Claude Vuillermoz

Shear-wave velocity and density estimation from PS-wave AVO analysis: Application to an OBS dataset from the North Sea

S-wave velocity and density information is crucial for hydrocarbon detection, because they help in the discrimination of pore filling fluids. Unfortunately, these two parameters cannot be accurately resolved from conventional P-wave marine data. Recent developments in ocean‐bottom seismic (OBS) technology make it possible to acquire high quality S-wave data in marine environments. The use of (S)-waves for amplitude variation with offset (AVO) analysis can give better estimates of S-wave velocity and density contrasts. Like P-wave AVO, S-wave AVO is sensitive to various types of noise. We investigate numerically and analytically the sensitivity of AVO inversion to random noise and errors in angles of incidence. Synthetic examples show that random noise and angle errors can strongly bias the parameter estimation. The use of singular value decomposition offers a simple stabilization scheme to solve for the elastic parameters. The AVO inversion is applied to an OBS data set from the North Sea. Special prestac...

Three‐dimensional multicomponent imaging of reservoir heterogeneity, Silo Field, Wyoming

The Reservoir Characterization Project at Colorado School of Mines acquired a three‐dimensional (3-D) multicomponent survey over Silo field in southeastern Wyoming with the objective of imaging reservoir heterogeneity. A 3-D shear‐wave survey resolved spatial variations in the fracture distribution of Niobrara chalks by detecting small percentages of anisotropy induced by fractures in chalks of the Niobrara reservoir. In addition, the compressional‐wave survey imaged structural drape over a zone of deeper salt dissolution, which fractured the brittle chalks. Rotation analysis of the shear‐wave survey took advantage of its 3-D nature to identify an azimuthal pattern of anisotropy associated with vertical fractures, known as extensive dilatancy anisotropy (EDA). The shear‐wave data were sorted by shot‐to‐geophone azimuth to search for the orthorhombic pattern of anisotropy that might be expected from the combined effects of sedimentary layering and vertical fractures, but it was not found at Silo Field. Alt...

Technology and economy of ocean bottom nodes on the first anniversary of the first 5C crew

Ocean bottom seismometers and surface towed streamers are known methods. They each have well understood advantages and disadvantages. The most significant advantage of the streamers is their efficiency in covering large areas at a low cost per km square. While data quality and the usefulness of wide azimuth, demultiple, and shear waves is field specific and is often debated, a clear advantage of ocean bottom seismometers is our ability to use them in obstructed areas such as active oilfields. Nodes are better than cables in the presence of seabed obstructions. Streamers and ocean bottom seismometers therefore complement each other. If one adds a streamer element to an ocean bottom node crew, one can provide the two methods at the same time as a seismic monitoring snapshot. The point of this paper is to share the experience of a crew with both nodes and a streamer on its first anniversary.

Evaluation and impact of sparse‐grid, wide‐azimuth 4C‐3D node data from the North Sea

For DEMO 2000 a consortia comprising of SeaBed Geophysical, SINTEF, Statoil, Norsk Hydro and TotalFinaElf submitted a proposal entitled IMPREDO or “improved prediction and delineation of hydrocarbon filled reservoir zones using high-quality four-component seismic data acquired in 3D at the seabed”. In July 2002 the consortia had an opportunity to record data on the Volve field during a conventional OBC survey. This was the first opportunity to deploy the node system in a fullscale offshore test and prove the reliability and capability of the system to acquire high quality, high vector-fidelity seismic data. The field chosen for the project, Volve, is located in Block 15/9 west of Haugesund, Norway, and the water depth is between 80 m and 90 m. To cover the area of interest a total of 128 units were deployed in a 400m grid covering an area 6 km by 2.8 km. The shooting grid of the conventional OBC survey required 6 overlapping swaths providing narrow azimuth data whereas the same shots used in this survey provide wider cross-line offsets due to a larger active receiver area. Evaluation and impact of sparse-grid, wide-azimuth 4C-3D node data from the North Sea Andrew Morton, Geir Woje, Anne Rollet, Eivind W. Berg, Claude Vuillermoz 1 SeaBed Geophysical, Transitt gt 14, N-7042 Trondheim, Norway. 2 CGG, 1 rue Leon Migaux, 91341 Massy cedex, France

Long-Wavelength Static Definition Through Partial Common-Midpoint Stacks

Modeling and spatial scanning of stacking velocity anomalies have usually been used to define long-wavelength residual statics. Basically, such methods involve differences between reflection times of different offset races. Direct comparison of partial common-midpoint stacks leads to equivalent results. Moreover, this approach facilitates the definition of the wavelength range that can really be covered. The response of the procedure is not constant within that range; it may be corrected in two ways: (1) Compensation of amplitude response can be computed and apIlied in the wavelength domain, provided the signal-to-noise ‘S/N) ratio is high enough. (2) Reiteration of the procedure is nore cumbersome, but can be applied to eliminate the remaining momalies, even when the S/N ratio is only fair. The affordable wvelength range depends on the offset difference of the partial tacks. In any case, some criteria must be defined to dispatch ime differences between very long wavelength statics and residal normal moveout.

Comparing 3‐D operations and results from convertedP‐Swaves

Concerning data processing, the asymmetry of the PS raypath is sometimes given as a drawback. In fact the CRP gather can be easily mastered at the level of a given target. If necessary timevariant techniques can be applied to make the gathering correct at anytime. Static corrections in SS mode are more difficult to master, whereas PS mode benefits from already known source statics. This alone makes data processing for PS mode much faster than for SS mode. A further problem with SS mode is the overlapping of the frequency spectra of the source generated noise and of the signal.