A method for assigning pre-exponential factors for kerogen kinetics, calibrated with Easy%RoDL, and comparison with EASY%Ro

Abstract

Modeling hydrocarbon-generation processes requires reliable kinetic models for the thermal decomposition of kerogens. To improve confidence and accuracy in modeling of generation, this study employs data from both natural and laboratory maturation to quantify thermal stress and strain for kerogens in 11 source-rock data sets. The method yields kinetic parameters (pre-exponential factor and Ea) for hydrocarbon generation that are constrained to make accurate predictions about thermal stress (quantified here as Ro-equivalent) and thermal strain (quantified as Hydrogen Index) under both laboratory and natural conditions. Methods for converting Tmax values to Ro-equivalents were examined and are discussed briefly. Vitrinite reflectance values were calculated at geological heating rates using the Easy%RoDL kinetic formulation, and were then compared with previous results obtained using EASY%Ro. The large differences observed between the EASY%Ro and Easy%RoDL evaluations are attributed to the differences in the pre-exponential factors in those two Ro-kinetic formulations. Understanding this relationship gives us a way to choose kinetic parameters for hydrocarbon generation that will work well for modeling under geological conditions. The single best A factor for hydrocarbon-generation when using EASY%Ro is 1e13 s−1 , while that for Easy%RoDL is 2e14 s−1 . The minor variation in A factors observed within each of the data sets may or may not be real. Using these results and concepts, more reliable hydrocarbon-generation windows in terms of either Ro-equivalent or Transformation Ratio can be achieved and cross-correlated. These results thus have the potential to increase both the accuracy of hydrocarbon-generation modeling, and the confidence in its results. Cited as: Waples, D. W., Yang, S. A method for assigning pre-exponential factors for kerogen kinetics, calibrated with Easy%RoDL, and comparison with EASY%Ro. Advances in Geo-Energy Research, 2023, 7(1): 1-6. https://doi.org/10.46690/ager.2023.01.01