James E. Gaiser

Advantages of 3-D PS-wave data to unravel S-wave birefringence for fracture detection

Summary Delineating reservoir fractures by exploiting S-wave birefringence (splitting) is an important application of 3-D converted P to S-wave (PS-wave) data. In azimuthally anisotropic (AA) media, fracture intensities and orientations are directly related to traveltime differences between the fast and slow S-wave and the polarization direction of the fast S-wave, respectively. Issues of survey design and propagation effects due to attenuation and dispersion impact the ability to unravel these S-wave properties for fracture characterization. Data collected with wide azimuths is advantageous because it allows the estimation of fracture orientation independent of propagation effects and provides multiple-azimuth measurements.

Enhanced PS-wave Images And Attributes Using Prestack Azimuth Processing

Summary Recently, 3-D four-component (4-C) marine ocean-bottom cable (OBC) data has come into broad use for a variety of applications. The compressional wavefield (P-wave) is obtained from the pressure response of the hydrophone plus the particle-motion response from the vertical geophone. A converted P-wave to shear wavefield (PS-wave) is obtained from two horizontal geophones oriented in acquisition coordinates of in-line and cross-line receivers. The horizontal PS-wave data can be processed utilizing prestack azimuth information, the polarization and propagation direction, to yield components in other coordinate systems for specific exploration applications. For example, a single radial component, oriented in the source-r eceiver azimuth, is useful for lithology discrimination (Vp/Vs attributes), and for imaging in media that contains gas or high-velocity layers such as salt or basalt. A different 4-C coordinate system of horizontal displacements is needed to unravel the effects of birefringence and enhance shear-waves (S-waves) for inversion (impedance attributes) or fracture detection (Swave splitting orientation and intensity attributes).

Role of Salt Base Converted Wave Phase Shift In Subsalt Imaging

Limited P-wave transmission through a salt body can make it difficult to image deeper reflectors in seismic imaging. For certain P-wave velocity (Vp) and S-wave velocity (Vs) contrasts, efficient energy conversion can occur from Pwaves to Swaves within the high-velocity layer (HVL). This coupling may result in extending the range of usable energy on deeper targets. This extended range results in an improved stack before and after migration. Phase calculations using Zoeppritz’s equations can provide useful insights in data stacking predictions using mode-converted waves instead of conventional Pwaves.

3-D Acquisition Realities And Processing Strategies In Mountainous Thrust Areas

SS3.1 Summary The inherent structural complexity of thrust plays makes them ideal candidates for 3-D seismic imaging. However, there are many practical constraints placed on the acquisition of 3-D data in the mountainous terrains typically associated with thrust regimes. Financial considerations can result in tradeoffs between a desired acquisition geometry and that which is practical. Topographic relief can also impose irregular geometries and shortened receiver arrays. Such factors create challenges to the formation of a valid 3-D seismic image. Therefore, the realities of acquiring data in mountainous areas must be coupled to the appropriate processing strategies to yield an optimal result. Short Arrays and Prestack Noise Suppression Rugged topography is typical of thrusted environments. Therefore, to reduce the filtering action of the receiver array on primary data, it is common practice to use short, contoured arrays. Unfortunately, short arrays also minimize the attenuation of shotgenerated coherent noise. To solve such noise problems on 2-D data we commonly use methods such as f-k filtering. However, the irregular sampling in azimuth and offset, found in most land 3-D surveys, often precludes the use of 2-D methodologies. Additionally, directional variations in array response and azimuthal variations in the noise itself imply that data-adaptive methods are preferable for robust noise attenuation. One solution to the coherent noise suppression problem is an f-x domain technique that derives a least-squares estimate of the coherent noise from the data within a user-defined range of dips. The modeled noise may then be subtracted from the shot record. In practice, shot records are binned into azimuth ranges and then grouped by increasing offset. Each azimuthally-ordered record is individually analyzed for coherent noise. Figure la is a shot record showing the 11 azimuth bins (12.5 degree increment) with the greatest cross-line orientation. The sudden jumps in the mute pattern correspond to gaps in the offset sampling. Here, a range of dips was defined that spanned the steeply-dipping noise visible on the records. Figure lb shows the least-squares estimate of the coherent noise within the specified dip range. The amount of coherent noise present in the data appears greater than a casual inspection of the shot records would initially indicate. Finally, Figure lc is the shot record with the coherent noise subtracted. Acquisition Geometry and Refraction/Reflection Statics The problem of reflection-static decoupling may be present to some extent in all 3-D surveys. Static decoupling, commonly seen as a trace-to-trace jitter in the CMP stack, is usually symptomatic of unresolved long-wavelength statics. More precisely, the lack of statistical overlap from one CMP trace to the next in the longwavelength static solution gives the appearance of a high-frequency static problem, especially when the stacked data are viewed as 2-D profiles. In reality, adjacent CMP traces have converged on different and incorrect structural solutions. 3-D decoupling problems, as manifested by this CMP jitter, may be effectively addressed by the application of a running-average or so-called coupling filter on the structural term during the residual-statics solution. Although the obvious jitter disappears, the resultant smooth structural shape still contains unresolved long-wavelength static errors. Since the 3-D structural term may be coupled during processing, yet still contain long-wavelength errors, it is clearly inappropriate to design a survey with the sole idea of solving the decoupling problem. Figure 2a shows a common 3-D geometry with a 50 ms static anomaly located approximately at the center of the survey. The anomaly was introduced to a noise-free synthetic dataset derived from the acquisition geometry. The data were properly corrected for normal moveout prior to 10 iterations of 3-D Gauss-Seidell residual-statics decomposition. Ideally, an exact solution to the static anomaly would be derived, leaving no structural errors in the stacked response. However, Figure 2b shows a maximum structural error of approximately 10 ms and many sudden steps (decoupling jitter) in the structural-error surface when the coupling filters are not used. With the coupling filters applied, the structural-error surface (Figure 2c) is smooth (coupled) but still shows a maximum structural error of 5 ms. The results above are consistent with those derived from modeling a range of geometries (Wisecup, 1994) and confirm that realistic acquisition geometries alone cannot address static decoupling caused by unresolved long-wavelength static problems. The appropriate methodology is to design surveys to support 3-D refraction static solutions in order to minimize the long-wavelength static errors.