By casting the problem of seismic signal detection as one of statistical detection theory, one can develop a myriad of detection statistics or detectors. Of these, one of the most promising appears to be sign‐bit semblance. This nonparametric detector makes use of only the sign bits of the seismic data and, hence, requires less storage and is faster to compute than other detection statistics. In addition, it is independent of the noise statistics, as are all nonparametric detectors. An automatic velocity analysis and interpretation program has been developed using sign‐bit semblance as the detection statistic. The statistical properties of sign‐bit semblance were such that this system could do a velocity analysis and an interpretation with no human intervention. In this mode of operation it yielded state‐of‐the‐art accuracy at greatly increased speed and with greatly reduced storage requirements. These results indicate that sign‐bit semblance can be used to advantage for certain other seismic‐data processing problems.
Learning Based Signal Detection for MIMO Systems with Unknown Noise Statistics
