Simultaneous vibroseis data separation through sparse inversion

2019 ◽  
Vol 38 (8) ◽  
pp. 625-629 ◽  
Author(s):  
Jiawen Song ◽  
Peiming Li ◽  
Zhongping Qian ◽  
Mugang Zhang ◽  
Pengyuan Sun ◽  
...  
Keyword(s):  
Seismic Data ◽  
High Fidelity ◽  
Data Sets ◽  
Sparse Constraint ◽  
Coherent Signal ◽  
Additional Processing ◽  
Seismic Acquisition ◽  
Sparse Inversion ◽  
Data Separation ◽  
Simultaneous Source

Compared with conventional seismic acquisition methods, simultaneous-source acquisition utilizes independent shooting that allows for source interference, which reduces the time and cost of acquisition. However, additional processing is required to separate the interfering sources. Here, we present an inversion-based deblending method, which distinguishes signal from blending noise based on coherency differences in 3D receiver gathers. We first transform the seismic data into the frequency-wavenumber-wavenumber domain and impose a sparse constraint to estimate the coherent signal. We then subtract the estimated signal from the original input to predict the interference noise. Driven by data residuals, the signal is updated iteratively with shrinking thresholds until the signal and noise fully separate. We test our presented method on two 3D field data sets to demonstrate how the method proficiently separates interfering vibroseis sources with high fidelity.

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.

Fully automated near-surface analysis by surface-consistent refraction method

Geophysics ◽  
2016 ◽  
Vol 81 (4) ◽  
pp. U39-U49 ◽  
Author(s):  
Daniele Colombo ◽  
Federico Miorelli ◽  
Ernesto Sandoval ◽  
Kevin Erickson
Keyword(s):  
Surface Analysis ◽  
Seismic Data ◽  
Linear Equations ◽  
Time Shift ◽  
Data Sets ◽  
Time Lags ◽  
Data Set ◽  
Near Surface ◽  
Seismic Acquisition ◽  
Key Aspects

Industry practices for near-surface analysis indicate difficulties in coping with the increased number of channels in seismic acquisition systems, and new approaches are needed to fully exploit the resolution embedded in modern seismic data sets. To achieve this goal, we have developed a novel surface-consistent refraction analysis method for low-relief geology to automatically derive near-surface corrections for seismic data processing. The method uses concepts from surface-consistent analysis applied to refracted arrivals. The key aspects of the method consist of the use of common midpoint (CMP)-offset-azimuth binning, evaluation of mean traveltime and standard deviation for each bin, rejection of anomalous first-break (FB) picks, derivation of CMP-based traveltime-offset functions, conversion to velocity-depth functions, evaluation of long-wavelength statics, and calculation of surface-consistent residual statics through waveform crosscorrelation. Residual time lags are evaluated in multiple CMP-offset-azimuth bins by crosscorrelating a pilot trace with all the other traces in the gather in which the correlation window is centered at the refracted arrival. The residuals are then used to build a system of linear equations that is simultaneously inverted for surface-consistent shot and receiver time shift corrections plus a possible subsurface residual term. All the steps are completely automated and require a fraction of the time needed for conventional near-surface analysis. The developed methodology was successfully performed on a complex 3D land data set from Central Saudi Arabia where it was benchmarked against a conventional tomographic work flow. The results indicate that the new surface-consistent refraction statics method enhances seismic imaging especially in portions of the survey dominated by noise.

Learning the blending spikes using sparse dictionaries

2020 ◽  
Vol 222 (3) ◽  
pp. 1846-1863
Author(s):  
Yangkang Chen ◽  
Shaohuan Zu ◽  
Wei Chen ◽  
Mi Zhang ◽  
Zhe Guan
Keyword(s):  
Seismic Data ◽  
Traditional Method ◽  
Ambient Noise ◽  
State Of The Art ◽  
Random Noise ◽  
New Approach ◽  
Learned Dictionary ◽  
Seismic Acquisition ◽  
Iterative Inversion ◽  
Simultaneous Source

