We evaluated how velocity and anisotropy model-building strategies affect seismic imaging in the Canadian Foothills Thrust Belt by comparing the results of a model-driven approach with those of a data-driven approach. Two independently run Kirchhoff prestack depth-imaging projects were initiated using different static corrections for near-surface weathering layers and using different velocity and anisotropy model-building strategies. We observed that an isotropic data-driven reflection tomography velocity model-building approach resulted in a significantly better stack image than did a highly interpretive anisotropic model-driven velocity model-building approach. By carefully introducing anisotropy into the former, data-driven approach, we achieved significant improvements in positioning, including more accurate depth ties between the seismic image and well tops and better definition of structural geometries. The differences in the imaging observed at the various stages of this case history illustrate the sensitivity of the final depth images to the treatment of the near-surface velocity field, the macrointerval velocity model-building technique, and the choices of [Formula: see text] and [Formula: see text], which are the Thomsen anisotropy parameters for tilted transverse isotropy. The data-driven approach successfully challenged the historical idea that we must perform a geologic interpretation of the seismic data to derive an accurate depth velocity model in a complex geologic setting.
Velocity model-building for depth imaging of PS converted-wave data requires significantly more effort than PP imaging. For PS depth imaging, we must produce a model that flattens events on both PP and PS gathers and images equivalent events at the same depth for both data types. To satisfy these constraints requires a high-quality anisotropic model with accurate estimates of anellipticity and Vp/Vs ratio. We present a ray-trace tomography algorithm with floating event constraints that allows simultaneous update of all velocity model parameters for efficient and accurate velocity model-building with PP and PS data input. Tests on synthetic data with typical North Sea geology illustrate the effectiveness of the joint PP/PS tomography. Figure 5: PP (left) and PS (middle) CIP gathers with event picks overlaid, relative shift between PS and PP depth sections (right) and true depth minus image depth (far right) for PP/PS tomography model with well marker constraints.
In some areas of the North Sea there are irregular highamplitude events that some call "gull-wing" reflections because of their characteristic appearance on seismic sections. The Oseberg area, the site of a recently acquired ocean-bottom cable (OBC) 3D survey, is severely affected by these anomalies, which are scattered over the area at a depth of about 1.5 km. Some gull-wing anomalies have been drilled and are seen in log data to have a thickness of up to about 50 m and a P-velocity of around 5500 m/s. The high velocity of these irregular features causes significant distortion in depth imaging of Oseberg seismic data, causing both vertical and lateral displacement of deeper events. Different approaches were explored to resolve the high-velocity anomalies during depth imaging of the OBC 3D data. One method that has proven successful is to use results of prestack AVO inversion to insert anomalies in the velocity model. Another method is high-resolution common-image-point (CIP) tomography using offset-vector-tile (OVT) input, which is also able to resolve a smooth representation of the gull-wing anomalies. Both of these methods reduce the distortion caused by the gull-wing anomalies and give improved depth-imaged results.
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