Reflectivity decomposition: Theory and application

2021 ◽  
pp. 1-57
Author(s):  
Chen Liang ◽  
John Castagna ◽  
Marcelo Benabentos
Keyword(s):  
Seismic Data ◽  
Seismic Inversion ◽  
Well Logs ◽  
Reflection Coefficients ◽  
3D Seismic ◽  
Decomposition Theory ◽  
Midland Basin ◽  
Reflection Seismic ◽  
Sparse Inversion ◽  
Reflectivity Inversion

Sparse reflectivity inversion of processed reflection seismic data is intended to produce reflection coefficients that represent boundaries between geological layers. However, the objective function for sparse inversion is usually dominated by large reflection coefficients which may result in unstable inversion for weak events, especially those interfering with strong reflections. We propose that any seismogram can be decomposed according to the characteristics of the inverted reflection coefficients which can be sorted and subset by magnitude, sign, and sequence, and new seismic traces can be created from only reflection coefficients that pass sorting criteria. We call this process reflectivity decomposition. For example, original inverted reflection coefficients can be decomposed by magnitude, large ones removed, the remaining reflection coefficients reconvolved with the wavelet, and this residual reinverted, thereby stabilizing inversions for the remaining weak events. As compared with inverting an original seismic trace, subtle impedance variations occurring in the vicinity of nearby strong reflections can be better revealed and characterized when only the events caused by small reflection coefficients are passed and reinverted. When we apply reflectivity decomposition to a 3D seismic dataset in the Midland Basin, seismic inversion for weak events is stabilized such that previously obscured porous intervals in the original inversion, can be detected and mapped, with good correlation to actual well logs.

Application of sparse-layer inversion and harmonic bandwidth extension for a channel system in Southern Alberta, Canada

2020 ◽  
Vol 8 (2) ◽  
pp. T217-T229
Author(s):  
Yang Mu ◽  
John Castagna ◽  
Gabriel Gil
Keyword(s):  
Seismic Data ◽  
Reflection Coefficients ◽  
3D Seismic ◽  
Bandwidth Extension ◽  
Data Set ◽  
Frequency Spectra ◽  
Channel System ◽  
Southern Alberta ◽  
Reflectivity Inversion ◽  
3D Seismic Data

Sparse-layer reflectivity inversion decomposes a seismic trace into a limited number of simple layer responses and their corresponding reflection coefficients for top and base reflections. In contrast to sparse-spike inversion, the applied sparsity constraint is less biased against layer thickness and can thus better resolve thin subtuning layers. Application to a 3D seismic data set in Southern Alberta produces inverted impedances that have better temporal resolution and lateral stability and a less blocky appearance than sparse-spike inversion. Bandwidth extension harmonically extrapolated the frequency spectra of the inverted layers and nearly doubled the usable bandwidth. Although the prospective glauconitic sand tunes at approximately 37 m, bandwidth extension reduced the tuning thickness to 22 m. Bandwidth-extended data indicate a higher correlation with synthetic traces than the original seismic data and reveal features below the original tuning thickness. After bandwidth extension, the channel top and base are more evident on inline and crossline profiles. Lateral facies changes interpreted from the inverted acoustic impedance of the bandwidth-extended data are consistent with observations in wells.

3D surface-related multiple elimination using parabolic sparse inversion

Geophysics ◽  
2006 ◽  
Vol 71 (6) ◽  
pp. V145-V152 ◽  
Author(s):  
Ketil Hokstad ◽  
Roger Sollie
Keyword(s):  
Seismic Data ◽  
Alternative Formulation ◽  
Practical Implementation ◽  
3D Seismic ◽  
Systems Of Equations ◽  
Production Scale ◽  
Seismic Acquisition ◽  
Sparse Inversion ◽  
Multiple Elimination ◽  
3D Seismic Data

