Bayesian calibration of a natural state geothermal reservoir model,
Krafla, north Iceland
Abstract
The Krafla area in north Iceland hosts a high-temperature geothermal
system within a volcanic caldera. Temperature measurements from
boreholes drilled for power generation reveal enigmatic contrasts
throughout the drilled area. While wells in the western part of the
production field indicate a 0.5-1 km thick near-isothermal
(~210 °C) liquid-dominated reservoir underlain by a
deeper boiling reservoir, wells in the east indicate boiling conditions
extending from the surface to the maximum depth of drilled wells
(~2 km). Understanding these systematic temperature
contrasts in terms of the subsurface permeability structure and overall
dynamics of fluid flow has remained challenging. Here, we present a new
numerical model of the natural, pre-exploitation state of the Krafla
system, incorporating a new geologic/conceptual model and a version of
TOUGH2 extending to supercritical conditions. The model shows how the
characteristic temperature distribution results from structural
partitioning of the system by a rift-parallel eruptive fissure and an
aquitard at the transition between deeper basement intrusions and
high-permeability extrusive volcanic rocks. As model calibration is
performed using a Bayesian framework, the posterior results reveal
significant uncertainty in the inferred permeability values for the
different rock types, often exceeding two orders of magnitude. While the
model shows how zones of single-phase vapor develop above the deep
intrusive heat source, more data from deep wells is needed to better
constrain the extent and temperature of the deep vapor zones. However,
the model suggests the presence of a significant untapped resource at
Krafla.