As week 4 at Indiana University comes to a close, Bradley and I are getting ready to head to Purdue for the remainder of the summer. I’ve really enjoyed our time here in Bloomington and will miss the awesome ethnic food and hiking nearby. Not to mention, Dr. Pavlis has been an amazingly patient mentor, especially with my less than impressive computer skills. We are only a month into our internship but I already feel that I have learned so much. I am beginning to make progress in my project and notice myself slowly becoming more comfortable with the computer work. Although I’ll miss some aspects of Bloomington, I’m excited to see what West Lafayette has to offer. Not to mention, Bradley and I have been living in a house with 7 guys and sleeping on air mattresses for a month. Needless to say, it has been… interesting, but I’m definitely looking forward to living in a clean house and sleeping in an actual bed. Also, I’m looking forward to having a new town to explore, new food to try, and a new computer screen to stare at!
This week, I’ve mostly been working on processing receiver functions for both 2012 and 2013 data in Matlab. I’ve also been reading and writing many many MANY emails… Dr. Gilbert is at Purdue so we’ve been corresponding via email. He has been connecting remotely to our database so we are able to exchange files that way. Overall, it is pretty inefficient but has actually forced me to learn quite a bit on my own, which I think is often the most effective way to learn. Because I am working with a lot of data remotely, I have gotten much more comfortable using the Unix terminal to maneuver around the database. Also, while I haven’t actually had to write any of my own Matlab code yet, I’m starting to gain a better understanding of what different pieces of code actually do.
As a physics major with very little geology background I was worried coming into this internship that I wouldn’t understand anything in my project. After all, how could I possibly contribute anything to OIINK having taken only a single introductory geology class? I certainly have struggled with some of the geology jargon, but I’m finally beginning to see how my project fits into the larger OIINK investigation and why it is important. Fortunately, I haven’t been totally in the dark, though. I have been able to apply much of the wave theory that I learned last semester in my optics class. It turns out waves act very similar whether they are electromagnetic and emitting from a laser or mechanical and passing through the earth’s interior!
Because I think it is good practice to try explaining new things I will now bore you with some details of the data processing. Actually, I think it is really cool and hopefully I can convince you of that with the help of some pretty pictures. After getting the files into the correct format, the first step for processing receiver functions was “picking” the “good” traces to be used for each station. Shown below are receiver functions for the station Q46A plotted using a Matlab script. Each trace represents a different earthquake event and the peaks are energy amplitudes of various P-wave to S-wave conversions arriving at the radial component of the seismometer. The goal here was to get rid of “bad”, noisy (red) traces so that only the accurate ones were left.
Once all the bad traces were removed, the good traces were “stacked” or averaged into one representative trace and migrated from time to depth, as shown below.
The strong peak at 55km depth indicates a sharp discontinuity in the earth and represents the crust-mantle boundary (Moho) below the Q46A station! I repeated this for each of the 2012 and 2013 stations and then combined them to make a 2-D cross section which shows the depth of the Moho, or in other words the crustal thickness.
In a perfectly simple world, the figure shown above would indicate a thickening of the crust at around 200km. The problem is that there are many other complexities in the crust that could be causing this apparent thickening. For example, these calculated depths are based on arrival times of different phases, and therefore, anything that affects the travel time appears as a change in the crustal thickness. There could actually just be a slow area in the shallow crust causing delayed travel times that APPEAR as thickening. This is exactly the type of thing that we will be trying to sort out in the next few weeks.
The next steps in the processing:
1. Try to identify smaller scale structures beneath the OIINK array. Due to the dense sampling of the array, we should be able to resolve structures in more detail.
2. Compare the receiver function signals with surface structures such as the edges of the Illinois Basin to see if there is any correlation.
3. Stack the 2-D cross sections into a 3-D volume in paraview. This is a matter of converting Matlab data point matrices into something that can be imported into paraview. We are still unsure exactly how to do this, but I’m looking forward to getting my hands dirty with some coding in the near future!
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