Simultaneous sources: blending & deblending
Learning objectives
- Define blended acquisition: firing two or more sources so close in time that their responses overlap
- Explain why random firing-time jitter is the key enabling ingredient
- Describe the basic iterative deblending algorithm
- Identify the failure mode: delays too small or too coherent
Classical acquisition waits for each shot’s response to fully decay before firing the next. That forces a minimum listening time (typically 6–10 s for deep targets) and caps crew productivity. Simultaneous (or "blended") acquisition fires multiple sources close enough in time that their responses overlap, then deblends in processing to separate them.
The enabling trick: random jitter
If every shot 2 fires exactly 200 ms after shot 1, the two responses are indistinguishable — you can’t separate them. But if shot 2 fires at 200 ± 80 ms (random per shot), then when you sort the data by shot 1’s time, shot 2’s contribution is in different places on different traces. Shot 2 looks like incoherent noise, which can be suppressed by coherence-based filters. Sort by shot 2’s time and the roles reverse.
Basic deblending algorithm (iterative)
- Start with the blended record b(t).
- Estimate shot 1: suppress shot 2 as noise (e.g., trace-space median filter).
- Subtract the estimated shot 1 from b(t), aligned by shot 1’s firing times. Residual should be mostly shot 2 + true noise.
- Estimate shot 2 from the residual.
- Iterate until both estimates stop changing.
Productivity gain
Two-source simultaneous doubles shooting efficiency at modest deblending cost. Four-source quadruples it; this is how modern marine WAZ surveys fit six-source streamers into realistic schedules. The math scales to N sources as long as the inter-shot jitter is large enough that each source’s timing is resolvable in the joint distribution.
References
- Beasley, C. J., Chambers, R. E., Jiang, Z. (1998). A new look at simultaneous sources. SEG Annual Meeting Expanded Abstracts, 133–135.
- Berkhout, A. J. (2008). Changing the mindset in seismic data acquisition. The Leading Edge, 27(7), 924–938.
- Mahdad, A., Doulgeris, P., Blacquière, G. (2011). Separation of blended data by iterative estimation and subtraction of blending interference noise. Geophysics, 76(3), Q9–Q17.