Leveraging 3D High Resolution PSDM Data Volumes for Early Geohazard Detection

Abstract

The exploiting of High Resolution (HR) Pre Stack Depth Migration (PSDM) 3D seismic volumes, normally used for Oil & Gas exploration, has been pushed forward in geomorphological and geohazard risk evaluation. The novel approach proposed here allows to carry out such activities very early in respect of the standard work flow. Early awareness of critical areas turns out to be crucial in fast-tracking projects and allows a design to cost optimization. The 3D HR PSDM outputs are processed in order to generate a detailed imaging of the shallower portion of the seismic volumes. The volumes are processed at a 2 meters depth interval and converted in time (DTT). Finally, a dedicated post migration time processing sequence, followed by time-to-depth conversion, is applied to generate a Higher Resolution Volume (HRV) in depth domain. The resulting 3D volume is then analyzed to study the seabed and the sub-bottom from a geomorphological standpoint. The analyses focus on the identification and mapping of the distribution of the "areas of instability" eventually classified according to a specific KPI (Safety Factor Index in static conditions), providing a quantitative slope stability assessment of the area. The new approach has been validated comparing the DTM (Digital Topographic Model) derived from the 3D HR PSDM volume and the available MBES (Multi Beam Echo Sounder) bathymetry. The proposed approach leads to a dramatic improvement in the detection capability, highlighting the major critical structures such as: canyon flanks, buried slides, creeps and tension cracks on the shelf break, boulders and compacted sediments, sediment banks and sediment waves reshaped by bottom currents, pockmark areas and fluid escapes, turbidity mass movements and furrows due to tectonic activities. The approach matches perfectly the detection capability of a traditional MBES approach. The described workflow is potentially highly beneficial for early de-risking assets and operations, especially for facilities installation. The proposed innovative approach allows a detailed planning of dedicated data acquisition campaigns, restricted to the most critical areas, with a tangible reduction in the turnaround times and cost savings crucial for project economics.