scholarly journals Method Comparison of Model Based Tomography and Grid Based Tomography to refine interval velocity

2016 ◽  
Vol 4 (01) ◽  
pp. 63
Author(s):  
Yuninggar Dwi Nugroho ◽  
Sudarmaji S
Keyword(s):  
Method Comparison ◽  
Velocity Model ◽  
Seismic Section ◽  
Initial Interval ◽  
Depth Migration ◽  
Interval Velocity ◽  
Model Based ◽  
Time Migration ◽  
Tomography Method ◽  
Grid Based

<span>The input data for pre stack time migration and pre stack depth migration is velocity model. <span>The exact velocity model can provide maximum result in seismic section. The best seismic <span>section can minimize possibility of errors during interpretation. Model based and grid based <span>tomography are used to refine the interval velocity model. The interval velocity will be used as <span>input in the pre stack depth migration. Initial interval velocity is obtained from RMS velocity<br /><span>using Dix formula. This velocity will be refined by global depth tomography method. The <span>global depth tomography method is divided into model based and grid based tomography. <span>Velocity analysis is performed along the horizon (depth model). Residual depth move out is <span>obtained from picking velocity. It is used as input in tomography method. The flat gather is <span>obtained at tenth iteration. The interval velocity that is obtained from tenth iteration has the <span>small errors. Tomography method can provide maximum result on velocity refinement. That is <span>shown by the result that the pre stack depth migration is much better than using initial interval <span>velocity. The pull up effect can be corrected by tomography method.</span></span></span></span></span></span></span></span></span></span></span></span><br /></span>

scholarly journals SEMBLANCE RESIDUAL MOVEOUT ANALYSIS TO FIND ERORRS AND UPDATING THE INTERVAL VELOCITY MODEL MODE IN THE HORIZON BASED TOMOGRAPHY METHOD

2020 ◽  
Vol 82 (6) ◽  
pp. 29-37
Author(s):  
Sudra Irawan ◽  
Siti Noor Chayati ◽  
Sismanto Sismanto
Keyword(s):  
Seismic Waves ◽  
Velocity Model ◽  
Depth Image ◽  
Model Errors ◽  
Initial Interval ◽  
Depth Migration ◽  
Interval Velocity ◽  
Imaging Results ◽  
Tomography Method ◽  
Well Data

The tomography method requires an excellent initial velocity model. On the horizon based tomography, it will correct the travel time error of seismic waves along the horizon which is analysed using input results from the analysis of residual depth moveout. In this study, a semblance residual moveout analysis will be conducted after the interval velocity model has applied to the SBI field seismic data (CDP Gathers and RMS velocity). Based on the imaging results generated by the PSDM running process, an aperture value of 550 for inline and 800 for crossline is selected. PSDM generated from the initial interval velocity model has an acoustic impedance value between 1000 kg/m2s to 14339.2 kg/m2s. The PSDM process, residual moveout analysis, and horizon-based tomography are carried out iteratively until the error in the interval velocity model approaches zero. In this study, five iterations were performed. The resulting residual moveout is increasingly oscillating around zero after the 5th iteration, which indicates that the error in the interval velocity model is getting smaller. There are two types of residual moveout, namely residuals moveout positively and residuals moveout negatively. Residual moveout positive indicates that the velocity used is too high, while the residual moveout negative indicates that the velocity used is too low. The identification of interval velocity model errors with analysis of residual moveout semblance is calculated from depth gathers. The semblance residual moveout analysis is used for the Pre Stack Depth Migration (PSDM) depth image analysis stage along with the marker (well data). .

Applying the Horizon Based Tomography Method to Update Interval Velocity Model, Identify The Structure of Pre-Stack Depth Migration 3D and Estimate The Hydrocarbon Reserve In SBI Field of North West Java Basin

2014 ◽  
Vol 69 (6) ◽  
Author(s):  
Sudra Irawan ◽  
Sismanto Sismanto ◽  
Adang Sukmatiawan
Keyword(s):  
Data Processing ◽  
Seismic Data ◽  
Velocity Model ◽  
Research Area ◽  
Seismic Data Processing ◽  
West Java ◽  
North West ◽  
Depth Migration ◽  
Interval Velocity ◽  
Tomography Method

