Sub-basalt Marchenko imaging with offshore Brazil field data

Geophysics ◽  
2021 ◽  
pp. 1-47
Author(s):  
Xueyi Jia ◽  
Anatoly Baumstein ◽  
Charlie Jing ◽  
Erik Neumann ◽  
Roel Snieder
Keyword(s):  
Seismic Waves ◽  
Mode Conversion ◽  
Imaging Techniques ◽  
Hydrocarbon Exploration ◽  
Sampled Data ◽  
Geological Interpretation ◽  
Propagating Waves ◽  
Seismic Acquisition ◽  
Internal Multiples ◽  
Multiple Elimination

Sub-basalt imaging for hydrocarbon exploration faces challenges with the presence of multiple scattering, attenuation and mode-conversion as seismic waves encounter highly heterogeneous and rugose basalt layers. A combination of modern seismic acquisition that can record densely-sampled data, and advanced imaging techniques make imaging through basalt feasible. Yet, the internal multiples, if not properly handled during seismic processing, can be mapped to reservoir layers by conventional imaging methods, misguiding geological interpretation. Traditional internal multiple elimination methods suffer from the requirement of picking horizons of multiple generators and/or a top-down adaptive subtraction process. Marchenko imaging provides an alternative solution to directly remove the artifacts due to internal multiples, without the need of horizon picking or subtraction. In this paper, we present a successful application of direct Marchenko imaging for sub-basalt de-multiple and imaging with an offshore Brazil field dataset. The internal multiples in this example are generated from the seabed and basalt layers, causing severe artifacts in conventional seismic images. We demonstrate that these artifacts are largely suppressed with Marchenko imaging and propose a general work flow for data pre-processing and regularization of marine streamer datasets. We show that horizontally propagating waves can also be reconstructed by the Marchenko method at far offsets.

scholarly journals Data-driven wavefield focusing and imaging with multidimensional deconvolution: Numerical examples for reflection data with internal multiples

Geophysics ◽  
2014 ◽  
Vol 79 (3) ◽  
pp. WA107-WA115 ◽  
Author(s):  
Filippo Broggini ◽  
Roel Snieder ◽  
Kees Wapenaar
Keyword(s):  
Green’S Function ◽  
Green's Function ◽  
Imaging Techniques ◽  
Velocity Model ◽  
Single Scattering ◽  
Data Driven ◽  
Multiple Reflections ◽  
Prestack Migration ◽  
Reflection Data ◽  
Internal Multiples

Standard imaging techniques rely on the single scattering assumption. This requires that the recorded data do not include internal multiples, i.e., waves that have bounced multiple times between reflectors before reaching the receivers at the acquisition surface. When multiple reflections are present in the data, standard imaging algorithms incorrectly image them as ghost reflectors. These artifacts can mislead interpreters in locating potential hydrocarbon reservoirs. Recently, we introduced a new approach for retrieving the Green’s function recorded at the acquisition surface due to a virtual source located at depth. We refer to this approach as data-driven wavefield focusing. Additionally, after applying source-receiver reciprocity, this approach allowed us to decompose the Green’s function at a virtual receiver at depth in its downgoing and upgoing components. These wavefields were then used to create a ghost-free image of the medium with either crosscorrelation or multidimensional deconvolution, presenting an advantage over standard prestack migration. We tested the robustness of our approach when an erroneous background velocity model is used to estimate the first-arriving waves, which are a required input for the data-driven wavefield focusing process. We tested the new method with a numerical example based on a modification of the Amoco model.

Imaging reflection-blind areas using transmitted PS-waves

Geophysics ◽  
2006 ◽  
Vol 71 (6) ◽  
pp. S241-S250 ◽  
Author(s):  
Yi Luo ◽  
Qinglin Liu ◽  
Yuchun E. Wang ◽  
Mohammed N. AlFaraj
Keyword(s):  
Mode Conversion ◽  
Imaging Techniques ◽  
Reverse Time ◽  
Reverse Time Migration ◽  
Reflected Waves ◽  
Prestack Migration ◽  
Reflection Data ◽  
Time Migration ◽  
Transmitted Waves ◽  
Vsp Data

