Abstract

Predictive painting is a numerical algorithm that spreads information in 3D volumes according to the local structure of seismic events. The algorithm consists of two steps. First, local spatially variable inline and crossline slopes of seismic events are estimated by the plane-wave-destruction method. Next, a seed trace is inserted in the volume, and the information contained in that trace is spread inside the volume, thus automatically “painting” the data space. Immediate applications of this technique include automatic horizon picking and flattening in applications to both prestack and poststack seismic data analysis. Synthetic and field data tests demonstrate the effectiveness of predictive painting.

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