This paper addresses stratigraphic uncertainty and its impact on subsurface forecasts. For this, we introduce a new assisted automatic method which detects possible sequence boundaries from well log data. This method uses multi-scale signal analysis (discrete wavelet transform) to compute the probability density of finding maximum flooding surfaces and maximum regressive surfaces as a function of depth. It then recursively decomposes the studied stratigraphic section into sub-intervals where the analysis is repeated. We applied this method on a shallow marine wave dominated siliciclastic reservoir located in the Vienna Basin. We observe that several reservoir models with different stratigraphic layering (keeping all other parameters constant) have a different reservoir behavior. This allowed us to locally resolve the mismatch between measured and simulated tracer tests. This illustrates the significance of stratigraphic uncertainties in reservoir modeling and the role of automatic methods to help assess and reduce these uncertainties.


Article metrics loading...

Loading full text...

Full text loading...


  1. Bond, C., Lunn, R., Shipton, Z. and Lunn, A
    . [2012] What makes an expert effective at interpreting seismic images?Geology, 40(1), 75–78.
    [Google Scholar]
  2. Catuneanu, O., Galloway, W.E., Kendall, C.G.S.C., Miall, A.D., Posamentier, H.W., Strasser, A. and Tucker, M.E
    . [2011] Sequence stratigraphy: methodology and nomenclature. Newsletters on stratigraphy, 44(3), 173–245.
    [Google Scholar]
  3. Edwards, J., Lallier, F., Caumon, G. and Carpentier, C.
    [2018] Uncertainty management in stratigraphic well correlation and stratigraphic architectures: A training-based method. Computers & Geosciences, 111, 1–17.
    [Google Scholar]
  4. Galloway, W.E
    . [1989] Genetic stratigraphic sequences in basin analysis I: architecture and genesis of flooding-surface bounded depositional units. AAPG bulletin, 73(2), 125–142.
    [Google Scholar]
  5. Johnson, J. and Murphy, M
    . [1984] Time-rock model for Siluro-Devonian continental shelf, western United States. Geological Society of America Bulletin, 95(11), 1349–1359.
    [Google Scholar]
  6. Lallier, F., Caumon, G., Borgomano, J., Viseur, S., Fournier, F., Antoine, C. and Gentilhomme, T
    . [2012] Relevance of the stochastic stratigraphic well correlation approach for the study of complex carbonate settings: Application to the Malampaya buildup (Offshore Palawan, Philippines)>. Geological Society, London, Special Publications, 370, SP370–12.
    [Google Scholar]
  7. Lallier, F., Caumon, G., Borgomano, J., Viseur, S., Royer, J.J. and Antoine, C
    . [2016] Uncertainty Assessment in the Stratigraphic Well Correlation of a Carbonate Ramp: Method and Application to the Beausset Basin, SE France. Comptes Rendus Geoscience, 348(7), 499–509.
    [Google Scholar]
  8. Ruiz, G. and Le Nir, I
    . [1999] Sequence Stratigraphy and Facies Analysis-Computer Aided Interpretation and Correlation. In: 61st EAGE Conference and Exhibition.
    [Google Scholar]
  9. Serra, O. and Serra, L
    . [2003] Well logging and geology. Technip Editions.
    [Google Scholar]
  10. Stollnitz, E.J., DeRose, A.D. and Salesin, D.H
    . [1995] Wavelets for computer graphics: a primer. 1. IEEE Computer Graphics and Applications, 15(3), 76–84.
    [Google Scholar]
  11. Tversky, A. and Kahneman, D
    . [1974] Judgment under Uncertainty: Heuristics and Biases. Science, 185(4157), 1124–1131.
    [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