We illustrate the use of mode-converted transmitted (e.g., PS- or SP-) waves in vertical seismic profiling (VSP) data for imaging areas above receivers where reflected waves cannot illuminate. Three depth-domain imaging techniques — move-out correction, common-depth-point (CDP) mapping, and prestack migration — are described and used for imag-ing the transmitted waves. Moveout correction converts an offset VSP trace into a zero-offset trace. CDP mapping maps each sample on an input trace to the location where the mode conversion occurs. For complex media, prestack migration (e.g., reverse-time migration) is used. By using both synthetic and field VSP data, we demonstrate that images derived from transmissions complement those from reflections. As an important application, we show that transmitted waves can illuminate zones above highly de-viated or horizontal wells, a region not imaged by reflection data. Because all of these benefits are obtained without extra data acquisition cost, we believe transmission imag-ing techniques will become widely adopted by the oil in-dustry.

scholarly journals Modeling and Imaging of Multiscale Geological Media: Exploding Reflection Revisited

Geosciences ◽  
2018 ◽  
Vol 8 (12) ◽  
pp. 476
Author(s):  
Evgeny Landa ◽  
Galina Reshetova ◽  
Vladimir Tcheverda
Keyword(s):  
Seismic Waves ◽  
Fractured Reservoirs ◽  
Single Shot ◽  
Middle Point ◽  
Seismic Surveys ◽  
Geological Interpretation ◽  
Time Migration ◽  
Diffraction Imaging ◽  
Heterogeneous Multiscale ◽  
Seismic Sections

Computation of Common Middle Point seismic sections and their subsequent time migration and diffraction imaging provides very important knowledge about the internal structure of 3D heterogeneous geological media and are key elements for successive geological interpretation. Full-scale numerical simulation, that computes all single shot seismograms, provides a full understanding of how the features of the image reflect the properties of the subsurface prototype. Unfortunately, this kind of simulations of 3D seismic surveys for realistic geological media needs huge computer resources, especially for simulation of seismic waves’ propagation through multiscale media like cavernous fractured reservoirs. Really, we need to combine smooth overburden with microstructure of reservoirs, which forces us to use locally refined grids. However, to resolve realistic statements with huge multi-shot/multi-offset acquisitions it is still not enough to provide reasonable needs of computing resources. Therefore, we propose to model 3D Common Middle Point seismic cubes directly, rather than shot-by-shot simulation with subsequent stacking. To do that we modify the well-known "exploding reflectors principle" for 3D heterogeneous multiscale media by use of the finite-difference technique on the base of grids locally refined in time and space. We develop scalable parallel software, which needs reasonable computational costs to simulate realistic models and acquisition. Numerical results for simulation of Common Middle Points sections and their time migration are presented and discussed.

Passive Seismic Marchenko Imaging

2020 ◽  
Author(s):  
Zhongyuan Jin
Keyword(s):  
Free Surface ◽  
Seismic Data ◽  
Low Cost ◽  
Body Waves ◽  
Seismic Survey ◽  
Significant Difference ◽  
Passive Seismic ◽  
Seismic Acquisition ◽  
Imaging Property ◽  
Internal Multiples

<p>In recent years, seismic interferometry (SI) has been widely used in passive seismic data, it allows to retrieve new seismic responses among physical receivers by cross-correlation or multidimensional deconvolution (MDD). Retrieval of reflected body waves from passive seismic data has been proved to be feasible. Marchenko method, as a new technique, retrieves Green’s functions directly inside the medium without any physical receiver there. Marchenko method retrieves precise Green’s functions and the up-going and down-going Green’s functions can be used in target-oriented Marchenko imaging, and internal multiples related artifacts in Marchenko image can be suppressed. </p><p>Conventional Marchenko imaging uses active seismic data, in this abstract, we propose the method of passive seismic Marchenko imaging (PSMI) which retrieves Green’s functions from ambient noise signal. PSMI employs MDD method to obtain the reflection response without free-surface interaction as an input for Marchenko algorithm, such that free-surface multiples in the retrieved shot gathers can be eliminated, besides, internal multiples don’t contribute to final Marchenko image, which means both free-surface multiples and internal multiples have been taken into account. Although the retrieved shot gathers are contaminated by noises, the up-going and down-going Green’s functions can be still retrieved. Results of numerical tests validate PSMI’s feasibility and robustness. PSMI provides a new way to image the subsurface structure, it combines the low-cost property of passive seismic acquisition and target-oriented imaging property of Marchenko imaging, as well as the advantage that there are no artifacts caused by internal multiples and free-surface multiples.</p><p>Overall, the significant difference between PSMI and conventional Marchenko imaging is that passive seismic data is used into Marchenko scheme, which extends the Marchenko imaging to passive seismic field. Passive seismic Marchenko imaging avoids the effects of free-surface multiples and internal multiples in the retrieved shot gathers. PSMI combines the low-cost property of passive seismic acquisition and target-oriented imaging property of Marchenko imaging which is promising in future field seismic survey.</p><p>This work is supported by the Fundamental Research Funds for the Central Universities (JKY201901-03). </p>

