Journal cover Journal topic
Geothermal Energy Science An open-access journal
Journal topic
Volume 2, issue 1
Geoth. Energ. Sci., 2, 49-54, 2014
https://doi.org/10.5194/gtes-2-49-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.

Special issue: Estimation and classification of geothermal potential...

Geoth. Energ. Sci., 2, 49-54, 2014
https://doi.org/10.5194/gtes-2-49-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.

  17 Dec 2014

17 Dec 2014

Stored-heat assessments: a review in the light of field experience

M. A. Grant M. A. Grant
  • MAGAK, 14A Rewi Rd, Auckland 1023, New Zealand

Abstract. Stored-heat or volumetric assessments of geothermal resources are appealingly simple: the resource being exploited is heat. A stored-heat calculation simply computes the amount of heat in the resource, similarly to computing the amount of ore in an ore body. The method has theoretical support in numerical simulations of resource production. While there are significant unknowns in any resource, some of these can be covered by probabilistic approaches, notably a Monte Carlo method. The Australian Geothermal Reporting Code represents one specification of such stored-heat assessments.

However the experience of recent decades, with the development of significant numbers of geothermal resources, has shown that the method is highly unreliable and usually biased high. The tendency to overestimates, in particular, has led to the reduced credibility of the method. An example is quoted where simple application of the apparently simple rules gives a ridiculous result. Much of the problem lies in the "recovery factor", the proportion of the resource that can actually be exploited, where comparison with actual performance shows past values have been in all cases too high, as is the current version of the Australian code.

There are further problems, usually overlooked, in the way that the reservoir volume and "cutoff temperature" are defined. Differing approaches mean that results between different reports are not comparable. The different approaches also imply unrecognised assumptions about the physical processes controlling reservoir depletion. The failure of Monte Carlo methods is similarly due to unrecognised violation of logical consistency in the use of probabilities.

The net effect of these problems is that the method is not a simple means to generate a rough resource estimate, and it often generates faulty results. Usually, such results are overestimates. Monte Carlo methods do not provide a protection against these errors.

The Australian Geothermal Reporting Code should be used for hydrothermal systems with an average recovery factor of 10%. With this average, results are subject to an error of ±70%. For enhanced geothermal systems (EGS), the recovery factor should be a few percent.

Publications Copernicus
Download
Short summary
Stored-heat assessment methods for geothermal fields are reviewed against observed field performance. For the method originated by the USGS, and used in the Australian Geothermal Reporting Code, the average recovery factor is shown to be 10%, with an error of ±70%. For enhanced geothermal systems (EGS) the recovery factor in experiments to date has been much less, a few percent at best.
Stored-heat assessment methods for geothermal fields are reviewed against observed field...
Citation