We have developed a new technique for interpreting induction logging data in horizontal wells. In addition to the accurate formation and invasion resistivity distribution near the borehole wall, the new inversion algorithm allows us to determine the distance to remote layers and their resistivities. The High Definition Induction Logging (HDIL) instrument collects data at multiple frequencies and various transmitter-receiver spacings. Focusing and inversion algorithms are designed for vertical and deviated wells to determine an invasion profile, to measure resistivity deep into the formation, and to provide high vertical resolution. In horizontal wells, the objectives are different. In addition to the resistivity distribution in the borehole vicinity, we wish to determine distances to remote cap rocks and water-bearing horizons. The vertical resolution (or, more accurately, the resolution along the borehole trajectory) is no longer important due to the relatively small lateral variation of the formation parameters. What becomes important is the depth of investigation. Low operating frequencies and long transmitter/receiver spacings allows the HDIL tool to provide reliable information from layers located up to 20 ft away from the instrument. The new inversion algorithm for interpreting induction logging data in horizontal wells consists of three components. First, we determine the parameters of the near zone formation using shallow and medium investigation measurements. At this stage, fast 2-D inversion allows us to recover invasion and formation parameters without being affected by remote layers. Second, we correct the medium and deep measurements for the presence of the borehole and invasion using the results of the near zone interpretation. Third, we interpret the corrected medium and deep measurements using 1-D layered inversion to characterize remote layers. We validate the new approach with a synthetic model consisting of a borehole, invaded formation, and a remote layer. All parameters of interest, such as formation and invasion resistivities (Rt and Rxo), invasion depth (Lxo), and the distance to the remote layer, are recovered with high accuracy (errors less than 10%). We also present a case study for a horizontal well in the North Sea. Successful completion of the well required distinguishing between low resistivity water-flooded zones with movable water and an underlying tight layer that exhibits low resistivity. The developed algorithms allow quantitative estimation of the distance to, and resistivity of, the tight layer as well as the resistivity of the permeable formation. The distance to the tight layer correlates with information from seismic data.
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