Over the next two years, Jean Prevost and postdoctoral researcher Bruno Huet will complete the implementation of a geochemical module in Dynaflow that includes the constituents of cement. Initially the model will be validated using data for calcium leaching from a European study. The model will incorporate the parameters obtained from collaborators at LANL and LLNL (see above), if that work is successful; if not, we will use Dynaflow to simulate our experimental results and refine the parameters ourselves. The multiphase flash calculation will further be modified to allow for pressure and temperature changes as the plume rises toward the surface, including thermal effects.
Once the basic geochemistry is in place, Bruno Huet and Jean Prevost will simulate attack on cement by carbonated brine rising through an annular gap around the cement in a well. Multiple leakage scenarios will be examined, including the impacts of varying brine composition, initial gap width, and depth at which the leak originates. The simulations will also be extended to include corrosion of the steel casing in the well.
In summary, at the end of about 2 years from today, we will be able to put bounds on the risk of leakage under unfavorable conditions (brine in a sandstone formation encountering a pre-existing annular gap in typical cement). Should we discover that the brine is quickly neutralized as it flows through the gap, so that the leak is not significantly expanded over the course of a century, then the behavior of the wells under more benign conditions is academic. On the other hand, if our simulations indicate that leaks worsen at a significant rate in sandstone formations, then we will need to see whether there is any such risk under more favorable circumstances (such as limestone formations). That information will emerge from the thesis work to begin this fall; the results will start flowing in about two years, and final results will be available by year 4 or 5 (that is, by the end of the project).
The results from the combined experimental and geochemical modeling should predict the most important variables affecting leakage rates within a well. This information will be combined with statistical information about well properties to provide input for the semi-analytical and coarse resolution models developed by Mike Celia and colleagues for risk assessment (see below).