Advanced Digital Signal Processing of Seismic Data

Seismic data must be interpreted using digital signal processing techniques in order to create accurate representations of petroleum reservoirs and the interior structure of the Earth. This book provides an advanced overview of digital signal processing (DSP) and its applications to exploration seismology using real-world examples. The book begins by introducing seismic theory, describing how to identify seismic events in terms of signals and noise, and how to convert seismic data into the language of DSP. Deterministic DSP is then covered, together with non-conventional sampling techniques. The final part covers statistical seismic signal processing via Wiener optimum filtering, deconvolution, linear-prediction filtering and seismic wavelet processing. With over sixty end-of-chapter exercises, seismic data sets and data processing MATLAB codes included, this is an ideal resource for electrical engineering students unfamiliar with seismic data, and for Earth Scientists and petroleum professionals interested in DSP techniques.

Preface; Part I. Seismic Theory Background: 1. Introduction; 2. Seismic theory and reflection surveying: a necessary background; Part II. Deterministic Digital Signal Processing for Seismic Data: 3. Spectral analysis of seismic data and useful transforms; 4. Sampling theorem for seismic data; 5. Seismic applications of digital filtering theory; Part III. Statistical Digital Signal Processing for Seismic Data: 6. Fundamentals of digital optimal filtering; 7. Seismic deconvolution; 8. Seismic wavelet processing; References; Index.