(363a) Relationship Between Kinetic and Flow Parameter Representations in Complex in-Situ Reactive Processes

Modeling reactive-transport processes is complex because it is necessary to calculate heat transfer, multicomponent/multiphase fluid flow, thermodynamics, reaction kinetics, and geomechanics, all models which may have continuously changing parameters. Some examples of these processes are in-situ combustion, pyrolysis, or gasification and CO2 sequestration with geochemical reactions. In this study a novel statistical approach has been implemented to understand the interdependences between reaction and flow parameters.

The approach is applied to in-situ oil shale pyrolysis. The appropriate molecular representation of kerogen, the insoluble solid hydrocarbon in oil shale, is highly uncertain due to its complex nature and variableness across resources. Component lumping schemes have different levels of detail, and the appropriate level of detail is debatable at large scales. Due to the complex nature of kerogen the reaction kinetics of conversion to products are uncertain. The appropriate representation of relative permeability is also a major uncertainty, and is often approximated. Sensitivities of simulated results to these parameters and their interactions are compared using fractional and full factorial experimental designs. Simulations were run with STARS, a thermal reservoir simulator created by CMG.

Ranges of activation energies in hydrocarbon cracking reaction schemes were tested, and it was discovered that specific reaction parameter combinations affect numerical behavior of the simulations. The distance between heating wells and producer wells is a crucial parameter for a successful processing strategy. Heat of reaction for kerogen pyrolysis is insignificant compared to the heat supplied. Relative permeability representation, activation energy distribution for kerogen pyrolysis, and activation energies for kerogen conversion and light oil cracking are dominant parameters.

The statistical approach described exposed parameters that dominate this complex process. Efforts for fundamental understanding and successful production strategies can focus on the most dominant parameters. The statistical methods applied to oil shale pyrolysis can be applied to other complex reactive-transport processes.