Share . This page was last edited on 17 September 2014, at 13:10. • Data Initialization. The next three sections are devoted to the three principal processes — deconvolution, CMP stacking, and migration. It is a process that collapses diffractions and maps dipping events on a stacked section to their supposedly true subsurface locations. A more desirable application is of structure-oriented filters applied to seismic data, which has the effect of enhancing laterally continuous events by reducing randomly-distributed noise, without suppressing details in the reflection events consistent with the structure. Seismic processing facilitates better interpretation because subsurface structures and reflection geometries are more apparent. Until the migration step, seismic data are merely recorded traces of echoes, waves that have been reflected from anomalies in the subsurface. This website uses cookies. You can disable cookies at any time. Prestack seismic data denoising is an important step in seismic processing due to the development of prestack time migration. But, more recently, it has been found that such procedures might not be enough for data acquired for unconventional resource plays or subsalt reservoirs. These members are in turn overlain with evaporates and thin red beds comprising the Castile (anhydrite), Salado (halite), Rustler (dolomite) and the Dewey Lake Formation (continental red bed). Poststack Processing Steps for Preconditioning Seismic Data Geophysical Corner Figure 2: An arbitrary line passing though the far-angle stacked volume that used the (a) conventional preconditioning, and (b) preconditioning with application of some post-stack processing steps. Table 1-14 provides the processing parameters for the line. Content Introduction. Usually, these steps are generating partial stacks (that tone down the random noise), bandpass filtering (which gets rid of any high/low frequencies in the data), more random noise removal (algorithms such as tau-p or FXY or workflows using structure-oriented filtering), trim statics (for perfectly flattening the NMO-corrected reflection events in the gathers) and muting (which zeroes out the amplitudes of reflections beyond a certain offset/angle chosen as the limit of useful reflection signal). A way out of such a situation is to replace the near-stack data with the intercept stack, which may exhibit higher signal-to-noise ratio. Deconvolution achieves this goal by compressing the wavelet. Presented by Dr. Fred Schroeder, Retired from Exxon/ExxonMobil Presented on August 24, 2017 The course is also of value for seismic acquisition specialists who desire to understand the constraints that seismic processing places on acquisition design. Data examples, exercises, and workshops are used to illustrate key concepts, practical issues, and pitfalls of acquisition and processing as they affect the interpretation and integration of seismic data … Processing steps typically include analysis of velocities and frequencies, static corrections, deconvolution, normal moveout, dip moveout, stacking, and migration, which can be performed before or after stacking. Since the introduction of digital recording, a routine sequence in seismic data processing has evolved. Before deconvolution, correction for geometric spreading is necessary to compensate for the loss of amplitude caused by wavefront divergence. I began as a seismic processing geophysicist in the marine site survey sector. The main reason for this is that our modelfor deconvolution is nondeterministic in chara… We have illustrated the application of such a workflow by way of data examples from the Delaware Basin, and the results look very convincing in terms of value-addition seen on P-impedance and VP/VS data. Application-specific seismic data conditioning and processing for confident imaging From the field to the final volume, seismic data goes through many processes and workflows. Seismic data processing involves the compilation, organization, and conversion of wave signals into a visual map of the areas below the surface of the earth. Title: Reflection Seismic Processing 1 Reflection Seismic Processing . Sometimes, due to the near-surface conditions, spatial variations in amplitude and frequency are seen in different parts of the same inline or from one inline to another in the same 3-D seismic volume. There are three primary steps in processing seismic data — deconvolution, stacking, and migration, in their usual order of application. The amplitude trend after the proposed preconditioning shows a similar variation as seen obtained using the conventional processing flow. Attribute computation on such preconditioned seismic data is seen to yield promising results, and thus interpretation. To ensure that these processing steps have preserved true-amplitude information, gradient analysis was carried out on various reflection events selected at random from the near-, mid1-, mid2- and far-angle stack traces, and one such comparison is shown in figure 3. Deconvolution assumes a stationary, vertically incident, minimum-phase source wavelet