OPTIMIZED DISTRIBUTION OF SNMR PULSE MOMENTS AND FIELD EFFICIENCY EVALUATED USING A MODEL UNCERTAINTY ANALYSIS

Abstract

Surface Nuclear Magnetic Resonance (SNMR) is a promising geophysical technique. One of the challenges of the technique is due to the long data acquisition time. The main factors controlling the acquisition time is the relaxation time of the affected molecules, the number of measurements in each stack, the number of pulse moments and how the pulses are transmitted by the system. Currently there are two different pulse transmission schemes: A) Transmitting all pulse moments, from high to low, in one de-charge of the system, distributed in a logarithmic manner. B) Doing all measurements at each pulse moment before going to the next pulse moment. The system has to be recharged before each measurement. The pulse distribution can be decided by the operator. The benefit of A) is regarding time, the system is not recharged before every single measurement, which is faster compared to a recharge before each measurement. The only time limiting factor in case A) is the relaxation of the affected molecules, which has to be completed before the next pulse. The benefit of B) is due to the pulse moment distribution, which can be optimized and decided by the user. These differences give rise to the following questions: Is there an optimal pulse distribution that gains more information compared to the log-distribution? Is there a trade-off between having a fast acquisition with log-distributed pulse moments and a slow acquisition with an optimized pulse distribution regarding measurement time? Is there a trade-off between acquisitions based on a high number of pulse moments versus a high number of stacks? We present results based on an analysis by calculating the model parameter uncertainties based on the a-posterior model covariance matrix. The analysis will be conducted both by adding synthetic random distributed noise to the data, and by adding noise collected with the GMR system.