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The major reservoirs is thin sand formed in large lake-face sandstone and mudstone inter-bed deposited environment of Changyuan Oilfield in Daqing, which is in the late stage of high water cut, the key to remaining oil research is how to describe spatial distribution of thin sand bodies and small faults. Seismic data in different bin scale have different capabilities of geological body characteristic, while which bin scale of seismic data can identify thin sand bodies and small faults of Changyuan oilfield is an unanswered question. In this paper we process three different scale bin data separately using same flow, then analysis the abilities to describe small faults and thin sand bodies among the three processing results. The results show that the small scale bin seismic data can identify faults throw more than 3m, describe distribution of sand bodies thickness than 3m clearly, and with the bin scale increasing, the spatial distribution of thin sand bodies and small faults becoming blurred .

Summary The noises produced by oil production well are of wide frequency, mighty energy variation, and the huge population of oil production well in Changyuan oilfield makes the noises stacked each other. That leads a tough issue for noise elimination during data processing. Based on the 3D seismic data with high density of Changyuan survey, the field test noise data of oil production well was first analyzed in this paper, and then compared with the noise recorded in real seismic data. 4 effective methods were researched for noise attenuation, including frequency divided noise attenuation in different data domain, zone anomaly process in shot gather, cross-spread noise attenuation, f-x coherent noise suppression in common receiver gather. These techniques were implemented in different stage during dada processing, mostly attenuate noises and keep seismic reflection uninjured. The final imaging data is of helpful for remaining oil development.