Inversion of source rock hydrocarbon generation kinetics from Rock-Eval data

• Published in: Fuel (Guildford) 2017-04, Vol.194, p.91-101
• Main Authors: Chen, Zhuoheng, Liu, Xiaojun, Guo, Qiulin, Jiang, Chunqing, Mort, Andy
• Format: Article
• Language: English
• Subjects: Activation energy; Case studies; Data processing; Devonian; History; Hydrocarbons; Inversion; Kerogen; Kinetic modeling; Kinetics; Mathematical models; Modelling; Petroleum; Petroleum hydrocarbons; Pyrolysis; Reaction kinetics; Reconstruction; Rocks; Sedimentary basins; Shale; Temperature requirements; Tmax-HI plot
• ISSN: 0016-2361; 1873-7153
• DOI: 10.1016/j.fuel.2016.12.052

•Numerical inversion for estimating petroleum generation kinetic parameters from Rock-Eval data.•A complementary tool to characterize the thermal decomposition of source rock.•Improved spatial resolution of source rock generation kinetics.•Useful for less well-known petroleum systems where no information on generation kinetics is available. Basin and petroleum system modeling requires source rock kinetics as input for the reconstruction of hydrocarbon generation history. For less well-studied petroleum systems, there may be little information on petroleum generation kinetic parameters publically available; thus, an analog of representative source rock kinetics must be chosen from available kinetics databases. Recent studies suggest that source rock kinetics may vary considerably even when they contain the same type of kerogen. Thus, kinetic parameters from analog basins/source rocks may lead to erroneous results in petroleum generation history reconstruction. Rock-Eval data contain information about source rock kinetics, and can be used to improve the kinetic model in petroleum system modeling. However, the kinetic information in Rock-Eval data is not in the form of activation energies and frequency factors required to solve the temperature dependency of reaction rate in the Arrhenius equation. This article proposes a kinetic inversion method so that the analogous kinetic model chosen by the user can be improved based on Rock-Eval data of the targeted source rock. We demonstrate the method using a synthetic dataset in a case study for method validation and its application to real source rock evaluation for examples from the Devonian Duvernay Shale in the Western Canada Sedimentary Basin (WCSB).