Can One-Run-Fixed-Arrhenius Kerogen Analysis Provide Comparable Organofacies Results to Detailed Palynological Analysis? A Case Study from a Prospective Mississippian Source Rock Reservoir (Bowland Shale, UK)

2019 
Organofacies analysis, a fundamental component within source rock appraisal based on the study of kerogen within a source rock, is typically produced from microscopy (palynological) and geochemical (kerogen kinetic) data, both of which are costly to acquire. One-Run-Fixed-Arrhenius (ORFA) kerogen kinetic analysis based on Rock–Eval pyrolysis offers a substantially cheaper kinetic dataset. Here, ORFA and palynological analyses are compared in organofacies characterization of a prospective Mississippian source rock reservoir (Bowland Shale, UK). Two-end-member organofacies were determined based on the abundance of the 56 kcal/mol activation energy peak derived from ORFA data: absence ( 15%) indicating ‘organofacies B’ containing the highest proportion of sporomorphs (Type II kerogen). A mud-dominated slope setting for the rock reservoir was also used to test the accuracy of organofacies analysis in determining depositional environment. Organofacies A found within lithofacies deposited from dilute waning density flows and hemipelagic suspension settling occurred between shelf edge, slope and basin. Organofacies B found within lithofacies deposited from dilute waning density flows, and low-strength cohesive debrites occurred only within the lower slope. This study demonstrates that ORFA kerogen kinetic analysis provides comparable net results to palynological analysis, enabling cheaper and faster organic characterization during initial source rock appraisal. However, caution must be exercised in drawing interpretations as to biological source(s), organic matter mixing and preservation state(s) without additional investigation using data from detailed palynological analysis.
    • Correction
    • Source
    • Cite
    • Save
    • Machine Reading By IdeaReader
    81
    References
    0
    Citations
    NaN
    KQI
    []