The Bering Glacier, located in Southeastern Alaska, extends from the Bagley Ice Field to Vitus Lake, a tidally influenced fresh-water lake draining into the Gulf of Alaska. Calving events from the grounded and floating portions of the terminus are shown to produce both acoustic and seismic signals measurable with infrasound detectors and geophones, respectively. Based on the complex, emergent seismic signals recorded from calving events during a short-term experiment conducted at the Bering Glacier in the summer of 2007, we sought another technique for accurately locating these events. In August 2008 we deployed three small-aperture arrays of infrasound detectors to test their utility at determining the locations of subaerial calving events. Despite the complex nature of both the seismic and acoustic signals generated by calving, through the determination of azimuth from three small arrays of infrasound detectors, we were able to accurately locate both terminus calving and iceberg breakup events without relying on first motion picks for hypocenter locations.

The Bering Glacier progresses downhill through the mechanisms of plastic crystal deformation and basal sliding. Two summer field campaigns involving seismic monitoring in 2007 and 2008 were conducted in order to investigate basal processes near the terminus of the glacier. Many events were observed at stations deployed on the ice in 2007 near the Grindle Hills, but owing to the large distance between stations and the short recording period, few events were large enough to be recorded on sufficient stations to be accurately located. During August 2008, five stations were deployed in the same general area on the ice with closer spacing. Using this improved array, along with stations to the south of the glacier, four events were located. Of these, three appear to have occurred at or near the base of the glacier, at a point near the terminus, where the ice is severely folded, above the possible location of the Hope Creek fault. The fourth event was farther upstream beneath or within the glacier, but its location is poorly constrained.

Abstract Our objective is to introduce you to the fundamentals of seismic data processing with a learn-by-doing approach. We do this with Seismic Un*x (SU), a free software package maintained and distributed by the Center for Wave Phenomena (CWP) at the Colorado School of Mines (CSM). At the outset, we want to express our gratitude to John Stockwell of the CWP for his expert counsel. SU runs on several operating systems, including Unix, Microsoft Windows, and Apple Macintosh. However, we discuss SU only on Unix. Detailed discussion of wave propagation, convolution, cross- and auto-correlation, Fourier transforms, semblance, and migration are too advanced for this Primer. Instead, we suggest you refer to other publications of the Society of Exploration Geophysicists, such as “Digital Processing of Geophysical Data – A Review” by Roy O. Lindseth and one of the two books by Ozdogan Yilmaz: “Seismic Data Processing,” 1987 and “Seismic Data Analysis,” 2001. Our goal is to give you the experience and tools to continue exploring the concepts of seismic data processing on your own. This Primer covers all processing steps necessary to produce a time migrated section from a 2-D seismic line. We use three sources of input data: Synthetic data generated by SU; Real shot gathers from the Oz Yilmaz collection at the Colorado School of Mines (ftp://ftp.cwp.mines.edu/pub/data); and Real 2-D marine lines provided courtesy of Prof. Greg Moore of the University of Hawaii: the “Nankai” data set and the “Taiwan” data set. The University of Texas, the

Abstract The following table lists essential Unix commands. This chapter explains fundamental Unix commands that are necessary for understanding later scripts. It will be helpful if you know elementary Unix commands. Books titled “Teach Yourself Unix” have excellent, simple, early chapters that give the basics. Also, by surfing the web, you can find universities that have good tutorial sites. The following file name suffixes are used throughout this Primer. .sh shell script .scr shell script that launches a .sh shell script .su binary seismic data .dat binary data, not seismic data .eps image file formatted as Encapsulated Postscript (EPS) .txt ASCII data file The SU seismic data format is based on, but is not identical to, the binary format called SEG-Y. SEG-Y was defined by the Society of Exploration Geophysicists (SEG) and has become an industry standard format for seismic data exchange. The following file types can be printed directly to the screen by the cat and more commands: .sh, .scr, .txt. We do not explain the following advanced Unix concepts in detail. Their usage will be made clear by the way we use them in later scripts. The following Unix commands are not complete. These are merely a selection of commands that we consider helpful for your understanding and reproduction of the processing in this Primer. Remember that Unix is case sensitive. That is, suplane is not the same as Suplane. To start the Bourne shell interpreter, the first line of any script we make must be:

Abstract When seismic traces are in SEG-Y format, the SU trace format, and many other formats, the beginning of every trace, the trace header, has information about the trace. You can think of these as slots of information above the data part of the trace. The data part is the time-amplitude series that we see in a seismic display. Trace header information might include the trace number and the offset of the trace (for shot or CMP gathers). In an SU seismic data set, the number of trace header slots is the same to ensure that every trace in a data set has the same length (in terms of bytes of storage). SU doesn't call them headers; it calls them keys. The following table lists some SU keys. You can use program surange to learn which keys are in a data set and the range of their values (the largest and smallest values). Now that you have run script myplot.sh (Section 2.4), use program surange to examine the trace headers of the .seismic file. Enter: The output (screen display) is: This synthetic data set has 32 traces. Only five of its keys (trace headers) have non-zero values. The minimum value of trad and tracr is 1; the maximum value of trad and tracr is 32. This is not surprising since there are 32 traces in the data set. We can suppose that the traces are numbered in sequence, 1 to 32. Surprisingly, all traces have the same offset: 400. The sample

