Modeling the Aliso Canyon underground gas storage well blowout and kill operations using the coupled well-reservoir simulator T2Well
- Author(s): Pan, L;
- Oldenburg, CM;
- Freifeld, BM;
- Jordan, PD
- et al.
Published Web Locationhttps://doi.org/10.1016/j.petrol.2017.11.066
A blowout of the Sesnon Standard-25 well (SS-25; API 03700776) at the Aliso Canyon Underground Gas Storage Facility, first observed on October 23, 2015, eventually resulted in emission of nearly 100,000 tonnes of natural gas (mostly methane) to the atmosphere. Several thousand people were displaced from their homes as the blowout spanned 111 days. Seven attempts to gain pressure control and stop the gas flow by injection of heavy kill fluids through the wellhead failed, a process referred to as a “top kill.” Introduction of drilling mud when a relief well milled through the casing of SS-25 at a depth of ∼8 400 ft (“bottom kill”) succeeded in halting the gas flow on February 11, 2016. We carried out coupled well-reservoir numerical modeling using T2Well to assess why the top kills failed to control the blowout. T2Well couples a reservoir simulation in which porous media flow is described using Darcy's law with a discretized wellbore in which the Navier-Stokes momentum equation implemented via a drift-flux model (Shi et al., 2005) is used to describe multi-phase fluid transport to allow detailed process modeling of well blowouts and kill attempts. Modeling reveals the critical importance of well geometry in controlling flow dynamics and the corresponding success or failure of the kill attempts. Geometry plays a role in controlling where fluids can flow, e.g., when gas flow prevents liquid flow from entering the tubing from the annulus, but geometry also provides the opportunity for dead end regions to accumulate stagnant gas and liquid that can also affect kill attempts. Simulations show that follow-up fluid injections after the main kill attempts likely would have been effective to ensure that gas leakage remains stopped. T2Well is capable of simulating well kills and understanding the mechanisms behind well control failures and successes.