1887
2nd Australasian Exploration Geoscience Conference: Data to Discovery
  • ISSN: 2202-0586
  • E-ISSN:

Abstract

Summary

Predicting the mineralogical composition of shales is crucial for drilling operations related to hydrocarbon exploration/production as well as for the assessment of their sealing capacity as hydrocarbon or CO barriers. Despite the importance of inferring the mineralogical composition, few methods have been developed.

A regional smectite-rich seal with a thickness of more than 1 km is hindering hydrocarbon exploration in the Northern Carnarvon Basin, North West Shelf of Australia. The complex structures of the channelised oil and gas fields in the area make it necessary to drill deviated wells through that seal. The maximum deviation angle at which successful drilling is possible strongly depends on the fraction of swelling clay minerals in shale composition, in particular, on the smectite content. Here we introduce a workflow to infer shale composition that combines seismic data, well logs, and laboratory measurements. It is applied to the Duyfken 3D seismic survey in the central part of the Northern Carnarvon Basin. Results of the interpretation are verified against laboratory XRD measurements from a test well that was not used for interpretation. The results match the test data well within the determined uncertainty bounds. Previously unpublished knowledge of shale mineralogical composition allows for a further analysis of the rock physics properties such as hydraulic permeability which is crucial for reservoir engineering and fluid flow simulations for CO sequestration and nuclear waste disposal.

Loading

Article metrics loading...

/content/journals/10.1080/22020586.2019.12073179
2019-12-01
2026-01-21
Loading full text...

Full text loading...

References

  1. Beloborodov, R., Pervukhina, M., and Lebedev, M., 2018, Compaction Trends of Full Stiffness Tensor and Fluid Permeability in Artificial Shales. Geophysical Journal International212, 1687-93.
  2. Bjorlykke, K., 2014, Relationships between Depositional Environments, Burial History and Rock Properties. Some Principal Aspects of Diagenetic Process in Sedimentary Basins. Sedimentary Geology301, 1-14.
  3. Dempster, A.P., Laird, N.M., and Rubin, D.B., 1977, Maximum Likelihood from Incomplete Data Via the Em Algorithm. Journal of the royal statistical society. Series B (methodological), 1-38.
  4. Mesri, G. and Olson, R.E., 1971, Mechanisms Controlling the Permeability of Clays. Clays and Clay Minerals19.
  5. Rüger, A., 1997, P-Wave Reflection Coefficients for Transversely Isotropic Models with Vertical and Horizontal Axis of Symmetry. Geophysics62, 713-22.
  6. Thomsen, L., 1986, Weak Elastic-Anisotropy. Geophysics51, 1954-66.
  7. Yang, Y.L. and Aplin, A.C., 2010, A Permeability-Porosity Relationship for Mudstones. Marine and Petroleum Geology27, 1692-97.
  8. Zou, H. and Hastie, T., 2005, Regularization and Variable Selection Via the Elastic Net. Journal of the Royal Statistical Society: Series B (Statistical Methodology)67, 301-20.
/content/journals/10.1080/22020586.2019.12073179
Loading
  • Article Type: Research Article
Keyword(s): mineral composition; permeability; quantitative interpretation; seal; shale; smectite
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