Abstract
During production start-ups and shutdowns, the ASA (Annulus Seal Assembly) is subjected to compression and tension cycling loads, featuring the normal condition loads, and for this reason, demanding an endurance qualification procedure. Furthermore, in a real well, these loads are not applied separately. As a result, the ASA is always under cyclic and combined loads that can affect its sealing capacity. In addition to the normal condition loads, some events may be characterized as an extreme event, in accordance with the API Standard 17G (Design and Manufacture of Subsea Well Intervention Equipment).
This paper will present the methodology and description of the test performed to evaluate the performance of ASA under extreme conditions, which falls beyond the scope of the API SPEC 17D (Specification for Subsea Wellhead and Tree Equipment) requirements and normal condition loads definition, in order to replicate the load conditions of a subsea well considering an extreme event. A full-scale experimental test facility has been built in a controlled laboratory environment to evaluate the behavior of the ASA under these extreme loads. The test facility was built to simulate the real conditions of the well, reproducing cyclic and combined axial and pressure loads. In this test facility, the ASA is tested together with the High-Pressure Housing and Casing Hanger, thus evaluating the whole subsea wellhead system.
The results showed downward CH displacement due to ballooning effect at 4,500 and 5,000 psi, as pressure end load increases, a significant upward displacement is seen before assembly failure, indicating the limit if the ASA. The test enabled the creation of a performance envelope that exceeds the parameters of the API 6A PR-2F and API 17D testing procedure. The device not only enhance the safety and efficiency, but also fosters the development of novel testing methodologies and equipment for the petroleum industry. With its ability to accurately assess equipment performance, the facility stands as a significant asset, empowering operators to make informed decisions and optimize their production processes.
