No abstract

Finding channel sandbodies is an important task in oil and gas exploration due to the importance of fl uvial reservoirs. It is diffi cult to describe fl uvial reservoirs in detail owing to their frequent changes and serious intersections, as well as limitations of S/N ratio and seismic data resolution. Based on the Laohekou 3D data in Shengli Oilfi eld, we analyze the general characteristics of fluvial reservoirs in this area, from which we find that they are characterized by strong amplitudes on seismic profi les, high continuity on time slices, and low frequency in the frequency domain. In addition, a cluster of strong string-beadlike refl ections was found after color processing and detailed interpretation. To understand this observation, we conduct forward modeling to explain the mechanism. This provides a new way to identify ancient channels in similar areas. By using the multi-attribute fusion and RGB display techniques, channel incision is more obvious and the characteristics of the channel structures are manifested much better. Finally, we introduce and apply multi-wavelet detection technology to identify weaker fl uvial reservoir signals.