In this study we are analyzing the balance between number of data points and data quality in SNMR survey design. In SNMR the number of data points increase with the number of pulse moments and data quality increase with the number of records at each pulse moment (stack size). The premise for our analysis is that the total amount of records is fixed to 1500 and the stack size and number of pulse moments are dependent on each other. Thus, for a high number of pulse moments the stack size and thereby data quality are low and for a low number of pulse moments the stack size and data quality are high. From our model uncertainty analysis we show that it is better to discretize the data space densely, by having a high number of pulse moments with a lower data quality compared to fewer pulse moments with a higher data quality. Furthermore, we analyze and compare the logarithmic pulse moment distribution scheme with an optimized pulse distribution scheme. We show that the determination of the model parameters at a certain depth can be improved by adding more pulse moments at corresponding interval.


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