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Objective The C-6 oilfield is one of the main oilfields in the billion ton Caofeidian oilfield group of the Bohai Sea. Its main development layer is the Guantao Formation III oil formation （N1gIII）， which is a set of sand rich braided river sediments. The connectivity of the internal reservoir is not yet clear， restricting the improvement of oilfield development efficiency. Methods The intelligent fusion technology of seismic attributes based on a deep feedforward neural network （DFNN） was used to finely characterize the spatial distribution of the fourth level configuration units in the braided river reservoir of the oilfield under the calibration of limited logging information. Results Based on log interpretation， N1gIII of the C-6 oilfield mainly contains two types of level-4 architectural units： channel bar and braided channel； braided bar is the best reservoir with high sandstone thickness and excellent physical properties. Based on seismic attribute extraction and correlation analysis with lithological and physical parameters， reflection intensity， relative impedance， sweet point， original amplitude， and envelop were chosen as intelligent fusion seismic attributes with the DFNN algorithm with porosity. The three-dimensional （3D） attribute of DFNN fusion， representative of lithology and petrophysical property， largely improves the detecting ability of the braided river sandstone unit and its boundary. A NE-SW braided flow zone was developed in N1gIII of the C-6 oilfield and could be internally sub-divided into 15 rhombic level-4 architectural units. Distributary channels， another level-4 architectural unit， surrounded the braided bar in a narrow strip. The level-4 architectural interface between the two units acted as seepage barriers for fluid migration. The braided bars cut and overlapped one another vertically， forming a “big bar and small channel” plan reservoir architectural pattern. Conclusions The fine characterization of reservoir architecture based on the intelligent fusion of seismic attributes deepens our understanding of the connectivity of braided river reservoirs controlled by sparse well networks， providing direct geological basis for the adjustment of the C-6 oilfield development plans， and has certain significance for the fine characterization of reservoir architecture in oil fields with the same sedimentary type under offshore sparse well network conditions..
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| 科 Family | 属数 Number of genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) | 属 Genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) |
|---|---|---|---|---|---|---|
| 鹅膏菌科Amanitaceae | 2 | 11 | 5.26 | 鹅膏菌属 Amanita | 10 | 4.78 |
| 小菇科 Mycenaceae | 2 | 12 | 5.74 | 丝盖伞属 Inocybe | 5 | 2.39 |
| 多孔菌科 Polyporaceae | 8 | 14 | 6.70 | 蜡蘑属 Laccaria | 5 | 2.39 |
| 红菇科 Russulaceae | 3 | 23 | 11.00 | 小皮伞属 Marasmius | 6 | 2.87 |
| 小菇属 Mycena | 11 | 5.26 | ||||
| 光柄菇属 Pluteus | 5 | 2.39 | ||||
| 红菇属 Russula | 17 | 8.13 | ||||
| 栓菌属 Trametes | 5 | 2.39 |
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