Appendix I: Exercises/en
<languages/>
|
| |
| Series | Geophysical References Series |
|---|---|
| Title | Digital Imaging and Deconvolution: The ABCs of Seismic Exploration and Processing |
| Author | Enders A. Robinson and Sven Treitel |
| Chapter | 9 |
| DOI | http://dx.doi.org/10.1190/1.9781560801610 |
| ISBN | 9781560801481 |
| Store | SEG Online Store |
1. Suppose that n = 128, Failed to parse (SVG (MathML can be enabled via browser plugin): Invalid response ("Math extension cannot connect to Restbase.") from server "https://en.wikipedia.org/api/rest_v1/":): dt = 0.004, f_s = 1/dt , Failed to parse (SVG (MathML can be enabled via browser plugin): Invalid response ("Math extension cannot connect to Restbase.") from server "https://en.wikipedia.org/api/rest_v1/":): f_n = f_{s}/2 , and Failed to parse (SVG (MathML can be enabled via browser plugin): Invalid response ("Math extension cannot connect to Restbase.") from server "https://en.wikipedia.org/api/rest_v1/":): df = f_{s}/n . Here, n is the total number of samples in a signal and dt is the sampling time interval in seconds. What is the sampling frequency Failed to parse (SVG (MathML can be enabled via browser plugin): Invalid response ("Math extension cannot connect to Restbase.") from server "https://en.wikipedia.org/api/rest_v1/":): f_s ? [Answer: 250 Hz.] What is the Nyquist frequency Failed to parse (SVG (MathML can be enabled via browser plugin): Invalid response ("Math extension cannot connect to Restbase.") from server "https://en.wikipedia.org/api/rest_v1/":): f_n ? [Answer: 125 Hz.] What is the sampling frequency interval df? [Answer: 1.95313 Hz.]
2. Discuss what you see on the sketches shown in Figure I-1.


Continue reading
| Previous section | Next section |
|---|---|
| Summary | none |
| Previous chapter | Next chapter |
| Synthetics | Deconvolution |
Also in this chapter
- Wavelets
- The shaping filter
- Spiking filter
- White convolutional model
- Wavelet processing
- All-pass filter
- Convolutional model
- Nonminimum-delay wavelet
- Signature deconvolution
- Vibroseis
- Dual-sensor wavelet estimation
- Deconvolution: Einstein or predictive?
- Summary