Joint assimilation of electromagnetic and seismic data - A stochastic approach

F. Vossepoel*

*Corresponding author for this work

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

1 Citation (Scopus)


The complementary nature of seismic and electromagnetic (EM) data asks for joint inversion of these data sets for reservoir characterisation and monitoring. EM data contain valuable information on the reservoir lithologies and have the ability to discriminate between hydrocarbon- and brine-filled rock. As the EM signal is diffusive, the resolution of the data is generally low, and is best combined with seismic data and appropriate prior models that help constrain the solution space. To account for uncertainties in the data in a statistically robust manner, we propose to make use of data assimilation techniques. This approach is especially attractive in monitoring applications where dynamic models provide a physically consistent prior estimate of the reservoir characteristics and its state evolution. After providing an overview of the possibilities for joint assimilation of EM and seismic data, a number of data-assimilation examples will illustrate the advantages and disadvantages of the various approaches.
Original languageEnglish
Title of host publication81st EAGE Conference and Exhibition 2019 Workshop Programme
Number of pages3
ISBN (Electronic)9789462822924
Publication statusPublished - 2019
Event81st EAGE Conference and Exhibition 2019 - ExCeL Centre, London, United Kingdom
Duration: 3 Jun 20196 Jun 2019


Conference81st EAGE Conference and Exhibition 2019
CountryUnited Kingdom
Internet address


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