Three-dimensional seismic modeling : velocity analysis and interpretation

In this research, interpretations based on theoretical and physical modeling data are given in the hope that they can be useful to the seismic interpreter for discerning pitfalls in real data. Recognition of these pitfalls could be an additional aid in the area of seismic interpretation. As for the theoretical modeling, several interpretational pitfalls were identified when a systematic analysis was carried out with respect to three basic geological structures: basins, domes and partial reflectors. The pitfalls identified include: apparent pinchouts and grabens which were related to the profile line direction; extra reflection layers related to the depth of the model and the areal size of the structure; cross-stratifications related to the profile line direction and the areal size of the structure; faults or extra events related to the data acquisition schemes; weak events related to the processing flow; apparent "ambient noise" related to structural dip change; etc. As for physical modeling, both the lateral and vertical velocity variations in a 3-D environment were evaluated and several pitfalls were identified. These pitfalls include: a dim spot which was related to an overlying high-velocity lens; a bright spot related to an overlying low velocity lens; an apparent velocity pullup where actually a velocity pushdown should be observed; a low frequency disturbed zone under the lens having a high velocity contrast; the "thick lens" effect which distorted the appearance of the true structure; the wave conversion within sharply curved 3-D structures which is yet an unsolved problem of converted wave; ghost events which result from wavelet processing; etc. Also in this research, three different velocity analysis algorithms were developed and evaluated for areally gathered seismic data. The first velocity algorithm was designed for data gathered by closely spaced conventional GDP lines. An optimum stacking velocity along with the apparent dip were obtained. The second velocity algorithm was designed for areal common-mid-point data. A migration velocity along with strike and dip were obtained. The third velocity algorithm was designed for multi-midpoint data such as would be gathered in a crooked-line survey. An optimum stacking velocity as a function of dip and strike and a final migration velocity were obtained. These velocity algorithms offered a new processing flow which was applied on the crooked-line data using the output parameters derived from the third velocity algorithm. A satisfactory depth reconstruction was obtained and it proved that the processing flow and velocity algorithm were correct.