SUMMARY Deblending plays an important role in preparing high-quality seismic data from modern blended simultaneous-source seismic acquisition. State-of-the-art deblending is based on the sparsity-constrained iterative inversion. Inversion-based deblending assumes that the ambient noise level is low and the data misfit during iterative inversion accounts for the random ambient noise. The traditional method becomes problematic when the random ambient noise becomes extremely strong and the inversion iteratively fits the random noise instead of the signal and blending interference. We propose a constrained inversion model that takes the strong random noise into consideration and can achieve satisfactory result even when strong random noise exists. The principle of this new method is that we use sparse dictionaries to learn the blending spikes and thus the learned dictionary atoms are able to distinguish between blending spikes and random noise. The separated signal and blending spikes can then be better fitted by the iterative inversion framework. Synthetic and field data examples are used to demonstrate the performance of the new approach.

Full-azimuth, full-offset, high-fidelity vector marine seismic acquisition

2020 ◽  
Vol 39 (4) ◽  
pp. 238-247
Author(s):  
Michel Manin ◽  
Luc Haumonté ◽  
Eric Bathellier
Keyword(s):  
Data Analysis ◽  
Seismic Data ◽  
Technology Development ◽  
High Fidelity ◽  
Successful Performance ◽  
High Quality ◽  
Pilot Survey ◽  
Autonomous Surface Vehicles ◽  
Seismic Acquisition ◽  
Marine Seismic

Ten years ago, Kietta launched a project to develop a new method of marine seismic acquisition using midwater stationary cables and autonomous surface vehicles. We present the concept and the technology bricks and recount the successful performance of a commercial pilot survey. The objective of the technology is to enable flexible acquisitions and deliver high-quality, high-fidelity seismic data without sacrificing productivity. After reviewing existing marine seismic acquisition methods, we describe the technology development, including sea trials. The geophysical advantages of acquiring true 3D/four-component data are demonstrated by seismic data analysis, including simultaneous sources and associated productivity calculation.

Unravelling an abandoned giant in Central Luconia Province, offshore Sarawak, Malaysia — Success story of Lang Lebah

2020 ◽  
Vol 39 (8) ◽  
pp. 566-573
Author(s):  
Aqilah Amir Jamalullail ◽  
Ong Swee Keong ◽  
Nik Ruzaimi Akmal Nik Ruhadi ◽  
Tengku Mohd Syazwan Tengku Hassan ◽  
Detchai Ittharat ◽  
...  
Keyword(s):  
Seismic Data ◽  
Reservoir Quality ◽  
Data Sets ◽  
3D Seismic ◽  
Success Story ◽  
Seismic Acquisition ◽  
Central Luconia ◽  
Drilling Conditions ◽  
3D Seismic Data ◽  
Carbonate Buildup

In 1994, two exploration wells were drilled consecutively to explore for gas prospectivity in Lang Lebah, a Miocene carbonate buildup in the geologic province of Central Luconia located in the Sarawak Basin in Malaysia. High overpressure and operational problems prevented both wells from fully evaluating the target. Postdrill analysis concluded that Lang Lebah has limited potential due to poor reservoir quality, small gas column, and challenging drilling conditions. For these reasons, it was left dormant for 25 years. In 2016, new 3D broadband seismic acquisition and megamerge reprocessing of 3D seismic data sets followed by an integrated application of multidisciplinary workflows successfully derisked key petroleum system elements of the Lang Lebah structure, yielding a more optimistic view of its potential. A new well was justified at Lang Lebah and resulted in one of the major gas discoveries of 2019.

