Articles | Volume 10, issue 4
Research article
05 Jul 2019
Research article |  | 05 Jul 2019

Quantification of uncertainty in 3-D seismic interpretation: implications for deterministic and stochastic geomodeling and machine learning

Alexander Schaaf and Clare E. Bond

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Cited articles

Abrahamsen, P., Lia, O., and Omre, H.: An Integrated Approach to Prediction of Hydrocarbon in Place and Recoverable Reserve With Uncertainty Measures, in: European Petroleum Computer Conference, Society of Petroleum Engineers,, 1992. a
Alcalde, J., Bond, C. E., Johnson, G., Butler, R. W., Cooper, M. A., and Ellis, J. F.: The Importance of Structural Model Availability on Seismic Interpretation, J. Struct. Geol., 97, 161–171,, 2017a. a, b
Alcalde, J., Bond, C. E., Johnson, G., Ellis, J. F., and Butler, R. W.: Impact of Seismic Image Quality on Fault Interpretation Uncertainty, GSA Today, 27, 4–10,, 2017b. a, b
Alcalde, J., Bond, C. E., and Randle, C. H.: Framing Bias: The Effect of Figure Presentation on Seismic Interpretation, Interpretation, 5, T591–T605, 2017c. a
Biondi, B.: 3D Seismic Imaging, Investigations in Geophysics, Society of Exploration Geophysicists, Tulsa, Oklahoma, USA,, 2006. a
Short summary
Seismic reflection data allow us to infer subsurface structures such as horizon and fault surfaces. The interpretation of this indirect data source is inherently uncertainty, and our work takes a first look at the scope of uncertainties involved in the interpretation of 3-D seismic data. We show how uncertainties of fault interpretations can be related to data quality and discuss the implications for the 3-D modeling of subsurface structures derived from 3-D seismic data.