyn, C., Jackson, M., Hampson, G., Moura de Carvalho, F., Coda Marques Machado Silva, C., Machado Silva, J., & Sousa, M. C. (2018). Fast Flow Computation Methods On Unstructured Tetrahedral Meshes For Rapid Reservoir Modelling. Paper presented at 16th European Conference on the Mathematics of Oil Recovery 2018, Barcelona, Spain. https://doi.org/10.3997/2214-4609.201802241