Resolution and error propagation analysis for tomographic data with correlated errors

Lars Nielsen; Bo Holm Jacobsen

doi:10.1007/BFb0011770

Resolution and error propagation analysis for tomographic data with correlated errors

Lars Nielsen, Bo Holm Jacobsen

Publikation: Bidrag til bog/rapport/konferenceproceedings › Bogkapitel › Forskning › peer review

Resumé

Tomographic data are likely to be contaminated with correlated errors. We use an approach based on data error covariance specification in order to analyse the effect of such errors. This approach is valid for arbitrary irregular measurement geometries and therefore offers great flexibility.

We have shown that the estimates in (1) and (2) behave differently in the presence of correlated errors. Taking the correct error correlations into account we obtain a more realistic description of error propagation, and we produce better model resolution with less smearing.

Originalsprog	Engelsk
Titel	Inverse methods
Undertitel	Interdisciplinary elements of methodology, computation, and applications
Redaktører	Bo Holm Jacobsen, Klaus Mosegaard, Paolo Sibani
Forlag	Springer
Sider	131–138
Antal sider	8
ISBN (Trykt)	978-3-540-61693-1
DOI	https://doi.org/10.1007/BFb0011770
Status	Udgivet - 1996
Udgivet eksternt	Ja

Publikationsserier

Navn	Lecture Notes in Earth Sciences
Vol/bind	63
ISSN	0930-0317

Programområde

Programområde 3: Energiressourcer

Adgang til dokumentet

10.1007/BFb0011770

Citationsformater

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abstract = "Tomographic data are likely to be contaminated with correlated errors. We use an approach based on data error covariance specification in order to analyse the effect of such errors. This approach is valid for arbitrary irregular measurement geometries and therefore offers great flexibility. We have shown that the estimates in (1) and (2) behave differently in the presence of correlated errors. Taking the correct error correlations into account we obtain a more realistic description of error propagation, and we produce better model resolution with less smearing.",

author = "Lars Nielsen and Jacobsen, \{Bo Holm\}",

year = "1996",

doi = "10.1007/BFb0011770",

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Resolution and error propagation analysis for tomographic data with correlated errors. / Nielsen, Lars; Jacobsen, Bo Holm.
Inverse methods: Interdisciplinary elements of methodology, computation, and applications. red. / Bo Holm Jacobsen; Klaus Mosegaard; Paolo Sibani. Springer, 1996. s. 131–138 (Lecture Notes in Earth Sciences, Bind 63).

Publikation: Bidrag til bog/rapport/konferenceproceedings › Bogkapitel › Forskning › peer review

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AU - Jacobsen, Bo Holm

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N2 - Tomographic data are likely to be contaminated with correlated errors. We use an approach based on data error covariance specification in order to analyse the effect of such errors. This approach is valid for arbitrary irregular measurement geometries and therefore offers great flexibility. We have shown that the estimates in (1) and (2) behave differently in the presence of correlated errors. Taking the correct error correlations into account we obtain a more realistic description of error propagation, and we produce better model resolution with less smearing.

AB - Tomographic data are likely to be contaminated with correlated errors. We use an approach based on data error covariance specification in order to analyse the effect of such errors. This approach is valid for arbitrary irregular measurement geometries and therefore offers great flexibility. We have shown that the estimates in (1) and (2) behave differently in the presence of correlated errors. Taking the correct error correlations into account we obtain a more realistic description of error propagation, and we produce better model resolution with less smearing.

U2 - 10.1007/BFb0011770

DO - 10.1007/BFb0011770

M3 - Chapter in book

SN - 978-3-540-61693-1

T3 - Lecture Notes in Earth Sciences

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BT - Inverse methods

A2 - Jacobsen, Bo Holm

A2 - Mosegaard, Klaus

A2 - Sibani, Paolo

PB - Springer

ER -

Resolution and error propagation analysis for tomographic data with correlated errors

Resumé

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