Common Image Point (CIP) Tomography | Schlumberger

Common Image Point (CIP) Tomography

High-resolution, multiscale, anisotropic hybrid tomography

Our 3D grid, multiscale, common image point tomography (CIP-tomo) provides you with industry-leading quality and resolution. Suitable for marine, land, and ocean bottom seismic geometries, CIP-tomo has a proven track record for producing detailed, accurate anisotropic earth models in the most challenging geological settings: from complex salt environments in the Gulf of Mexico, offshore West Africa, and Brazil to fault shadows and gas clouds in offshore Southeast Asia, Australia, and the North Sea; permafrost conditions in Alaska and Siberia; and mud volcanoes in the Caspian Basin.

CIP-tomo is a generalized reflection tomography method that uses residual moveout (RMO, residual curvature) analysis of prestack depth-migrated CIP gathers to update an initial model. Multiparameter (nonhyperbolic, general, or nonparametric) RMO is automatically estimated from offset vector tile (OVT) or angle gathers. The input model is a space-partitioned hybrid model representation that enables the isolation of different geologic units in the model space. This facilitates the application of geological and other constraints and the implementation of multilayer tomography. In addition, it supports the application of flexible weighting schemes. For challenging subsalt areas, CIP-tomo has the capability to update from migration scan input.

CIP-tomo is suitable for both compaction-driven (where velocity heterogeneity is dominated by a compaction gradient) and layered (where velocity heterogeneity is dominated by lithology or age) geologic environments. Its multilayer capability is flexible and enables inverting for property updates in specific layers or zones. It can account for transversely isotropic (TI) media and orthorhombic (OR) media with a vertical (VTI and VOR) or tilted (TTI and TOR) axis of symmetry, with different combinations of parameters updated as needed. Depending on the geology, data type (including converted modes), and anisotropy class, the most suitable tomographic inversion scheme can be applied to achieve optimal results.

Multiple tomographic iterations provide high resolution detail of velocity variations above top-salt in this Gulf of Mexico example.
Multiple tomographic iterations provide high-resolution detail of velocity variations above top of salt in this Gulf of Mexico example.

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