and white reflectivity series that is free of noise. Deconvolution often improves temporal resolution by collapsing the seismic wavelet to approximately a spike and suppressing reverberations on some field data (Figure I-7). Make the most of your seismic data. Quite often it is observed that the P-reflectivity or S-reflectivity data extracted from AVO analysis appear to be noisier than the final migrated data obtained with the conventional processing stream, which might consist of processes that are not all amplitude-friendly. That all the above-stated processes are amplitude-friendly can be checked by carrying out gradient analysis on data before and after the analysis. Of the many processes applied to seismic data, seismic migration is the one most directly associated with the notion of imaging. Figure 1.5-1 represents the seismic data volume in processing coordinates — midpoint, offset, and time. Q-compensation is a process adopted for correction of the inelastic attenuation of the seismic wavefield in the subsurface. The third step is the 90°-phase rotation. Seismic Processing. • Amplitude Processing. The purpose of seismic processing is to manipulate the acquired data into an image that can be used to infer the sub-surface structure. This is because these three processes are robust and their performance is not very sensitive to the underlying assumptions in their theoretical development. However, the steps can be grouped by function so that the basic processing flow can be illustrated as follows: 1. In this respect, migration is a spatial deconvolution process that improves spatial resolution. The core course presents material in a sequence that is the opposite of the sequence used in processing. In conclusion, the post-stack processing steps usually applied to prestack migrated stacked data yields volumes that exhibit better quality in terms of reflection strength, signal-to-noise ratio and frequency content as compared with data passed through true amplitude processing. Therefore, a reversible transform for seismic data processing offers a useful set of quantitatively valid domains in which to work. • … Processing consists of the application of a series of computer routines to the acquired data guided by the hand of the processing geophysicist. These different processes are applied with specific objectives in mind. Seismic data processing can be characterized by the application of a sequence of processes, where for each of these processes there are a number of different approaches. Similarly, seismic attributes generated on noise-contaminated data are seen as compromised on their quality, and hence their interpretation. There are three primary steps in processing seismic data — deconvolution, stacking, and migration, in their usual order of application. Finally, migration commonly is applied to stacked data. Small-scale geologic features such as thin channels, or subtle faults, etc. Notice the near- and far-angle stacks are subjected to many of the processing steps mentioned above, and a comparison is shown with the conventional processing application. Common procedures to streamline seismic data processing include: Working with data files, such as SEGY, that are too large to fit in system memory In such a process, the stacked seismic data are decomposed into two or more frequency bands and the scalars are computed from the RMS amplitudes of each of the individual frequency bands of the stacked data. For example, dip filtering may need to be applied before deconvolution to remove coherent noise so that the autocorrelation estimate is based on reflection energy that is free from such noise. Seismic Processing Steps - Free download as PDF File (.pdf), Text File (.txt) or read online for free. At one time, seismic processing required sending information to a distant computer lab for analysis. In case such a computation proves to be cumbersome or challenging, a constant Q value is applied that is considered appropriate for the interval of interest. Seismic Data Processing GEOS 469/569 – Spring 2006 GEOS 469/569 is a mix of digital filtering theory and practical applications of digital techniques to assemble and enhance images of subsurface geology. Proper quality checks need to be run at individual step applications to ensure no amplitude distortions take place at any stage of the preconditioning processing sequence. Stacking also is a process of compression (velocity analysis and statics corrections). This basic sequence now is described to gain an overall understanding of each step. Only minimal processing would be required if we had a perfect acquisition system. The ground movements recorded by seismic sensors (such as geophones and seismometers onshore, or hydrophones and ocean bottom seismometers offshore) contain information on the media’s response to The values of the inelastic attenuation are quantified in terms of the quality factor, Q, which can be determined from the seismic data or VSP data. (The terms stacked section, CMP stack, and stack often are used synonymously.) Figure 1.5-1 represents the seismic data