Vibrator Data Quality Prediction from Remote Sensing-based Near-surface Analysis

Remote sensing allows a spatially dense look into the near surface. By leveraging technology such as multispectral satellite data, experienced users are able to create maps that aid logistics planning for surface seismic acquisition and give an estimation of data quality that can be achieved. This paper draws upon examples from a seismic survey in a coastal area of the UAE. We demonstrate that the integration of Landsat 7 ETM imagery calibrated by selected surface geology sampling makes it possible to predict probable instances of wet sabkha, investigate the correlation between the multispectral remote sensing data, and correlate the vibrator sweep performance data with the near surface. The integration of the data is aided by a GIS database.