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.

Randomized sampling and sparsity: Getting more information from fewer samples

Geophysics ◽  
2010 ◽  
Vol 75 (6) ◽  
pp. WB173-WB187 ◽  
Author(s):  
Felix J. Herrmann
Keyword(s):  
Compressive Sensing ◽  
Sampling Method ◽  
New Technology ◽  
Seismic Exploration ◽  
Transform Domain ◽  
Sampled Data ◽  
Randomized Sampling ◽  
Seismic Acquisition ◽  
Small Factor ◽  
Incoherent Sampling

Many seismic exploration techniques rely on the collection of massive data volumes that are subsequently mined for information during processing. Although this approach has been extremely successful in the past, current efforts toward higher-resolution images in increasingly complicated regions of the earth continue to reveal fundamental shortcomings in our workflows. Chiefly among these is the so-called “curse of dimensionality” exemplified by Nyquist’s sampling criterion, which disproportionately strains current acquisition and processing systems as the size and desired resolution of our survey areas continue to increase. We offer an alternative sampling method leveraging recent insights from compressive sensing toward seismic acquisition and processing for data that are traditionally considered to be undersampled. The main outcome of this approach is a new technology where acquisition and processing related costs are no longer determined by overly stringent sampling criteria, such asNyquist. At the heart of our approach lies randomized incoherent sampling that breaks subsampling related interferences by turning them into harmless noise, which we subsequently remove by promoting transform-domain sparsity. Now, costs no longer grow significantly with resolution and dimensionality of the survey area, but instead depend only on transform-domain sparsity. Our contribution is twofold. First, we demonstrate by means of carefully designed numerical experiments that compressive sensing can successfully be adapted to seismic exploration. Second, we show that accurate recovery can be accomplished for compressively sampled data volumes sizes that exceed the size of conventional transform-domain data volumes by only a small factor. Because compressive sensing combines transformation and encoding by a single linear encoding step, this technology is directly applicable to acquisition and to dimensionality reduction during processing. In either case, sampling, storage, and processing costs scale with transform-domain sparsity. We illustrate this principle by means of number of case studies.

Efficient wave-equation-based diffraction imaging

Geophysics ◽  
2019 ◽  
Vol 84 (5) ◽  
pp. S389-S399 ◽  
Author(s):  
Dongliang Zhang ◽  
Tong W. Fei ◽  
Constantine Tsingas ◽  
Yi Luo
Keyword(s):  
Wave Equation ◽  
Seismic Waves ◽  
Secondary Sources ◽  
Propagating Waves ◽  
Diffracted Waves ◽  
Diffraction Imaging ◽  
Left And Right ◽  
Zero Offset ◽  
Left Image ◽  
The Right

We have developed an efficient and practical wave-equation-based technique to image subsurface geologic features such as isolated scatterers, reflector edges, fault, fracture zones, and erosion whose information is mainly contained in diffracted waves. This technique has the ability to directly reveal and differentiate important geologic features compared with results obtained using reflected seismic waves. This new technique comprises three steps. First, the source and receiver wavefields are decomposed into left- and right-downgoing propagating waves, respectively. Second, applying the imaging condition to the right-downgoing source and receiver wavefields to generate the so-called right-right image. Similarly, a left-left image is generated. Third, the left-left and right-right images are multiplied sample-by-sample to form the final diffraction-based image. The key idea of this method is based on the fact that any dipping reflector exhibits a particular dip direction, so its subsurface image can exist either in the left-left or the right-right image, but not in both. As a result, the sample-by-sample multiplication of the two images eliminates the reflector images. Alternatively, because diffractions are generated by subsurface geologic features, which act as secondary sources and radiate in all directions, ranging from [Formula: see text] to 90°, their energy can exist in both images. After multiplication of both images, only the diffractors remain, whereas the reflectors are suppressed. Our method is applicable only for diffracting objects that radiate in all directions. An exception occurs when reflectors exhibit zero dip. In such a case, zero-dip reflectors could be present in both images and leak into the final diffractor image. We mitigate this problem in several ways, such as omitting near zero-offset input data, muting vertical-propagation components, or applying an [Formula: see text]-[Formula: see text] filter on the final diffraction image.