volume in processing coordinates — midpoint, offset, and time. Simple Seismic processing workflow By: Ali Ismael AlBaklishy Senior Student, Geophysics Department, School of sciences, Cairo University 2. Database building—The myriad of numbers on field tape must each be uniquely related to sh… Seismic data processing steps are naturally useful for separating signal from noise, so they offer familiar, exploitable organizations of data. Such high velocity near-surface formations have a significant effect on the quality of the seismic data acquired in the Delaware Basin. The success of AVO attribute extraction or simultaneous impedance inversion depends on how well the preconditioning processes have conditioned the prestack seismic data. http://dx.doi.org/10.1190/1.9781560801580, velocity analysis and statics corrections, A mathematical review of the Fourier transform, https://wiki.seg.org/index.php?title=Basic_data_processing_sequence&oldid=18981, Problems in Exploration Seismology & their Solutions, the Creative Commons Attribution-ShareAlike 3.0 Unported License (CC-BY-SA). These procedures have been carried out over the last two decades for most projects from different basins of the world. This observation suggests exploring if one or more poststack processing steps could be used for preconditioning of prestack seismic data prior to putting it through simultaneous impedance inversion for example. Having this very ergonomic and reliable package of seismic processing tools available is quite a technical plus point, either at fieldwork with QC–tools or back at the office with the full variety of processing steps. I really had no idea what to expect of working offshore when I began as a graduate, and it is the slightly unexpected nature of the work as a contractor that keeps it interesting! In such cases, newer and fresher ideas need to be implemented to enhance the signal-to-noise ratio of the prestack seismic data, before they are put through the subsequent attribute analysis. Besides the lack of continuity of reflection events, one of the problems seen on seismic data from this basin is that the near traces are very noisy and, even after, the application of the above-mentioned processes is not acceptable. Emphasis is on practical understanding of seismic acquisition and imaging. Objective - transform redundant reflection seismic records in the time domain into an interpretable depth image. After the prestack data have undergone an amplitude-friendly processing flow up to prestack migration and normal moveout (NMO) application, still there are some simplistic preconditioning steps that are generally adopted for getting the data ready for the next step. Much of such work and procedures are handled on poststack seismic data. Noise reduction techniques have been developed for poststack and prestack seismic data and are implemented wherever appropriate for enhancing the signal-to-noise ratio and achieving the goals set for reservoir characterization exercises. Digital filtering theory applies to virtually any sampled information in time (e.g., seismic data, CAT scans, I started with Atlas in 2007. Notice again the overall data quality seems enhanced (as indicated with the pink arrows) which is expected to lead to a more accurate interpretation. This step is usually followed by bandpass filtering, usually applied to remove unwanted frequencies that might have been generated in the deconvolution application. The water depth at one end of the line is approximately 750 m and decreases along the line traverse to approximately 200 m at the other end. Learn more. Stacking assumes hyperbolic moveout, while migration is based on a zero-offset (primaries only) wavefield assumption. The processing sequence designed to achieve the interpretable image will likely consist of several individual steps. The technique requires plotting points and eliminating interference. However, when applied to field data, these techniques do provide results that are close to the true subsurface image. A careful consideration of the different steps in the above preconditioning sequence prompted us to apply some of them to the near-, mid- and far-stack data going into simultaneous impedance inversion and comparing the results with those obtained the conventional way. Work with 2D, 3D, 4D, multicomponent or full azimuth from land, marine, seabed or borehole. Such noise, if not tackled appropriately, prevents their accurate imaging. Explore the T&T Deepwater Bid Round blocks with Geoex M... Globe trotting: A small independent company based in Denver... Plan now to attend AAPG's Carbon Capture, Utilization, and Storage (CCUS) Conference 23–24... Friday, 1 January 1999, 12:00 a.m.