Online Journal for E&P Geoscientists

McNeice, Gary W.^*1; Colombo, Daniele X.²
(1) EXPEC ARC GPT, Saudi Aramco Oil Company, Dhahran, Saudi Arabia. (2) EXPEC ARC GPT, Saudi Arabian Oil Company, Dhahran, Saudi Arabia.

Geophysical monitoring of enhanced oil recovery (EOR) is a rapidly growing field and there are a number of products and solutions available. Electromagnetic (EM) techniques are promising for EOR monitoring because of the large dependence of electrical resistivity on fluid saturation. In typical Saudi Arabian carbonate reservoirs, electrical resistivity can change by greater than 90% through production and water injection. In contrast, density and seismic velocity change by less than 5%.

Both reservoir-to-surface and surface-to-reservoir electromagnetic methods have been applied to reservoir characterization. In both techniques, a grounded galvanic electric source is used and electromagnetic measurements are recorded either within a borehole, as in surface-to-borehole electromagnetics (SBEM), or at the surface, as in borehole-to-surface electromagnetics (BSEM). The recorded electromagnetic variations are mapped and then inverted to infer reservoir properties.

Here we present the results of a three-dimensional finite element simulation of a typical Saudi Arabian reservoir. We simulate both SBEM and BSEM acquisition geometries using a reservoir model undergoing production and injection. Sensitivity analyses show that time-lapse EM measurements have sufficient sensitivity for monitoring waterflood operations and reservoir development when the data are properly conditioned. The critical aspects related to these types of techniques consists of the sensitivity of different electromagnetic measurements to the fluid saturations, measurement repeatability, near-surface statics effects, electrical anisotropy and the type of imaging/inversion method used. We examine some of these aspects by means of numerical modeling. We address possible solutions to these potential problems ranging from improved data acquisition practices, to advanced data analysis techniques.