| Title | Refining geological models through 3D gravity modelling at Wairākei, Tauhara and Rotokawa geothermal fields |
|---|---|
| Authors | J. Barretto, C. Miller, L. Carson, S. Alcaraz, I. Chambefort |
| Year | 2024 |
| Conference | New Zealand Geothermal Workshop |
| Keywords | gravity, forward modelling, inversion, geological model |
| Abstract | Three-dimensional forward and inverse modelling of gravity data from Wairākei, Tauhara and Rotokawa geothermal fields were undertaken to reconcile geological models with geophysical observations. Our aim is to improve areas of the geological model unconstrained by drilling through utilising geophysical information. We developed a starting geological block model using well log data where each geological unit is assigned a density based on petrophysical data. We converted the block model into a vertical prism (VP) model for geophysical modelling. Initial forward modelling of the VP model showed a large misfit between observed and calculated gravity in several areas indicating areas where the geological model did not match geophysical data. To improve the fit, we undertook inversion modelling. Gravity inversion was performed on the VP model in three ways: 1) geometry inversion of basement depth in areas with no well data; 2) homogeneous inversion to get best fit densities distributed uniformly within geological units, and 3) heterogeneous inversion where density distribution was allowed to vary within each geological unit. The resulting geological model shows that greywacke basement is probably present beneath Wairākei at >3000 m depth. The model also suggests the presence of a low-density vertical zone cutting through the Rotokawa Andesite and underlying greywacke interpreted to be a buried vent focusing fluid flow and manifesting on the surface as Lake Rotokawa. Other minor refinements to the geological model were made that are consistent with gravity observations. We show that refinement of geological models through forward and inverse modelling of dense geophysical datasets helps enhance subsurface models and guide future drilling plans. |