Land Controlled Source Electromagnetic Technique for Shallow Viscous Oil Reservoir Characterization of North Kuwait

Abstract

Controlled Source Electromagnetic (CSEM) method provides an effective imaging tool for the reservoirs characterized by distinctive resistivity signature, such as lithological change or fluid saturated channels. Acquisition, processing and modeling of CSEM data provide us an effective complementary information to seismic in characterization and potentially production of viscous oil from the shallow reservoir. CSEM methods using electric dipole sources are very sensitive to thin resistive layers similar to shallow clastic reservoir of North Kuwait. Prior to CSEM survey, the sensitivity of this method to presence of viscous oil bearing layers was tested through synthetic simulation study utilizing several well logs of shallow clastic reservoir. Feasibility study highlighted the good sensitivity of CSEM to resistive shallow clastic reservoir. In CSEM survey layout, the source position started with offset from the receiver spread progressing through the spread and move to the opposite side by same offset. The electric field data are recorded on 100m dipoles, at continuous 100m interval, with 100m between receiver lines. Transmitter dipoles were also 100m, but spaced at 300m intervals along line. Data processing is carried out in the frequency domain. Source and receiver calibration functions are included in the process along with all geometry data. Amplitude and phase response is obtained for each source and receiver combination at multiple frequencies. Measured amplitude and phase values varied depending on the source-receiver separation and more importantly on the subsurface resistivity distribution between source and receiver. The CSEM synthetic responses obtained through forward modeling are compared with observed processed data to perform a further quality control step and start a qualitative data imaging. In fact, the measured electric field amplitude and phase deviate from the synthetic data as much as true subsurface resistivity distribution deviates from reference model. Another essential step in CSEM data analysis consists of inverting the data to infer a resistivity model that could fit the observed measured data. We followed an incrementally more complex workflow from 1D CSEM laterally constrained anisotropic inversions to 3D anisotropic CSEM inversion. 3D inversion of co-located MT data and 1D CSEM inversion helped to build a reliable a priori model. The output anisotropic resistivity earth model showed good consistency with the previous step qualitative imaging results and with the available resistivity logs. Resistivity volume obtained from 3D CSEM inversion can be interpreted to correlated resistivity lateral variation in depth and space with known features to infer rock physics variations at the shallow reservoir levels. This information, together with the results of non-seismic data acquired at the same time and of the seismic dataset has helped in characterizing the shallow clastic viscous oil reservoir.