Inversion versus migration: A new perspective to an old discussion

Geophysics ◽  
1996 ◽  
Vol 61 (3) ◽  
pp. 804-814 ◽  
Author(s):  
C. P. A. Wapenaar
Keyword(s):  
Explicit Form ◽  
Imaging Techniques ◽  
Nonlinear Effects ◽  
Volume Integral ◽  
Primary Representation ◽  
New Perspective ◽  
Internal Multiples ◽  
And Migration ◽  
The One ◽  
The Relationship

Seismic imaging techniques can be subdivided into inversion and migration. The object functions for inversion and migration are, respectively, the medium contrast parameters and reflectivity. In this paper, the relationship between inversion and migration is approached by analyzing the underlying representations (the forward models). It appears that the “two‐way representation” (which underlies inversion) as well as the “one‐way representation” (which underlies migration) can both be expressed in terms of a volume integral over the appropriate object function. In their linearized form, these representations account for primaries only. In this case, the one‐way representation in terms of reflectivity is the most accurate of the two, which implies that proper migration is more accurate than linearized inversion. Internal multiples can be taken into account by the nonlinear representations. As an alternative, however, the “generalized primary representation” is introduced. In its explicit form, this one‐way representation is linear in the reflectivity (opposed to linearized). Nonlinear effects are implicitly accounted for by the generalized primary propagators. The generalized primary representation is a suitable basis for true amplitude migration, taking the angle‐dependent dispersive effects of fine layering into account.

Local primary-and-multiple orthogonalization for leaked internal multiple crosstalk estimation and attenuation on full-wavefield migrated images

Geophysics ◽  
2020 ◽  
Vol 86 (1) ◽  
pp. A7-A13
Author(s):  
Dong Zhang ◽  
D. J. (Eric) Verschuur ◽  
Mikhail Davydenko ◽  
Yangkang Chen ◽  
Ali M. Alfaraj ◽  
...  
Keyword(s):  
Data Driven ◽  
Sampled Data ◽  
Receiver Side ◽  
Model Driven ◽  
Internal Multiples ◽  
Reliable Solution ◽  
Constraint Model ◽  
Seismic Images ◽  
Dense Sampling ◽  
New Framework

An important imaging challenge is creating reliable seismic images without internal multiple crosstalk, especially in cases with strong overburden reflectivity. Several data-driven methods have been proposed to attenuate the internal multiple crosstalk, for which fully sampled data in the source and receiver side are usually required. To overcome this acquisition constraint, model-driven full-wavefield migration (FWM) can automatically include internal multiples and only needs dense sampling in either the source or receiver side. In addition, FWM can correct for transmission effects at the reflecting interfaces. Although FWM has been shown to work effectively in compensating for transmission effects and suppressing internal multiple crosstalk compared to conventional least-squares primary wavefield migration (PWM), it tends to generate relatively weaker internal multiples during modeling. Therefore, some leaked internal multiple crosstalk can still be observed in the FWM image, which tends to blend in the background and can be misinterpreted as real geology. Thus, we adopted a novel framework using local primary-and-multiple orthogonalization (LPMO) on the FWM image as a postprocessing step for leaked internal multiple crosstalk estimation and attenuation. Due to their opposite correlation with the FWM image, a positive-only LPMO weight can be used to estimate the leaked internal multiple crosstalk, whereas a negative-only LPMO weight indicates the transmission effects that need to be retained. Application to North Sea field data validates the performance of the proposed framework for removing the weak but misleading leaked internal multiple crosstalk in the FWM image. Therefore, with this new framework, FWM can provide a reliable solution to the long-standing issue of imaging primaries and internal multiples automatically, with proper primary restoration.

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