| Title | Fast-tracking numerical modelling projects using Volsung and Leapfrog Energy |
|---|---|
| Authors | C. Baxter, J. Clearwater, P. Franz, J. OBrien, B. Williams |
| Year | 2023 |
| Conference | New Zealand Geothermal Workshop |
| Keywords | modelling, reservoir model, reservoir simulation, geological model, conceptual model, Volsung, Leapfrog |
| Abstract | The key input to a geothermal reservoir numerical model is a robust conceptual model, which is a concise representation of the primary structures and processes that determine a reservoir’s characteristics and behaviours. These key elements are often modelled, updated and stored in Leapfrog Energy 3D models and presented graphically on cross sections or 3D scenes. In this paper we present a workflow for quickly transferring model outputs from Leapfrog Energy to the Volsung flow simulation software to fast-track the development of the numerical reservoir model and ensure that it is based closelyon sound geoscience. This workflow is based on using volumes and faults from the Leapfrog Energy model to define numerical model regions and adding qualitative conceptual model elements using geo-referenced cross section image files. Well track information can also be exported from Leapfrog Energy to Volsung. All data are represented and transferred independent of a particular explicit grid structure. Outputs from the numerical model simulation, such as the time-dependent spatial distribution of pressure and temperature, can be exported from Volsung and imported back into Leapfrog Energy to be visualized in conjunction with other multi-disciplinary geoscience data. Any revision to the geological or conceptual model can easily be transferred to Volsung to update the associated reservoir numerical model, leading to a robust system for updating and maintaining models over the duration of a geothermal resource development. This workflow is a practical and efficient methodology for fast-tracking the development of a numerical model. It reduces numerical model development time and enables teams of geoscientists to collaborate to produce better numerical models, leading to higher confidence in numerical model predictions and improved geothermal reservoir management. |