1887

Abstract

Summary

Routine core analysis (RCA) for Reservoir Quality (RQ) prediction comprises a collection of measurements acquired with different analytical techniques, which does not include operator-bias evaluation, or integration of continuous sedimentological core description with spot measurements on plugs and thin sections. RCA data rarely have verified uncertainty specifications, thus hampering statistically-rigorous extrapolation of spot measurements such as petrographic description, to the entire reservoir volume. Petrographic analysis gives insight into the controls on RQ through unravelling the diagenetic fingerprint that shapes the eventual porosity and permeability in the reservoir. Because thin-section analysis is time consuming and costly, protocols for selection of representative thin sections should aim at maximizing information obtained from small data sets, so as to minimize costs and prevent unnecessary destruction of core material. This paper presents a flexible protocol for representative thin-section selection based on evaluation of RCA data (i.e., poro-perm and grain-density plug measurements), illustrated on a core of a Carboniferous fluvial sandstone reservoir. The results of the petrographic analysis are interpreted in terms of their relation with sedimentological and geochemical signatures, and it is demonstrated that application of the protocol highly increased the RCA data value which to date merely served as petrophysical indicators.

Loading

Article metrics loading...

/content/papers/10.3997/2214-4609.201801136
2018-06-11
2020-07-05
Loading full text...

Full text loading...

References

  1. Pettijohn, F.J., Potter, P.E. and Siever, R.
    [1973] Sand and Sandstones. Springer-Verlag, Berlin, 617 pp.
    [Google Scholar]
  2. Van Buggenum, J.M. and Den Hartog Jager, D.G.
    [2007] Silesian. In: Wong, Th.E., Batjes, D.A.J. and de Jager, J. (Eds.) Geology of the Netherlands. Royal Academy of Arts and Sciences, 43–62.
    [Google Scholar]
  3. Weltje, G.J., Bloemsma, M.R., Tjallingii, R., Heslop, D., Rohl, U. and Croudace, I.W.
    [2015] Prediction of geochemical composition from XRF-core-scanner data: A new multivariate approach including automatic selection of calibration samples and quantification of uncertainties. In: Rothwell, R.G. and Croudace, I.W. (Eds.) Micro-XRF Scanning of Sediment Cores. Developments in Paleoenviron-mental Research17, 507–534.
    [Google Scholar]
  4. Weltje, G.J. and Tjallingii, R.
    [2008] Calibration of XRF core scanners for quantitative geochemical analysis of sediment cores: principles and applications. Earth & Planetary Science Letters, 274, 423–438.
    [Google Scholar]
http://instance.metastore.ingenta.com/content/papers/10.3997/2214-4609.201801136
Loading
/content/papers/10.3997/2214-4609.201801136
Loading

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