TY - JOUR
T1 - Numerical simulation and optimization of CO 2 sequestration in saline aquifers for vertical and horizontal well injection
AU - Zhang, Zheming
AU - Agarwal, Ramesh K.
N1 - Funding Information:
Acknowledgement The financial support of Consortium for Clean Coal Utilization (CCCU) at Washington University in St. Louis is gratefully acknowledged.
PY - 2012/9
Y1 - 2012/9
N2 - With heightened concerns on CO 2 emissions from pulverized-coal (PC) power plants, there has been major emphasis in recent years on the development of safe and economical geological carbon sequestration (GCS) technology. Saline aquifers are considered very attractive for GCS because of their large storage capacity in U. S. and other parts of the world for long-term sequestration. However, uncertainties about storage efficiency as well as leakage risks remain major areas of concern that need to be addressed before the saline aquifers can be fully exploited for carbon sequestration. A genetic algorithm-based optimizer has been developed and coupled with the well-known multiphase numerical solver TOUGH2 to optimally examine various injection strategies for increasing the CO 2 storage efficiency as well as for reducing its plume migration. The optimal injection strategies for CO 2 injection employing a vertical injection well and a horizontal injection well are considered. To ensure the accuracy of the results, the combined hybrid numerical solver/optimizer code was validated by conducting simulations of three widely used benchmark problems employed by carbon sequestration researchers worldwide. The validated code is then employed to optimize the proposed water-alternating-gas injection scheme for CO 2 sequestration using both the vertical and the horizontal injection wells. The results suggest the potential benefits of CO 2 migration control and dissolution. The optimization capability of the hybrid code holds a great promise in studying a host of other problems in GCS, namely how to optimally enhance capillary trapping, accelerate the dissolution of CO 2 in water or brine, and immobilize the CO 2 plume.
AB - With heightened concerns on CO 2 emissions from pulverized-coal (PC) power plants, there has been major emphasis in recent years on the development of safe and economical geological carbon sequestration (GCS) technology. Saline aquifers are considered very attractive for GCS because of their large storage capacity in U. S. and other parts of the world for long-term sequestration. However, uncertainties about storage efficiency as well as leakage risks remain major areas of concern that need to be addressed before the saline aquifers can be fully exploited for carbon sequestration. A genetic algorithm-based optimizer has been developed and coupled with the well-known multiphase numerical solver TOUGH2 to optimally examine various injection strategies for increasing the CO 2 storage efficiency as well as for reducing its plume migration. The optimal injection strategies for CO 2 injection employing a vertical injection well and a horizontal injection well are considered. To ensure the accuracy of the results, the combined hybrid numerical solver/optimizer code was validated by conducting simulations of three widely used benchmark problems employed by carbon sequestration researchers worldwide. The validated code is then employed to optimize the proposed water-alternating-gas injection scheme for CO 2 sequestration using both the vertical and the horizontal injection wells. The results suggest the potential benefits of CO 2 migration control and dissolution. The optimization capability of the hybrid code holds a great promise in studying a host of other problems in GCS, namely how to optimally enhance capillary trapping, accelerate the dissolution of CO 2 in water or brine, and immobilize the CO 2 plume.
KW - Computational fluid dynamics
KW - Genetic algorithm
KW - Geological CO sequestration
KW - Injection well orientation
KW - Water-alternating-gas (WAG) injection
UR - http://www.scopus.com/inward/record.url?scp=84866438069&partnerID=8YFLogxK
U2 - 10.1007/s10596-012-9293-3
DO - 10.1007/s10596-012-9293-3
M3 - Article
AN - SCOPUS:84866438069
SN - 1420-0597
VL - 16
SP - 891
EP - 899
JO - Computational Geosciences
JF - Computational Geosciences
IS - 4
ER -