Combining high-definition formation microelectrical imaging and wireline formation tester for improved reservoir characterization in high-resistivity low-permeability carbonate reservoir

Wireline formation microelectrical imaging has been used for many decades to characterize reservoirs. The geological interpretation of image data is mainly used for structural analysis, fracture characterization, porosity analysis, heterogeneity analysis, rock typing, and facies classification. In addition, formation microelectrical images are commonly needed for complex reservoirs to help with the selection of wireline formation tester straddle packer locations. The quality of the data acquired using conventional formation microelectrical imaging tools may be degraded in highly resistive formations even with conductive mud because of the high noise-to-signal ratio, whichcan lead to fuzzy images with very few geological features visible. Phase shift, which is common in resistive formations, can result in reversed images, reversed contrast, and pad/flap mismatch, which can render the data unusable. A new tool for microelectrical imaging presents a solution to this problem by obtaining high-definition, full-coverage images in formations with moderate to high resistivity. This new technology was applied in a complex carbonate tight gas reservoir drilled with water-based mud (WBM). Conventional formation microelectrical imager data suffered from a huge phase shift, low quality, and low-resolution, withvery few geological features visible. The high-definition formation microelectrical imaging resulted in much better data quality, which enabled the identification of the different geological features. The data obtained from standard and the high-definition formation imaging are presented and compared. Use of the high-definition data enabled positioning the wireline formation tester at the optimal zones. The new selected stations enabled proper fluid identification where pressures and samples were obtained. In addition, reservoir permeability data were obtained using pressure transient analysis. Pressure transient interpretation of the straddle-packer data corresponded well with the geological features observed from the high-definition images.