CO_(2) storage capacity is significantly influenced by the saturation levels of reservoir rocks,with underground fluid saturation typically evaluated using resistivity data.The conductive pathways of fluids in various...CO_(2) storage capacity is significantly influenced by the saturation levels of reservoir rocks,with underground fluid saturation typically evaluated using resistivity data.The conductive pathways of fluids in various states within rock pores differ,alongside variations in conductive mechanisms.To clarify the conductivity of water in rocks across different states,this study employed a three-pore segment saturation model,which corrected for the additional conductivity of clay by categorizing water into large-pore segment,medium-pore segment,and small-pore segment types.Addressing the heterogeneity of tight sandstone reservoirs,we classified distinct pore structures and inverted Archie equation parameters from NMR logging data using a segmented characterization approach,yielding dynamic Archie parameters that vary with depth.Ultimately,we established an improved saturation parameter method based on joint inversion of NMR and resistivity data,which was validated through laboratory experiments and practical downhole applications.The results indicate that this saturation parameter inversion method has been effectively applied in both settings.Furthermore,we discussed the varying conductive behaviors of fluids in large and medium pore segment under saturated and drained states.Lastly,we proposed a workflow for inverting saturation based on downhole data,providing a robust foundation for CO_(2) storage and predicting underground fluid saturation.展开更多
基金supported in part by the Key National Research Project of China under Grant 2023YFC3707900in part by the National Natural Science Foundation of China under Grant 42204122 and Grant 42072323。
文摘CO_(2) storage capacity is significantly influenced by the saturation levels of reservoir rocks,with underground fluid saturation typically evaluated using resistivity data.The conductive pathways of fluids in various states within rock pores differ,alongside variations in conductive mechanisms.To clarify the conductivity of water in rocks across different states,this study employed a three-pore segment saturation model,which corrected for the additional conductivity of clay by categorizing water into large-pore segment,medium-pore segment,and small-pore segment types.Addressing the heterogeneity of tight sandstone reservoirs,we classified distinct pore structures and inverted Archie equation parameters from NMR logging data using a segmented characterization approach,yielding dynamic Archie parameters that vary with depth.Ultimately,we established an improved saturation parameter method based on joint inversion of NMR and resistivity data,which was validated through laboratory experiments and practical downhole applications.The results indicate that this saturation parameter inversion method has been effectively applied in both settings.Furthermore,we discussed the varying conductive behaviors of fluids in large and medium pore segment under saturated and drained states.Lastly,we proposed a workflow for inverting saturation based on downhole data,providing a robust foundation for CO_(2) storage and predicting underground fluid saturation.
