Saturday, May 9. 2015Amplitude balancing
Another old paper is added to the collection of reproducible documents:
Iterative leastsquare inversion for amplitude balancing Variations in source strength and receiver amplitude can introduce a bias in the final AVO analysis of prestack seismic reflection data. In this paper we tackle the problem of the amplitude balancing of the seismic traces from a marine survey. We start with a 2D energy map from which the global trend has been removed. In order to balance this amplitude map, we first invert for the correction coefficients using an iterative leastsquare algorithm. The coefficients are calculated for each shot position along the survey line, each receiver position in the recording cable, and each offset. Using these coefficients, we then correct the original amplitude map for amplitude variations in the shot, receiver, and offset directions. Thursday, May 7. 2015Twodimensional Hilbert transform
A new paper is added to the collection of reproducible documents:
Seismic dip estimation based on the twodimensional Hilbert transform and its application in random noise attenuation In seismic data processing, random noise seriously affects the seismic data quality and subsequently the interpretation. This study aims to increase the signaltonoise ratio by suppressing random noise and improve the accuracy of seismic data interpretation without losing useful information. Hence, we propose a structureoriented polynomial fitting filter. At the core of structureoriented filtering is the characterization of the structural trend and the realization of nonstationary filtering. First, we analyze the relation of the frequency response between twodimensional (2D) derivatives and the 2D Hilbert transform (Riesz transform). Then, we derive the noniterative seismic local dip operator using the 2D Hilbert transform to obtain the structural trend. Second, we select polynomial fitting as the nonstationary filtering method and expand the application range of the nonstationary polynomial fitting. Finally, we apply variableamplitude polynomial fitting along the direction of the dip to improve the adaptive structureoriented filtering. Model and field seismic data show that the proposed method suppresses the seismic noise while protecting structural information. Wednesday, May 6. 2015Structureconstrained acoustic impedance
A new paper is added to the collection of reproducible documents:
Structureconstrained relative acoustic impedance using stratigraphic coordinates Acoustic impedance inversion involves conversion of seismic traces to a reflection coefficient time series, and then into acoustic impedance. The usual assumption for the transformation of poststack seismic data into impedance , is that seismic traces can be modeled using the simple convolutional model. According to the convolutional model, a seismic trace is a normalincidence record, which is an assumption that is strictly true only if the earth structure is composed of horizontal layers. In the presence of dipping layers, such an assumption is violated, which introduces bias in the result of impedance inversion. I propose to implement impedance inversion in the stratigraphic coordinate system, where the vertical direction is normal to reflectors and seismic traces represent normalincidence seismograms. Tests on field data produce more accurate and detailed impedance results from inversion in the stratigraphic coordinate system, compared to impedance results using the conventional Cartesian coordinate system. Tuesday, May 5. 2015Summer events
Two exciting events are being planned for this summer.
The Madagascar School for Advanced Users is being planned for August 89, 2015. The school will take place in Qingdao, China, and will be hosted by the China University of Petroleum. Unlike previous Madagascar schools, the intended audience are not beginners but current users of Madagascar who want to learn more about advanced topics (parallel computing; graphical user interfaces; interfaces to C++, Python, and Matlab, etc.) More information is available at http://www.ahay.org/wiki/Qingdao_2015. The Working Workshop on 3D Seismic Data Processing is being planned for August 1922, 2015. The workshop will take place in Houston and will be hosted by Rice University. Unlike previous working workshops, the participations is not limited to Madagascar users. Users of other software packages with interest in seismic field data processing are encouraged to participate. The workshop is being organized by Karl Schleicher, with support of SEG. More information is available at http://www.ahay.org/wiki/SEG_3D_Seismic_Processing_Working_Workshop_Houston_2015_Land_3D Thursday, April 23. 2015Tutorial on seismic survey design
The example in rsf/tutorials/survey reproduces the tutorial from Evan Bianco on designing 3D seismic surveys. For more explanation, see Evian's blog post Laying out a seismic survey.