Seismic data processing is one of the three stages in the seismic method that has an important role in the exploration of oil and gas. Without good data processing, it is impossible to get seismic image cross section for good interpretation. A research using seismic data processing was done to update the velocity model by horizon based tomography method in SBI Field, North West Java Basin. This method reduces error of seismic wave travel time through the analyzed horizon because the existence velocity of high lateral variation in research area. There are three parameters used to determine the accuracy of the resulting interval velocity model, namely, flat depth gathers, semblance residual moveout that coincides with the axis zero residual moveout, and the correspondence between image depth (horizon) with wells marker  (well seismic tie). Pre Stack Depth Migration (PSDM) form interval velocity model and updating using horizon-based tomography method gives better imaging of under-surfaced structure results than PSDM before using tomography. There are three faults found in the research area, two normal faults have southwest-northeast strike and the other has northwest-southeast strike. The thickness of reservoir in SBI field, North West Java Basin, is predicted between 71 to 175 meters and the hydrocarbon (oil) reserve is predicted about  with 22.6% porosity and 70.7% water saturation. 

scholarly journals QUALITY IMPROVEMENT OF SEISMIC IMAGE FROM 2D PSDM (PRE STACK DEPTH MIGRATION) USING TOMOGRAPHY FOR INTERVAL VELOCITY MODEL REFINEMENT

2016 ◽  
Vol 28 (2) ◽  
pp. 43
Author(s):  
Hagayudha Timotius ◽  
Yulinar Firdaus
Keyword(s):  
Velocity Model ◽  
Seismic Exploration ◽  
Lateral Velocity ◽  
Model Refinement ◽  
Initial Interval ◽  
Depth Migration ◽  
Interval Velocity ◽  
Imaging Tool ◽  
Main Challenge ◽  
Seismic Image

The main goal of seismic exploration is to get an accurate image of subsurface section so it can be easily interpreted. Pre Stack Depth Migration (PSDM) is such a powerful imaging tool especially for complex area such an area where strong lateral velocity variations exist. The main challenge of PSDM is the need of accurate interval velocity model.In this research, Dix Transformation, coherency inversion, and tomography are used for initial interval velocity model, and then tomography is used for interval velocity model refinement. We compare also between seismic image resulted from PSDM and PSTM to determine the best method. The seismic data that processed in this paper is derived from north western part of Australian Waters. Kata kunci: Pre Stack Depth Migration, Dix Transformation, coherency inversion, tomography. Tujuan utama dari eksplorasi seismik adalah menghasilkan citra yang akurat dari penampang bawah permukaan sehingga diinterpretasi lebih mudah. Pre Stack Depth Migration (PSDM) merupakan suatu metode yang memberikan hasil peningkatan kualitas citra seismik pada daerah kompleks dimana terjadi variasi kecepatan lateral yang signifikan. Salah satu syarat penting yang harus dipenuhi agar hasil PSDM lebih optimal adalah model kecepatan interval yang akurat. Dalam penelitian ini Transformasi Dix, inversi koheren, dan tomografi digunakan untuk memenuhi syarat tersebut. Perbandingan hasil penampang seimik PSDM dan PSTM dilakukan untuk menentukan metode terbaik. Data seismik yang diolah dalam tulisan ini berasal dari wilayah Perairan Baratlaut Australia. Kata kunci: Pre Stack Depth Migration, Transformasi Dix, inversi koheren, tomografi

scholarly journals PRE STACK DEPTH MIGRATION UNTUK KOREKSI EFEK PULL UP DENGAN MENGGUNAKAN METODE HORIZON BASED DEPTH TOMOGRAPHY PADA LAPANGAN ‘A1 DAN A2’

2020 ◽  
Vol 4 (1) ◽  
pp. 64-77
Author(s):  
Attikah Azzahra ◽  
Bagus Sapto Mulyatno ◽  
Bambang Mujihardi
Keyword(s):  
Data Processing ◽  
Time Domain ◽  
Depth Migration ◽  
Velocity Transformation ◽  
Velocity Modeling ◽  
Interval Velocity ◽  
Time Migration ◽  
And Migration ◽  
Tomography Method ◽  
The Time Domain

