Characterizing shallow subsurface using 3D seismic while drilling with a downhole pilot

Abstract

Seismic while drilling (SWD) can provide high-resolution subsurface information and characterize near-surface geology. We present a case study of SWD analysis using a data set from a desert environment acquired over a complex overburden. The data were acquired with a system composed of wireless surface geophones as well as top-drive and downhole sensors. The drill-bit noise data were reprocessed using a specialized workflow with two essential elements. First, a downhole pilot from a near-bit sensor was used for deconvolution, which led to improved data quality, particularly in the shallow subsurface. Second, nonlinear beamforming leveraged the 3D carpet of geophones to enhance signal quality and enable picking 3D traveltimes. A simple workflow for building a 1D velocity model used 3D traveltimes from an offset of 180 to 500 m. We vertically projected and averaged all 3D traveltimes to obtain a robust checkshot profile for the section from 190 to 1855 m. For the shallow subsurface (0–800 m), we further applied an advanced workflow with 3D traveltime inversion that more accurately handled mid- and far-offset data using a ray-tracing engine. More than 100,000 offset traveltime picks were inverted for a 1D velocity model. The model closely ties with the geology of the near surface, namely the formation tops associated with major impedance and lithologic contrasts. Amplitude signatures of 3D SWD gathers also correlate with the velocity model and lithologic changes, showing weak energy associated with soft formations and higher-energy first-arrival waveforms associated with compacted formations. Finally, we used the data extracted from a 2D line to reconstruct a migrated image of the back-propagated drill-bit sources. Joint use of kinematic and dynamic signatures helps characterize markers associated with loss circulation zones and target layers.

Extracting high‐resolution P‐wave reflectivity of the shallow subsurface by seismic interferometry based on autocorrelation of blast mining signals

“…Our study also demonstrates that only one blast shot with sufficiently high signal-to-noise ratio (SNR) and frequency components can provide high-resolution autocorrelation reflections. In autocorrelation analysis, the source locations are crucial aspects for effectively retrieving reflections beneath the station from stationary phase zones (Aldawood et al, 2019(Aldawood et al, , 2022Mroczek & Tilmann, 2021;Oren & Nowack, 2017;Schuster, 2009;Ito & Shiomi, 2012), although such information is challenging to determine in our situations. To evaluate the stationary phase contribution in the second survey result, we assumed that the reflections from stacking 40 autocorrelations in the first survey are close to the stationary phase.…”