Wednesday, October 22. 2014Tutorial on parameter testing
The example in rsf/tutorials/parameters reproduces the tutorial from Matt Hall on parameter testing.
Madagascar users are encouraged to try improving the results. In his blog post and in the discussion that follows, Matt brings up an interesting question about finding the best way for parameter selection. For the lack of a better approach, parameter selection in seismic attributes is just an interactive game. In the Madagascar version, the key parameter for the Canny edge detector is the amount of prior anisotropicdiffusion smoothing, controlled by the smoothing radius (rect= parameter.) We can do different things with it: for example, make a movie of different images looping through different values of the radius, or, by exposing the parameter to the commandline SCons interface, build a simple GUI script for controlling it. The question posted by Matt waits for a better answer. See also: Saturday, October 18. 2014Tutorial on colormaps
The example in rsf/tutorials/colormaps reproduces the tutorial from Matteo Niccoli on how to evaluate and compare color maps. The tutorial was published in the August 2014 issue of The Leading Edge.
Madagascar users are encouraged to try improving the results. See also:
Several new color palettes have been recently added to Madagascar (thanks to Aaron Stanton): color=seismic (redyellowwhiteblack, popular among seismic interpreters), color=owb (orangewhiteblack), and color=rwb (redwhiteblack). Friday, October 17. 2014Petition to raise awareness about the role of software in researchThe Software Sustainability Institute in the UK has created an online petition to "everyone in the research community", which states "We must accept that software is fundamental to research, or we will lose our ability to make groundbreaking discoveries." 1. We want software to be treated as a valuable research object which befits the same level of investment and effort as any other aspect of the research infrastructure. You can sign the petition at Change.org. Wednesday, October 8. 2014Program of the month: sfsigmoid
sfsigmoid generates a 2D synthetic reflectivity model, created by Jon Claerbout.
One of the first occurrences of this model is in SEP73 sponsor report from 1992, where it appeared in several papers
The model was described as "a synthetic model that illustrates local variation in bedding. Notice dipping bedding, curved bedding, unconformity between them, and a fault in the curved bedding." Later, the sigmoid model made an appearance in Claerbout's book Basic Earth Imaging. The following example from bei/krch/sep73 illustrates the effect of aliasing on Kirchhoff modeling and migration: The model has appeared in numerous other tests. The following example from tccs/flat/flat shows automatic flattening of the sigmoid model by predictive painting. sfsigmoid has several parameters that control the model. The usual n1=, n2=, o1=, o2=, d1=, d2= parameters control the mesh size and sampling, taper= indicates whether to taper the sides of the model, large= controls the length of the synthetic reflectivity series. The program takes no input. 10 previous programs of the month:Highperformance computing and opensource software
A recent Report on High Performance Computing by the US Secretary of Energy Advisory Board contains a bizarre section on open source software, which states
There has been very little open source that has made its way into broad use within the HPC commercial community where great emphasis is placed on serviceability and security. In his thoughtful blog post in response to this report, Will Schroeder, the CEO an cofounder of the legendary Kitware Inc. makes a number of strong points defending the role of open source in the past and future development of HPC. He concludes The basic point here is that issues of scale require us to remove inefficiencies in researching, deploying, funding, and commercializing technology, and to find ways to leverage the talents of the broader community. Open source is a vital, strategic tool to do this as has been borne out by the many OS software systems now being used in HPC application... It’s easy to overlook open source as a vital tool to accomplish this important goal, but in a similar way that open source Linux has revolutionized commercial computing, open source HPC software will carry us forward to meet the demands of increasingly complex computing systems. See also Will Schroeder's presentation The New Scientific Publishers at SciPy2013. Wednesday, September 24. 2014Program of the month: sfmax1
sfmax1 finds local maxima along the first axis of the input. It takes floatingpoint input but outputs complex numbers, where the real part stands for the location of the local minima and the imaginary part stands for the value of the input at local minima.
The number of minima to output is controlled by np= parameter. To control the range for the minima locations (in the case that it is smaller than the full range of the data), use min= and max=. The output is sorted by value so that the largest maxima appear first. Here is a quick example. Let us create some data: bash$ sfmath n1=5 output="sin(x1)" > data.rsf Observing the data values, we can suspect that the local maximum is between 1 and 2. bash$ < data.rsf sfmax1 np=1  sfdisfil sfmax1 uses local parabolic interpolation to locate the minimum at 1.581 with the value of 0.9826. In the following example, from tccs/flat/flat, sfmax1 is used to locate the strongestamplitude horizons for predictive painting. 10 previous programs of the month:Wednesday, August 20. 2014Tutorial on data slicing
The example in rsf/tutorials/slicing reproduces the tutorial from Evan Bianco of simple data slicing.
See also: Madagascar users are encouraged to try improving the results. Iterative deblending using shaping regularization
A new paper is added to the collection of reproducible documents:
Iterative deblending of simultaneoussource seismic data using seisletdomain shaping regularization We introduce a novel iterative estimation scheme for separation of blended seismic data from simultaneous sources. The scheme is based on an augmented estimation problem, which can be solved by iteratively constraining the deblended data using shaping regularization in the seislet domain. We formulate the forward modeling operator in the common receiver domain, where two sources are assumed to be blended using a random timeshift dithering approach. The nonlinear shapingregularization framework offers some freedom in designing a shaping operator to constrain the model in an underdetermined inverse problem. We design the backward operator and the shaping operator for the shaping regularization framework. The backward operator can be optimally chosen as a half of the identity operator in the twosource case, and the shaping operator can be chosen as coherencypromoting operator. Three numerically blended synthetic datasets and one numerically blended field dataset demonstrate the highperformance deblending effect of the proposed iterative framework. Compared with alternative fk domain thresholding and fx predictive filtering, seisletdomain soft thresholding exhibits the most robust behavior. Tuesday, August 5. 2014Second Madagascar Working Workshop
"Working workshops" as opposed to "talking workshops" are meetings where the participants work together (possibly divided into pairs or small teams) to develop new software code or to conduct computational experiments addressing a particular problem. Working workshops are a cross between scientific workshops and coding sprints or hackathons common among opensource software communities.