In the case of seismic data processing with sandstone lithology such as shale and carbonate often get the result of data processing which have pull up effect especially on the time domain migration result. Pre stack depth migration is a processing based on focusing the amplitude according to the actual depth by using the input interval velocity. Migration is performed using kirchhoff pre stack depth migration algorithm. Pre stack depth migration is done with modeling of horizontal based depth tomography method. This method uses residual moveout correction applied along the horizon-picking line. This research uses two field data that is A1 and A2 Field. A1field has characteristics of carbonate rock that produce pull up shaped similar to carbonate layer. A2 field has a pull-up effect that is not very clear but has build up because of the layer above it. Stages performed starting from the processing of pre stack time migration in the form of velocity picking, generate rms velocity and migration time domain. The pre stack depth migration process begins with a velocity transformation with the dix transformation equation to generate interval velocity, migrate Pre stack depth migration, perform horizon interpretations and perform velocity modeling using the horizon based depth tomography method. The iteration is done 4 times and resulted in the final section of pre stack depth migration which has been corrected by pull up effect.

IMAGING BENEATH COMPLEX STRUCTURE: A CASE HISTORY

1981 ◽  
Vol 21 (1) ◽  
pp. 112
Author(s):  
K. Lamer ◽  
B. Gibson ◽  
R. Chambers
Keyword(s):  
Velocity Structure ◽  
Deep Structure ◽  
Complex Structure ◽  
Velocity Model ◽  
Important Conclusion ◽  
Depth Migration ◽  
Interval Velocity ◽  
Velocity Models ◽  
Time Migration ◽  
Zero Offset

Migration is recognised as the essential step in converting seismic, data into a representation of the earth's subsurface structure. Ironically, conventional migration often fails where migration is needed most—when the data are recorded over complex structures. Processing field data shot in Central America, and synthetic data derived for that section, demonstrates that time migration actually degrades the image of the deep structure that lies below a complicated overburden.In the Central American example, velocities increase nearly two-fold across an arched and thrust-faulted interface. Wavefront distortion introduced by this feature gives rise to distorted reflections from depth. Even with interval velocity known perfectly, no velocity is proper for time migrating the data here; time migration is the wrong process because it does not honour Snell's Law. Depth migration of the stacked data, on the other hand, produces a reasonable image of the deeper section. The depth migration, however, leaves artifacts that could be attributed to problems that are common in structurally complicated areas: (1) departures of the stacked section from the ideal, a zero-offset section; (2) incorrect specification of velocities; and (3) loss of energy transmitted through the complex zoneFor such an inhomogeneous velocity structure, shortcomings in CDP stacking are directly related to highly non- hyperbolic moveout. As with migration velocity, no proper stacking velocity can be developed for these data, even from the known interval-velocity model. Proper treatment of nonzero-offset reflection data could be accomplished by depth migration before stacking. Simple ray-theoretical correction of the complex moveouts, however, can produce a stack that is similar to the desired zero-offset section.Overall, the choice of velocity model most strongly influences the results of depth migration. Processing the data with a range of plausible velocity models, however, leads to an important conclusion: although the velocities can never be known exactly, depth migration is essential for clarifying structure beneath complex overburden.

Depth migration by the Gaussian beam summation method

Geophysics ◽  
2010 ◽  
Vol 75 (2) ◽  
pp. S81-S93 ◽  
Author(s):  
Mikhail M. Popov ◽  
Nikolay M. Semtchenok ◽  
Peter M. Popov ◽  
Arie R. Verdel
Keyword(s):  
Wave Equation ◽  
Model Building ◽  
Velocity Structure ◽  
Velocity Model ◽  
Summation Method ◽  
Reverse Time ◽  
Reverse Time Migration ◽  
Depth Migration ◽  
Time Migration ◽  
Ray Methods

