Citation: | QIN Dewen, ZHANG Yan, YU Jie. “Sweet spot” prediction technique for mid-deep low permeability gas reservoirs in M Structure of East China Sea[J]. Marine Geology Frontiers, 2024, 40(4): 83-91. doi: 10.16028/j.1009-2722.2023.138 |
In recent years, structural-lithological complex reservoirs have gradually become the key in reservoir expansion and production in the East China Sea. The low permeability gas reservoir in the middle and deep low-permeability gas reservoir in the M Structure of the East China Sea was studied. The study area has large burial depth, strong internal heterogeneity, and complex porosity-permeability relationship, but little difference in geophysical response characteristics. It is urgent to study the fine characterization of sweet spot reservoir in the reservoir. Seismic rock physics were analyzed, in which the Young’s impedance was used to distinguish clastic rock reservoir from non-reservoir. By classifying and optimizing parameters in seismological profiling, shear modulus was found and used as a comprehensive sensitive elastic factor, and combined with a high sensitivity hydrocarbon detection factor, clear clean, coarse-grained, and high-permeability high quality reservoirs could be detected. In addition, to reduce the influence of rock skeleton porosity, a highly sensitive fluid factor was used to detect hydrocarbons. Finally, combined with lithology and attributes of hydrocarbon detection, good sweet spot reservoir areas were finely characterized. Results show that the sweet spot prediction using this method reached a high successful prediction rate of 86.07%, which provided an important basis for well deployment and trajectory optimization and a reference for working on similar blocks.
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The location and tectonic background of the study area
Comparison in precision of different reflection coefficient equations
Flow chart of seismic prediction for sweet spot reservoir
Litho-physical analysis of seismic sensitive attributes
Quantitative analysis of fluid sensitivity of different elastic parameters
The primal set (a) and optimized set (b) of pre-stack angles
The data inversion results of reservoirs in the study area
Horizontal distribution of sweet prediction at the main layer H3 in the study area