First Modelling Results of the EM Response of a CO2Storage in the Paris Basin

Abstract

We study the feasibility of using electrical/EM methods for monitoring the injection of supercritical CO<sub>2<sub/> at a depth of 1700 m in a saline aquifer of the Paris Basin (Dogger carbonates). We first establish the theoretical interest of resistivity methods for CO<sub>2<sub/> monitoring through the basic laws of electrical physics in porous sedimentary rocks, assuming that supercritical CO<sub>2<sub/> is a perfect insulator. Various combinations of EM sources and sensors are discussed and it is shown that the best type of array consists of a galvanic source (i.e. injection of current via a pair of electrodes A and B) and of a grid of electric (and possibly magnetic) sensors at the ground surface. Given the usual depth and thinness of CO<sub>2<sub/> storage layers, current injection at depth was investigated in order to increase the current density in the reservoir and thus enhance the CO<sub>2<sub/> response. Point injection at the reservoir depth in the so-called “Mise À la Masse” (MAM) configuration is generally impossible in deep wells due to the presence of metallic casings. Therefore, the possibility of using a deep metallic casing as a long electrode distributing the current all along a borehole is studied. This kind of source is named “LEMAM” (Long Electrode Mise À la Masse) in order to differentiate it from the conventional MAM.Numerical simulations are presented for the LEMAM array and for the gradient or rectangle array (RECT), for which the current is injected by a pair of point electrodes at the ground surface. The geoelectric model used is based on an area close to the Saint-Martin-de-Bossenay (SMB) oilfield, in the south-east of the Paris Basin. The storage reservoir considered in this study is the 75-m-thick “Oolithe Blanche” formation (Mid Jurassic or Dogger, Bathonian age), located at a depth of about 1700 m below ground surface. In the models presented, the CO<sub>2<sub/> plume is simplified to a square horizontal slab of 2 km side, 70 m thick, floating at the top of the oolite aquifer. A uniform CO<sub>2<sub/> saturation of 80% is assumed, yielding a resistivity contrast of 25 with the initial reservoir.Two variants of the model with different reservoir resistivities are compared. The first model is calculated with a realistic reservoir resistivity of 20 ohm.m, reflecting the low salinity of the aquifer in this part of the Basin (≈ g g/L of NaCl). With this model, the time-lapse electric response of the CO<sub>2<sub/> plume is less than 0.5% of the initial electric field, which is below the estimated “repetition noise”. This poor result can be explained by the fact that the reservoir, in this case, is far from being the most conductive layer of the model. As a consequence, only a minor part of the injected current is used for energizing the CO<sub>2<sub/> plume: a rough calculation shows that only about 2% of the injected current crosses the reservoir, hence the poor response of the plume.A second model is calculated with an idealistic reservoir resistivity of 1 ohm.m, corresponding to about 50-70 g/L of NaCl in the aquifer (though such salinity is not observed anywhere in the Dogger aquifer of the Paris Basin, it is common in many storage aquifers). With this favourable model, it is estimated that about 30% of the injected current crosses the reservoir and energizes the plume, resulting in a time-lapse electric response as high as 6% of the initial field, which is quite measurable. For comparison, the timelapse electric response obtained with the same model for a surface current injection (RECT array) is only 2% of the initial field. With this same model, the time-lapse magnetic response obtained for the LEMAM injection is about 3% of the initial magnetic field.We conclude that the LEMAM array is very promising for the resistivity monitoring of a CO<sub>2<sub/> injection in a deep aquifer, provided that the water salinity is high enough for the reservoir to channel a significant fraction of the injected current (say > 10%).