Seismic depth migration aims to produce an image of seismic reflection interfaces. Ray methods are suitable for subsurface target-oriented imaging and are less costly compared to two-way wave-equation-based migration, but break down in cases when a complex velocity structure gives rise to the appearance of caustics. Ray methods also have difficulties in correctly handling the different branches of the wavefront that result from wave propagation through a caustic. On the other hand, migration methods based on the two-way wave equation, referred to as reverse-time migration, are known to be capable of dealing with these problems. However, they are very expensive, especially in the 3D case. It can be prohibitive if many iterations are needed, such as for velocity-model building. Our method relies on the calculation of the Green functions for the classical wave equation by per-forming a summation of Gaussian beams for the direct and back-propagated wavefields. The subsurface image is obtained by cal-culating the coherence between the direct and backpropagated wavefields. To a large extent, our method combines the advantages of the high computational speed of ray-based migration with the high accuracy of reverse-time wave-equation migration because it can overcome problems with caustics, handle all arrivals, yield good images of steep flanks, and is readily extendible to target-oriented implementation. We have demonstrated the quality of our method with several state-of-the-art benchmark subsurface models, which have velocity variations up to a high degree of complexity. Our algorithm is especially suited for efficient imaging of selected subsurface subdomains, which is a large advantage particularly for 3D imaging and velocity-model refinement applications such as subsalt velocity-model improvement. Because our method is also capable of providing highly accurate migration results in structurally complex subsurface settings, we have also included the concept of true-amplitude imaging in our migration technique.

3-D prestack Kirchhoff depth migration: From prototype to production in a massively parallel processor environment

Geophysics ◽  
1998 ◽  
Vol 63 (2) ◽  
pp. 546-556 ◽  
Author(s):  
Herman Chang ◽  
John P. VanDyke ◽  
Marcelo Solano ◽  
George A. McMechan ◽  
Duryodhan Epili
Keyword(s):  
Model Building ◽  
Velocity Model ◽  
Production Scale ◽  
Data Set ◽  
Depth Migration ◽  
Prestack Migration ◽  
Prototype Development ◽  
Time Migration ◽  
Intel Paragon ◽  
Kirchhoff Depth Migration

Portable, production‐scale 3-D prestack Kirchhoff depth migration software capable of full‐volume imaging has been successfully implemented and applied to a six‐million trace (46.9 Gbyte) marine data set from a salt/subsalt play in the Gulf of Mexico. Velocity model building and updates use an image‐driven strategy and were performed in a Sun Sparc environment. Images obtained by 3-D prestack migration after three velocity iterations are substantially better focused and reveal drilling targets that were not visible in images obtained from conventional 3-D poststack time migration. Amplitudes are well preserved, so anomalies associated with known reservoirs conform to the petrophysical predictions. Prototype development was on an 8-node Intel iPSC860 computer; the production version was run on an 1824-node Intel Paragon computer. The code has been successfully ported to CRAY (T3D) and Unix workstation (PVM) environments.

Noise removal by migration of time-shift images

Geophysics ◽  
2014 ◽  
Vol 79 (3) ◽  
pp. S105-S111 ◽  
Author(s):  
Sheng Xu ◽  
Feng Chen ◽  
Bing Tang ◽  
Gilles Lambare
Keyword(s):  
Time Lag ◽  
Real Data ◽  
Velocity Model ◽  
Noise Removal ◽  
Time Shift ◽  
Reverse Time ◽  
Coherent Noise ◽  
Data Set ◽  
Depth Migration ◽  
Time Migration

When using seismic data to image complex structures, the reverse time migration (RTM) algorithm generally provides the best results when the velocity model is accurate. With an inexact model, moveouts appear in common image gathers (CIGs), which are either in the surface offset domain or in subsurface angle domain; thus, the stacked image is not well focused. In extended image gathers, the strongest energy of a seismic event may occur at non-zero-lag in time-shift or offset-shift gathers. Based on the operation of RTM images produced by the time-shift imaging condition, the non-zero-lag time-shift images exhibit a spatial shift; we propose an approach to correct them by a second pass of migration similar to zero-offset depth migration; the proposed approach is based on the local poststack depth migration assumption. After the proposed second-pass migration, the time-shift CIGs appear to be flat and can be stacked. The stack enhances the energy of seismic events that are defocused at zero time lag due to the inaccuracy of the model, even though the new focused events stay at the previous positions, which might deviate from the true positions of seismic reflection. With the stack, our proposed approach is also able to attenuate the long-wavelength RTM artifacts. In the case of tilted transverse isotropic migration, we propose a scheme to defocus the coherent noise, such as migration artifacts from residual multiples, by applying the original migration velocity model along the symmetry axis but with different anisotropic parameters in the second pass of migration. We demonstrate that our approach is effective to attenuate the coherent noise at subsalt area with two synthetic data sets and one real data set from the Gulf of Mexico.