Madagascar users are encouraged to try improving the results. Tuesday, April 21. 2015Reproducible research in psychology
An article A Perfect Storm: The Record of a Revolution by EricJan Wagenmakers, a mathematical psychologist from the Unversity of Amsterdam, describes a reproducibility revolution, which is taking place in psychology:
The dynamics of political revolutions are in some ways similar to the academic revolution that has recently gripped the field of psychology. Over the last two decades, increasing levels of competition for scarce research funding have created a working environment that rewards productivity over reproducibility; this perverse incentive structure has caused some of the findings in the psychological literature to be spectacular and counterintuitive, but likely false [...] The general dissatisfaction with the state of the field was expressed in print only occasionally, until in 2011 two major events ignited the scientific revolution that is still in full force today. The article was published this month by the Inquisitive Mind (InMind) magazine. EricJan concludes: Although some researchers are less enthusiastic about the "replicability movement" than others, it is my prediction that the movement will grow until its impact is felt in other empirical disciplines including the neurosciences, biology, economy, and medicine. The problems that confront psychology are in no way unique, and this affords an opportunity to lead the way and create dependable guidelines on how to do research well. Such guidelines have tremendous value, both to individual scientists and to society as a whole. Program of the month: sfslant
sfslant is a TX implementation of slant stack, also known as Radon transform or taup transform.
The two middle panels in the example below from cwp/geo2006TimeShiftImagingCondition/zicig show a timeshift commonimage gather and its transformation by slant stack. sfslant is a linear operator and has an adjoint flag adj=: When adj=n, the transformation is from taup to tx. When adj=y, the transformation is from tx to taup. The sampling on the transformed coordinate is controlled in the two cases by nx=, dx=, x0= or, respectively np=, dp=, p0=. Antialiasing is enabled by default with anti=1 parameter. The central slope for antialiasing is given by p1=. A space integration is sfslant generally requires a corrective "rho filter" (halforder differentiation). It is enabled by rho= parameter. For an FX implementation of the Radon transform, see sfradon. 10 previous programs of the month:Friday, April 17. 2015Seisletbased MCA
A new paper is added to the collection of reproducible documents:
Seisletbased morphological component analysis using scaledependent exponential shrinkage Morphological component analysis (MCA) is a powerful tool used in image processing to separate different geometrical components (cartoons and textures, curves and points etc). MCA is based on the observation that many complex signals may not be sparsely represented using only one dictionary/transform, however can have sparse representation by combining several overcomplete dictionaries/transforms. In this paper we propose seisletbased MCA for seismic data processing. MCA algorithm is reformulated in the shapingregularization framework. Successful seisletbased MCA depends on reliable slope estimation of seismic events, which is done by planewave destruction (PWD) filters. An exponential shrinkage operator unifies many existing thresholding operators and is adopted in scaledependent shaping regularization to promote sparsity. Numerical examples demonstrate a superior performance of the proposed exponential shrinkage operator and the potential of seisletbased MCA in application to trace interpolation and multiple removal. Thursday, April 16. 2015Tutorial on image resolution
The example in rsf/tutorials/images reproduces the tutorial from Matt Hall on playing with image resolution. For more explanation, see Matt's blog post R is for Resolution.
Madagascar users are encouraged to try improving the results. Monday, April 13. 2015madagascar1.7 released
The 1.7 stable release features 21 new reproducible papers and multiple other enhancements including improved tools for parallel computing developed at the Second Working Workshop.
