No abstract

Conventionally, interval velocities are derived from picked stacking velocities. The velocity-analysis algorithm proposed in this paper is also based on stacking velocities; however, it eliminates the conventional picking stage by always considering stacking velocities from the point of view of an interval-velocity model. This view leads to a model-based, automatic velocityanalysis algorithm.The algorithm seeks to find an interval-velocity model such that the stacking velocities calculated from that model give the most powerful stack. An additional penalty is incurred for models that differ in smoothness from an initial interval-velocity model. The search for the best model is conducted by means of a conjugategradient method.The connection between the interval-velocity model and the stacking velocities plays an important role in the algorithm proposed in this paper. In the simplest case, stacking velocity is assumed to be equal to rms velocity. For the more general case, a linear theory is developed, connecting interval velocity and stacking velocity through the intermediary of traveltime. When applied to a field data set, the method produces an interval-velocity model that explains the lateral variation in both stacking velocity and traveltime.

No abstract

No abstract

Depth imaging technology plays an essential role in decisions made at both the exploration and development phases of a project. This talk concentrates on examples taken from field development, in particular one example in which a large, shallow and spatially varying gas zone has severely degraded the conventional, post-stack migrated seismic image of a large oil field. Through the application of prestack depth migration, we are able to dramatically improve on these seismic images, resulting in an improved understanding of the geometry of the structure. The key to improving the seismic images through prestack depth migration is the construction of an accurate and spatially consistent interval velocity model. In the shallow gas example shown here, the well information is too sparse to accurately capture the spatial variation in velocities. Thus, we achieved the required accuracy of the interval velocity model through the application of iterative 20 prestack depth migration and seismic tomography along closely spaced analysis lines. We achieved the spatial consistency of the interval-velocity model through careful, interpretive analysis of the velocity volume assembled from the set of 20 lines. The velocity and depth information provided by the well control is introduced as part of this interpretive analysis. This shallow gas example differs from much of our imaging work in its concentration on 20 velocity analysis and migration. However, this example and the more fully 3D examples follow the same basic approach: they integrate localized velocity measurements into a full 3D velocity model, subject to the constraints of the well control. Thus, many of the same model-building techniques and issues apply to the 3D examples. We believe this 3D model-building experience is critical to the success of our imaging efforts. Introduction In recent years, depth imaging technology has matured to become a standard component of geophysical analysis. This paper presents examples of the application of that technology to field appraisal, in particular one example in which a large, shallow and spatially varying gas zone has severely degraded the conventional, post-stack time-migrated seismic image of a large oil field. Figure I shows the conventional time image of an oil field in offshore Angola. The image of the relatively shallow reservoir interval (at about 700 – 800 msec), is both unclear and distorted. The cause of the distortion is shown in the cross section in Figure 2: overlying layers contain significant quantities of gas. This shallow gas serves to both attenuate the seismic waves that pass through it, and create substantial lateral velocity gradients, which distort the associated wavefronts. Because of the potential hazards of drilling through these high-pressure, shallow-gas layers, a high resolution 20 hazard survey (cross-line spacing of 100m) was conducted in the area. Figure 3 shows the acquisition parameters. Of particular note are the very short cable (600 m) and the very wide-band recording filter (8–256 Hz), both of which are consistent with the stated purpose of this survey: to delineate shallow gas zones. In addition to serving this stated purpose, the survey also provided us with a low-cost opportunity to improve the quality of the seismic image through the application of depth-imaging technology.