Full-waveform static corrections using blind channel identification

Geophysics ◽  
2007 ◽  
Vol 72 (4) ◽  
pp. U55-U66 ◽  
Author(s):  
Robbert van Vossen ◽  
Jeannot Trampert
Keyword(s):  
Synthetic Data ◽  
Depth Resolution ◽  
Surface Heterogeneity ◽  
Surface Velocity ◽  
Coherent Noise ◽  
Data Set ◽  
Channel Identification ◽  
Near Surface ◽  
Full Waveform ◽  
Static Corrections

Near-surface wavefield perturbations can be very complex and completely mask the target reflections. Despite this complexity, conventional methods rely on parameterizations characterized by simple time and amplitude anomalies to compensate for these perturbations. Determining and compensating for time shifts is generally referred to as (residual) static corrections, whereas surface-consistent deconvolution techniques deal with amplitude anomalies. We present an approach that uses the full waveform to parameterize near-surface perturbations. Therefore, we refer to this method as waveform statics. Important differences from conventional static corrections are that this approach allows time shifts to vary with frequency and takes amplitude variations directly into account. Furthermore, the procedure is fully automated and does not rely on near-surface velocity information. The waveform static corrections are obtained usingblind channel identification and applied to the recordings using multichannel deconvolution. As a result, the method implicitly incorporates array forming. The developed method is validated on synthetic data and applied to part of a field data set acquired in an area with significant near-surface heterogeneity. The source and receiver responses obtained are strongly correlated to the near-surface conditions and show changes, both in phase and frequency content, along the spread. The application of the waveform statics demonstrates that they not only correct for near-surface wavefield perturbations, but also strongly reduce coherent noise. This results in substantial improvements, both in trace-to-trace coherency and in depth resolution. In addition, the procedure delineates reflection events that are difficult to detect prior to our proposed correction. Based on these results, we conclude that complex near-surface perturbations can be successfully dealt with using the multichannel, full-waveform, static-correction procedure.

High‐resolution seismic traveltime tomography incorporating static corrections applied to a till‐covered bedrock environment

Geophysics ◽  
2004 ◽  
Vol 69 (4) ◽  
pp. 1082-1090 ◽  
Author(s):  
Björn Bergman ◽  
Ari Tryggvason ◽  
Christopher Juhlin
Keyword(s):  
High Resolution ◽  
Velocity Model ◽  
Surface Velocity ◽  
Data Set ◽  
Near Surface ◽  
Seismic Processing ◽  
Simultaneous Inversion ◽  
Reflection Seismic ◽  
Static Corrections ◽  
Velocity Variations

A major obstacle in tomographic inversion is near‐surface velocity variations. Such shallow velocity variations need to be known and correctly accounted for to obtain images of deeper structures with high resolution and quality. Bedrock cover in many areas consists of unconsolidated sediments and glacial till. To handle the problems associated with this cover, we present a tomographic method that solves for the 3D velocity structure and receiver static corrections simultaneously. We test the method on first‐arrival picks from deep seismic reflection data acquired in the mid‐ late to 1980s in the Siljan Ring area, central Sweden. To use this data set successfully, one needs to handle a number of problems, including time‐varying, near‐surface velocities from data recorded in winter and summer, several sources and receivers within each inversion cell, varying thickness of the cover layer in each inversion cell, and complex 3D geology. Simultaneous inversion for static corrections and velocity produces a much better image than standard tomography without statics. The velocity model from the simultaneous inversion is superior to the velocity model produced using refraction statics obtained from standard reflection seismic processing prior to inversion. Best results using the simultaneous inversion are obtained when the initial top velocity layer is set to the near‐surface bedrock velocity rather than the velocity of the cover. The resulting static calculations may, in the future, be compared to refraction static corrections in standard reflection seismic processing. The preferred final model shows a good correlation with the mapped geology and the airborne magneticmap.

An application of full-waveform inversion to land data using the pseudo-Hessian matrix

2016 ◽  
Vol 4 (4) ◽  
pp. T627-T635
Author(s):  
Yikang Zheng ◽  
Wei Zhang ◽  
Yibo Wang ◽  
Qingfeng Xue ◽  
Xu Chang
Keyword(s):  
Hessian Matrix ◽  
Waveform Inversion ◽  
Computational Cost ◽  
Velocity Model ◽  
Surface Velocity ◽  
Full Waveform Inversion ◽  
Data Set ◽  
Near Surface ◽  
Full Waveform ◽  
The Time Domain

Full-waveform inversion (FWI) is used to estimate the near-surface velocity field by minimizing the difference between synthetic and observed data iteratively. We apply this method to a data set collected on land. A multiscale strategy is used to overcome the local minima problem and the cycle-skipping phenomenon. Another obstacle in this application is the slow convergence rate. The inverse Hessian can enhance the poorly blurred gradient in FWI, but obtaining the full Hessian matrix needs intensive computation cost; thus, we have developed an efficient method aimed at the pseudo-Hessian in the time domain. The gradient in our FWI workflow is preconditioned with the obtained pseudo-Hessian and a synthetic example verifies its effectiveness in reducing computational cost. We then apply the workflow on the land data set, and the inverted velocity model is better resolved compared with traveltime tomography. The image and angle gathers we get from the inversion result indicate more detailed information of subsurface structures, which will contribute to the subsequent seismic interpretation.

