Programmed pyrolysis (Rock-Eval) data and shale paleoenvironmental analyses: A review

Abstract

We use public-domain data from programmed pyrolysis, collected using Rock-Eval or similar apparatuses, to illustrate the utility and challenges of using this method for paleoenvironmental analyses. These data are widely available and commonly collected and analyzed for a variety of purposes in the petroleum industry in the fields of paleo-oceanography and paleoclimate research and elsewhere. We show how factors such as sample condition, mineralogy, organic content, and others can influence the results, leading to potential interpretational complications. We also evaluate ways that the data can be plotted to maximize their utility for interpretation purposes. Four types of organic matter are commonly identified based on programmed pyrolysis results. Type I organic matter has a high (e.g., [Formula: see text]) hydrogen index (HI), is oil-prone and is commonly assumed to represent lacustrine depositional settings. Type II organic matter is also oil-prone (i.e., having an HI between 350 and 700) but is commonly assumed to represent marine organic matter. Type III organic matter has a lower HI ([Formula: see text]), will tend to generate gas, and is commonly assumed to represent terrigenous (e.g., land plants) organic matter. Type IV organic matter has very low HI values and is associated with nongenerative (i.e., inert) organic matter. We show that these simple associations between organic matter type and paleoenvironment were not always valid. Preburial degradation of the organic matter and mixing of different organic matter types are two possibilities that can lead to erroneous paleoenvironmental interpretations. Furthermore, the programmed pyrolysis results characterize the present composition of the organic matter which, especially at high thermal maturities (e.g., dry gas window), can be significantly different to that of the original organic matter. Other types of advanced geochemical and sedimentologic analyses should be integrated with the programmed pyrolysis results during their interpretation.