3D Borehole Sonic Imaging for Input to Structural Modeling-A Quantitative Approach

Abstract

Abstract Sonic imaging is a technique to obtain a high-resolution acoustic image of the earth formation structures several meters away from the well by utilizing the azimuthal sonic waveforms recorded for extended listening times downhole. The method has been used since the early 1990's to identify subseismic scale features (boundaries, faults, fractures, etc.) by migrating the sonic waveforms into a high- resolution 2D image. Over the past two decades, the sonic imaging in the oil industry has been looked at as a ‘niche’ service. Limitations in acquisition telemetry to handle large datasets downhole and surface software processing capabilities as well as long job turnaround times have meant that sonic imaging service was primarily done on very few wells. Recently, sonic imaging has regained the interest of the community for input to structural modeling along with advancements of higher downhole data transmission capabilities and more powerful processing capabilities. The processing workflow itself, however, has mainly largely remained the same and has consisted of first filtering the sonic waveforms to reduce the interference of the borehole modes and then migrating the filtered waveforms to obtain a 2D image of a well section. Although the 2D image obtained from sonic data is of much higher resolution as compared to other available images such as surface seismic data and vertical seismic profiling (VSP), it does not provide quantitative information on the true dip and azimuth of the acoustic reflectors. With the advancements in the use of borehole resistivity images for geomodeling, the true dip and azimuth information is now essential for fracture characterization and structural geomodeling. We introduce a new technique to obtain reflector location and associated attributes such as true dip and azimuth from fractures, faults, and layering from azimuthal sonic waveform measurements. The technique consists of two main steps. In the first step, an automated time pick and event localization procedures collect possible reflections from filtered waveforms; in the second step, an automatic ray tracing and 3D slowness time coherence (STC) procedure determines the ray path type and a 3D structural map of the reflector, as well as its true dip and azimuth. This technique also provides appropriate parameters for the orientation of the optimum 2D plane to migrate for the traditional image. The new technique enables determining the key parameters of true dip, azimuth, and reflector locations from higher-resolution sonic data required for reservoir evaluation and geomodeling. Direct integration with borehole resistivity images provides an opportunity to build a more accurate single-well structural model for identifying formation dip as well as a near-wellbore connectivity to far-field fractures. This technique has been demonstrated using a case study, where sonic data were recorded in a horizontal well placed in unconventional Wolfcamp formation of North America. Characterization of natural fractures was critical for well completion and hydraulic fracturing. The 3D slowness time coherence (STC) results derived from multi-spaced and multi-azimuthal sonic data provided dip and azimuth of the fractures, which showed good agreement with image log interpretation. Image log results, which provides near-field information, were complimented with far-field 3D STC results.