CO2 Plume Detection Using Ras, Temperature and Noise Tools in A CO2 WAG Reservoir

Abstract

In alignment with most company's vision to reduce greenhouse effects by expanding CO2 carbon capture and utilization for oil fields, CO2 gas is injected into the reservoir to enhance oil displacement and maintain reservoir pressure. Since CO2 gas is miscible in the oil, the gas flood front is not piston-like; the gas is slowly absorbed by the oil changing the oil properties. Detection of the CO2 plume is necessary to monitor CO2/ injected water/ oil distribution (at and away from the well) and to track the effectiveness of the complicated CO2 WAG injection process in terms of improved sweep efficiency. Monitoring CO2 flood front movement requires a logging measurement that can distinguish oil from CO2 in the formation. This measurement must have a sufficiently large dynamic range for the change from no CO2 to a high CO2 saturation to be distinguished within measurement error. This paper highlights the utilization and integration of Reservoir Analysis System (RAS) and Noise tools in CO2 plume detection. It also highlights some of the limitations of the RAS tool in high water transition zone in CO2 WAG environment. As the oil is push away from the injection well, the flood front will be characterized by oil having varying amounts of miscible CO2 gas dissolved in it. The rate and composition of the injection gas determines how much of the oil that will expand. The density of the oil may not change much (since the oil density is close to the CO2 gas density) but the hydrogen density of the oil will decrease considerably as is the case for CO2. Another factor that controls the CO2 plume movement is the stratigraphy of the heterogeneous carbonate reservoir – where the coarsening upwards trend of the facies associations of High Stand Systems Tract (HST) coupled with pervasive cementation, creates non-uniform movement of CO2 plume vertically and spatially. Logging results shows Neutron porosity (PHIRN) and PNC near/far capture ratio are the preferred log measurement curves because they have the most sensitivity to the large decrease in hydrogen index when CO2 replaces oil or is dissolve in oil. Other curves like Ratio of Near to Long at Burst (RLNB), Long Inelastic Rate Sigma (LIRS), temperature and noise logs also play significant roles in CO2 plume indications. The outcome of this study has helped understand the vertical and lateral extent of the CO2 WAG flood front, estimate saturations, evaluate the well integrity, and locate un-swept zones. Additionally, RAS data is hard data used as calibration (blind test) to check the robustness of the dynamic model.