Classification of Total Storage Resources and Storage Coefficients

Publication Overview

The CO2 Storage Resources Management System (SRMS) is a classification scheme to quantify, classify and categorise CO2 storage resources. It comprises ‘total storage resources’, which are understood as maximum (theoretical) storage quantities that could ever be accommodated in the subsurface. Comprising maximum mobile CO2 in structural/stratigraphic traps, maximum residually trapped CO2 in other parts of the formation, and maximum dissolution potential in remaining formation water. ‘Storable quantities’ are understood as accessible from one or several current or future projects. It is the sum of capacity, contingent and prospective resources. The concept of ‘storage coefficient’ ‘E’ is the ratio of the subsurface volume of CO2 storable quantities to either the total storage resources or the pore volume. The calculation is arguably complicated as E is impacted by lithological heterogeneity, trapping structures, boundary conditions, injection rates, well spacing, fluid properties etc. Due to its complexity, there is much controversy on how to estimate E, with some arguing it should not be used at all and that reservoir simulation is a better path. However, estimates for E are used in most regional mapping studies. This study explores storage resource classification schemes and their evolution in understanding, the calculation of storage resources and the storage co-efficient. This is explored in terms of calculating E for CO2 storage sites, through flow modelling and analytical solutions.

Publication Summary

• The classification of storage resources and associated schemes have become more complex over time and more aligned to the requirements of operational storage with the SRMS becoming the industry standard.
• Storage coefficients are vital for quantifying accessible storage resources, standard methodologies have been presented and examples of usage within national and international databases. 97% of global storage is of a prospective nature and having quick screening criteria are useful in initial basin screening.
• Data from CO₂ storage sites can be used to calculate storage efficiency through time by measuring plume area on time-lapse seismic data. These results can then be compared to numerical models and analytical approximations.
• Numerical simulations were run with key parameters identified through publicly available modelling studies with storage coefficients evaluated for each case.
  • Structure and injection rates have a significant influence on storage coefficients
  • The evolution of the storage coefficient through a 30 year injection period and 70 year post injection period was modelled and in the case of a dipping aquifer the storage coefficient peaks at 20-30 years and then gradually reduces whereas a structural closure sees a more stable post injection storage coefficient.
  • Water production did not impact the storage coefficient, but modelling an open system may have impacted the results.
  • Hysteresis may not impact storage coefficient significantly, but it does cause the distribution of CO₂ with more trapped in deeper layers of the reservoir increasing storage security.
• Analytical models from the literature have been modified to estimate storage coefficients and compared to modelled and data from the storage sites. At first pass they give a quick and easy estimate for lower stages of development but results slightly underperform. Another approach using dimensionless variables to emulate or build upon some of the numerical modelling work may provide a way to estimate storage coefficients for a cheaper cost than using full dynamic simulations.