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 APLIKASI METODE PSEUDO 3D SEISMIK DI CEKUNGAN JAWA BARAT UTARA MENGGUNAKAN K.R. BARUNA JAYA II

Oseanika ◽  
2021 ◽  
Vol 1 (2) ◽  
pp. 1-12
Author(s):  
Trevi Jayanti Puspasari ◽  
Sumirah Sumirah
Keyword(s):  
Data Processing ◽  
Seismic Data ◽  
Oil And Gas ◽  
Oil And Gas Industry ◽  
Processing Technique ◽  
3D Seismic ◽  
Seismic Data Processing ◽  
West Java ◽  
Gas Industry ◽  
North West

ABSTRAK Tuntutan untuk mengikuti perkembangan kebutuhan industri migas menjadi motivasi dalam mengembangkan teknik penerapan dan aplikasi akuisisi seismik multichannel 2D. Perkembangan kebutuhan eksplorasi industri migas tidak diimbangi dengan  anggaran peningkatan alat survei seismik milik negara termasuk yang terpasang di K.R. Baruna Jaya II – BPPT. Penerapan metode pseudo 3D pada disain survei dan pengolahan data dapat menjadi solusi efektif dan efisien dalam mengatasi persoalan tersebut. Metode Pseudo 3D merupakan suatu teknik akuisisi dan pengolahan data dengan menitik beratkan pada disain akuisisi dan inovasi pengolahan data seismik 2D menghasilkan penampang keruangan (3D) berdasarkan input data seismik yang hanya 2D. Penelitian ini bertujuan untuk mengaplikasikan metode pseudo 3D seismik di Cekungan Jawa Barat Utara menggunakan wahana KR. Baruna Jaya II yang dilakukan pada Desember 2009. Sebagai hasil, pengolahan data 2D lanjutan telah dilakukan dan diperoleh profil penampang seismik keruangan (3D). Profil hasil pengolahan data Pseudo 3D ini dapat menjadi acuan dalam pengambilan keputusan dan rencana survei berikutnya. Kata Kunci: Seismik Pseudo 3D, Seismik multichannel 2D, K.R. Baruna Jaya II, Cekungan Jawa Barat Utara. ABSTRACT [Aplication of Seismic Pseudo 3D in Nort West Java Basin Using K.R. Baruna Jaya II] The demand to follow the growth of  needs in the oil and gas industry is a motivation in the developing of techniques for assessment and applying 2D multichannel seismic acquisition. The development of exploration needs for the oil and gas industry is not matched by budget for an upgrade Government’s seismic equipment including equipment installed in K.R. Baruna Jaya II. Applied Pseudo 3D method in survey and seismic data processing can be an effective and efficient solution. The pseudo 3D method is a data acquisition and processing technique with an emphasis on the acquisition design and 2D seismic data processing innovation to produce a 3D seismic volume. This study aims to apply the pseudo 3D seismic method in the North West Java Basin using the K.R. Baruna Jaya II which was held in Desember 2009. As a Result, advanced seismic processing was carried out to output a seismic volume (3D) profile. This profile can be used as a reference in making decisions and planning the next survey.   Keywords:          Pseudo 3D Seismic, Seismic 2D multichannel, K.R. Baruna Jaya II, Nort West Java Basin.

Unified imaging of multichannel seismic data: Combining traveltime inversion and prestack depth migration

Geophysics ◽  
2008 ◽  
Vol 73 (5) ◽  
pp. VE269-VE280 ◽  
Author(s):  
Priyank Jaiswal ◽  
Colin A. Zelt
Keyword(s):  
Seismic Data ◽  
Joint Inversion ◽  
Velocity Model ◽  
Depth Image ◽  
Prestack Depth Migration ◽  
Traveltime Inversion ◽  
Depth Migration ◽  
Interval Velocity ◽  
Wide Aperture ◽  
Zero Offset

Imaging 2D multichannel land seismic data can be accomplished effectively by a combination of traveltime inversion and prestack depth migration (PSDM), referred to as unified imaging. Unified imaging begins by inverting the direct-arrival times to estimate a velocity model that is used in static corrections and stacking velocity analysis. The interval velocity model (from stacking velocities) is used for PSDM. The stacked data and the PSDM image are interpreted for common horizons, and the corresponding wide-aperture reflections are identified in the shot gathers. Using the interval velocity model, the stack interpretations are inverted as zero-offset reflections to constrain the corresponding interfaces in depth; the interval velocity model remains stationary. We define a coefficient of congruence [Formula: see text] that measures the discrepancy between horizons from the PSDM image andtheir counterparts from the zero-offset inversion. A value of unity for [Formula: see text] implies that the interpreted and inverted horizons are consistent to within the interpretational uncertainties, and the unified imaging is said to have converged. For [Formula: see text] greater than unity, the interval velocity model and the horizon depths are updated by jointly inverting the direct arrivals with the zero-offset and wide-aperture reflections. The updated interval velocity model is used again for both PSDM and a zero-offset inversion. Interpretations of the new PSDM image are the updated horizon depths. The unified imaging is applied to seismic data from the Naga Thrust and Fold Belt in India. Wide-aperture and zero-offset data from three geologically significant horizons are used. Three runs of joint inversion and PSDM are required in a cyclic manner for [Formula: see text] to converge to unity. A joint interpretation of the final velocity model and depth image reveals the presence of a triangle zone that could be promising for exploration.

