Technical Study on the Partial Common-offset and Common-reflection-surface Stacking
Shi Li-yuan
Abstract
Shi Li-yuan
Abstract
Common-offset and common-reflection-surface(CO CRS) stacking was expanded from conventional Zero-offset common-reflection-surface(ZO CRS) stacking.The valid range of the stacking operator was wider and the better imaging of complex subsurface structures could be obtained with far-offset information.The parameter splitting algorithm used in this paper obviously reduced the calculation time of CO CRS stacking,which effectively resolved the difficulty of low computational efficiency in actual application.The partial CO CRS stacking method is used to enhance the quality of sparse low fold prestack seismic data,which is regularized by filling the gaps in cases of missing traces for improving signal-to-noise ratio.The improved prestack data can be used in many conventional processing steps,such as velocity analysis or prestack migration instead of the original data.Satisfactory results are obtained in the model test.
A significance statement is not available in the OpenAlex record.
A contribution statement is not available in the OpenAlex record.
Method details are not available in the OpenAlex metadata.
Findings are not separately available in the OpenAlex metadata.
Limitations are not available in the OpenAlex metadata.
Application details are not available in the OpenAlex metadata.
Common-offset and common-reflection-surface(CO CRS) stacking was expanded from conventional Zero-offset common-reflection-surface(ZO CRS) stacking.The valid range of the stacking operator was wider and the better imaging of complex subsurface structures could be obtained with far-offset information.The parameter splitting algorithm used in this paper obviously reduced the calculation time of CO CRS stacking,which effectively resolved the difficulty of low computational efficiency in actual application.The partial CO CRS stacking method is used to enhance the quality of sparse low fold prestack seismic data,which is regularized by filling the gaps in cases of missing traces for improving signal-to-noise ratio.The improved prestack data can be used in many conventional processing steps,such as velocity analysis or prestack migration instead of the original data.Satisfactory results are obtained in the model test.
Key concepts: Stacking, Prestack, Offset (computer science), Reflection (computer programming), Computer science, Algorithm, Geology, Physics