High resolution compressional slowness log estimation using first motion detection

Abstract

Semblance processing is a robust and reliable processing used to measure formation slowness that is of significant value for geophysical, petrophysical and geomechanical applications. Nevertheless, the vertical resolution of the computed slowness log is linked to the length of the receiver array used to record the data. Therefore it can be difficult to compare slowness logs with other measurement of higher vertical resolution. To overcome this problem, an improved first motion algorithm allowing the computation of a high‐resolution sonic log has been developed. The technique considers that the part of the waveform before and after the first break can be modeled as an AR process. Next the use of the Bayesian information criterion combined with the computation of the envelope of the signal will allow for an automatic computation and estimation of the first break. We will demonstrate that this first motion technique does not require any human intervention and in most cases provides a robust and accurate transit times. This algorithm will then be applied on real data to produce a high‐resolution log that will be compared with some others high vertical resolution wireline measurements