The growth of interest around carbon capture and storage (CCS) projects pushes towards in-depth studies into several disciplines. In particular, the monitoring phase at the so-called spy wells plays a critical role for the proper understanding of carbon dioxide (CO2) plume development far from the injectors. In this respect, time-lapse pulsed neutron logging (PNL) represents a mainstay for the quantitative evaluation of fluid saturation changes behind casing. However, the latter task can be not straightforward in case CO2 injection is performed into depleted gas reservoirs.

This paper deals with a deep study of various PNL measurements for fluid identification and saturation monitoring purposes in CCS projects. First, in a given reservoir rock, several sensitivity analyses have been performed to model the typical PNL responses of mixtures of water, methane (CH4) and CO2. These include different neutron interactions with matter (e.g. scattering and capture) together with their dependence on pressure and temperature. The outcomes of the first step lay the groundwork for the definition of the most effective PNL interpretation approach, as appropriate.

Next, a real case study has been presented. Several simulations of PNL response have been performed in order to forecast the deviation from the acquired baselines in two selected spy-wells, according to the possible arrival of a plume composed by a CH4-CO2 mixture with different relative concentrations, displacing different amounts of water volume fraction, and at different pressure and temperature. Therefore, a random error has been generated for the simulated PNL curves to be used for the following uncertainty quantification in obtaining the desired water saturation and CH4-CO2 relative concentrations, mimicking future time-lapse interpretations. The latter represents a useful template to understand the real PNL monitoring capability in this environment.


In Carbon Capture and Storage (CCS) projects a paramount role is played by monitoring activities. In fact, the accurate identification and possible characterization of the plume at spy-wells is a critical aspect for the understanding of injection and reservoir behavior. This is even more important in depleted gas reservoirs since methane (CH4) and carbon dioxide (CO2) mixtures can migrate at different pressure/temperature/saturation regimes, and a detailed discrimination of the two components could be not straightforward.

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