The Bohai Bay Basin is a Meso-Cenozoic rifted basin where the Paleozoic buried hills with great hydrocarbon potentials are well developed. The reservoir space types are complex and diverse due to tectonic activities, ...The Bohai Bay Basin is a Meso-Cenozoic rifted basin where the Paleozoic buried hills with great hydrocarbon potentials are well developed. The reservoir space types are complex and diverse due to tectonic activities, making fracture distribution highly heterogeneous. Reservoir identification and mapping is challenging due to their large burial depth and poor resolution of seismic data. An integration of well-logging, seismic data interpretation and core observation is applied to identify three structural unit types in the study area, that is, fault breccia zone, fault cataclastic zone, and fault massive rock zone. A comprehensive well-logging identification template and a comprehensive discriminant function M for the reservoir are established based on the well-logging response characteristics. A M value greater than 0.12 indicates a fault breccia zone, that between 0.04 and 0.12 marks a fault cataclastic zone, and that in the range from 0.02 to 0.04 represents a fault massive rock zone. A seismic prediction method with multi-parameter fusion is proposed in the study. The large-scale fractures are mapped by coherence-clutter parameters, while small fractures are predicted via waveform indication inversion. The spatial distribution of “fault-fracture reservoirs” is precisely mapped by frequency fusion technology. It is found that the fault breccia zones usually occur close to the fault planes, while the fault cataclastic zones are slightly away from the fault planes. The hydrocarbon abundance of the breccia zones is greater than that of the fault cataclastic and fault massive rock zones.展开更多
文摘The Bohai Bay Basin is a Meso-Cenozoic rifted basin where the Paleozoic buried hills with great hydrocarbon potentials are well developed. The reservoir space types are complex and diverse due to tectonic activities, making fracture distribution highly heterogeneous. Reservoir identification and mapping is challenging due to their large burial depth and poor resolution of seismic data. An integration of well-logging, seismic data interpretation and core observation is applied to identify three structural unit types in the study area, that is, fault breccia zone, fault cataclastic zone, and fault massive rock zone. A comprehensive well-logging identification template and a comprehensive discriminant function M for the reservoir are established based on the well-logging response characteristics. A M value greater than 0.12 indicates a fault breccia zone, that between 0.04 and 0.12 marks a fault cataclastic zone, and that in the range from 0.02 to 0.04 represents a fault massive rock zone. A seismic prediction method with multi-parameter fusion is proposed in the study. The large-scale fractures are mapped by coherence-clutter parameters, while small fractures are predicted via waveform indication inversion. The spatial distribution of “fault-fracture reservoirs” is precisely mapped by frequency fusion technology. It is found that the fault breccia zones usually occur close to the fault planes, while the fault cataclastic zones are slightly away from the fault planes. The hydrocarbon abundance of the breccia zones is greater than that of the fault cataclastic and fault massive rock zones.
