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Volumetric resource assessment

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Titill: Volumetric resource assessmentVolumetric resource assessment
Höfundur: Sarmiento, Zosimo F. ; Benedikt Steingrímsson 1947 ; Guðni Axelsson 1955 ; LaGeo ; Jarðhitaskóli Háskóla Sameinuðu þjóðanna ; United Nations University ; United Nations University, Geothermal Training Programme
URI: http://hdl.handle.net/10802/16522
Útgefandi: United Nations University
Útgáfa: 2018
Ritröð: United Nations University., UNU Geothermal Training Programme, Iceland. Short Course ; SC-26
Efnisorð: Jarðhiti
ISSN: 1670-794x
Tungumál: Enska
Tengd vefsíðuslóð: https://orkustofnun.is/gogn/unu-gtp-sc/UNU-GTP-SC-26-34.pdf
Tegund: Bók
Gegnir ID: 991010134869706886
Athugasemdir: Presented at SDG Short Course III on Geothermal Reservoir Characterization: Well Logging, Well Testing and Chemical Analysis organized by UNU-GTP and LaGeo, in Santa Tecla, El Salvador, September 16-22, 2018.
Útdráttur: Geothermal resource assessment is the estimation of the amount of thermal energy that can be extracted from a geothermal reservoir and used economically for a period of time, usually several decades. Various methods have been developed for this purpose. At early stages of geothermal development, when available data are limited, relatively simple methods are used in assessing the reservoirs. But as more information are gathered on the reservoir parameters and experience is gained in producing energy from the reservoir, sophisticated numerical computer models are used to simulate the geothermal reservoir in the natural state and the response to utilization which eventually will determine the generating potential of the reservoir. The main focus in this paper is on the volumetric method (stored heat calculations) and the key elements that constitute a thorough evaluation of a geothermal resource. Calculation of the geothermal energy reserves based on the range of values of the various reservoir parameters can be carried out using Monte Carlo simulation. It applies a probabilistic method of evaluating reserves or resources that captures uncertainty. Given the complexity and heterogeneity of the geological formations of most geothermal reservoirs, this method is preferred as opposed to the usual deterministic approach which assumes a single value for each parameter to represent the whole reservoir. Instead of assigning a “fixed” value to a reservoir parameter, numbers within the range of the distribution model are randomly selected and drawn for each cycle of calculation over a thousand iterations.


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