1887
  1. Home
  2. Conferences
  3. Conference Proceedings
  4. 80th EAGE Conference and Exhibition 2018
  5. Conference paper

Abstract

Summary

Digital Rock Analysis is an important rock characterisation technique that enables the extraction of many relevant petrophysical parameters via a combination of experimental and computational methods. Fluid flow simulations deployed on top of such geometrical representations -- either mesh, lattice or network based -- can estimate oil recovery parameters as part of oil exploration and production. In this work, we present a cloud-based Digital Rock Analysis platform for reservoir rock characterisation and evaluation of oil recovery strategies. We illustrate how one can run a Digital Rock Analysis workflow on a representative reservoir rock sample in a matter of minutes using a laptop equipped with a web browser.

© EAGE Publications BV
Loading

Article metrics loading...

/content/papers/10.3997/2214-4609.201800779
2018-06-11
2024-04-19

  • From This Site

    /content/papers/10.3997/2214-4609.201800779
    dcterms_title,dcterms_subject,pub_keyword
    -contentType:Journal -contentType:Contributor -contentType:Concept -contentType:Institution
    10
    5
Loading full text...

Full text loading...

References

  1. Hoshen, J., Berry, M. W. and MinserK. S.
    [Hoshen 1997] . “Percolation and Cluster Structure Parameters: The Enhanced Hoshen-Kopelman Algorithm.” Physical Review E56.2 (1997): 1455.
     [Google Scholar]
  2. Falcão, Alexandre X., Stolfi, Jorge and LotufoRoberto De Alencar
    [Falcão 2004] . “The Image Foresting Transform: Theory, Algorithms, And Applications.” IEEE Transactions on Pattern Analysis and Machine Intelligence26.1 (2004): 19–29.
     [Google Scholar]
  3. Mell, Peter, and GranceTim
    [Mell 2011] . “The NIST definition of cloud computing.” (2011).
     [Google Scholar]
  4. Andrä, Heiko, et al.
    [Andrä 2013a] “Digital rock physics benchmarks—Part I: Imaging and segmentation.” Computers & Geosciences50 (2013): 25–32.
     [Google Scholar]
  5. [Andrä 2013b] “Digital rock physics benchmarks—Part II: Computing effective properties.” Computers & Geosciences50 (2013): 33–43.
     [Google Scholar]
  6. Muljadi, Bagus P., et al.
    [Muljadi 2015] DOI: 10.17612/P73W2C
     https://doi.org/10.17612/P73W2C
  7. [Engel 2017] Engel, Michael, et al. “Nanoscale Flow Chip Platform for Laboratory Evaluation of Enhanced Oil Recovery Materials.” SPE Annual Technical Conference and Exhibition. Society of Petroleum Engineers, 2017.
     [Google Scholar]
  8. Giro, Ronaldo, et al.
    [Giro 2017] “Adsorption energy as a metric for wettability at the nanoscale.” Scientific Reports7 (2017).
     [Google Scholar]
http://instance.metastore.ingenta.com/content/papers/10.3997/2214-4609.201800779
Loading
Cloud-Enabled Digital Rock Analysis for Enhanced Oil Recovery
Conference Proceedings 2018, 1 (2018); https://doi.org/10.3997/2214-4609.201800779
/content/papers/10.3997/2214-4609.201800779
/content/papers/10.3997/2214-4609.201800779
Loading

Data & Media loading...

Most Cited This Month Most Cited RSS feed

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