TGS NOPEC Geophysical Company

Norway

TGS NOPEC Geophysical Company

Norway
SEARCH FILTERS
Time filter
Source Type

Zeng C.,TGS NOPEC Geophysical Company | Dong S.,TGS NOPEC Geophysical Company | Wang B.,TGS NOPEC Geophysical Company
Interpretation | Year: 2017

Least-squares reverse time migration (LSRTM) overcomes the shortcomings of conventional migration algorithms by iteratively fitting the demigrated synthetic data and the input data to refine the initial depth image toward true reflectivity. It gradually enhances the effective signals and removes the migration artifacts such as swing noise during conventional migration. When imaging the subsalt area with complex structures, many practical issues have to be considered to ensure the convergence of the inversion. We tackle those practical issues such as an unknown source wavelet, inaccurate migration velocity, and slow convergence to make LSRTM applicable to subsalt imaging in geologic complex areas such as the Gulf of Mexico. Dynamic warping is used to realign the modeled and input data to compensate for minor velocity errors in the subsalt sediments. A windowed crosscorrelation based confidence level is used to control the quality of the residual computation. The confidence level is further used as an inverse weighting to precondition the data residual so that the convergence rates in shallow and deep images are automatically balanced. It also helps suppress the strong artifacts related to the salt boundary. The efficiency of the LSRTM is improved so that interpretable images in the area of interest can be obtained in only a few iterations. After removing the artifacts near the salt body using LSRTM, the image better represents the true geology than the outcome of conventional RTM, thus it facilitates the interpretation. Synthetic and field data examples are given to examine and demonstrate the effectiveness of the adaptive strategies. © 2017 Society of Exploration Geophysicists and American Association of Petroleum Geologists.


Liu D.,TGS NOPEC Geophysical Company
SEG Technical Program Expanded Abstracts | Year: 2013

AVO analysis contributes significantly to reservoir characterization. Because AVO analysis places high demands on seismic data as do many other techniques in reservoir characterization, the needs for specially dedicated data conditioning processes are becoming more essential for the success of this task. This paper discusses two pre-stack data conditioning techniques: Structural Filter (SF) and Trim Statics. We found that these two techniques are complementary, and they can improve AVO analysis in CMP and CRP gathers. Synthetic and real data examples demonstrated that SF greatly enhances the Signal-to-Noise Ratio (SNR) of gathers by removing abnormal single high amplitude events, and strong random noise, whereas, the relative amplitude is well preserved. The application of trim statics followed by SF helped to flatten seismic reflectors, and the resulting gathers fulfill the basic assumptions of AVO theory. Using the conditioned CRP gathers in AVO analysis, the improved intercept and gradient section and clustered AVO cross-plots allowed better identification of the reservoir and AVO anomaly classification. Conversely, both the intercept and gradient section and cross-plot produced from the raw data contained noisy data that obscured the pay zone delineation, and misled to inaccurate categorization of the AVO anomaly. © 2013 SEG.


Zeng C.,TGS NOPEC Geophysical Company | Dong S.,TGS NOPEC Geophysical Company | Wang B.,TGS NOPEC Geophysical Company
Interpretation | Year: 2017

Least-squares reverse time migration (LSRTM) overcomes the shortcomings of conventional migration algorithms by iteratively fitting the demigrated synthetic data and the input data to refine the initial depth image toward true reflectivity. It gradually enhances the effective signals and removes the migration artifacts such as swing noise during conventional migration. When imaging the subsalt area with complex structures, many practical issues have to be considered to ensure the convergence of the inversion. We tackle those practical issues such as an unknown source wavelet, inaccurate migration velocity, and slow convergence to make LSRTM applicable to subsalt imaging in geologic complex areas such as the Gulf of Mexico. Dynamic warping is used to realign the modeled and input data to compensate for minor velocity errors in the subsalt sediments. A windowed crosscorrelation-based confidence level is used to control the quality of the residual computation. The confidence level is further used as an inverse weighting to precondition the data residual so that the convergence rates in shallow and deep images are automatically balanced. It also helps suppress the strong artifacts related to the salt boundary. The efficiency of the LSRTM is improved so that interpretable images in the area of interest can be obtained in only a few iterations. After removing the artifacts near the salt body using LSRTM, the image better represents the true geology than the outcome of conventional RTM; thus, it facilitates the interpretation. Synthetic and field data examples examine and demonstrate the effectiveness of the adaptive strategies. © 2017 Society of Exploration Geophysicists and American Association of Petroleum Geologists.


Goloshubin G.M.,University of Houston | Chabyshova E.,TGSNopec Geophysical Company
6th Saint Petersburg International Conference and Exhibition on Geosciences 2014: Investing in the Future | Year: 2014

We consider a possible explanation of the seismic low frequency anomalies using converted Fast-Slow-Fast P-waves in a thinly layered porous permeable fluid-saturated medium. Wave propagation in highly interbedded permeable gas reservoirs suggests significant and anomalous amount of mode conversions between Fast and Slow P-waves, which may be observed from surface seismic reflection data. Those converted P-waves experience high frequency dependent attenuation. In case if some converted waves propagated only a short fraction of their travel paths as Slow P-waves they will be notably delayed and attenuated relative to Fast P-wave reflections. A model of sandstone reservoir with typical parameters is used to estimate time delays of the converted Fast-Slow-Fast P-waves and their influence into total reflected P-waves energy at seismic frequencies. Copyright © 2014 by the European Association of Geoscientists & Engineers. All rights reserved.


