10:45 〜 11:00
[HSC04-07] Numerical Analysis of Self-potential Change Related to CO2 Geological Storage and Leakage
キーワード：CO2地中貯留、CO2漏洩、数値シミュレーション、地球物理モニタリング、自然電位、ジオバッテリー
Injecting oxidizing substance such as CO2 in the deeper formation causes self-potential (SP) changes at the metallic well casing due to a mechanism known as “geobattery” (Bigalke and Grabner, 1997). Previous field tests found observable SP increase around the wellhead in association with CO2 injection due to geobattery mechanism at some onshore sites (Nishi and Ishido, 2022), and a monitoring at an offshore site, Tomakomai CCS project site in Japan found a few hundred higher SP at the directional injection wells than that at the observation wells out range of the injected CO2 (Horikawa, 2022; Kano et al., 2022). These results indicate that monitoring such SP changes can be useful method to detect a CO2 breakthrough and/or a leakage along the well in the CO2 geological storage site.
In this study, numerical analyses were conducted to investigate what range of the SP change is expected for variety of settings of CO2 geological storage and leakage. Simple geological model of the combination of a reservoir and a thick seal was built for the analyses. Two vertical wells were modelled; one is the injection well and the other is the observation well which is located 1,000 m away from the injection well. The center depth of the reservoir is 1,000 m, and its thickness is 100 m in the base case. Sensitivity parameters include 1) injection rate and total amount of the injected CO2, 2) the thickness of the reservoir, which affects the contact area between dissolved CO2 and the well casing, 3) the reaching depth of the faults, and some other key parameters.
Fluid flow simulations were carried out using the reservoir simulation code “STAR” (Pritchett, 2002) with the equations of state “SQSCO2” (three pore components: H2O, CO2 and NaCl) (Pritchett, 2008), and then the changes of SP data were calculated using STAR’s “Redox Electrical Postprocessor” (Pritchett, 2003).
Simulation results indicate that SP change would be large enough to be observed under most of the conditions in this study assuming from demonstration to commercial scale.
This presentation is based on results obtained from a project (JPNP18006) commissioned by the New Energy and Industrial Technology Development Organization (NEDO) and the Ministry of Economy, Trade and Industry (METI) of Japan.
References
Bigalke, J., and Grabner, E.W. (1997): The geobattery model: a contribution to large scale electrochemistry. Electrochimica Acta 1997; 42:3443-3452.
Horikawa, T. (2022): Developments Low-Cost Monitoring Techniques using Microgravity and Self-Potential (in Japanese). Institute for Geo-Resources and Environment, GREEN Report 2021. AIST04-C00014-20: 14-15.
Kano, Y. (2021): Numerical Investigation of “Geobattery” Monitoring based upon CO2 Geological Storage. Presentation at AGU Fall Meeting 2021. Dec. 13-17, 2021, New Orleans, LA & online.
Nishi, Y. and Ishido, T. (2022): Self-Potential Monitoring for Geologic Carbon Dioxide Storage. In Geophysical Monitoring for Geologic Carbon Storage (eds Huang, L.). John Wiley & Sons, Inc in press:303-320.
Pritchett, J.W. (2002): STAR User’s Manual Version 9.0, SAIC Report Number 02/1055
Pritchett, J.W. (2003): Verification and Validation Calculations Using the STAR Geophysical Postprocessor Suite. SAIC Report Number 03/1040; 2003.
Pritchett, J.W. (2008): New “SQSCO2” equation of state for the “STAR” code, SAIC.
In this study, numerical analyses were conducted to investigate what range of the SP change is expected for variety of settings of CO2 geological storage and leakage. Simple geological model of the combination of a reservoir and a thick seal was built for the analyses. Two vertical wells were modelled; one is the injection well and the other is the observation well which is located 1,000 m away from the injection well. The center depth of the reservoir is 1,000 m, and its thickness is 100 m in the base case. Sensitivity parameters include 1) injection rate and total amount of the injected CO2, 2) the thickness of the reservoir, which affects the contact area between dissolved CO2 and the well casing, 3) the reaching depth of the faults, and some other key parameters.
Fluid flow simulations were carried out using the reservoir simulation code “STAR” (Pritchett, 2002) with the equations of state “SQSCO2” (three pore components: H2O, CO2 and NaCl) (Pritchett, 2008), and then the changes of SP data were calculated using STAR’s “Redox Electrical Postprocessor” (Pritchett, 2003).
Simulation results indicate that SP change would be large enough to be observed under most of the conditions in this study assuming from demonstration to commercial scale.
This presentation is based on results obtained from a project (JPNP18006) commissioned by the New Energy and Industrial Technology Development Organization (NEDO) and the Ministry of Economy, Trade and Industry (METI) of Japan.
References
Bigalke, J., and Grabner, E.W. (1997): The geobattery model: a contribution to large scale electrochemistry. Electrochimica Acta 1997; 42:3443-3452.
Horikawa, T. (2022): Developments Low-Cost Monitoring Techniques using Microgravity and Self-Potential (in Japanese). Institute for Geo-Resources and Environment, GREEN Report 2021. AIST04-C00014-20: 14-15.
Kano, Y. (2021): Numerical Investigation of “Geobattery” Monitoring based upon CO2 Geological Storage. Presentation at AGU Fall Meeting 2021. Dec. 13-17, 2021, New Orleans, LA & online.
Nishi, Y. and Ishido, T. (2022): Self-Potential Monitoring for Geologic Carbon Dioxide Storage. In Geophysical Monitoring for Geologic Carbon Storage (eds Huang, L.). John Wiley & Sons, Inc in press:303-320.
Pritchett, J.W. (2002): STAR User’s Manual Version 9.0, SAIC Report Number 02/1055
Pritchett, J.W. (2003): Verification and Validation Calculations Using the STAR Geophysical Postprocessor Suite. SAIC Report Number 03/1040; 2003.
Pritchett, J.W. (2008): New “SQSCO2” equation of state for the “STAR” code, SAIC.