An investigation to illustrate the relative importance of the controlling factors in estimating seismic net pay from colour-inverted band-limited impedance data has been performed. This was achieved by using a new, semi-automated implementation of the process, allowing the sensitivity of each of the key controls on the resulting net pay to be found quickly and easily. This automated workflow was run over a synthetic dataset varying different input parameters. The chi angle and the low

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... s used in building the tuning wedge were found to have the largest effect on the final volume. Using this technique on real datasets could greatly improve the understanding of the possible range of pay volumes, reducing risk and highlighting the key input parameters. The presentation will work through one manual iteration of the complete workflow, then show how this workflow can be automated. The results running the workflow on a synthetic dataset will be described and discussed.