vi 4-266 pp. Price $62.00.The art of interpreting seismic reflection data is an interesting mix of physical science and geologic intuition. Successful interpretation of seismic data requires experience, a solid geologic understanding of the area being investigated, and an appreciation of data acquisition and processing issues. In Practical Seismic Interpretation, Michael Badley presents an introduction to the geological aspects of interpretation, writing primarily for the inexperienced interpreter working in hydrocarbon exploration. While this volume contains many interesting seismic data examples, some distinct weaknesses make this an uneven overview of a complex subject.After a brief introduction outlining seismic data acquisition, processing, and interpretation, the book is organized as follows: Chaps. 2 and 3 cover fundamental seismic reflection theory and the common data problems of noise and velocity distortion; Chap. 4 discusses the reflection response of some basic geologic features; Chap. 5 covers the seismic expression of geologic structures such as faults and folds; Chaps. 6 and 7 give an overview of the many different types of data that support a seismic interpretation and describe one approach to the mechanics of interpreting a survey; Chap. 8 describes the preparation of structural maps from interpreted seismic sections; and finally, Chap. 9 contains a valuable collection of questions and answers.Badley's volume is packed with examples of the diverse types of geology revealed by the seismic reflection method. Many seismic sections are shown with and without interpretation, and several examples concern noise problems that interpreters must confront. The wealth of visual material, along with a step-by-step description of the mechanics of seismic interpretation, are the strongest points of this book for those unfamiliar with seismic interpretation. The final section of questions is thought-provoking and lends further insight into the material in preceding chapters. This volume, however, has a number of serious shortcomings. Although Badley states that the book is not intended as a comprehensive discussion of the seismic reflection method, his discussion of seismic data processing is particularly weak. The quality of data processing is crucial to the image finally presented for intrepretation, but Badley outlines the standard data processing sequence in less than a page (plus subsequent short discussions of individual issues). One is left with the impression that data processing can be neatly treated as a separate subject, and that all the interpreter need do is learn the rules of decyphering the processed traces. In fact, a significant trend of the last decade has been to integrate the once-separate stages of seismic reflection surveys; data acquisition, processing, and interpretation need to be carefully coordinated in order to understand the more subtle targets of exploration. The interpretation of seismic data also requires understanding the geologic framework of the area being explored. While Badle...
Various wave‐scattering mechanisms are known to degrade reflection signals by producing noise in seismic reflection data. Synthetic 2-D acoustic‐wave finite‐ difference data sets illustrate the effects of two such mechanisms. Twenty‐five shot gathers were generated for each of two models and the data were processed as standard CMP surveys. In one model, an irregular low‐ velocity surface layer produced multiply scattered surface waves that appear as linear noise trains in common‐shot gathers and stacked sections. The scattering of upcoming reflections at the lower interface of the layer also produced a significant amount of noise. When predictive deconvolution was applied before stack to reduce reverberations, the spectral character of the scattered surface waves seriously inhibited the action of that process. In the second model, a zone of smooth, random velocity variation was imposed between two reflectors deeper in the model. The heterogeneous zone (±5 percent rms velocity variation) substantially degraded the signal reflected from below it; events produced by body‐wave scattering are characterized by higher phase velocities than those seen in the first model. Conventional CMP stacking produced discontinuous subhorizontal events from the disturbed zone. The limited bandwidth of the propagating signal and spatial filtering attributable to CMP stacking cause these events to bear no simple relation to the velocity anomalies of the model, even after migration.
Model studies with finite‐difference synthetic data demonstrate a fundamental spatial bias in the appearance of common‐midpoint (CMP) stacked images. The CMP stack of data recorded over a target having 2-D random variations in velocity shows numerous short reflection segments; similar reflection patterns in field data are often interpreted in terms of 1-D fine‐scale layering. The stacked image appears layered because of enhanced lateral continuity attributable to the well‐known dip filter of the stacking process. The stack filter can be characterized using the formulation of Bolondi et al. (1982). Lateral correlation in the target and its seismic image is quantified with a measure based on the spectral coefficient of coherence. Broadband primary reflectivity (defined as the vertical‐incidence, primaries‐only reflection coefficients of the 2-D target) is often taken as an ideal seismic image. The primary reflectivity section of a 2-D random target, however, shows greater apparent lateral correlation than is present in the random structure. This apparent increase in lateral continuity is attributable to the fact that reflectivity measured from the surface depends on the vertical derivative of velocity but depends on horizontal changes in velocity directly. The dip‐filtering effects of stacking cannot be reversed by poststack migration; the synthetic data demonstrate the necessity of migration before stack or equivalent processing (such as dip moveout correction). A field data example illustrates the effects of CMP stack filtering using lateral coherence functions measured on stacked and unstacked sections.
The character of deep reflections recorded in wide‐angle seismic experiments often suggests fine‐scale layering in the structure of the reflecting target. The lateral continuity of wide‐angle reflections is enhanced, however, because energy arriving at a long‐off set receiver is confined to a narrow range of apparent slowness. The distribution of energy with slowness was studied by Levander and Gibson (this issue), who show that the restricted range amounts to a dip filter. Their energy‐slowness distribution is used here to relate lateral correlation in a reflected wave field to the correlation properties of a randomly heterogeneous target. Tests with finite difference synthetic data from Levander and Gibson confirm a simple convolutional relation between the statistics of the wave field and those of a target with small‐magnitude velocity variations. Field data recorded in the Basin and Range Province, Nevada, show a progressive increase in reflection continuity with increasing source‐receiver offset, as expected. Interpretation of reflector heterogeneity for this data set, however, is complicated by noise contamination and scattering above the target.
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