Analysis of seismic anisotropy in 3D multi-component seismic data
The importance of seismic anisotropy has been recognized by the oil industry since its first observation in hydrocarbon reservoirs in 1986, and the application of seismic anisotropy to solve geophysical problems has been keenly pursued since then. However, a lot of problems remain, which have limited the applications of the technology. Nowadays, more and more 3D multi-component seismic data with wide-azimuth are becoming available. These have provided more opportunities for the study of seismic anisotropy. My thesis has focused on the study of using seismic anisotropy in 3D multi-component seismic data to characterize subsurface fractures, improve converted wave imaging and detect fluid content in fractured reservoirs, all of which are important for fractured reservoir exploration and monitoring. For the use of seismic anisotropy to characterize subsurface fracture systems, equivalent medium theories have established the link between seismic anisotropy and fracture properties. The numerical modelling in the thesis reveals that the amplitudes and interval travel-time of the radial component of PS converted waves can be used to derive fracture properties through elliptical fitting similar to P-waves. However, sufficient offset coverage is required for either the P- or PS-wave to reveal the features of elliptical variation with azimuth. Compared with numerical modelling, seismic physical modelling provides additional insights into the azimuthal variation of P and PS-wave attributes and their links with fracture properties. Analysis of the seismic physical model data in the thesis shows that the ratio of the offset to the depth of a target layer (offset-depth ratio), is a key parameter controlling the choice of suitable attributes and methods for fracture analysis. Data with a small offset-depth ratio from 0.7 to 1.0 may be more suitable for amplitude analysis; whilst the use of travel time or velocity analysis requires a large offset-depth ratio above 1.0, which can help in reducing the effect of the acquisition footprint and structural imprint on the results. Multi-component seismic data is often heavily contaminated with noise, which will limit its application potential in seismic anisotropy analysis. A new method to reduce noise in 3D multi-component seismic data has been developed and has proved to be very helpful in improving data quality. The method can automatically recognize and eliminate strong noise in 3D converted wave seismic data with little interference to useful reflection signals. Component rotation is normally a routine procedure in 3D multi-component seismic analysis. However, this study shows that incorrect rotations may occur for certain acquisition geometry and can lead to errors in shear-wave splitting analysis. A quality control method has been developed to ensure this procedure is correctly carried out. The presence of seismic anisotropy can affect the quality of seismic imaging, but the study has shown that the magnitude of the effects depends on the data type and target depth. The effects of VTI anisotropy (transverse isotropy with a vertical symmetry axis) on P-wave images are much weaker than those on PS-wave images. Anisotropic effects decrease with depth for the P- and PS-waves. The real data example shows that the overall image quality of PS-waves processed by pre-stack time migration has been improved when VTI anisotropy has been taken into account. The improvements are mainly in the upper part of the section. Monitoring fluid distribution is an important task in producing reservoirs. A synthetic study based on a multi-scale rock-physics model shows that it is possible to use seismic anisotropy to derive viscosity information in a HTI medium (transverse isotropy with a horizontal symmetry axis). The numerical modelling demonstrates the effects of fluid viscosity on medium elastic properties and seismic reflectivity, as well as the possibility of using them to discriminate between oil and water saturation. Analysis of real data reveals that it is hard to use the P-wave to discriminate oil-water saturation. However, characteristic shear-wave splitting behaviour due to pore pressure changes demonstrates the potential for discriminating between oil and water saturation in fractured reservoirs.