I was going through a report on MASW (Multi Station Analysis of Surface Wave) and found this

"To avoid the aliasing in the space domain, geophone spacing (Δx) needs to be less than half of the minimum wavelength of interest but channels of the seismograph are limited. As a consequence, geophone spread length (L) is constrained in a certain range. However, on the other hand, a sufficient geophone spread is required for mode separation and the investigation depth."

I understand that this may depend a lot on optimization but is there any approach or research which can be used to make this decision considering both small and large offsets might be useful based on what we are trying to determine.

  • $\begingroup$ Not sure how much of my answer is relevant to MASW. I'll delete it if someone comes up with something more direct. $\endgroup$
    – Matt Hall
    Commented May 22, 2015 at 13:04
  • 1
    $\begingroup$ Briefly: use as large receiver spread length as possible, but remember to keep your geophone spacing small enough. You may want to take a look at these tables, with best acquisition parameters for a given depth of investigation. And a "must-read" thing for anyone dealing with MASW is Claudio Strobbia's PhD thesis with lots of useful results and descriptions. My advice is definitely not as fundamental as the answer by @kwinkunks , so I add this as a comment :) $\endgroup$
    – antongrin
    Commented May 27, 2015 at 7:53

1 Answer 1


It depends.

Caveat: my experience is with reflection seismic surveys, but I think many of the principles are similar to MASW.

As you guessed: it's an optimization problem. There are lots of factors at play. It's up to the geophysicist to balance the various needs of the survey:

  • You need to image the target with useful accuracy (small natural bin size).
  • You want useful signal:noise levels (high fold and trace density).
  • You want near offsets for good estimates of P-wave reflectivity.
  • You want far offsets for good estimates of elastic properties (e.g. density).
  • You may need far offsets to image certain types of geology.
  • You want the acquisition crew to have enough receivers for the design.
  • You want to be able to afford the acquisition and processing!

A while ago, I wrote a blog post on the subject: Fold for sale. It's about balancing fold (how many traces go into the stack, basically, a big driver of signal:noise) with cost.

My colleague Evan Bianco and I also did a series on modelling seismic acquisition. If you're into Python at all, there's some code to play with:

The greatest minimum offset in a bin is an important consideration, as you guessed. Also notice the spider plots, which try to visualize both maximum offset in a bin, and the range of azimuths going into that bin (which could be important for stress analysis, for example):

Spider plot for a seismic survey

It's hard to go into a lot more detail, other than pointing at more things to read. There are a couple of really good books on this subject:

For a quick overview, I recommend reading this great paper by Norm Cooper:

  • $\begingroup$ Takes me back :-) I don't know msw either but when I was in the industry, we were using a lot of very long offsets (8km+) in an attempt to image under the basalt lavas West of Shetland. So geology also plays a part. $\endgroup$
    – winwaed
    Commented May 22, 2015 at 13:26
  • $\begingroup$ thanks @kwinkunks for your answer.On a similar note is there any process for choosing which of the following transforms f-k,f-v,f-x,t-x...... would provide most correct interpretation?. $\endgroup$
    – shrey
    Commented May 24, 2015 at 11:57

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