There are immerging technologies related to volume-based fault interpretation using automated fault extraction that can be integrated and used with other volume-based interpretation and model building workflows.
This talk will present the steps required to produce high-quality structural interpretations of 3D volumes using coherency attributes as input for Automatic Fault Extraction (AFE) processes. The AFE process will be discussed and visualizations of various outputs from this process will be shown. We will then show how the results of the AFE process can be integrated into horizon auto-tracking interpretation and 3D model building workflows.
Fault interpretation still remains one of the most time-intensive areas faced by seismic interpreters today. As this is mostly a manual process, it is also an area prone to error. During the initial interpretation of 3D seismic volumes, the importance of fault scale is not clearly understood. Small scale faults are often not interpreted due to time constraints. Similarly, in extensively fractured reservoir, it is not practical (or possible) to pick all faults at all scales even though they are visible on coherency-type volumes. Volume-based fault extraction resolves this issue.
The processes and methods we describe in this paper are aimed at removing interpretational bias from the fault picking process with the goal of improving the quality and accuracy of fault plane interpretation. The AFE process will be an important approach in interpretation of new or unfamiliar 3D volumes, allowing the interpreter to get an unbiased quick look at fault distributions and geometries. AFE will also be particularly useful in areas where complex geometries are not clearly understood and play a roll in reservoir distribution and compartmentalization.
