The Krafla Geothermal Field, Iceland: 1. Analysis of well test data

Bodvarsson, G.S.; Benson, Sally M.; Sigurðsson, Ómar; Stefansson, V.; Eliasson, E.T.

doi:10.1029/wr020i011p01515

Cited by 40 publications

(23 citation statements)

References 12 publications

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“…Since 1975 magma has intruded into chambers 3-8 km below the geothermal fi eld, and the most recent subaerial eruption was in 1984 (Björnsson et al 1977;Einarsson 1978;Ármannsson et al 1987;Arnórsson 1995). Permeability in the Krafl a system is low (2 millidarcies: Bödvarsson et al 1984), possibly due to the abundance of igneous intrusions at depth. Basalt and dolerite intrusions dominate the stratigraphy below 1200-1300 m depth and gabbro occurs below 1800 m in some areas.…”

Section: Icelandmentioning

confidence: 99%

Epidote in Geothermal Systems

Bird

Spieler

2004

Reviews in Mineralogy and Geochemistry

109

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Section: Icelandmentioning

confidence: 99%

Epidote in Geothermal Systems

Bird

Spieler

2004

Reviews in Mineralogy and Geochemistry

109

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“…Well flow testing and subsequent modeling provide information about permeability and porosity in the region of the flowing zones of the well (Antunez et al, 1990;Bodvarsson et al, 1984a;Bodvarsson et al, 1990b;Bodvarsson et al, 1987a;Bodvarsson et al, 1987b;Doughty and Pruess, 1992;Menzies et al, 1991;Menzies et al, 1996;O'Sullivan, 1981;Pruess, 1990;Pruess et al, 1984a). Self-potential surveys can provide information on the size and location of flowing hydrothermal systems (Nishi et al, 1998), and microgravity data and their spatial and temporal variations can aid in the location of vapordominated regions and indicate changes in their size (Atkinson and Pedersen, 1988;Hunt et al, 1990).…”

Section: Modeling Methodsmentioning

confidence: 99%

Geothermal reservoir simulation to enhance confidence in predictions for nuclear waste disposal

Kneafsey¹,

Pruess²,

O’Sullivan³

et al. 2002

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Numerical simulation of geothermal reservoirs is useful and necessary in understanding and evaluating reservoir structure and behavior, designing field development, and predicting performance. Models vary in complexity depending on processes considered, heterogeneity, data availability, and study objectives. They are evaluated using computer codes written and tested to study single and multiphase flow and transport under nonisothermal conditions. Many flow and heat transfer processes modeled in geothermal reservoirs are expected to occur in anthropogenic thermal (AT) systems created by geologic disposal of heat-generating nuclear waste. We examine and compare geothermal systems and the AT system expected at Yucca Mountain, Nevada, and their modeling. Time frames and spatial scales are similar in both systems, but increased precision is necessary for modeling the AT system, because flow through specific repository locations will affect long-term ability radionuclide retention. Geothermal modeling experience has generated a methodology, used in the AT modeling for Yucca Mountain, yielding good predictive results if sufficient reliable data are available and an experienced modeler is involved. Codes used in geothermal and AT modeling have been tested extensively and successfully on a variety of analytical and laboratory problems. Key WordsNuclear waste disposal, simulation, geothermal, Yucca Mountain, post-audit Kneafsey, Pruess, O'Sullivan, and Bodvarsson 2 IntroductionSubsurface disposal of heat-generating, high-level nuclear waste, such as at the potential repository at Yucca Mountain, Nevada will induce changes in the thermal, hydrologic, and chemical processes that will occur for some distance from the waste for many thousands of years.These changes include water boiling within the rock, flow of the water vapor, condensation of the water vapor, flow of the condensate, mineral dissolution in the condensate, mineral precipitation upon boiling, and hydrothermal flows in the saturated zone. Understanding flow through the mountain in its natural state, during the heating phase, and as the mountain cools is necessary to adequately assess the protection provided by the repository, and to predict the behavior of the repository for a time scale of 10,000 years or more. To this end, investigators have constructed numerical models to study present moisture flow, analyze thermal test data, evaluate the impact of the imposed heat source on the local environment, and assess how both natural and anthropogenic thermal (AT) systems may affect the potential repository Buscheck, 1998;Buscheck and Nitao, 1993;Buscheck and Nitao, 1994;Haukwa et al., 1999;Nitao, 1988;Nitao et al., 1992;Pruess and Tsang, 1994;Pruess et al., 1984b;Pruess et al., 1990a;Pruess et al., 1990b;Tsang and Birkholzer, 1999;Tsang and Pruess, 1987;Tsang and Pruess, 1989;Tsang and Pruess, 1990;Wu et al., 1999).In this paper, we critically examine fluid-and heat-flow modeling in geothermal systems and the potential nuclear waste disposal in the unsaturat...

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“…Total circulation losses exceeding 50 l/s and an estimated transmissivity of 2 Darcy-meters were taken as preliminary indicators for a good producer. For comparison, Well KJ-14 also drilled in the Southern Slopes had a maximum circulation loss of 50 l/s and a step-rate injection-based transmissivity of 2.2 Darcy-meters [Bodvarsson et al, 1984]. This well has been a good producer since 1980, yielding a near constant flow of 10 kg/s of dry steam.…”

Section: Well Kj-31 Data Sourcesmentioning

confidence: 99%

Evaluation of geothermal well behavior using inverse modeling

Finsterle¹,

Björnsson²,

Pruess³

et al. 2000

Dynamics of Fluids in Fractured Rock

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Characterization of fractured geothermal reservoirs for numerical prediction of fluid and heat flow requires determination of a large number of hydrologic, thermal, and geometric properties. For use in a computer model that is based on a simplified conceptual model, these properties must be capable of reflecting the complex multiphase flow behavior in a fracture network, including fracture-matrix interaction. We discuss the potential of inverse modeling techniques to provide model-related input parameters based on a joint inversion of field testing and actual production data from a geothermal reservoir. Using synthetically generated data, we demonstrate the need to simultaneously analyze multiple data sets in a joint inversion. The impact of parameter correlations on the estimated values and their uncertainties is also discussed. Inverse modeling techniques are then applied to data from the Krafla geothermal field, Iceland, in an attempt to estimate some critical reservoir parameters such as steam saturation after 20 years of production from that two-phase system. We conclude that inverse modeling is a powerful tool not only to provide input parameters to a numerical model, but also to improve the understanding of fractured geothermal systems. Its efficiency and the insight gained from the formalized error analysis allow an evaluation of alternative conceptual models, which remains the most crucial step in geothermal reservoir modeling.

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The Krafla Geothermal Field, Iceland: 1. Analysis of well test data

Cited by 40 publications

References 12 publications

Epidote in Geothermal Systems

Epidote in Geothermal Systems

Geothermal reservoir simulation to enhance confidence in predictions for nuclear waste disposal

Evaluation of geothermal well behavior using inverse modeling

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