An overview of reproducible 3D seismic data processing and imaging using Madagascar

Geophysics ◽  
2018 ◽  
Vol 83 (2) ◽  
pp. F9-F20 ◽  
Author(s):  
Can Oren ◽  
Robert L. Nowack

We present an overview of reproducible 3D seismic data processing and imaging using the Madagascar open-source software package. So far, there has been a limited number of studies on the processing of real 3D data sets using open-source software packages. Madagascar with its wide range of individual programs and tools available provides the capability to fully process 3D seismic data sets. The goal is to provide a streamlined illustration of the approach for the implementation of 3D seismic data processing and imaging using the Madagascar open-source software package. A brief introduction is first given to the Madagascar open-source software package and the publicly available 3D Teapot Dome seismic data set. Several processing steps are applied to the data set, including amplitude gaining, ground roll attenuation, muting, deconvolution, static corrections, spike-like random noise elimination, normal moveout (NMO) velocity analysis, NMO correction, stacking, and band-pass filtering. A 3D velocity model in depth is created using Dix conversion and time-to-depth scaling. Three-dimensional poststack depth migration is then performed followed by [Formula: see text]-[Formula: see text] deconvolution and structure-enhancing filtering of the migrated image to suppress random noise and enhance the useful signal. We show that Madagascar, as a powerful open-source environment, can be used to construct a basic workflow to process and image 3D seismic data in a reproducible manner.

2014 ◽  
Vol 10 ◽  
pp. 641-652 ◽  
Author(s):  
Richard J Ingham ◽  
Claudio Battilocchio ◽  
Joel M Hawkins ◽  
Steven V Ley

Here we describe the use of a new open-source software package and a Raspberry Pi® computer for the simultaneous control of multiple flow chemistry devices and its application to a machine-assisted, multi-step flow preparation of pyrazine-2-carboxamide – a component of Rifater®, used in the treatment of tuberculosis – and its reduced derivative piperazine-2-carboxamide.


2018 ◽  
Author(s):  
Tejas R. Rao

We develop an efficient software package to test for the primality of p2^n+1, p prime and p>2^n. This aids in the determination of large, non-Sierpinski numbers p, for prime p, and in cryptography. It furthermore uniquely allows for the computation of the smallest n such that p2^n+1 is prime when p is large. We compute primes of this form for the first one million primes p and find four primes of the form above 1000 digits. The software may also be used to test whether p2^n+1 divides a generalized fermat number base 3.


2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Yu-Hua Dean Fang ◽  
Chien-Yu Lin ◽  
Meng-Jung Shih ◽  
Hung-Ming Wang ◽  
Tsung-Ying Ho ◽  
...  

Background. The quantification of tumor heterogeneity with molecular images, by analyzing the local or global variation in the spatial arrangements of pixel intensity with texture analysis, possesses a great clinical potential for treatment planning and prognosis. To address the lack of available software for computing the tumor heterogeneity on the public domain, we develop a software package, namely, Chang-Gung Image Texture Analysis (CGITA) toolbox, and provide it to the research community as a free, open-source project.Methods. With a user-friendly graphical interface, CGITA provides users with an easy way to compute more than seventy heterogeneity indices. To test and demonstrate the usefulness of CGITA, we used a small cohort of eighteen locally advanced oral cavity (ORC) cancer patients treated with definitive radiotherapies.Results. In our case study of ORC data, we found that more than ten of the current implemented heterogeneity indices outperformed SUVmeanfor outcome prediction in the ROC analysis with a higher area under curve (AUC). Heterogeneity indices provide a better area under the curve up to 0.9 than the SUVmeanand TLG (0.6 and 0.52, resp.).Conclusions. CGITA is a free and open-source software package to quantify tumor heterogeneity from molecular images. CGITA is available for free for academic use athttp://code.google.com/p/cgita.


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