Abstract
Ongoing research into geothermal energy sources in Greece has indicated various high enthalpy reservoirs that have not yet been exploited, although the Aegean Sea volcanic arc has proven to be of great potential. Nevertheless, the recent roadmap for the utilization of renewable resources suggests that within next decade, geothermal energy will provide 630 GWh of electric power annually. The development of the Milos field by 2025 is ongoing. Clearly, the need for expertise on the setup and utilization of geothermal numerical reservoir simulation models is major. In this work, we examine the capabilities of the two main options—distributed and lumped parameter models—for the mathematical description and optimization of geothermal energy fields. We investigate their applicability to the high enthalpy fields in Greece by treating history matching and energy extraction optimization. Additionally, we examine their contribution to field management aiming at minimizing the operating cost and environmental effects as well as ensuring sustainable energy production.
Highlights
Proc. 2021, 5, 120. https://doi.org/The ever-increasing need for “green” energy has forced attention towards geothermal energy sources, aiming mostly at the utilization of geothermal steam to run electricity plants
The geology of Greece supports geothermal energy exploitation as various sites such as Methana and the islands of Milos, Kimolos and Nisiros lie on the so-called Aegean Sea volcanic arc
The Milos high enthalpy field has been proven to bear a reservoir temperature of 320 ◦ C of single phase liquid water, which ends up at a slightly lower temperature at the wellhead [1]
Summary
The ever-increasing need for “green” energy has forced attention towards geothermal energy sources, aiming mostly at the utilization of geothermal steam to run electricity plants. The mass and heat flow differential equations are solved numerically in the reservoir domain, which in turn requires the discretization of space and time into small blocks so that the exact derivatives are approximated accurately enough by the numerical ones Properties of interest such as pressure, temperature and gas saturation (i.e., p( x, y, z, t), T ( x, y, z, t) and Sg ( x, y, z, t), with the latter being applicable only to saturated reservoirs) can be estimated individually at any point in the reservoir, allowing for their detailed spatial and temporal description. We focus on the overwhelming advantages of the distributed parameter modeling as well as the numerical difficulties that may be encountered that may lead to an entire lack of a physical interpretation Such inconsistencies may completely destroy the capability of the model to provide reasonable and accurate predictions of the future behavior of the reservoir as far as both its hydraulic and thermal conditions are concerned and eventually lead to an erroneously predicted sustainability of geothermal fluid production
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