A generalized partial molar volume algorithm provides fast estimates of CO 2 storage capacity in depleted oil and gas reservoirs
Conference Paper
Overview
Overview
abstract
Understanding fluid behavior is critical for the success of any gas injection project into a reservoir whether this is to recover additional oil or to sequester and store greenhouse gases including CO 2. Fluid phase behavior of mixtures resulting from the injected streams and reservoir fluids determine the design of production and injection schemes and facilities. This manuscript presents an analytical method to estimate the ultimate CO 2 storage capacity in depleted oil and gas reservoirs by implementing a volume-constrained thermodynamic equation of state (EOS) and using average reservoir pressure and fluid compositions. This method can handle all impurities contained in the injection stream by defining and applying a generalized partial molar volume calculation. The developed algorithm provides fast and thermodynamically consistent estimates of storage capacity and enables the selection of candidate storage reservoirs, schedule injection strategies, and design of surface facilities including compressors and tubulars. Results from this analytical method are in excellent agreement with those from a commercial reservoir simulator. A total of 24 numerical runs were conducted to evaluate scenarios with large pressure and compositional gradients while injecting. The reservoir used was heterogeneous, had a five-spot injection pattern and local grid refinement in the neighborhood of wells. CO 2 storage capacity was predicted with an average difference of 1.26 wt% between analytical and numerical methods; the average oil, gas, and water saturations at the end of injection were also matched within 2.35% difference. Additionally, the analytical algorithm performed several orders of magnitude faster than numerical simulation, with an average of 5 seconds per run.
