Important Info
For full consideration, please submit the required appliation materials to Dr. Jenny Suckale (jsuckale@stanford.edu) with “Post-doc Application” listed in the subject line. We will begin reviewing applications March 1st, 2024 and the position will remain open until filled.
The Department of Geophysics and the Department of Energy Resources Engineering seek a creative individual for a fully-funded, 2-year postdoctoral position to model fluid transport through interconnected fracture networks in sedimentary stacks.
Motivation:
The patterns of fluid migrating through granular media is of fundamental importance for many Earth Science problems including but not limited to hydrocarbon seepage, permafrost destabilization, and volcanic degassing. Observations often suggest that fluids emerge as a distinct, non-dispersed column of fluid. Seepage occurs in spatially distinct areas, indicative of the existence of preferential pathways underneath, but is variable in both time and space. Typically, the seeping fluids share a striking similarity to the hydrocarbons contained within reservoirs directly below the seeps, suggesting a common origin and arduous pathways to the surface. Our goal is to better understand the processes that govern fluid transport in interconnected networks.
Tasks:
The post-doctoral scholar will work on developing and analyzing models that quantify fluid migration along an interconnected network of preferential pathways in sedimentary stacks. The position requires experience in modeling multiphase flow, ideally through both numerical and analytical approaches. The primary advisors for this project are Dr. Jenny Suckale (Stanford, Department of Geophysics) and Dr. Hamdi Tchelepi (Stanford, Department of Energy Resources Engineering).
The position is located in the Doerr School of Sustainability, Stanford University with a target start data in Spring 2024.
- A Ph.D. in geophysics, fluid mechanics, reservoir engineering, mechanical engineering or a similar field is required
- The successful candidate will be a friendly, self-directed individual who is excited about working on collaborative projects
- Has experience developing and calibrating models, and communicates well
- Cover letter
- CV
- Names of three references