Migration of seismic data from inhomogeneous media

Geophysics ◽  
1981 ◽  
Vol 46 (5) ◽  
pp. 751-767 ◽  
Author(s):  
Les Hatton ◽  
Ken Larner ◽  
Bruce S. Gibson
Keyword(s):  
Theoretical Approach ◽  
Synthetic Data ◽  
Velocity Model ◽  
Implicit Assumption ◽  
Geologic Structure ◽  
Structural Shape ◽  
Depth Migration ◽  
Position Errors ◽  
Time Migration ◽  
Imaging Results

Because conventional time‐migration algorithms are founded on the implicit assumption of locally lateral homogeneity, they leave events mispositioned when overburden velocity varies laterally. The ray‐theoretical depth migration procedure of Hubral often can provide adequate first‐order corrections for such position errors. Complex geologic structure, however, can so severely distort wavefronts that resulting time‐migrated sections may be barely interpretable and thus not readily correctable. A more accurate, wave‐theoretical approach to depth migration then becomes essential to image the subsurface properly. This approach, which transforms an unmigrated time section directly into migrated depth, more completely honors the wave equation for a medium in which variations in interval velocity and details of structural shape govern wave propagation. Where geologic structure is complicated, however, we usually lack an accurate velocity model. It is important, therefore, to understand the sensitivity of depth migration to velocity errors and, in particular, to assess whether it is justified to go to the added effort of doing depth migration. We show a synthetic data example in which the wave‐theoretical approach to depth migration properly images deep reflections that are poorly resolved and left distorted by either time migration or ray‐theoretical depth migration. These imaging results are, moreover, surprisingly insensitive to errors introduced into the velocity model. Application to one field data example demonstrates the superior treatment of amplitude and waveform by wave‐theoretical depth migration. In a second data example, deep reflections are so influenced by anomalous overburden structure that the only valid alternative to performing wave‐theoretical depth migration is simply to convert the unmigrated data to depth. When the overburden is laterally variable, conventional time migration of unstacked data can be as destructive to steeply dipping reflections as is CDP stacking prior to migration. A schematic example illustrates that when migration of unstacked data is judged necessary, it should normally be performed as a depth migration.

Incorporating geologic information into reflection tomography

Geophysics ◽  
2004 ◽  
Vol 69 (2) ◽  
pp. 533-546 ◽  
Author(s):  
Robert G. Clapp ◽  
Biondo L. Biondi ◽  
Jon F. Claerbout
Keyword(s):  
Velocity Structure ◽  
Null Space ◽  
Velocity Model ◽  
Prestack Depth Migration ◽  
Depth Migration ◽  
Interval Velocity ◽  
Velocity Models ◽  
Regularized Inversion ◽  
Symmetric Operators ◽  
Reflection Tomography

In areas of complex geology, prestack depth migration is often necessary if we are to produce an accurate image of the subsurface. Prestack depth migration requires an accurate interval velocity model. With few exceptions, the subsurface velocities are not known beforehand and should be estimated. When the velocity structure is complex, with significant lateral variations, reflection‐tomography methods are often an effective tool for improving the velocity estimate. Unfortunately, reflection tomography often converges slowly, to a model that is geologically unreasonable, or it does not converge at all. The large null space of reflection‐tomography problems often forces us to add a sparse parameterization of the model and/or regularization criteria to the estimation. Standard tomography schemes tend to create isotropic features in velocity models that are inconsistent with geology. These isotropic features result, in large part, from using symmetric regularization operators or from choosing a poor model parameterization. If we replace the symmetric operators with nonstationary operators that tend to spread information along structural dips, the tomography will produce velocity models that are geologically more reasonable. In addition, by forming the operators in helical 1D space and performing polynomial division, we apply the inverse of these space‐varying anisotropic operators. The inverse operators can be used as a preconditioner to a standard tomography problem, thereby significantly improving the speed of convergence compared with the typical regularized inversion problem. Results from 2D synthetic and 2D field data are shown. In each case, the velocity obtained improves the focusing of the migrated image.

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