dc.contributor |
KenGen |
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dc.contributor |
Jarðhitaskóli Háskóla Sameinuðu þjóðanna |
is |
dc.contributor |
United Nations University |
is |
dc.contributor |
United Nations University, Geothermal Training Programme |
is |
dc.contributor.author |
Mwakirani, Raymond M. |
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dc.date.accessioned |
2020-06-30T17:54:29Z |
|
dc.date.available |
2020-06-30T17:54:29Z |
|
dc.date.issued |
2018 |
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dc.identifier.issn |
1670-794x |
|
dc.identifier.uri |
http://hdl.handle.net/10802/23825 |
|
dc.description |
Presented at SDG Short Course III on Exploration and Development of Geothermal Resources, organized by UNU-GTP and KenGen, at Lake Bogoria and Lake Naivasha, Kenya, Nov. 7-27, 2018. |
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dc.description.abstract |
One of the most successful ways to improve the quality of MT transfer functions estimations is to follow the principles of robust statistics. Adaptation of robust statistics to the MT data processing problem has been discussed by Egbert and Booker (1986), Chave et al. (1987) and Chave and Thomson (2003). This paper is intended to guide on the Magneto-telluric data processing. It introduces softwares applied in data processing. It details procedures used in the MT data processing with emphasis on actual steps that are followed to realise good results. |
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dc.format.extent |
1 rafrænt gagn (7 bls.). |
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dc.language.iso |
en |
|
dc.publisher |
United Nations University |
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dc.relation.ispartof |
991011808709706886 |
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dc.relation.ispartofseries |
United Nations University., UNU Geothermal Training Programme, Iceland. Short Course ; SC-27 |
|
dc.relation.uri |
https://orkustofnun.is/gogn/unu-gtp-sc/UNU-GTP-SC-27-0402.pdf |
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dc.subject |
Jarðfræði |
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dc.subject |
Jarðeðlisfræði |
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dc.subject |
Jarðhitaleit |
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dc.title |
Magneto-telluric (MT) data processing |
en |
dc.type |
Bók |
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dc.identifier.gegnir |
991011813119706886 |
|