The basic theory of surface-related multiple elimination (SRME) can be formulated easily for 3D seismic data. However, because standard 3D seismic acquisition geometries violate the requirements of the method, the practical implementation for 3D seismic data is far from trivial. A major problem is to perform the crossline-summation step of 3D SRME, which becomes aliased because of the large separation between receiver cables and between source lines. A solution to this problem, based on hyperbolic sparse inversion, has been presented previously. This method is an alternative to extensive interpolation and extrapolation of data. The hyperbolic sparse inversion is formulated in the time domain and leads to few, but large, systems of equations. In this paper, we propose an alternative formulation using parabolic sparse inversion based on an efficient weighted minimum-norm solution that can be computed in the angular frequency domain. The main advantage of the new method is numerical efficiency because solving many small systems of equations often is faster than solving a few big ones. The method is demonstrated on 3D synthetic and real data with reflected and diffracted multiples. Numerical results show that the proposed method gives improved results compared to 2D SRME. For typical seismic acquisition geometries, the numerical cost running on 50 processors is [Formula: see text] per output trace. This makes production-scale processing of 3D seismic data feasible on current Linux clusters.

scholarly journals Structural Geometry Analysis of Khasib Formation in West Qurna I and II Supergiant Oilfields, Southern Iraq

2021 ◽  
Vol 54 (1E) ◽  
pp. 54-66
Author(s):  
Rafea Ahmed Abdullah ◽  
Muwafaq Al-Shahwan
Keyword(s):  
Cross Sections ◽  
Seismic Data ◽  
Seismic Analysis ◽  
Seismic Profile ◽  
Well Logs ◽  
3D Seismic ◽  
Structural Geometry ◽  
Zero Offset ◽  
Geometry Analysis ◽  
Southern Iraq

The West Qurna I and II supergiant oilfields are one of the largest oil-producing fields, southern Iraq. They are parts of a supergiant anticline that extends more than 120 km. This anticline is oriented north-northwest and it's included the South Rumaila, North Rumaila, West Qurna I, and West Qurna II. The aim of this study is to integrate all available data to provide a better understanding of the subsurface structure for both West Qurna I and II. 3-D high-quality seismic data (in SEGY format) that executed for both oilfields independently were used as a key tool to supply perfect structural images. In addition to Zero-Offset Vertical Seismic Profile, set of well logs and well tops from 569 wells that distributed over the study area, 423 wells are located in West Qurna I, 146 wells situated in West Qurna II. OpenWorks, DecisionSpace G1 10ep and Seismic Analysis 10ep software of Halliburton were used to perform the 3D seismic interpretation and create structure maps (in-depth domain). While the cross-sections were done by Schlumberger software (Petrel 2018). Finally, the well tops were picked using Geolog 8.0. The study concludes that the structure of West Qurna I and II can be classified as an antiform, non-cylindrical, horizontal, gentle, brachy, asymmetrical anticline.

Seismic Quantitative Interpretation for Uncertainty Reduction of Subsurface Modeling of the Deep Visean Reservoirs

2021 ◽  
Author(s):  
Pavlo Kuzmenko ◽  
Rustem Valiakhmetov ◽  
Francesco Gerecitano ◽  
Viktor Maliar ◽  
Grigori Kashuba ◽  
...  
Keyword(s):  
Elastic Properties ◽  
Seismic Data ◽  
Seismic Anisotropy ◽  
Rock Physics ◽  
Seismic Inversion ◽  
Well Logs ◽  
Quantitative Interpretation ◽  
Structural Interpretation ◽  
Elastic Inversion ◽  
Subsurface Modeling

