Quantitative Estimation of CO2Saturation in Saline Aquifer Storage Based on Resistivity Data
Yoshihiro Nakatsuka, Jong Wook Kim, Ziqiu Xue, Toshifumi Matsuoka, Kenji Kubota
Abstract
Yoshihiro Nakatsuka, Jong Wook Kim, Ziqiu Xue, Toshifumi Matsuoka, Kenji Kubota
Abstract
To overcome the current limitation of seismic velocity to estimate the CO2 saturation in saline aquifer storage, we considered the use of resistivity in order to obtain more accurate estimations. From the laboratory experiment which we conducted for the first step, geological factors influencing the resistivity measurement was recognized. Also the simple but effective way of relating measured resistivity to CO2 saturation was shown in this study. The experimental result shows that, in the case of heterogeneous pore structure including clay, resistivity seems to be estimated lower than the true resistivity. CO2 saturations estimated by both Archie's equation and Resistivity Index showed the same trend. But, because of the single rock relating parameter (saturation exponent n) included in the formula, which needs to be determined or assumed, estimation of saturation of CO2 are easier for Resistivity Index. This Resistivity Index tends to reflect the trends of increasing resistivity due to the increase of CO2 to CO2 saturation. For the second step, we estimate CO2 saturations from logging data acquired in a field scale CO2 sequestration project: The Nagoka CO2 injection test. The reference saturations of CO2 were estimated from the neutron porosity change because the neutron log gives a direct indication of the amount of the formation water in the pore space. Compare to the reference saturation, estimated saturation from Archie's equation and Resistivity Index or other formulas including clay corrections showed lower saturation. To estimate the correct saturation of CO2, new equation with clay correction was suggested in this study. The estimated saturation from this equation showed good agreement with the reference saturation. We suggested new equation for estimating CO2 saturation in clay including reservoir of saline aquifer storage.
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To overcome the current limitation of seismic velocity to estimate the CO2 saturation in saline aquifer storage, we considered the use of resistivity in order to obtain more accurate estimations. From the laboratory experiment which we conducted for the first step, geological factors influencing the resistivity measurement was recognized. Also the simple but effective way of relating measured resistivity to CO2 saturation was shown in this study. The experimental result shows that, in the case of heterogeneous pore structure including clay, resistivity seems to be estimated lower than the true resistivity. CO2 saturations estimated by both Archie's equation and Resistivity Index showed the same trend. But, because of the single rock relating parameter (saturation exponent n) included in the formula, which needs to be determined or assumed, estimation of saturation of CO2 are easier for Resistivity Index. This Resistivity Index tends to reflect the trends of increasing resistivity due to the increase of CO2 to CO2 saturation. For the second step, we estimate CO2 saturations from logging data acquired in a field scale CO2 sequestration project: The Nagoka CO2 injection test. The reference saturations of CO2 were estimated from the neutron porosity change because the neutron log gives a direct indication of the amount of the formation water in the pore space. Compare to the reference saturation, estimated saturation from Archie's equation and Resistivity Index or other formulas including clay corrections showed lower saturation. To estimate the correct saturation of CO2, new equation with clay correction was suggested in this study. The estimated saturation from this equation showed good agreement with the reference saturation. We suggested new equation for estimating CO2 saturation in clay including reservoir of saline aquifer storage.
Key concepts: Electrical resistivity and conductivity, Saturation (graph theory), Aquifer, Soil science, Materials science, Environmental science, Geology, Remote sensing