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The AAPG/Datapages Combined Publications Database

AAPG Special Volumes

Abstract


Memoir 112: Imaging Unconventional Reservoir Pore Systems, 2016
Pages 185-231
DOI: 10.1306/13592022M1123698

Chapter 10: 2-D Pore Architecture Characterization of a Carbonate Mudrock Reservoir: Insights from the Mid-Continent “Mississippi Lime”

Beth Vanden Berg, G. Michael Grammer

Abstract

This study shows examples of how fundamental relationships between pore shape, porosity, permeability, and acoustic response differ in carbonate mudrocks with micro- to picoporosity (<62 μm diameter) compared to conventional carbonates with primarily macroporosity (256–4 mm diameter). Quantitative data show that some positive correlations exist between porosity and permeability, similar to those observed in conventional carbonates. However, several expected relationships between properties, such as pore shape and laboratory-measured porosity and permeability, are not readily apparent and appear to be complicated by the internal pore architecture coupled with diagenetic alterations and a multiscale fracture network. Additionally, there is a significant shift in measured sonic velocity relative to values calculated from empirically derived equations that are applicable to conventional carbonates. Deviations from expected quantitative data trends can be partially explained through qualitative observations of the pore types and internal pore geometries. Visual observations show how diagenesis can increase the complexity of the internal pore network by nonsystematically subdividing the pores. When correlated to facies, the internal pore geometry partially clarifies deviations to expected relationships between quantitative pore architecture measurements, porosity, and permeability. Although there is an added level of complexity in the pore architecture of carbonate mudrocks, this study shows there are fundamental relationships that exist between the pore architecture, pore shape, porosity, permeability, acoustic response, facies, and sequence stratigraphic framework with variable levels of predictability that, when used as an integrated data set, can be used to enhance the predictability of key petrophysical properties within these types of reservoir systems.


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