26 participants from 11 different organizations gathered at Rice University at the end of July and beginning of August for the Second Madagascar Working Workshop, hosted by The Rice Inversion Project. The topic of the workshop was parallel highperformance computing. The participants divided into teams of 23 people by pairing experienced Madagascar developers with novice users. Each team worked on a small project, creating examples of parallel computing or improving generalpurpose tools such as sfmpi, sfomp, and (newly created) sfbatch. The participants used Stampede, the world's seventh most powerful supercomputer, provided by the Texas Advanced Computing Center, for their computational experiments. Sunday, August 3. 2014Program of the month: sfstolt
sfstolt implements zerooffset (poststack) seismic migration using Stolt method.
Stolt migration is described in the classic paper Stolt, R. H., 1978, Migration by Fourier transform: Geophysics, 43, 2348. The following example from gallery/french/stolt shows the result of Stolt migration in the French model: The classic Stolt migration works for constant velocity. However, it can be extended to the case of V(z) by using Stolt stretch and cascaded migrations. See Evaluating the Stoltstretch parameter and its references, including Beasley, C., W. Lynn, K. Larner, and H. Nguyen, 1988, Cascaded frequencywavenumber migration  Removing the restrictions on depthvarying velocity: Geophysics, 53, 881893. The following example from sep/stoltst/elfst compares the results of Stolt migration with Stolt stretch, phaseshift migration, and cascaded Stolt migration with Stolt stretch. sfstolt2 is another version of Stolt migration, with a control on interpolation accuracy. The following example from sep/forwd/stolt compares results from two different interpolations: 10 previous programs of the month:Sunday, July 13. 2014Program of the month: sfltft
sfltft (Local TimeFrequency Transform) decomposes input data into frequency components. The algorithm is described in the paper Seismic data analysis using local timefrequency decomposition and is based on regularized nonstationary regression.
The following example from tccs/ltft/timefreq shows 1D synthetic data composed of two chirp signals and the magnitude of coefficients in its timefrequency decomposition: The frequency sampling in the output of sfltft is controled by nw=, w0=, and dw=. By default, these parameters correspond to the sampling of the discrete Fourier transform. The critical parameters for regularized regression are rect= (smoothing radius in time, in samples) and niter= (number of iterations). To output the details of iterative regularization, use verb=y. The frequency sampling and the rect= parameter provide explicit controls on timefrequency resolution. In the example above, rect=7. It is possible to change smoothing radius with frequency by using alpha= parameter. The iterative inversion can be controlled additionally by specifying a data weight (with mask=) or a model weight (with weight=). Optionally, the Fourier basis used in the decomposition can be extracted from the program by specifying basis= file. To perform the inverse transform from timefrequency back to time domain, use inv=y. sfltft takes realvalued input and produces complexvalued output. An analogous program for transforming complexvalued data is sfcltft. A related program is sftimefreq described in Timefrequency analysis of seismic data using local attributes. 10 previous programs of the month:Thursday, July 10. 2014Madagascar in the cloud
SageMathCloud is a free cloud computing platform for computational mathematics created by William Stein, the leader of the Sage project.
SageMathCloud provides a rich environment, which allows one, for example, to easily install Madagascar and to access it interactively through its Python interface. The example above shows Madagascar running interactively in the cloud using an IPython notebook hosted by SageMathCloud. Support for interactive widgets is a new feature in IPython version 2 released earlier this year. See also Tuesday, July 1. 2014Making a wedge
The example in rsf/tutorials/wedge reproduces the example from Evan Bianco of simple convolution modeling with a wedge model.
See also: Madagascar users are encouraged to try improving the results. Tuesday, June 24. 2014Fast elastic mode separation in anisotropic media
A new paper is added to the collection of reproducible documents:
Fast algorithms for elasticwavemode separation and vector decomposition using lowrank approximation for anisotropic media Wave mode separation and vector decomposition are significantly more expensive than wavefield extrapolation and are the computational bottleneck for elastic reversetime migration (ERTM) in heterogeneous anisotropic media. We express elastic wave mode separation and vector decomposition for anisotropic media as spacewavenumberdomain operations in the form of Fourier integral operators, and develop fast algorithms for their implementation using their lowrank approximations. Synthetic data generated from 2D and 3D models demonstrate that these methods are accurate and efficient. Thursday, June 12. 2014How do I do interactive picking?
While interactive picking is generally discouraged because of its nonreproducibility, occasionally it might be useful.
Using interact= option with xtpen outputs mouseclick coordinates in a text file. However, they are Vplot coordinates, not easily related to physical coordinates of the image. Joe Dellinger has a more comprehensive plan for adding interactivity to Vplot graphics. sfipick is a simple Tkinter script which allows for interactive picking. The interface is straightforward. Use leftbutton mouse clicks to add picks, rightbutton mouse clicks to remove wrong picks, middlebutton to drag picks. The picks are written in a plain text file and can be processed later. See also:
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