Image- and horizon-guided interpolation

Abstract

Seismic data are uniformly sampled images of geologic structures, and they spatially cover a big area as opposed to well log data, which are often scattered sparsely within the seismic cube. A common strategy to extend the coverage of the well log data is to interpolate them away from the boreholes on the seismic image grid. Image-guided interpolation is a form of blended neighbor interpolation in which the structural information that guides the interpolation is calculated from a seismic image and represented by structure tensors. Deriving this structural information from only the seismic image might not lead to desirable interpolated results, especially in cases of complex structure, a low-quality seismic image, and few well logs. In such cases, constraining the structure tensors with additional information is beneficial. We have developed a three-step hybrid method in the log-Euclidean domain to use interpreted horizons as well as the seismic image to construct the final structure tensor field. Also, we determined how to incorporate the curvature attributes from horizons for better performance of the algorithm in the presence of faults. Synthetic and real data examples determined the ability of this new technique to achieve better conformance of interpolated properties with the seismic image and interpreted horizons.