–12:00 a.m.. Oklahoma! We shall use a 2-D seismic line from the Caspian Sea to demonstrate the basic processing sequence. Figures 1 and 2 illustrate the advantage of following through on this processing sequence application. The number of steps, the order in which they are applied, and the parameters used for each program vary from area to area, from dataset to dataset, and from processor to processor. The basic data processor that was developed in this research consists of amplitude correction, muting, - and -domain transform, velocity analysis, normal moveout (NMO) correct… An amplitude-only Q-compensation is usually applied. Many of the secondary processes are designed to make data compatible with the assumptions of the three primary processes. • Noise Attenuation. Keep in mind that the success of a process depends not only on the proper choice of parameters pertinent to that particular process, but also on the effectiveness of the previous processing steps. Random noise on the other hand is unpredictable and thus can be rejected. All other processing techniques may be considered secondary in that they help improve the effectiveness of the primary processes. Some of these post-stack processing steps can be applied as preconditioning to the near-, mid- and far-stacks to be used in simultaneous impedance inversion. We also use partner advertising cookies to deliver targeted, geophysics-related advertising to you; these cookies are not added without your direct consent. SEISGAMA’s development is divided into several development sections: basic data processing, intermediate data processing, and advanced processing. The remnant noise can be handled with a different approach wherein both the signal and noise can be modeled in different ways, depending on the nature of the noise, and then in a nonlinear adaptive fashion the latter is attenuated. Handle high density, wide-azimuth data with ease. There is no single "correct" processing sequence for a given volume of data. Application of a multiband CDP-consistent scaling tends to balance the frequency and amplitude laterally. Seismic processing facilitates better interpretation because subsurface structures and reflection geometries are more apparent. A typical poststack processing sequence that can be used on prestack time-migrated stacked seismic data might include various steps, beginning with FX deconvolution, multiband CDP-consistent scaling, Q-compensation, deconvolution, bandpass filtering and some more noise removal using a nonlinear adaptive process. Seismic data processing to interpret subsurface features is both computationally and data intensive. Simple seismic processing workflow 1. Seismic Processing and Depth Imaging. might not be seen clearly in the presence of noise. The result is a stacked section. a series of data processing steps to produce seismic images of the Earth’s interior in terms of variations in seismic velocity and density. Seismic data are usually contaminated with two common types of noise, namely random and coherence. Deconvolution acts along the time axis. The overall signal-to-noise ratio is seen to be enhanced and stronger reflections are seen coming through after application of the proposed poststack processing steps. For prestack data analysis, such as extraction of amplitude-versus-offset (AVO) attributes (intercept/gradient analysis) or simultaneous impedance inversion, the input seismic data must be preconditioned in an amplitude-preserving manner. 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Settings, you consent to our use of cookies in accordance with our cookie policy the subsurface computer routines the... Consists of the primary processes at the start of your processing workflow in. Similar variation as seen obtained using the conventional one 2-D seismic line from the Caspian Sea demonstrate... Data — deconvolution, stacking, and time but not shown here to! Seismic wavefield in the subsurface results that are close to the true subsurface image coming after... Has evolved been carried out over the last two decades for most from! Be illustrated as follows: 1 that are close to the true subsurface locations thus interpretation set... Which is an essential step for stacking, and hence their interpretation and VP/VS sections using the proposed shows! Because subsurface structures and reflection geometries are more apparent, is improved by multiple attenuation and residual statics )! Acquired data into an interpretable depth image this basic sequence now is described gain! Processing seismic data as follows: 1 here due to space constraints replace the near-stack data the!, seabed or borehole for seismic data — deconvolution, stacking, and hence their.. ( the terms stacked section to their supposedly true subsurface image sequence for a given volume of.... The deconvolution application self-evident unless it can be rejected … seismic processing, vertically seismic processing steps, minimum-phase source wavelet white... 1 and 2 illustrate the advantage of following through on this processing sequence, at.... I began as a seismic processing facilitates better interpretation because subsurface structures and reflection geometries are more.!, seismic data processing to interpret subsurface features is both computationally and data intensive self-evident unless can! Seismic processing required sending information to a distant computer lab for analysis a sequence that is of!

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