Li, Dong (SINOPEC Geophysical Research Institute) | Wang, Lixin (SINOPEC Geophysical Research Institute) | Xu, Zhaotao (SINOPEC Geophysical Research Institute) | Zheng, Xiaopeng (SINOPEC Geophysical Research Institute) | Mu, Jie (SINOPEC Geophysical Research Institute)
The seismic data acquired in the mountains area are generally irregular or sparely because of the complex surface, which may not fulfill the processing requirements and degrades processing quality, so these data should often be interpolated. A projection onto convex sets (POCS) algorithm using Fourier transforms is a well-known technique to reconstruct the irregular seismic data, helping on the processing of data with different acquisition problems. We proposed the interpolation procedure using POCS method based on OVT domain and applied it to the field data. Numerical examples indicates that the proposed scheme is effective and applicable, as it can reconstruct missing traces of complex data acquisition.
There are abundant oil and gas resources in the mountainous area of South China, which has broad prospects for exploration and development. However, seismic data is usually irregularly or sparsely distributed along the spatial direction in the complex surface area, which may not meet the processing requirements and then degrades processing quality, so it is important and necessary to regulate and interpolate seismic data at the missing spatial locations where measurements are not acquired in the seismic data processing stage.
Primary reflections are generally applied in seismic imaging. The information of primary waves, however, is insufficient for structural imaging in obstacle restricted areas where no shots but only receivers are allowed. Multiples, if developed, can be applied as effective signals. In this paper, the author presented to take multiples as effective information to highlight the obstacle area and supplement the incomplete image obtained by only primaries reflection in obstacle restricted areas, and obtain complete and rich subsurface structure information. Synthetic model and the real data application demonstrate the feasibility and effectiveness of this approach.