Although deconvolution usually is applied to prestack data trace by trace, it is not uncommon to design a single deconvolution operator and apply it to all the traces on a shot record. The seismic convolutional model states that a seismic record is the convolution of the earths reflectivity with the seismic wavelet. Earthquakes and explosions generate depth phases such as pp and sp as reflections of the underlying p signal generated by the event. In this paper, a seismic blind deconvolution algorithm based on bayesian. Accurate determination of the source depth of a seismic event is a potentially important goal for better discrimination between deeper earthquakes and more shallow nuclear tests. Basis pursuit inversion figures 1b and 2b show the synthetic traces, which are a result of convolution between the wavelet and the re. Full waveform tomography is a tomographic technique that takes advantage of numerical solutions of the elastic wave equation. Introduction to deconvolution and image preparation. Processing of seismic reflection data using matlab. Optics cleaning and objective correction collar alignment tip. Judging from the amount of time that seismic processors put into phase matching intersecting 2d seismic lines, and overlapping 3d seismic surveys, it appears to be simply a statement of the truth. Large data in matlab a seismic data processing case study. Large data in matlab a seismic data processing case study search form the following matlab project contains the source code and matlab examples used for large data in matlab a seismic data processing case study. Pdf seismic data deconvolution using kalman filter based.
An ideal seismic source would be a spike maximum amplitude at every frequency, but the best practical one would be minimum phase. Convolution of two series, ui, and wi, denoted uw, is. This article is based on crains seismic petrophysics by e. Note that if we need to multiply two polynomials, with coefficients uk and wk, we would use exactly the formula above.
Convolution and filtering seismology and geophysics. Seismic data processing to interpret subsurface features is both computationally and data intensive. Usually an averaging of 8 makes the best images, if the dye is strong enough. Convolution of a wavelet with the reflection coefficients.
It removes the basic seismic wavelet the source time function modified by various effects of the earth and recording system from the recorded seismic trace and thereby increases temporal resolution. Time seriesdata processing and analysis math 587geop 505 brian borchers and rick aster november 8, 20 notes on deconvolution we have seen how to perform convolution of discrete and continuous signals in both the time domain and with the. Stuart kozola is a product manager at mathworks and focuses on matlab and addon products for data analysis, mathematical modeling, and computational finance. This is the only way to have usable images for processing never saturate an image averaging noise on image, statistics tip. Includes readytorun matlab algorithms for most of the techniques presented.
The objective of deconvolution is to nullify objectionable effects of an earlier filter action and thus improve the recognizability and resolution of. The objective of the deconvolution procedure is to remove the obscuring effect of the wavelets replica making up the seismic trace and therefore obtain an esti. An investigation of the tools of seismic data processing. Deconvolution deconvolution is the reverse of convolution. Mar 18, 2016 download deconvolution an intuitive image deconvolution and deblur application that can apply multiple different algorithms in order to improve the quality of your pictures. Predictive deconvolution in seismic data processing in atala prospect of rivers state, nigeria. The mathematical form of the convolution of two functions, a filter ft and a timeseries xt, is. The deconvolution of seismic data as a fluctuation analysis. Enhancing a seismic image after migration using deconvolution. Young work completed under doe st485d saiidia national laboratories received sponsored by doe aug 1 6 19% osti to support the signal processing and data visualization needs of ctbt related projects at snl, a matlab based gui was developed.
Digital filtering theory applies to virtually any sampled information in time e. Deconvolution is a process universally applied to seismic data, but is one that is mysterious to many geoscientists. Recent progress in numerical methods and computer science allows us today to simulate the propagation of seismic waves through realistically heterogeneous earth models with unprecedented accuracy. Compressive sensing in seismic signal processing is a construction of the unknown reflectivity sequence from the incoherent measurements of the seismic records. An investigation of the tools of seismic data processing 2 in the frequency domain, the convolution is equivalent to multiplication i. James brown, and zhihong nancy cao abstract three basic methods for suppressing multiples exist in published literature. Jan 01, 2016 deconvolution is basically the opposite of convolution. Hence, it increases resolution and yields a more interpretable seismic section. A process designed to restore a waveshape to the form it had before it underwent a linear filtering action convolution. A seismic blind deconvolution algorithm based on bayesian.
The complete software package is available electronically 6. Blind seismic deconvolution is the recovery of reflectivity sequence from the seismic records, when the seismic wavelet is unknown. Since wiener deconvolution tries to estimate stationary wavelets from noisy, nonstationary seismic data, we should not be too surprised to see some. Common procedures to streamline seismic data processing include.
The signaltonoise ratio snr is quite high snr 10 db. This book serves as a fundamental guide to seismic imaging principles and algorithms and their foundation in inverse scattering theory and is a valuable resource for. Deconvolution compresses the basic wavelet in the recorded seismogram and attenuates reverberations and shortperiod multiples. Deconvolution is basically the opposite of convolution. Bioxtas raw is a program for analysis of smallangle xray scattering saxs data.
