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Carbonates and Evaporites

, Volume 15, Issue 1, pp 49–80 | Cite as

Subsurface arbuckle group (cambro-ordovician) in the Bowman #4 Well of the Wilburton field in the Arkoma Basin, Oklahoma: Depositional facies, diagenetic signatures, petrophysical aspects, and economic potential

  • Blanca Y. Ching
  • Gerald M. Friedman
Article

Abstract

Detailed petrographic and petrophysical analyses were performed on a core section of the Nicor #4 Bowman Well, Arkoma Basin, Oklahoma. The studied interval represents the Cambro-Ordovician Arbuckle Group. Petrographic analyses of core samples distinguish six lithofacies. They are as follows from the bottom to the top of the studied core: (1) Quartzose dolostone, (2) conglomeritic dolostone, (3) brecciated dolostone, (3a) crackle breccia, (3b) dissolution-collapse breccia, (4) oolitic dolostone, (5) stylolitic dolostone, and (6) stromatolitic dolostone. Diagenetic evolution has affected the petrophysical properties of these different lithofacies. The diagenetic history of the selected section records early to late dolomitization, stylolitization, dedolomitization (calcification), and silicification. Petrophysical analyses employing mercury porosimetric techniques determine three distinct petrofacies. These petrofacies are as follow: (1) low porosity and high recovery efficiency, (2) low porosity and low recovery efficiency, and (3) high porosity and high recovery efficiency. Based on petrophysical analyses, the best reservoir candidate is the crackle breccia petrofacies because it has intermediate porosity and high recovery efficiency values, plus this lithofacies is bounded by strata with low porosity and recovery efficiency values (impermeable layer).

The Arbuckle Group carbonates were uplifted and subaerially exposed, which, led to the development of an unconformity surface. Consequently, karstification developed and modified various petrophysical properties of the core.

Keywords

Dolomite Lithofacies Dolomitization Stylolite Petrophysical Property 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer 2000

Authors and Affiliations

  • Blanca Y. Ching
    • 1
    • 2
  • Gerald M. Friedman
    • 1
    • 2
  1. 1.Brooklyn College and Graduate School of the City University of New YorkBrooklynUSA
  2. 2.affiliated with Brooklyn College, Rensselaer Center of Applied GeologyNortheastern Science Foundation, Inc.TroyUSA

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