Abstract This chapter shows you how to create 2-D geologic models, create synthetic shot gathers from the models, and examine the shot gathers for quality control (QC the gathers). Chapter 5 shows you how to use the models to “acquire” (create synthetic) seismic data sets. Models developed in this chapter have layers that are homogeneous and isotropic. Each layer has a single acoustic (P-wave) velocity. This chapter and the next are computer-intensive in two ways: (1) the scripts are complex and (2) it will probably take your computer two hours to most of a day to generate the shot gathers. If you want to skip this complexity, skim these two chapters to familiarize yourself with the geologic models, then simply use the synthetic data set generated from Model 4 (Chapter 6) that accompanies this Primer. Seismic data generated from Model 4 are processed in Chapters 7, 8, and 9. Our first model consists of five homogenous, isotropic layers. In the x-direction, the model goes from zero to six kilometers. In the z-direction, the model goes from zero to two kilometers. In Figure 4.1, as with all the model images in this Primer, the model is drawn 1:1 (the horizontal units have the same length as the vertical units; the model is not stretched or squeezed). It is important to see a model 1:1 to assess the complexity of source-receiver raypaths. Let's examine the script that created Model 1 and Figure 4.1. The numbers on the left are added for discussion; they

Abstract In the previous chapter, we developed three simple models and used them to generate single shot gathers and images of rays and wavefronts. In this chapter, we use the same models to acquired 2-D lines of seismic data. Script acql.sh acquires seismic data over model modell.dat , generated by script modell.sh (Section 4.2). The survey layout: 40 shots (line 28) Shots are equally spaced at 50m intervals (line 32 and line 35) 60 split-spread traces are recorded from each shot location (line 42) Geophone spacing is 50m (line 46 and line 49) Geophone offsets range from −1475 m to +1475 m (line 52) Shot locations range from 2 km to 3.95 km (line 68) Geophone locations range from 0.525 km to 5.425 km (line 68) The final data set has 2400 traces (40 shots x 60 geophones per shot). The generation of this data set took about half an hour on a Sun UltraSPARC III with four processors. Lines 61 and 62 write variable values to the screen. Notice that line 4 is commented out. We find that once a script is perfected, the messages from line 4 interfere with reading the values printed to the screen by lines 61 and 62. Previously (Section 4.5), we discussed variables nangle (the number of rays or angles that emanate from the source), fangle (the first angle of the fan of rays that emanate from the source), and langte (the last angle of the fan of rays that emanate from the

Abstract In the previous two chapters, we developed three simple models and used them to acquire 2-D lines of seismic data. In this chapter, we combine some of the attributes of those models to create a fourth model and use the model to acquire a 2-D line of seismic data In the following two sections, we explain the model and acquisition scripts in detail; you do not have to be familiar with the related scripts that are in the previous two chapters. The next three sections of this chapter explain how to build the model, acquire seismic data, and view selected gathers. While those sections are important, the last two sections about quality control (QC) are equally important. The QC sections explain how you can acquire survey information and seismic data from selected portions of the model. You can examine preliminary survey information and seismic data to increase your confidence in your model and your acquisition script before spending time acquiring the full seismic data set. As with previous models, Model 4 layers are homogeneous and isotropic. Each layer has a single acoustic (P-wave) velocity. Let's examine script model4.sh . The numbers on the left are added for discussion; they are not part of the script. This script can be divided into sets: System: Line 1 invokes the shell, line 5 turns on messages, and line 64 exits the shell. Variables: Line 8 lets us vary the number of each run as we perfect the script (2a, 2b, etc.). This number becomes

Abstract From the previous chapter, we have a 2-D line of seismic data. In this chapter, we: sort the shot gathers to common midpoint (CMP) gathers and perform velocity analysis on selected CMP gathers. Because our synthetic data are noise-free, we can proceed quickly from shot gathers to migration. If we wanted to, we could use suaddnoise to add noise to the data; this is often useful. You should consider adding some noise to the data set, then processing it using the examples we provide in this chapter and the next. Let's discuss “common-depth-point” (CDP) and “common midpoint” (CMP) (Sheriff, 2002). We try to avoid the term CDP because there is no common (same) point at the reflector if the reflector dips. On the other hand, common-midpoints almost always exist because they are defined by the geometric midpoint between sources and receivers. Because SU does not have a cmp key, we reluctantly use the cdp key. Script sort2cmp.sh does two jobs: We use program suchw (Change Header Word) to create header (key) cdp and assign values to it. Using the equation below, values of cdp (key1) are computed from gx (key2) and sx (key3). Scalars a, b, c, and d need to be determined by sketching the geometry. Our geometry dictates a = 1525, b =1, c = 1, and d = 50. Therefore, We use program susort to sort the traces based on primary sort key cdp and secondary sort key offset . A secondary sort is the order within the

Abstract Now that we have a file of time-velocity (t-v) picks at selected CMPs, we check the quality of those picks. Then, we apply NMO to the data. After reviewing the results of NMO, it is simple (a one-line command) to stack the gathers. For the sake of presentation in Section 8.2.1, what was one line in vpick4.txt (line 1) are now two lines in tvQC.sh (lines 13-14). Notice that THERE ARE NO SPACES AT THE END OF LINE 13 AND NO SPACES AT THE BEGINNING OF LINE 14 . We removed line 2 from file vpick4.txt . That line would be between lines 14 and 15 below. We removed it because A COMMENT LINE WITHIN THE LINES OF AN SU COMMAND WILL MAKE THE SCRIPT CRASH . We also removed the continuation mark from the end of line 50. At the end of interactive velocity analysis (Section 7.6.6.10), we have a file that contains a row of cdp values. Also within that file, there is a pair of tnmo values and vnmo values for each cdp value. Before we use these cdp - tnmo - vnmo values in normal moveout correction (NMO), we want to check the quality of our picks. Each time series (set of tnmo values) input to the Seismic Un*x NMO program, sunmo , must increase in time. In other words, in a time series, each successive pick must be at a later time than the previous pick. The following script, tvqc.sh , offers a fast way to check that the tnmo values are acceptable to