CGG InsightEarth® 3D Seismic Analysis
Gustavson Associates has unique access and expertise in the utilization of the CGG InsightEarth® 3D Seismic post-processing, visualization and interpretation software. The software is utilized by major petroleum companies for reservoir characterization and salt and stratigraphic geobody modeling, well location optimization, storage reservoir delineation, unconventional reservoir analysis, fracture detection, precise fault placemen resulting in improved interpretation, accuracy and speed.
InsightEarth Services achieve client objectives of cost-effective interpretation and drilling and reservoir risk mitigation.
InsightEarth® Software Services
Gustavson Associates LLC provides 3D seismic post processing visualization and interpretation services to the petroleum industry. Gustavson geoscientists utilize the innovative CGG InsightEarth® Software platform to reduce project risk for our multinational and large independent clients. Use of 3D seismic data attributes and specialized post-stack processing services delineate amplitude anomalies and stratigraphic and structural details concealed in existing seismic data processing. Completed projects include salt, stratigraphic and structure models of the Gulf of Mexico Onshore, Gulf of Mexico Shelf and Deep Water Offshore, South Atlantic, Kazakhstan, Africa Offshore, North Sea and Peru Onshore and Offshore. These models include supra and subsalt reservoirs. Gustavson has completed several facies and fracture models of reservoirs from numerous basins of the North America interior.
Risk Reduction Client Services
- Geo-body Modeling – Accurate Vertical and horizontal salt and other geobody models – mitigates drilling risk
- Stratal Domain – Stratal slice volumes of paleo-depositional surfaces through transformation of the accurate time or depth volume structure interpretation – mitigates interpretation errors
- Edge Detection – Precise and rapid fault, horizon and fracture analyses attributes for conventional and unconventional plays
- Automated Fault Extraction (AFE) – Multiple fault plane surfaces extracted by 3D algorithm-based automated function – saves time, mitigates interpretation errors
- Post Stack Volume Conditioning – Seismic volumes conditioned by acquisition footprint removal, statistical filtering and structure/voxel attribute post processing – provides a more accurate data volume for mapping, mitigates interpretation errors
Geobody Modeling
Salt and other stratigraphic geo-body models are created through co-rendering a maximum of four amplitude and attribute volumes permitting the precise definition of facies boundaries. Depicted below is a 3D triangulated mesh image of a piercement salt dome. The modeling of salt wings and overhangs is accomplished by incorporating multi-Z dimensions.
Stratal Slices (Paleo-Depositional Surfaces) and Structural Accuracy
Removal of structure deformation and flattening the volume processes reveal stratigraphic slices that represent paleo-surfaces. Rendering the volume into stratal slices provides a unique view of the data as shown below. Each stratal slice generated is inverse-transformed into the current structural domain as a new horizon with stratigraphic information.
Edge Detection Attributes
Edgestack and curvature processes based on structure tensor analysis produce Edge Detection Attributes. The resulting 3D volumes are a visual representation of the edges in the seismic data. The plan view below is the Edgestack process result showing detailed fault patterns (edges).
3D Fault Extraction Process
Fault surfaces are generated through an interpreter-guided automated methodology based on proprietary algorithms. The 3D image below illustrates accurate fault planes generated using all inlines and crosslines.
Post Stack Volume Conditioning
The Acquisition Footprint Removal process is a coherent noise filter based on Landsat imagery algorithms that remove linear artifacts from an amplitude volume [S1 (before process), S2 (after process)]. The statistical filter process clarifies features in noisy data by removing random artifacts using xyz vector information [S3 (before process), S4 (after process)]. The result of this process is an edge-preserved coherent data volume.