Month: December 2014

NMO with super resolution

December 16, 2014 Documentation No comments

Another old paper is added to the collection of reproducible documents:
A prospect for super resolution

Wouldn’t it be great if I could take signals of 10-30 Hz bandwidth from 100 different offsets and construct a zero-offset trace with 5-100 Hz bandwidth? This would not violate Shannon’s sampling theorem which theoretically allows us to have a transform from 100 signals of 20 Hz bandwidth to one signal at 2000 Hz bandwidth. The trouble is that simple NMO is not such a transformation. Never-the-less, if the different offsets really did give us any extra information, we should be able to put the information into extra bandwidth. Let us consider noise free synthetic data and see if we can come up with a model where this could happen.

Earthquake stacks

December 10, 2014 Documentation No comments

Another old paper is added to the collection of reproducible documents:
Earthquake stacks at constant offset

I show Shearer’s earthquake stacks over all source-receiver locations at constant offset and compare them to exploration seismic data. This electronic document simply reads the stacks and plots them.

T-X-Y adaptive filtering for random noise attenuation

December 7, 2014 Documentation 1 comment

A new paper is added to the collection of reproducible documents:
Adaptive prediction filtering in t-x-y domain for random noise attenuation using regularized nonstationary autoregression

Many natural phenomena, including geologic events and geophysical data, are fundamentally nonstationary. They may exhibit stationarity on a short timescale but eventually alter their behavior in time and space. We propose a 2D t-x adaptive prediction filter (APF) and further extend this to a 3D t-x-y version for random noise attenuation based on regularized nonstationary autoregression (RNA). Instead of using patching, a popular method for handling nonstationarity, we obtain smoothly nonstationary APF coefficients by solving a global regularized least-squares problem. We use shaping regularization to control the smoothness of the coefficients of APF. 3D space-noncausal t-x-y APF uses neighboring traces around the target traces in the 3D seismic cube to predict noise-free signal, so it provides more accurate prediction results than the 2D version. In comparison with other denoising methods, such as frequency-space deconvolution, time-space prediction filter, and frequency-space RNA, we test the feasibility of our method in reducing seismic random noise on three synthetic datasets. Results of applying the proposed method to seismic field data demonstrate that nonstationary t-x-y APF is effective in practice.

This reproducible paper is the first direct contribution from Jilin University, China.

SCons is “Community Choice” Project of the Month

December 5, 2014 Links No comments

The favorite tool of all Madagascar users, SCons, is featured as the December 2014 “Community Choice” Project of the Month at SourceForge.

SCons is a software construction tool (build tool, or make tool) implemented in Python, which uses Python scripts as “configuration files” for software builds. It is an easier, more reliable, and faster way to build software, solving a number of problems associated with other build tools, especially including the classic and ubiquitous make itself.
Distinctive features of SCons include: a modular design that lends itself to being embedded in other applications; a global view of all dependencies in the source tree; an improved model for parallel (“-j”) builds; automatic scanning of files for dependencies; use of MD5 signatures for deciding whether a file is up-to-date; use of Python functions or objects to build target files; and easy user extensibility.
A large number of open-source projects, companies, universities, and other scientific institutions use SCons as their build system, and are very happy with its stability and ease of maintenance. There are also several projects like Parts, PlatformIO, Madagascar, and FuDePAN, which use the SCons framework as a building block to provide highly specialized build environments to their users.

Back in 2006, when Madagascar became an open-source project, SourceForge was the dominant platform for such projects. Since then, it has remained a highly useful resource but has lost its popularity to GitHub.

Madagascar developers have not yet seen a compelling need to migrate the Madagascar repository from SourceForge to GitHub or to switch from Subversion (SVN) to Git, but will keep all options open.


December 3, 2014 Documentation No comments

Another old paper is added to the collection of reproducible documents:
The time and space formulation of azimuth moveout

Azimuth moveout (AMO) transforms 3-D prestack seismic data from one common azimuth and offset to different azimuths and offsets. AMO in the time-space domain is represented by a three-dimensional integral operator. The operator components are the summation path, the weighting function, and the aperture. To determine the summation path and the weighting function, we derive the AMO operator by cascading dip moveout (DMO) and inverse DMO for different azimuths in the time-space domain. To evaluate the aperture, we apply a geometric approach, defining AMO as the result of cascading prestack migration (inversion) and modeling. The aperture limitations provide a consistent description of AMO for small azimuth rotations (including zero) and justify the economic efficiency of the method.

Program of the month: sfbin

December 1, 2014 Programs No comments

sfbin bins traces with irregular spatial sampling to a regularly sampled 3-D cube.

The following example from sep/precon/cube shows the output of binning a common-offset seismic cube which corresponds to the following distribution of common midpoints Optionally, sfbin can also output the fold map (using fold= parameter). The fold map shows the number of input traces in each output bin. Parameters that control output grid sampling are nx=, dx=, x0= (for the second axis), ny=, dy=, y0= (for the third axis). Alternatively, one can specify the range values xmin=, xmax=, ymin=, ymax=.

By default, the range is determined from the input trace coordinates. The input trace coordinates can be specified in an auxiliary trace header file (head= parameter), where x and y coordinates are given in keys number xkey= and ykey= (0 and 1 by default).

By default, nearest-neighbor binning is applied. Alternatively, it is possible to use median binning by specifying interp=0 or bilinear-interpolation binning by specifying interp=2.

By default, the output values are normalized by the fold. To switch fold-normalization off, use norm=n.

10 previous programs of the month: