We present an approach for quality control (QC) of massive prestack land seismic datasets, focusing on evaluating data enhancement procedures critical for processing success. The QC scheme contains such measures as coherency, signal-to-noise ratio, frequency content, and phase characteristics. We apply this to single-sensor data from the desert environment. We show that proposed metrics can quantitatively measure challenging data quality even when the signal remains mostly invisible. We further demonstrate similar analysis after data enhancement emphasizing their role in the data processing. The proposed QC method allows efficient evaluation of seismic acquisition and processing.