Fig 1.
Block structure location in the Yueman area.
Fig 2.
Comparison between forward model data volume and forward geological model.
(a) Geological model; (b) Reverse time migration data volume from the forward model.
Fig 3.
Attribute fracture recognition profiles compared to the forward model profile.
(a) Geological model; (b) seismic forward modeling data volume, with a sampling rate of 2 ms and dominant frequency of 25 Hz; (c) coherence attribute profile; (d) curvature attribute profile; (e) gradient structure tensor attribute data volume; and (f) amplitude attribute.
Fig 4.
Comparison of optimal surface voting fracture identification profile with forward model profile.
(a) Forward model profile; (b) Seismic record profile; and (C) Optimal surface voting fracture identification profile.
Fig 5.
Comparison of seismic record with optimal surface voting fracture identification profile with 25 m trace spacing.
(a) Seismic record profile with 25 m trace spacing; (b) Optimal surface voting fracture identification profile with 25 m trace spacing.
Fig 6.
Comparison of equal depth slices from optimal surface voting fracture identification with forward model slices.
(a) equi-depth slice of the model at 7000 m; (b) fault detection results of our method at 7000 m; (c) equi-depth slice of the model at 7800 m; and (d)fault detection results of our method at 7800 m.
Fig 7.
(a) the forward-simulated seismic data and (b) actual seismic data from the study area.
Both exhibit certain characteristic similarities. However, it is evident from the actual data that the seismic data quality of the target layer segment in the study area is poor.
Fig 8.
Tarim Basin area seismic record (profile).
The energy of the fault breakage zones is uneven, and the reflection characteristics are chaotic.
Fig 9.
Tarim Basin area multi-attribute optimal surface voting fault identification data volume (profile).
Fig 10.
Tarim Basin area strike-slip fault identification data volume overlaid with seismic record (profile).
Fig 11.
Tarim Basin Yueshan area strike-slip fault identification along layer slice.
The fault identification results are clear and can effectively identify minor faults.
Fig 12.
Strike-slip fault identification profile passing through well Y2 within study area.
The fault identification results are consistent with the seismic profile characteristics.