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Fluvial Reservoir Architecture Characterization of Mature Oilfields With Seismic Sedimentology Method


Reservoir architecture was generally characterized with outcrops and wells. But in petroleum reservoir study, it is found that interwell reservoir architecture is not clear even in mature oilfields with dense well net. In this study, a seismic sedimentology method is developed to characterize reservoir architecture of point bar complex. There are 3 challenges: 1) thin bed VS seismic resolution limit; 2) mismatch of different data including seismic data, well logs and dynamic oil production data; 3) geological meaning of seismic reflection in thin bed. In this case study, 3D seismic data, drilling cores, well logs and production data of 200 wells (include 5 drilling core wells) are used. This work is focused on three levels of reservoir architectures: sedimentary microfacies (point bar complex), single point bar and lateral accretion sand body. In study of the first and second levels, seismic interpretation technologies, such as seismic facies analysis, strata slice and multi-seismic attributes analysis, are used. For lateral accretion body characterization, seismic technologies (including frequency decomposition and reconstruction, seismic attributes and slice interpretation), sedimentology analyzes methods, quantitative knowledge base and dynamic production data (including water and tracers injection data) are integrated. Main lateral accretion boundaries are recognized in this result. In this study, the area, which was thought to be a single point bar deposition, is proved to be formed by a point bar complex. It has three single point bars which were formed in different periods. Point bar #1 was formed in the first period, and then point bar#2 eroded it. Point bar #3 was formed in the last deposition period. They formed very complex and heterogeneous reservoir. Such a deposition process can also be observed in modern depositions. This seismic interpretation result has been verified by well logs of new wells and production data. This result is very important in prediction and development of remaining oil.