Risk Reduction in Exploration: Implementation of Seismic–Derived Source Rock Attributes into Basin Modelling
J. C. Vandré¹,² and M. Erdmann¹
¹Statoil, Exploration Excellence, Bergen, Norway
²Statoil, Research & Development, Bergen, Norway
Basin modelling is routinely used in Statoil for evaluating and risking petroleum systems, play concepts, and prospects. In basin modelling, uncertainties exist concerning the geological concept of a model and its input parameters. Therefore, the quality of basin modelling results depends on the quality of the input data and the accuracy of the applied boundary conditions. Most basin modelling studies are characterised by a lack of reliable source rock data. In fact source rock properties are commonly described by average values based on data from only few wells. More accurate quantifications of source rock properties such as presence, thickness, and richness can have significant impact on modelled petroleum volumes in a given kitchen area and consequently affect risking on both basin and prospect scales.
Statoil has developed a method for identifying and qualifying petroleum source rocks from seismic data (Løseth et al., 2011; Wensaas et al., 2011). The characteristic acoustic–elastic rock properties and AVO (amplitude versus offset) behaviour of marine organic–rich shales allows their recognition and mapping on seismic data, providing more accurate information about their presence and thickness which can serve directly as input to basin modelling. The source rock total organic carbon content (TOC) may also be estimated from the seismic domain by inversion techniques if suitable well data is available for calibration. In consequence, generated petroleum and expelled volumes can be modelled with much higher confidence.
The application and potential of the method is demonstrated using data from the Tampen Area in the Northern North Sea. TOC logs for the Draupne Formation source rock in two wells were computed using well log data. They provided the basis for calibration of the expected seismic response which was used to compute TOC maps for the area. Source rock maturity was modelled using PetroMod for various thermal end member cases which all satisfy observed well calibration data and subsequent expulsion modelling was performed using Statoil’s proprietary QuickVol3D tool (Zwach and Angard, 2007). Deviation of those results to commonly applied averaged TOC data over given stratigraphic gross intervals were evaluated to understand the error being made in case of absence of such advanced investigations. In addition, the possible seismic recognition of source rock maturity as well as petroleum expulsion is discussed.
Løseth, H., Wensaas, L., Gading, M., Duffaut, K., Springer, M., 2011. Can hydrocarbon source rocks be identified on seismic data? Geology 39, 1167–117.
Wensaas, L., Gading, M., Løseth, H., Springer, M., 2011. Source Rock Prediction from Seismic Part I: Links Between Rock Properties and Seismic Attributes. Abstract AAPG Annual Convention and Exhibition, Houston, TX, USA.
Zwach, C., Angard, K., 2007. Stochastic Prospect Charge Evaluation – Old Challenges and New Solutions. Abstract AAPG Hedberg Research Conference, The Hague, The Netherlands.
AAPG Search and Discovery Article #120098©2013 AAPG Hedberg Conference Petroleum Systems: Modeling the Past, Planning the Future, Nice, France, October 1-5, 2012