Abstract
Proximity Sensing is a recently introduced approach to reservoir characterization, which uses high frequency, pulsed electromagnetic (EM) signals that are propagated through naturally occurring transmission lines adjacent to oil reservoirs, such as continuous anhydrite layers that serve as the seal for major carbonate reservoirs in and around the GCC. While propagating through the anhydrite channel the pulse is modulated by the saturation properties of the adjacent reservoirs. Previous 2-D simulations demonstrated the feasibility of using the anhydrite as a low loss transmission line and showed the potential to detect changes in reservoir saturation adjacent to the propagation channel. This work presents further verification of the Proximity Sensing method with 3-D simulations including antenna modelling and polarization effects, dependence of EM modulation with reservoir saturation changes and injection water flood front mapping capabilities. A series of models were created to study the effect of the conductivity and permittivity of the reservoir and the polarization of the EM pulse. The effect of varying each of the EM properties of the reservoir on the speed of propagation of the pulse and the polarization of the antenna is presented. The data shows that in general, large contrasts in conductivity and/or permittivity between the anhydrite channel and the adjacent reservoirs will confine the signal within the anhydrite and will result in shorter travel times than in the absence of strong contrasts. For the purpose of detecting oil and saline water this means that if the reservoir adjacent to the anhydrite is saturated with water the EM pulse will travel faster and the signal will have greater amplitude. In contrast, if the adjacent reservoir is oil saturated and EM signal will slow down and will display lower amplitude. This work aims to identify the most important variables needed to take this approach to small scale field testing. The success of Proximity Sensing would provide an accurate and inexpensive method to characterize reservoir saturation and flood front progression either as part of a logging operation or as a standalone sensing platform.
