Transcripción del resumen del autor. As conventional resources for liquid fuels in the world become scarcer and less secure, there is a need to develop other feasible resources. Oil shale is a massive resource local to the United States for potential liquid fuel production. In situ oil shale processing strategies are attractive for reduced environmental impact (in comparison to surface production operations) and provide access to resources inaccessible to mining. The efficiency of feasible and economical development is greatly enhanced with predictive power that is both efficient and accurate. However, modeling thermal subsurface processes is a complex problem, involving many simultaneously occurring physical phenomena. In this study, an oil reservoir simulator capable of representing thermal processes was used to explore the impact and interplay of various pertinent parameters to an in situ oil shale processing strategy. A statistical methodology was developed using designed factorial experiments (simulations) to expose probable dominating parameters, including synergistic or diminutive interactions between parameters. An empirical regression model or response surface was built from the simulated data. Monte Carlo simulations were used to characterize the response surface and to estimate the uncertainty in predicted oil recovery results because of the explored parameters.

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