A method is presented to link prior geological information, from wells and interpretation, to full wave-form inversion at reservoir scale. The method converts the layer-based prior information to grid-based property probability density distributions that are highly non-Gaussian and is based on Bayes’ Rule. The likelihood function for the unconstrained inversion is based on the Hessian of the inversion kernel and the minimum residual energy in the objective function. Good results have been obtained from a synthetic case study based on a very realistic outcrop model (Book Cliffs,Utah). Also results from a real data case study will be shown.


Article metrics loading...

Loading full text...

Full text loading...


  1. Gisolf and van den Berg
    , Target oriented non-linear inversion of seismic data, 74th EAGE Conference and Exhibition, Copenhagen, 2012.
    [Google Scholar]
  2. A.Gisolf, D.Tetyukhina, and S. M.Luthi
    : Full Elastic Inversion of Synthetic Seismic Data Based on an Outcrop Model, Extended abstract, 82nd SEG Annual meeting, Las Vegas, 2012.
    [Google Scholar]
  3. R.Feng, S.M.Luthi and A.Gisolf
    , Reservoir Lithology Classification by the Hidden Markov Model, EAGE Exploration Workshop, Oman, 2017
    [Google Scholar]
  4. Feng, R., Sharma, S., Luthi, S.M. & Gisolf, A.
    An outcrop-based detailed geological model to test automated interpretation of seismic inversion results. 77th EAGE Annual Meeting, Madrid, 2015.
    [Google Scholar]

Data & Media loading...

This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error