Chabyshova E.,University of Houston | Chabyshova E.,TGSNopec Geophysical Company | Goloshubin G.,University of Houston
Geophysics | Year: 2014

P-wave amplitude anomalies below reservoir zones can be used as hydrocarbon markers. Some of those anomalies are considerably delayed relatively to the reflections from the reservoir zone. High P-wave attenuation and velocity dispersion of the observed P-waves cannot justify such delays. The hypothesis that these amplitude anomalies are caused by wave propagation through a layered permeable gaseous reservoir is evaluated. The wave propagation through highly interbedded reservoirs suggest an anomalous amount of mode conversions between fast and slow P-waves. The converted P-waves, which propagated even a short distance as slow P-waves, should be significantly delayed and attenuated comparatively, with the fast P-wave reflections. The amplitudes and arrival time variations of conventional and converted P-wave reflections at low seismic frequencies were evaluated by means of an asymptotic analysis. The calculations confirmed that the amplitude anomalies due to converted P-waves are noticeably delayed in time relatively to fast P-wave reflections. However, the amplitudes of the modeled converted P-waves were much lower than the amplitude anomalies observed from exploration cases. © 2014 Society of Exploration Geophysicists.


Masoomzadeh H.,TGS NOPEC Geophysical Co. | Hardwick A.,TGS NOPEC Geophysical Co.
74th European Association of Geoscientists and Engineers Conference and Exhibition 2012 Incorporating SPE EUROPEC 2012: Responsibly Securing Natural Resources | Year: 2012

As an alternative to the conventional high-resolution Radon transform, we propose a time-domain approach to transform a gather of pre-stack seismic data into a gather of highly-resolved traces in the transformed domain. Using a range of various velocity functions in a standard NMO correction routine we iteratively identify the most energy-bearing functions and transfer the corresponding stackable energy consecutively. Iso-moveout functions can be used to avoid the distortions related to the NMO stretching. Application to synthetic and real data has shown improvements in resolution and performance. Higher resolution results in less ambiguous aperture compensation and therefore more successful reconstruction of stackable seismic events in the large gaps of missing data. This feature helps to improve the accuracy of modeling multiple events particularly in the near offset zone.


Krasnov A.A.,Concern CSRI Elektropribor | Sokolov A.V.,Concern CSRI Elektropribor | Usov S.V.,TGS NOPEC Geophysical Company
Gyroscopy and Navigation | Year: 2011

Special features of using a Chekan-AM gravimeter in airborne gravimetric surveys are discussed. Software and procedures for gravimetric data processing are described. The results of airborne gravimetric surveys conducted in 2007-2009 on the shelf of Greenland are given. © 2011 Pleiades Publishing, Ltd.,.


Zeng C.,TGS NOPEC Geophysical Company | Dong S.,TGS NOPEC Geophysical Company | Wang B.,TGS NOPEC Geophysical Company
Leading Edge | Year: 2016

Least-squares reverse time migration (LSRTM) refines the seismic image toward true reflectivity by inversion. Its iterative nature and modeling capability enable the use of synthetic data to guide the preconditioning of input data. When the velocity contains errors, dynamic warping can be used to shift the input data and force the traveltime to be consistent with the imperfect migration velocity. A crosscorrelation-based confidence level is introduced to control the quality of dynamic warping for field data. The confidence level also is used as an inverse weighting to adaptively precondition the data residual. The adaptive preconditioning automatically balances data fitting in the shallow and deep and speeds up convergence in subsalt. Both synthetic and field data experiments based in the Gulf of Mexico show that the adaptive LSRTM can improve the image quality in subsalt effectively and efficiently. Within only a few iterations, the adaptive LSRTM suppresses the salt halo artifacts and increases the signal-to-noise ratio in poorly illuminated areas. It also improves the termination of sediments against salt boundaries and enhances subsalt image coherency. Compared with conventional RTM, the adaptive LSRTM image is more favorable to geologic interpretation. © 2016 by The Society of Exploration Geophysicists.


Trademark
TGS NOPEC Geophysical Company | Date: 2013-06-19

Computer software for use on the oil and gas industry, namely computer software for seismic data processing, geophysical investigation of seismic data, and related seismic attribute and interpretation of seismic and related seismic attribute data, seismic prestack interpretation and analysis.


Trademark
TGS NOPEC Geophysical Company | Date: 2010-03-22

Prerecorded electronic media featuring geophysical data, namely seismic-data images; computer program for use in producing depth processed images from geophysical data. Computer services, namely, producing depth processed images from geophysical data; data conversion and digitization services, namely creating depth processed images from geophysical data for the oil and gas industry.

Loading TGS NOPEC Geophysical Company collaborators
Loading TGS NOPEC Geophysical Company collaborators