Abstract
Carbon dioxide (CO2) capture and storage (CCS) is presented as an alternative measure and promising approach to mitigate the large-scale anthropogenic CO2 emission into the atmosphere. In this context, CO2 sequestration into depleted oil reservoirs is a practical approach as it boosts the oil recovery and facilitates the permanent storing of CO2 into the candidate sites. However, the estimation of CO2 storage capacity in subsurfaces is a challenge to kick-start CCS worldwide. Thus, this paper proposes an integrated static and dynamic modeling framework to tackle the challenge of CO2 storage capacity in a clastic reservoir, S1A filed, Masila basin, Yemen. To achieve this work's ultimate goal, the geostatistical modeling was integrated with open-source code (MRST-CO2lab) for reducing the uncertainty assessment of CO2 storage capacity. Also, there is a significant difference between static and dynamic CO2 storage capacity. The static CO2 storage capacity varies from 4.54 to 81.98 million tons, while the dynamic CO2 simulation is estimated from 4.95 to 17.92 million tons. Based on the geological uncertainty assessment of three ranked realizations (P10, P50, P90), our work was found that the upper Qinshn sequence could store 15.64 Million tons without leakage. This result demonstrates that the potential of CO2 utilization is not only in this specific reservoir, but the further CO2 storage for the other clastics reservoirs is promising in the Masila Basin, Yemen.
Integrated static modelling and dynamic simulation framework for CO2 storage capacity in upper Qishn Clastics, S1A reservoir, Yemen
