A three-phase fluid distinguishing method based on dual-parameter from neutron gamma logging technology in CO2 enhanced oil recovery

Carbon capture, utilization, and storage (CCUS) is widely recognized as a key technological pathway for mitigating greenhouse gas emissions and supporting the global energy transition. Among CCUS applications, carbon dioxide enhanced oil recovery (CO₂-EOR) plays an important role by simultaneously improving hydrocarbon recovery and enabling geological storage of CO₂. During CO₂ flooding, reservoir pores typically contain a three-phase fluid system composed of water, oil, and supercritical CO₂, which poses significant challenges for fluid discrimination and saturation evaluation. In particular, quantitative differentiation between CO₂ and oil remains difficult under three-phase conditions because of weak nuclear-physics contrasts and strong environmental interference, limiting the reliability of current neutron logging interpretations.

Neutron gamma logging tools equipped with multiple detectors provide inelastic and capture gamma responses that are sensitive to elemental composition and fluid properties, offering potential for three-phase fluid evaluation. To establish a physically consistent basis for fluid discrimination, Monte Carlo simulations based on the FLUKA code are performed to systematically investigate the response characteristics of near- and far-detector inelastic gamma spectra, as well as near–long detector capture gamma count ratios, for pure water, oil, and supercritical CO₂ under varying porosity conditions in sandstone formations. Based on the simulation results, quantitative relationships between carbon-to-oxygen (C/O) ratios, capture gamma count ratios, and porosity are established. A dual-parameter fluid evaluation method that combines C/O and capture gamma information is then proposed to effectively distinguish water, oil, and CO₂ over a wide porosity range.

In addition, the influences of borehole fluid, formation water salinity, lithological mineral composition, and clay content on neutron gamma responses are systematically analyzed. The results indicate that the presence of CO₂ in the borehole can significantly distort inelastic gamma measurements and bias the apparent C/O response. To mitigate this effect, a self-compensation correction method based on the near-to-far inelastic gamma count ratio is developed to suppress borehole CO₂ interference.

Finally, multiple formation models with varying porosity, clay content, and fluid combinations are constructed to simulate C/O ratios, capture gamma counts, and related the evaluation based on the combination of two parameters. The simulation results demonstrate the effectiveness of the proposed dual-parameter evaluation method and the borehole CO₂ self-compensation approach. This study provides a physically based framework for improving the interpretation of neutron gamma logging data in CO₂ flooding and CCUS-related reservoir monitoring.

Keywords: neutron gamma logging; carbon–oxygen ratio; capture gamma count ratio; CO₂ flooding; CCUS monitoring