According to the SourceForge statistics, the previous 1.5 stable distribution has been downloaded more than 4,000 times. The top country (with 24% of all downloads) was USA, followed by China, Colombia, Germany, and Brazil. According to Openhub.net (last updated in January 2015), the year of 2014 was a period of a high development activity, with 33 contributors making 1,876 commits to the repository (up 16% from the previous year). Openhub.net says that Madagascar "has a well established, mature codebase maintained by a very large development team with stable yearoveryear commits " and estimated 239 manyears of effort (an estimated development cost of $13 million). Thursday, April 2. 2015How to make your research irreproducible
Yesterday (April 1, 2015) a group of computer scientists from UK (Neil Chue Hong, Tom Crick, Ian Gent, and Lars Kotthoff) announced a seminal paper Top Tips to Make Your Research Irreproducible.
Here are the tips that the authors share: These tips will be undoubtedly embraced by all scientists trying to make their research irreproducible. The paper ends with an important conjecture: We make a simple conjecture: an experiment that is irreproducible is exactly equivalent to an experiment that was never carried out at all. The happy consequences of this conjecture for experts in irreproducibility will be published elsewhere, with extremely impressive experimental support. Friday, March 27. 2015Fast 3D velocity scan
A new paper is added to the collection of reproducible documents:
A fast algorithm for 3D azimuthally anisotropic velocity scan Conventional velocity scan can be computationally expensive for largesize seismic data, particularly when the presence of anisotropy requires multiparameter estimation. We introduce a fast algorithm for 3D azimuthally anisotropic velocity scan, which is a generalization of the previously proposed 2D butterfly algorithm for hyperbolic Radon transform. To compute the semblance in a twoparameter residual moveout domain, the numerical complexity of our algorithm is roughly as opposed to of the straightforward velocity scan, with being representative of the number of points in either dimension of data space or parameter space. We provide both synthetic and fielddata examples to illustrate the efficiency and accuracy of the algorithm. Multiple suppression using PEF
Another old paper is added to the collection of reproducible documents:
Multiple suppression using predictionerror filter I present an approach to multiple suppression, that is based on the moveout between primary and multiple events in the CMP gather. After normal moveout correction, primary events will be horizontal, whereas multiple events will not be. For each NMOed CMP gather, I reorder the offset in random order. Ideally, this process has little influence on the primaries, but it destroys the shape of the multiples. In other words, after randomization of the offset order, the multiples appear as random noise. This "manmade" random noise can be removed using predictionerror filter (PEF). The randomization of the offset order can be regarded as a random process, so we can apply it to the CMP gather many times and get many different samples. All the samples can be arranged into a 3D cube, which is further divided into many small subcubes. A 3D PEF can then be estimated from each subcube and reapplied to it to remove the multiple energy. After that, all the samples are averaged back into one CMP gather, which is supposed to be free of multiple events. In order to improve the efficiency of the algorithm of estimating the PEF for each subcube, except for the first subcube which starts with a zerovalued initial guess, all the subsequent subcubes take the last estimated PEF as an initial guess. Therefore, the iteration count can be reduced to one step for all the subsequent subcubes with little loss of accuracy. Three examples demonstrate the performance of this new approach, especially in removing the nearoffset multiples. FWI on GPU
A new paper is added to the collection of reproducible documents:
A graphics processing unit implementation of timedomain fullwaveform inversion The graphics processing unit (GPU) has become a popular device for seismic imaging and inversion due to its superior speedup performance. In this paper we implement GPUbased full waveform inversion (FWI) using the wavefield reconstruction strategy. Because the computation on GPU is much faster than CPUGPU data communication, in our implementation the boundaries of the forward modeling are saved on the device to avert the issue of data transfer between host and device. The ClaytonEnquist absorbing boundary is adopted to maintain the efficiency of GPU computation. A hybrid nonlinear conjugate gradient algorithm combined with the parallel reduction scheme is utilized to do computation in GPU blocks. The numerical results confirm the validity of our implementation. Thursday, March 26. 2015Tutorial on phase and the Hilbert transform
The example in rsf/tutorials/hilbert reproduces the tutorial from Steve Purves on phase and the Hilbert transform. The tutorial was published in the October 2014 issue of The Leading Edge.
Madagascar users are encouraged to try improving the results. See also:
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