Joint Rock Physics Inversion and Basin Modeling for Comprehensive Source Rock Characterization

Jiayuan Huang, Tapan Mukerji

This study presents an integrated workflow that combines statistical rock physics inversion with Monte Carlo basin modeling to comprehensively quantify source rock properties and their uncertainties. First, well-log and seismically-derived elastic properties are used in a statistical rock physics inversion to estimate porosity, kerogen content, and mineral fractions. These posterior distributions capture key compositional variability but provide limited constraint on thermal maturity due to weak sensitivity of elastic properties to thermally controlled changes. To address this limitation, inversion-derived properties are propagated through forward burial and thermal history simulations using Monte Carlo basin modeling. Uncertain geological and kinetic inputs, including geothermal history, erosion, and kerogen kinetics, are sampled to generate probabilistic predictions of vitrinite reflectance, transformation ratio, temperature, and pore pressure. Application to the Goldwyer III source rock in the Canning Basin demonstrates that the integrated workflow reduces uncertainty in thermal maturity while maintaining consistency with geochemical indicators and measured temperature. The results reveal spatial variability in source rock quality and maturity that is not evident from elastic properties alone. This work establishes a practical, uncertainty-aware framework that couples geological, geophysical, geochemical, and geomechanical processes, ultimately improving confidence in hydrocarbon generation assessment and supporting risk reduction in exploration, particularly in frontier or data-limited settings.