Development of a Fit-for-Purpose CO2 Injection Model for Carbon Capture, Utilization, and Storage Casing and Tubing Design

Summary The development and application of a fit-for-purpose CO2 injection model (CIM) is presented in the context of a front-end engineering design for a new carbon capture and storage (CCS) project targeting a depleted gas reservoir in the North Sea. The growing trend toward long-term industrial-scale CCS presents challenges for the current industry design capabilities. In conjunction with the wider CCS system design, particular engineering design and integrity assurance requirements must be addressed for the wellbore components. An appropriate equation of state (EOS) that accounts for impurities and multiphase flow conditions is required to predict rapid changes in fluid behavior. With a depleted gas reservoir as the storage target, early-life vs. late-life wellbore conditions can be significantly different. The tubular design workflow was finalized using a CIM deployed via a cloud-based software platform developed in concert with the well engineering design process in an agile manner. Validation of the model was provided by comparison with benchmarks from legacy software. Coupled with drilling and cementing conditions from the well construction phase, the resultant thermal stresses on tubulars, connections, and completion components during gaseous, dense, and multiphase CO2 well operating conditions need to be accurately predicted as they can be significant. Downhole conditions can be affected by cooling from adiabatic expansion and Joule-Thomson effects across chokes, due to wellbore friction and at the sandface. Transient operations during shut-in and restart result in low design case temperatures. Low-probability survival conditions under simulated blowout or leakage scenarios require to be modeled and can result in worst-case temperature qualification requirements for wellbore equipment. Industry work groups have proposed the GERG-2008 EOS as a standard model for CCS operations and well design. However, potential limitations noted in technical literature appear evident from detailed well sensitivity analysis. Potential improvements to the GERG-2008 model as well as requirements for an improved fit-for-purpose EOS are outlined.