Adaptive iterative deblending of simultaneous-source seismic data based on sparse inversion

2021 ◽  
Vol 69 (2) ◽  
pp. 497-507
Author(s):  
Yajie Wei ◽  
Jingjie Cao ◽  
Xiaogang Huang ◽  
Xue Chen ◽  
Zhicheng Cai
Keyword(s):  
Seismic Data ◽  
Sparse Inversion ◽  
Simultaneous Source

scholarly journals Integrated magnetotelluric and seismic investigation of Cenozoic graben structure near Obrzycko, Poland

2021 ◽  
Author(s):  
Adam Cygal ◽  
Michał Stefaniuk ◽  
Anna Kret
Keyword(s):  
Seismic Data ◽  
Geophysical Methods ◽  
Geological Structure ◽  
Data Sets ◽  
Low Velocity ◽  
Shallow Subsurface ◽  
Geophysical Model ◽  
Novel Approach ◽  
Loose Deposits ◽  
Static Corrections

AbstractThis article presents the results of an integrated interpretation of measurements made using Audio-Magnetotellurics and Seismic Reflection geophysical methods. The obtained results were used to build an integrated geophysical model of shallow subsurface cover consisting of Cenozoic deposits, which then formed the basis for a detailed lithological and tectonic interpretation of deeper Mesozoic sediments. Such shallow covers, consisting mainly of glacial Pleistocene deposits, are typical for central and northern Poland. This investigation concentrated on delineating the accurate geometry of Obrzycko Cenozoic graben structure filled with loose deposits, as it was of great importance to the acquisition, processing and interpretation of seismic data that was to reveal the tectonic structure of the Cretaceous and Jurassic sediments which underly the study area. Previously, some problems with estimation of seismic static corrections over similar grabens filled with more recent, low-velocity deposits were encountered. Therefore, a novel approach to estimating the exact thickness of such shallow cover consisting of low-velocity deposits was applied in the presented investigation. The study shows that some alternative geophysical data sets (such as magnetotellurics) can be used to significantly improve the imaging of geological structure in areas where seismic data are very distorted or too noisy to be used alone

scholarly journals Comparing global tomography-derived and gravity-based upper mantle density models

2020 ◽  
Vol 221 (3) ◽  
pp. 1542-1554 ◽  
Author(s):  
B C Root
Keyword(s):  
Seismic Tomography ◽  
Upper Mantle ◽  
Seismic Data ◽  
Gravity Data ◽  
Heterogeneous Data ◽  
Clear Correlation ◽  
Data Sets ◽  
Satellite Gravity ◽  
Similar Density ◽  
Similar Peak

SUMMARY Current seismic tomography models show a complex environment underneath the crust, corroborated by high-precision satellite gravity observations. Both data sets are used to independently explore the density structure of the upper mantle. However, combining these two data sets proves to be challenging. The gravity-data has an inherent insensitivity in the radial direction and seismic tomography has a heterogeneous data acquisition, resulting in smoothed tomography models with de-correlation between different models for the mid-to-small wavelength features. Therefore, this study aims to assess and quantify the effect of regularization on a seismic tomography model by exploiting the high lateral sensitivity of gravity data. Seismic tomography models, SL2013sv, SAVANI, SMEAN2 and S40RTS are compared to a gravity-based density model of the upper mantle. In order to obtain similar density solutions compared to the seismic-derived models, the gravity-based model needs to be smoothed with a Gaussian filter. Different smoothening characteristics are observed for the variety of seismic tomography models, relating to the regularization approach in the inversions. Various S40RTS models with similar seismic data but different regularization settings show that the smoothening effect is stronger with increasing regularization. The type of regularization has a dominant effect on the final tomography solution. To reduce the effect of regularization on the tomography models, an enhancement procedure is proposed. This enhancement should be performed within the spectral domain of the actual resolution of the seismic tomography model. The enhanced seismic tomography models show improved spatial correlation with each other and with the gravity-based model. The variation of the density anomalies have similar peak-to-peak magnitudes and clear correlation to geological structures. The resolvement of the spectral misalignment between tomographic models and gravity-based solutions is the first step in the improvement of multidata inversion studies of the upper mantle and benefit from the advantages in both data sets.

Iterative Deblending of Simultaneous-Source Seismic Data With Structuring Median Constraint

2018 ◽  
Vol 15 (1) ◽  
pp. 58-62 ◽  
Author(s):  
Weilin Huang ◽  
Runqiu Wang ◽  
Xiangbo Gong ◽  
Yangkang Chen
Keyword(s):  
Seismic Data ◽  
Simultaneous Source
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