Three–Dimensional Seismic Diffraction Imaging for Detecting Near-Surface Inhomogeneities

One of the problems encountered in a variety of near-surface investigations is detecting and mapping localized inhomogeneities. Typical examples of such inhomogeneous sources are cavities, caves and tunnels. Different methods for detecting shallow subsurface sources utilizing seismic waves diffracted by these sources were proposed by many researchers in the last three decades. Most of these methods suggest that every subsurface point is a possible location of a point diffractor. Imaging of the diffractors is based on a spatial summation of the diffracted wavefield along diffraction time surfaces (defined by source-receiver geometry) in 2D or 3D space. The summation is performed with a fixed velocity value estimated from velocity analysis of the diffraction data. In this study, we present a path integral summation approach, where for every subsurface point the wavefield is stacked together along all possible diffraction time surfaces having a common apex at a given time. The result of the imaging is a 3D volume in which prominent diffraction anomalies appear at spatial locations close to the imaged sources. This path integral summation approach has been successfully tested on synthetic data and further applied at several sites with known subsurface sources

Detection of subsurface lineaments using edge diffraction

Detection and imaging of subwavelength features in the subsurface using diffracted waves are rapidly gaining momentum in the oil and gas industry as well as in the fields of engineering, archeology, and homeland security. Most of the methods include coherent summation of the recorded wavefield along diffraction traveltime surfaces from point scatterers. The summation focuses energy onto point-like diffractors that appear at the resulting images as prominent anomalies. However, in cases in which the target is an elongated object such as a fault plane, fracture, tunnel, or elongated cave, a more efficient imaging method can be constructed. We have developed an algorithm for detecting and characterizing linear subsurface elements using a linear-diffractor operator. Our algorithm is based on the coherent summation of the edge diffraction generated by the entire lineament and on the analysis of the calculated coherence measure (semblance). The advantages and limitations of our method are discussed, and the results are compared to conventional point-diffractor-based techniques. Synthetic and real data examples demonstrate that using a linear-diffractor-based algorithm can dramatically improve the detection of linear objects. </jats:p