Improving fractured carbonate-reservoir characterization with remote sensing of beds, fractures, and vugs
Author(s) -
Daniel Kurtzman,
Joseph A. El Azzi,
F. Jerry Lucia,
Jerome A. Bellian,
Christopher K. Zahm,
Xavier Janson
Publication year - 2009
Publication title -
geosphere
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.879
H-Index - 58
ISSN - 1553-040X
DOI - 10.1130/ges00205.1
Subject(s) - geology , outcrop , carbonate , carbonate rock , aquifer , permeability (electromagnetism) , reservoir modeling , mineralogy , geomorphology , petrology , dissolution , geochemistry , petroleum engineering , geotechnical engineering , sedimentary rock , groundwater , metallurgy , genetics , chemistry , materials science , membrane , biology
Many key aquifers and oil reservoirs are in carbonate rocks. Understanding the flow behavior within this commonly complex pore space requires new perspectives and technology in order to improve carbonate aquifer and reservoir characterization. Dissolution of carbonates is related to flow; hence, quantifying the size of dissolution vugs on carbonate outcrops can help characterize controls on flow, namely matrix permeability and fracture connectivity. LIDAR (light detection and ranging) scans, combined with high-resolution photography, enable us to both measure vugs' areas and assess spatial relationships between vugs, beds, and fractures. We developed a method of obtaining and interpreting necessary vug, bed, and fracture data on the basis of these technologies. Application of this method on a Cretaceous Edwards Group outcrop in Texas (United States) revealed a significant correlation between the relative vug area of beds obtained remotely and air permeability measured in plugs extracted from these beds (R2 = 0.94, P = 0.001). The total area of vugs intersected by fractures was used to establish a probability density function of fracture lengths that can improve flow modeling of the reservoir. These findings show the potential of using LIDAR and photo images in reservoir characterization by data analysis of geological features, in addition to their use for accurate mapping.
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