Sensitivity Analysis of the Grid Refinement and Case Study of Reykjanes High Temperature Geothermal Field

Abstract

Determination of appropriate grid size for geothermal modelling have been frequently discussed in recent years. Results of TOUGH2 simulations are affected by the quality of the grid geometry. The most common approach is lowering the volume of blocks in area of interest. Therefore, number of blocks that are placed in the area of interest will increase, and the accuracy of TOUGH2 will be increased. In this paper, PyTOUGH (Croucher, 2011) scripting library and AUTOUGH2_5 (University of Auckland version) are used to investigate the behavior of Reykjanes high temperature reservoir in different grid size approaches. In order to investigate the sensitivity of the generated grids when comparing measured downhole temperature distribution and the natural state, five different complex grid systems were created, derived from a simple geometry. Although all other parameters except grid sizes were kept constant, slightly different results were found in the natural state temperature and production history pressure distributions. To summarize, the paper examines the current approaches to horizontal & vertical grid refinement of TOUGH2 models, considering the advantages and disadvantages of each, with reference to the performance of five different grid models for Reykjanes Geothermal Reservoir. Overall results showed that, all the grid systems have quite similar temperature distribution with minor differences except for shallow depth range. Especially, the geometry with the thinnest layers in shallow depths have the lowest temperature range.