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. Although groundroll contaminated some of the “pie slices” of azimuth in the rotation analysis, the redundancy of ten “pie slices” enabled us to determine an overall fracture orientation of N 58° W. The 3-D shear‐wave survey yielded a picture of fracture variability that could not be determined from well control alone. Fracture‐identification logs and production records were used in interpreting the anisotropy determined from the shear waves. Large positive values of anisotropy in the Niobrara interval, up to 5 percent, coincided with good producers in the field, while smaller magnitudes of anisotropy were tied to poor producers. Combining the multicomponent seismic recording with 3-D survey techniques added lateral resolution to the reservoir description and rendered a more complete understanding of the pattern of anisotropy resulting from fractures in the reservoir.

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 prestack processing techniques are required for the success of S-wave AVO inversion. The derived S-wave velocity and density contrasts help in detecting the fluid contacts and delineating the extent of the reservoir sand.

No abstract

No abstract

In July 2002 a 3D multi-component survey was recorded on a North Sea field as part of the DEMO 2000 sponsored IMPREDO project. The recording systems deployed were autonomous nodes: the result of over 5 years of research, development and testing of 4C systems. The PP dataset has been successfully processed with full 3D pre-stack time migration.