Deconvolution can also be performed on other types of data, such as gravity, magnetic or well log data. Seismic exploration deconvolution free open source codes. Prior to joining mathworks in 2006, stuart worked at pratt. In this way, the deconvolved seismic record provides an estimate of the reflectivity. Download deconvolution an intuitive image deconvolution and deblur application that can apply multiple different algorithms in order to improve the quality of your pictures. He also received segs awards for best paper in geophysics in 1992 imaging salt with seismic turning waves and best paper presented at the annual meeting in 2002 atomic meshing of seismic images. Seismic exploration of the three major processing part of the deconvolution, is the seismic exploration of the students undergraduate, graduate students must master a program, very classic sponsored links. Convolution general formulae the resulting lake levels can be calculated by the following procedure, called convolution. Working with data files, such as segy, that are too large to fit in system memory. Renaut june 27, 2006 abstract this note provides complete details of the numerical algorithm implemented in the software package for signal resortoration of seismic signals 5. V31v42 january 2016 with 545 reads how we measure reads. The comprehensive and physically complete linear imaging foundation developed presents new results at the leading edge of seismic processing for target location and identification. Time seriesdata processing and analysis math 587geop 505 brian borchers and rick aster november 8, 20 notes on deconvolution we have seen how to perform convolution of discrete and continuous signals in both the time domain and with the help of the fourier transform. For example, a convolution can be used to model the filtering of seismic energy by the various rock layers in the earth.
The book includes essential research and teaching material for digital signal and image processing individuals interested in learning seismic data interpretation from the point of. In the lecture portion of the course gpgn452561 now gpgn4615 61 advanced seismic methodsseismic processing the student is given a word, picture, and chalkboard introduction of the process of seismic data acquisition and the application of a myriad of processing steps for converting raw seismic data into a scientifically useful picture of. The demo also shows how to speed up the solution of the wave equation finite difference pde using a custom cuda kernel. Purchase optimal seismic deconvolution 1st edition. Do not copy or distribute in any form without explicit permission.
Seismic data processing geos 469569 spring 2006 geos 469569 is a mix of digital filtering theory and practical applications of digital techniques to assemble and enhance images of subsurface geology. In seismology we create an impulse seismic energysource and this signal after interacting with the. Full modeling software 2d, 3d, and 4d seismic survey design, processing, and modeling are created using industry and proprietary software packages. Doherty society of exploration geophysicists, 2001 seismic prospecting.
An illustration of the learning curve for effective use of the dap architecture. Seismic inversion is now commonly used on poststack and prestack seismic data for estimating rock properties used in reservoir characterization. The quality of modern seismic data owes a great deal to the success of deconvolution. Conduct geospatial and seismic analysis mathworks consulting. Enhancing a seismic image after migration using deconvolution john c.
In seismic processing the purpose of deconvolution is to remove or collapse the seismic wavelet. Feb 23, 2011 introduce gpu computing for speeding up solutions of the wave equation for seismic analysis. Figures 1cf and 2cf show the results of each of the. Time seriesdata processing and analysis math 587geop 505.
The commonest way to perform deconvolution is to design a wiener filter to transform one wavelet into another wavelet in a leastsquares sense. Deghosting benefits traditional seismic processing and is a prerequisite to all inversescatteringseries based processing. Processing, inversion, and interpretation of seismic data, issue 10, volume 2 ozdogan yilmaz, stephen m. Seismic data interpretation using digital image processing. Nonparametric deconvolution of seismic depth phases.
Presents image processing concepts that may be readily applied directly to seismic data. This short book is for students, professors and professionals interested in signal processing of seismic data using matlab tm. Seismic data deconvolution using kalman filter based on a new system model article pdf available in geophysics 811. Seismic processing often involves several stages of deconvolution, each of a different type and with a different objective. This webpage version is the ed intellectual property of the author. Deconvolution, or inverse filtering, can improve seismic data that were adversely affected by filtering, or convolution that occurs naturally as seismic energy is filtered by the earth. Introduce gpu computing for speeding up solutions of the wave equation for seismic analysis.
Pdf seismic data deconvolution using kalman filter based on. Durham etheses directional seismic source signature. Read the readme file to locate the public data sources on the internet. While seismic migration is aimed at imaging the reflectors or the interfaces at their correct subsurface locations, seismic inversion attempts to estimate elastic and flow properties of the layers. The stepbystep demo of the full reflection seismic data processing workflow using a complete real seismic data set places itself as a very useful feature of the book. It is quite common to convert a given wavelet source wavelet into its minimum phase equivalent since several processing stages e. Deconvolution is a filtering process which removes a wavelet from the recorded seismic trace by reversing the process of convolution.
Time seriesdata processing and analysis math 587geop. Convolution gives the overlapp of one function with another function reversed in time. A step in seismic signal processing to recover high frequencies, attenuate multiples, equalize amplitudes, produce a zerophase wavelet or for other purposes that generally affect the waveshape. Their directivity is due to the use of arrays of source elements and to the free. Deconvolution techniques used in conventional processing are based on optimum wiener filtering. Seismic processing and imaging gain deeper insight with the industrys most accurate subsurface imaging tools.
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