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>

MAZ depth-velocity modelling and imaging with azimuthal anisotropy

2010 ◽  
Vol 50 (2) ◽  
pp. 723
Author(s):  
Sergey Birdus ◽  
Erika Angerer ◽  
Iftikhar Abassi
Keyword(s):  
Seismic Data ◽  
Real Data ◽  
Azimuthal Velocity ◽  
Velocity Model ◽  
Azimuthal Anisotropy ◽  
Lessons Learned ◽  
Seismic Survey ◽  
Depth Migration ◽  
Velocity Anisotropy ◽  
Interval Velocity

Processing of multi and wide-azimuth seismic data faces some new challenges, and one of them is depth-velocity modelling and imaging with azimuthal velocity anisotropy. Analysis of multi-azimuth data very often reveals noticeable fluctuations in moveout between different acquisition directions. They can be caused by several factors: real azimuthal interval velocity anisotropy associated with quasi-vertical fractures or present day stress field within the sediments; short-wavelength velocity heterogeneities in the overburden; TTI (or VTI) anisotropy in the overburden; or, random distortions due to noise, multiples, irregularities in the acquisition geometry, etcetera. In order to build a velocity model for multi-azimuth pre-stack depth migration (MAZ PSDM) taking into account observed azimuthal anisotropy, we need to recognise, separate and estimate all the effects listed above during iterative depth-velocity modelling. Analysis of seismic data from a full azimuth 3D seismic land survey revealed the presence of strong spatially variable azimuthal velocity anisotropy that had to be taken into consideration. Using real data examples we discuss major steps in depth processing workflow that took such anisotropy into account: residual moveout estimation in azimuth sectors; separation of different effects causing apparent azimuthal anisotropy (see A–D above); iterative depth-velocity modelling with azimuthal anisotropy; and, subsequent MAZ anisotropic PSDM. The presented workflow solved problems with azimuthal anisotropy in our multi-azimuth dataset. Some of the lessons learned during this MAZ project are relevant to every standard narrow azimuth seismic survey recorded in complex geological settings.

ADVANCES IN 3-D SEISMIC DATA PROCESSING TECHNIQUES

1992 ◽  
Vol 32 (1) ◽  
pp. 276
Author(s):  
T.J. Allen ◽  
P. Whiting
Keyword(s):  
Data Processing ◽  
Seismic Data ◽  
Three Dimensional ◽  
Velocity Model ◽  
Migration Velocity ◽  
Seismic Data Processing ◽  
Data Set ◽  
Migration Velocity Analysis ◽  
Processing Techniques ◽  
Made In

Several recent advances made in 3-D seismic data processing are discussed in this paper.Development of a time-variant FK dip-moveout algorithm allows application of the correct three-dimensional operator. Coupled with a high-dip one-pass 3-D migration algorithm, this provides improved resolution and response at all azimuths. The use of dilation operators extends the capability of the process to include an economical and accurate (within well-defined limits) 3-D depth migration.Accuracy of the migration velocity model may be improved by the use of migration velocity analysis: of the two approaches considered, the data-subsetting technique gives more reliable and interpretable results.Conflicts in recording azimuth and bin dimensions of overlapping 3-D surveys may be resolved by the use of a 3-D interpolation algorithm applied post 3-D stack and which allows the combined surveys to be 3-D migrated as one data set.

Seismic Data Processing and Depth Imaging for Yingxionglin Complex Structures-Belt in Qaidam Basin, Tibetan Plateau

2021 ◽  
Author(s):  
Yongsheng Wang ◽  
Chenqing Tan ◽  
Bo Zhu ◽  
Yanming Tong ◽  
Haifeng Wang ◽  
...  
Keyword(s):  
Data Processing ◽  
Seismic Data ◽  
Qaidam Basin ◽  
Surface Condition ◽  
Complex Surface ◽  
Seismic Data Processing ◽  
Depth Migration ◽  
Velocity Modeling ◽  
Static Correction ◽  
Exploration And Production

Abstract The Yingxionglin structural belt located in the world's highest-altitude petroliferous basin, Qaidam Basin. Due to its complex surface condition, subsurface structure and low signal-to-noise ratios (SNR) of seismic data, exploration and production is quite challenging. From 2012 to now, we continued developing and improving seismic data processing and interpretation workflow. After several rounds field support and testing, new techniques exploring and velocity modelling iteration, we gradually developed a suitable workflow for complex dipping structure imaging including signal processing, velocity modeling, and depth migration. The quality of final delivered 3D seismic data is significantly improved with the integrated static correction techniques, fidelity multi-domain noise attenuation, 5D MPFI regularization, integrated velocity modelling and final pre-stack depth migration. According to our final deliverables, we identified credible traps and high-production reservoirs were found.

Vertical seismic profiling depth migration of a salt dome flank

Geophysics ◽  
1986 ◽  
Vol 51 (5) ◽  
pp. 1087-1109 ◽  
Author(s):  
N. D. Whitmore ◽  
Larry R. Lines
Keyword(s):  
Data Processing ◽  
Survey Design ◽  
Velocity Model ◽  
Salt Dome ◽  
Velocity Estimation ◽  
Seismic Profiles ◽  
Depth Migration ◽  
Vertical Seismic Profiles ◽  
Interval Velocity ◽  
Vsp Data

Vertical seismic profiles (VSPs) can supply information about both velocity and subsurface interface locations. Properly designed VSPs can be used to map steeply dipping interfaces such as salt dome flanks. Mapping subsurface interfaces with VSP data requires careful survey design, appropriate data processing, interval velocity estimation, and reflector mapping. The first of these four ingredients is satisfied, in most cases, by preacquisition modeling. The second is accomplished by careful data processing. Initial velocity estimates are provided by seismic tomography. Velocity‐model refinement is accomplished by a combination of iterative modeling and iterative least‐squares inversion. Finally, the resultant interval velocities are used in depth migration of the processed VSP. These four ingredients have been combined to map a salt dome flank.

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). .

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