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Inversion (Geophysik)

Joint inter-disciplinary 3D inversion applying structural referencing to porosity via cross-gradients. Top row shows porosity section along profile ‘WE’. Centre: joint MT+gravity inversion results. Bottom: Vp+gravity inversion results. Porositycontours are superimposed on all inverted properties for comparison. The estimated top of the lava petrophysical group is shown in pink. Quelle: Soyer

Als Inversion oder inverse Modellierung bezeichnet man in der Geophysik Rechenprozesse, die aus den Daten ein geologisches Modell erzeugen.

Die Inversion ist ein zentrales Thema der Geophysik und kann hier nur angedeutet beschrieben werden. Neben linearen und nicht-linearen Verfahren spielt oft auch 'trial and error' eine Rolle, wobei teils manuell nach einer Lösung gesucht wird. Wesentlich ist oft auch die Wahl eine Ausgangsmodells, das dann im Zuge der Inversion an die Messdaten angepasst wird.

Bei vielen geophysikalischen Verfahren ist die Inversion nicht eindeutig, sondern eine Vielzahl von Modellen kann die Messdaten befriedigen (z.B. Gravimetrie). Hier sind dann einschränkende Informationen (constrains) in den Prozess zu importieren. Gelegenlich werden auch Messdaten unterschiedlicher Messungen (z.B. Seismik und Elektrik zusammen invertiert (joint inversion).

Joint inversion

Ein zentrales Ziel der Interpretation geophysikalischer Daten ist es, ein Modell des Untergrundes zu entwickeln, das neben strukturellen Informationen auch Gesteins- und Fluideigenschaften abbildet und zwar gegebenenfalls auch in unterschiedlichen Skalen. Hierzu ist es oft sinnvolle Messdaten unterschiedlicher geophysikalischer Verfahren zu kombinieren. Am konsequentesten erfolgt dies in einer zusammengefassten Inversion (joint inversion), bei der alle Daten in einen gemeinsamen Inversionsprozess eingespeist werden. Eine Herausforderung sind dabei oft die sehr unterschiedlichen Skalen. Ein Beispiel ist hier die Kombination von Oberflächendaten mit Bohrlochdaten.

Joint inversion wird heute in vielen Bereichen der Geophysik angewendet, von der Ingenieurgeophysik bis zu Untersuchungen von Kruste und Mantel.

Literatur

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Dell, P.’Aversana, “Joint Inversion of Seismic, Gravity and Magnetotelluric Data Combined with Depth Seismic Imaging,” EMG International Workshop, Capri, 2007

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Gyulai, A., T. Ormos and M. Dobróka, “A Quick 2-D Geoelectric Inversion Method Using Series Expansion,” Journal of Applied Geophysics, Vol. 72, No. 4, 2010, pp. 232-241. doi:10.1016/j.jappgeo.2010.09.006

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Hering, A., R. Misiek, á. Gyulai, T. Ormos, M. Dobróka and L. Dresen, “A Joint Inversion Algorithm to Process Geoelectric and Surface Wave Data, Part. I.,” Geophysical Prospecting, Vol. 43, No. 2, 1995, pp. 153-156. doi:10.1111/j.1365-2478.1995.tb00128.x

Jegen, R., R. W. Hobbs, P. Tartis and A. Chave, “Joint Inversion of Marine Magnetotelluric and Gravity Data Incorporating Seismic Constrains. Preliminary Results of Sub-Basalt Imaging off the Farve Shelf,” Earth and Planetary Science Letters, Vol. 282, No. 1-4, 2009, pp. 47-95. doi:10.1016/j.epsl.2009.02.018

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Margrave, G., F., R. R. Steward and J. A. Larsen, “Joint PP and PS Seismic Inversion,” The Leading Edge, Vol. 20, No. 9, 2001, pp. 1048-1052. doi:10.1190/1.1487311

Menke, W., “Geophysical Data Analysis-Discrete Inverse Theory,” Academic Press, Inc., London, 1984.

Misiek, R., A. Liebig, á. Gyulai, T. Ormos, M. Dobróka and L. Dresen, “A Joint Inversion Algorithm to Process Geoelectric and Surface Wave Seismic Data Part II,” Geophysical Prospecting, Vol. 45, No. 1, 1997, pp. 65-85. doi:10.1046/j.1365-2478.1997.3190241.x

Salát, P., Gy. Tarcsai, L. Cserepes, M. Vermes and D. Drahos, “Information-Statistical Methods of Geophysical Interpretation (in Hungarian),” Tankonyvkiadó, 1982.

Salát, P., Gy. Tarcsai, L. Cserepes, M. Vermes and D. Drahos, “Information-Statistical Methods of Geophysical Interpretation (in Hungarian),” Tankonyvkiadó, 1982

Sharma, S., P. and S. K. Verma, “Solutions of the Inherent Problem of the Equivalence in Direct Current Resistivity and Electromagnetic Methods through Global Optimalisation and Joint Inversion by Successive Refinement of Model Space,” Geophysical Prospecting, Vol. 59, No. 4, 2011, pp. 760-776. doi:10.1111/j.1365-2478.2011.00952.x

Soyer, Wolfgang, Randall Mackie, Stephen Hallinan, Alice Pavesi, Gregg Nordquist, Aquardi Suminar, Rindu Intani and Chris Nelson, Geologically consistent multiphysics imaging of the Darajat geothermal steam field, First Break, Vol 36, No 6, 2018 pp. 77 - 83

Spitzer, K., “A 3-D Finite Difference Algorithm for DC Resistivity Modelling Using Conjugate Gradient Methods,” Geophysical Journal International, Vol. 123, No. 3, 1995, pp. 902-914. doi:10.1111/j.1365-246X.1995.tb06897.x

Szabó, N., P., “Global Inversion of Well-Logging Data,” Geophysical Transactions, Vol. 44, No. 3-4, 2004, pp. 313-329.

Vozoff, K. and D. L. B. Jupp, “Joint Inversion of Geophysical Data,” Geophysical Journal of the Royal Astronomical Society, Vol. 42, No. 3, 1975, pp. 977-991. doi:10.1111/j.1365-246X.1975.tb06462.x

Weitere Literatur siehe unter Literaturdatenbank und/oder Konferenzdatenbank unter 'inversion'.

Weblinks

www.spektrum.de/lexikon/geowissenschaften/inversion/76

www.resistivity.net/invprob/invprob.pdf