Abstract The seismic data have historically been utilized to perform structural interpretation of the geological subsurface. Modern approaches of Quantitative Interpretation are intended to extract geologically valuable information from the seismic data. This work demonstrates how rock physics enables optimal prediction of reservoir properties from seismic derived attributes. Using a seismic-driven approach with incorporated prior geological knowledge into a probabilistic subsurface model allowed capturing uncertainty and quantifying the risk for targeting new wells in the unexplored areas. Elastic properties estimated from the acquired seismic data are influenced by the depositional environment, fluid content, and local geological trends. By applying the rock physics model, we were able to predict the elastic properties of a potential lithology away from the well control points in the subsurface whether or not it has been penetrated. Seismic amplitude variation with incident angle (AVO) and azimuth (AVAZ) jointly with rock-derived petrophysical interpretations were used for stochastical modeling to capture the reservoir distribution over the deep Visean formation. The seismic inversion was calibrated by available well log data and by traditional structural interpretation. Seismic elastic inversion results in a deep Lower Carboniferous target in the central part of the DDB are described. The fluid has minimal effect on the density and Vp. Well logs with cross-dipole acoustics are used together with wide-azimuth seismic data, processed with amplitude control. It is determined that seismic anisotropy increases in carbonate deposits. The result covers a set of lithoclasses and related probabilities: clay minerals, tight sandstones, porous sandstones, and carbonates. We analyzed the influence of maximum angles determination for elastic inversion that varied from 32.5 to 38.5 degrees. The greatest influence of the far angles selection is on the density. AI does not change significantly. Probably the 38,5 degrees provides a superior response above the carbonates. It does not seem to damage the overall AVA behavior, which result in a good density outcome, as higher angles of incidence are included. It gives a better tie to the wells for the high density layers over the interval of interest. Sand probability cube must always considered in the interpretation of the lithological classification that in many cases may be misleading (i.e. when sand and shale probabilities are very close to each other, because of small changes in elastic parameters). The authors provide an integrated holistic approach for quantitative interpretation, subsurface modeling, uncertainty evaluation, and characterization of reservoir distribution using pre-existing well logs and recently acquired seismic data. This paper underpins the previous efforts and encourages the work yet to be fulfilled on this subject. We will describe how quantitative interpretation was used for describing the reservoir, highlight values and uncertainties, and point a way forward for further improvement of the process for effective subsurface modeling.

Recognition and characterization of small-scale sand injectites in seismic data: Implications for reservoir development

2021 ◽  
pp. jgs2021-041
Author(s):  
Alma Dzozlic Bradaric ◽  
Trond Andersen ◽  
Isabelle Lecomte ◽  
Helge Løseth ◽  
Christian Haug Eide
Keyword(s):  
Seismic Data ◽  
Small Scale ◽  
3D Seismic ◽  
Well Placement ◽  
Reflection Seismic ◽  
Seismic Modelling ◽  
Link Type ◽  
Reservoir Development ◽  
Net To Gross ◽  
Seismic Images

Small-scale (< 20 m), non-resolvable sand injectites can constitute a large part of the net-to-gross volume and affect fluid flow in the reservoir. However, they may also cause challenges for well placement and reservoir development because they are too small to be reliably constrained by reflection seismic data. It is therefore important to better understand how small-scale injectites influence seismic images and may be recognized and characterized above reservoirs. The Grane Field (North Sea) hosts numerous small-scale sand injectites above the main reservoir unit, causing challenges for well placement, volume estimates and seismic interpretation. Here, we investigate how such small-scale sand injectites influence seismic images and may be characterized by (1) using well-, 3D seismic- and outcrop data to investigate geometries of small-scale sand injectites (0-15 m) and creating conceptual models of injectite geometries, (2) performing seismic convolution modelling to investigate how these would be imaged in seismic data, and (3) compare these synthetic seismic images to actual 3D seismic from the well-investigate Grane Field.Our results show that despite injectites being below seismic resolution, small-scale sand injectites can be detected in seismic data. They are more likely to be detected with high thickness (> 5 m), steep dip (> 30°), densely spaced sand injectites, and homogeneous background stratigraphy. Furthermore, as fraction of sand injectites increases the top reservoir amplitude will decrease. Moreover, comparison of the synthetic seismic images with real seismic data from the Grane Field indicates that the low-amplitude anomalies and irregularities observed above the reservoir may be a result of the overlying sand injectites. Additionally, the comparison strongly suggests that the Grane Field hosts sand injectites that are thicker and located further away from the top reservoir than what is indicated by well observations. These results may be used to improve well planning and develop reservoirs with overlying sand injectites.Supplementary material: A PDF file containing all the seismic modelling results allowing the reader to flip back and forth between the different models is available at https://www.doi.org/10.6084/m9.figshare.14333102 . Well logs from well 25/11-18 T2 are available at https://factpages.npd.no/pbl/wellbore_documents/2358_25_1_18_COMPLETION_REPORT_AND_LOG.pdf

