Borehole imaging challenges and added value in fracture reservoir characterisation

M. Al-Rashdi*, M. Al-Raisi, F. Knap, S. Bulushi, F. Al Jahwari

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)


Borehole Image logging (BHI) are becoming very essential tools for fracture reservoir characterization. These tools physically detect fractures and measure fracture properties (orientation, dipping magnitude, etc.,). This paper provides an overview of some challenges in interpreting image log data from conventional fractured reservoirs, heavy oil, tight gas and unconventional fractured reservoirs. The papers also highlight causes of the match and the mismatches between core and image log data from different reservoirs. Most of the mismatches and discrepancies between core and image logs result from: 1) lack of resistivity (conductivity) contrast between host rock and fracture fill; 2) size of fractures, 3) overall image and core quality; 4) hydrocarbon and fluid impact on images. The greatest degree of mismatch between core vs. BHI fracture counts was observed in tight gas reservoirs and heavy oil fracture reservoir analysis. In summary, core calibration and proper understanding of image interpretation pitfalls associated with different reservoir types is important for better understanding vertical and lateral fracture connectivity and modelling.

Original languageEnglish
Title of host publicationEAGE Borehole Geology Workshop
Subtitle of host publicationOptimising the Use of Your Borehole Image Data
PublisherEAGE Publishing BV
ISBN (Electronic)9789462820371
Publication statusPublished - 2014
EventEAGE Borehole Geology Workshop: Optimising the Use of Your Borehole Image Data - Dubai, United Arab Emirates
Duration: Oct 12 2014Oct 15 2014


OtherEAGE Borehole Geology Workshop: Optimising the Use of Your Borehole Image Data
Country/TerritoryUnited Arab Emirates

ASJC Scopus subject areas

  • Geotechnical Engineering and Engineering Geology
  • Computer Science Applications
  • Computer Vision and Pattern Recognition


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