ffA's Subsurface Information Volumes bring efficiency improvements in seismic interpretation and geological modelling

The Project:

The brief ffA received from StatoilHydro was to investigate and compare manual high-density fault interpretations with the Subsurface Information Volumes generated by ffA's fault imaging software & services.

The Volumes:

The host dataset was a Reflectivity Volume from an exploration block in the Norwegian North Sea. The dataset covers a region characterised by a high density of intersecting faults that proved time consuming to interpret using conventional techniques. ffA's "Fault Attribute", "Fault Image" and "Fault In" Subsurface Information Volumes fast-track fault interpretation by indicating the likelihood that a fault exists at any given point in the dataset,automatically extracting 3-D objects representing the most likely fault sections and providing a volume for visualising the detected potential faults within the original seismic data.
The volumes were created at ffA's dedicated services centre in Aberdeen and illustrate the quality of results achievable by asset geoscientists using ffA's image processing and analysis software.

The Results:

StatoilHydro concluded that ffA's fault imaging volumes have the potential for substantially improving the efficiency of the fault interpretation and geological modelling work processes.

• There was a good match between Fault Image and the majority of the manual interpretation.

• Fault Image was able to highlight faults not identified in the original interpretation due to their small throws. These faults were then further investigated and considered for incorporation into the fault model.

• Fault Volumes provided valuable information on the geometric relationship between branching faults and their "master" faults.

• ffA were able to provide an accurate and detailed overview of the complex faulting within the dataset within days. A process that, when undertaken using conventional techniques, had previously taken StatoilHydro substantially longer.

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Fault Image (high probability of faulting in orange) embedded in FaultAttribute (greyscales - highest probabilities in black) with Reflectivity Volume behind. Fault Image shows the planar sections of highest fault likelihood in the Fault Attribute

Fault Image shows in grey high probabilities of faulting.

Manual fault interpretations (above in multiple colours) when placed onto the Fault Image Volume show a close correlation between the conventional and ffA's automated interpretation techniques