The domain of applicability of acoustic full-waveform inversion for marine seismic data

Geophysics ◽  
2009 ◽  
Vol 74 (6) ◽  
pp. WCC91-WCC103 ◽  
Author(s):  
Christophe Barnes ◽  
Marwan Charara
Keyword(s):  
Seismic Data ◽  
Seismic Inversion ◽  
Three Dimensions ◽  
Acoustic Medium ◽  
Physical Parameters ◽  
S Wave ◽  
Data Set ◽  
Reflection Seismic ◽  
Wave Inversion ◽  
Full Wave

Marine reflection seismic data inversion is a compute-intensive process, especially in three dimensions. Approximations often are made to limit the number of physical parameters we invert for, or to speed up the forward modeling. Because the data often are dominated by unconverted P-waves, one popular approximation is to consider the earth as purely acoustic, i.e., no shear modulus. The material density sometimes is taken as a constant. Nonlinear waveform seismic inversion consists of iteratively minimizing the misfit between the amplitudes of the measured and the modeled data. Approximations, such as assuming an acoustic medium, lead to incorrect modeling of the amplitudes of the seismic waves, especially with respect to amplitude variation with offset (AVO), and therefore have a direct impact on the inversion results. For evaluation purposes, we have performed a series of inversions with different approximations and different constraints whereby the synthetic data set to recover is computed for a 1D elastic medium. A series of numerical experiments, although simple, help to define the applicability domain of the acoustic assumption. Acoustic full-wave inversion is applicable only when the S-wave velocity and the density fields are smooth enough to reduce the AVO effect, or when the near-offset seismograms are inverted with a good starting model. However, in many realistic cases, acoustic approximation penalizes the full-wave inversion of marine reflection seismic data in retrieving the acoustic parameters.

scholarly journals Transition zones analysis using empirical capillary pressure model from well logs and 3D seismic data on ‘Stephs’ field, onshore, Niger Delta, Nigeria

2019 ◽  
Vol 10 (3) ◽  
pp. 1227-1242
Author(s):  
O. Abiola ◽  
F. O. Obasuyi
Keyword(s):  
Capillary Pressure ◽  
Seismic Data ◽  
Niger Delta ◽  
Time Structure ◽  
Well Logs ◽  
3D Seismic ◽  
Seismic Section ◽  
Transition Zones ◽  
Mobile Water ◽  
3D Seismic Data

AbstractCapillary pressure is an important characteristic that indicates the zones of interaction between two-phase fluids or fluid and rock occurring in the subsurface. The analysis of transition zones (TZs) using Goda (Sam) et al.’s empirical capillary pressure from well logs and 3D seismic data in ‘Stephs’ field, Niger Delta, was carried out to remove the effect of mobile water above the oil–water contact in reservoirs in the absence of core data/information. Two reservoirs (RES B and C) were utilized for this study with net thicknesses (NTG) ranging from 194.14 to 209.08 m. Petrophysical parameters computed from well logs indicate that the reservoirs’ effective porosity ranges from 10 to 30% and the permeability ranges from 100 to > 1000 mD, which are important characteristics of good hydrocarbon bearing zone. Checkshot data were used to tie the well to the seismic section. Faults and horizons were mapped on the seismic section. Time structure maps were generated, and a velocity model was used to convert the time structure maps to its depth equivalent. A total of six faults were mapped, three of which are major growth faults (F1, F4 and F5) and cut across the study area. Reservoir properties were modelled using SIS and SGS. The capillary pressure log, curves and models generated were useful in identifying the impact of mobile water in the reservoir as they show the trend of saturating and interacting fluids. The volume of oil estimated from reservoirs B and C without taking TZ into consideration was 273 × 106 and 406 × 106 mmbbls, respectively, and was found to be higher than the volume of oil estimated from the two reservoirs while taking TZ into consideration which was 242 × 106 and 256 × 106 mmbbls, respectively. The results have indicated the presence of mobile water, which have further established that conventionally recoverable hydrocarbon (RHC) is usually overestimated; hence, TZ analysis has to be performed for enhancing RHC for cost-effective extraction and profit maximization.

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