Advances in Dynamic Monitoring Technologies for Formation Water in CCUS-EOR Systems

In the CCUS-EOR technology, formation water as an important part of reservoir fluid is the ‘natural tracer’ of CO2 migration-reaction-storage process in the reservoir. The temporal and spatial evolution of its chemical-physical-isotope parameters can reveal the storage mechanism and potential risks in multiple dimensions. However, the existing CCUS-EOR formation water monitoring is fragmented and lacks a systematic technical framework, which is difficult to meet the needs of collaborative optimization of carbon dioxide flooding and storage. In this paper, by analyzing the multi-phase coupling mechanism of CO2-formation water system with crude oil, rock, microorganism and oil well string, the synergistic changes of CCUS-EOR formation water chemical indexes (pH-TDS, δ13C (DIC)–δ18O (H2O), HCO3−–Ca2+/Mg2+, Fe2+-dsrB, etc.) on the dissolution and diffusion kinetics of CO2, mineral dissolution and precipitation flux, wellbore corrosion risk and microbial community structure succession were clarified. The index system of formation water monitoring for CCUS-EOR oil displacement and storage efficiency evaluation, leakage and corrosion risk early warning was constructed (including basic dynamic parameters, key tracer parameters, risk early warning parameters, auxiliary diagnostic parameters). By integrating existing real-time online monitoring technologies, high-precision laboratory analytical techniques, and numerical simulation methodologies, this study proposes a hierarchical indicator monitoring system. Combining the existing real-time online monitoring technology, high-precision laboratory analysis and detection technology, and numerical simulation technology, an index hierarchical monitoring technology system is proposed. Based on the CCUS-EOR (Carbon Capture, Utilization and Storage—Enhanced Oil Recovery) engineering practices, a standardized framework for the dynamic monitoring of formation water chemistry is proposed, which includes the optimization of the monitoring well network, multi-index hierarchical monitoring, and the construction of an intelligent early warning model. This will promote the improvement of the risk management and control technology system for the entire CCUS industrial chain.