Regularization and datuming of seismic data by weighted, damped least squares

Geophysics ◽  
2006 ◽  
Vol 71 (5) ◽  
pp. U67-U76 ◽  
Author(s):  
Robert J. Ferguson
Keyword(s):  
Least Squares ◽  
Seismic Data ◽  
Synthetic Data ◽  
Real Data ◽  
Structural Data ◽  
Irregular Sampling ◽  
Data Set ◽  
Near Surface ◽  
Damped Least Squares ◽  
Wavefield Extrapolation

The possibility of improving regularization/datuming of seismic data is investigated by treating wavefield extrapolation as an inversion problem. Weighted, damped least squares is then used to produce the regularized/datumed wavefield. Regularization/datuming is extremely costly because of computing the Hessian, so an efficient approximation is introduced. Approximation is achieved by computing a limited number of diagonals in the operators involved. Real and synthetic data examples demonstrate the utility of this approach. For synthetic data, regularization/datuming is demonstrated for large extrapolation distances using a highly irregular recording array. Without approximation, regularization/datuming returns a regularized wavefield with reduced operator artifacts when compared to a nonregularizing method such as generalized phase shift plus interpolation (PSPI). Approximate regularization/datuming returns a regularized wavefield for approximately two orders of magnitude less in cost; but it is dip limited, though in a controllable way, compared to the full method. The Foothills structural data set, a freely available data set from the Rocky Mountains of Canada, demonstrates application to real data. The data have highly irregular sampling along the shot coordinate, and they suffer from significant near-surface effects. Approximate regularization/datuming returns common receiver data that are superior in appearance compared to conventional datuming.

Refraction wavefield migration

Geophysics ◽  
2020 ◽  
Vol 85 (6) ◽  
pp. Q27-Q37
Author(s):  
Yang Shen ◽  
Jie Zhang
Keyword(s):  
Signal To Noise Ratio ◽  
Surface Velocity ◽  
Data Set ◽  
Near Surface ◽  
Depth Migration ◽  
Reflection Data ◽  
Imaging Tool ◽  
Imaging Results ◽  
Migration Method ◽  
Single Method

Refraction methods are often applied to model and image near-surface velocity structures. However, near-surface imaging is very challenging, and no single method can resolve all of the land seismic problems across the world. In addition, deep interfaces are difficult to image from land reflection data due to the associated low signal-to-noise ratio. Following previous research, we have developed a refraction wavefield migration method for imaging shallow and deep interfaces via interferometry. Our method includes two steps: converting refractions into virtual reflection gathers and then applying a prestack depth migration method to produce interface images from the virtual reflection gathers. With a regular recording offset of approximately 3 km, this approach produces an image of a shallow interface within the top 1 km. If the recording offset is very long, the refractions may follow a deep path, and the result may reveal a deep interface. We determine several factors that affect the imaging results using synthetics. We also apply the novel method to one data set with regular recording offsets and another with far offsets; both cases produce sharp images, which are further verified by conventional reflection imaging. This method can be applied as a promising imaging tool when handling practical cases involving data with excessively weak or missing reflections but available refractions.

Estimation of Near-Surface Velocity for 3-D Complicated Topography and Seismic Tomographic Static Corrections

2001 ◽  
Vol 44 (2) ◽  
pp. 268-274 ◽  
Author(s):  
Yi-Ke LIU ◽  
Xu CHANG ◽  
Hui WANG ◽  
Fu-Zhong LI
Keyword(s):  
Surface Velocity ◽  
Near Surface ◽  
Static Corrections

Near-surface scattering phenomena and implications for tunnel detection

2015 ◽  
Vol 3 (1) ◽  
pp. SF43-SF54 ◽  
Author(s):  
Shelby L. Peterie ◽  
Richard D. Miller
Keyword(s):  
Synthetic Data ◽  
P Wave ◽  
S Wave ◽  
Seismic Line ◽  
Data Set ◽  
Near Surface ◽  
Tunnel Detection ◽  
Impedance Contrast ◽  
Diffraction Imaging ◽  
Imaging Algorithms

Tunnel locations are accurately interpreted from diffraction sections of focused mode converted P- to S-wave diffractions from a perpendicular tunnel and P-wave diffractions from a nonperpendicular (oblique) tunnel. Near-surface tunnels are ideal candidates for diffraction imaging due to their small size relative to the seismic wavelength and large acoustic impedance contrast at the tunnel interface. Diffraction imaging algorithms generally assume that the velocities of the primary wave and the diffracted wave are approximately equal, and that the diffraction apex is recorded directly above the scatterpoint. Scattering phenomena from shallow tunnels with kinematic properties that violate these assumptions were observed in one field data set and one synthetic data set. We developed the traveltime equations for mode-converted and oblique diffractions and demonstrated a diffraction imaging algorithm designed for the roll-along style of acquisition. Potential processing and interpretation pitfalls specific to these diffraction types were identified. Based on our observations, recommendations were made to recognize and image mode-converted and oblique diffractions and accurately interpret tunnel depth, horizontal location, and azimuth with respect to the seismic line.

Full waveform inversion: early start of model building process to resolve the complex near surface model in the Exmouth sub-basin, North West Shelf Australia

2018 ◽  
Vol 58 (2) ◽  
pp. 884
Author(s):  
Lianping Zhang ◽  
Haryo Trihutomo ◽  
Yuelian Gong ◽  
Bee Jik Lim ◽  
Alexander Karvelas
Keyword(s):  
Model Building ◽  
Waveform Inversion ◽  
Velocity Model ◽  
Surface Velocity ◽  
Image Point ◽  
Surface Model ◽  
Full Waveform Inversion ◽  
Near Surface ◽  
North West ◽  
Full Waveform

The Schlumberger Multiclient Exmouth 3D survey was acquired over the Exmouth sub-basin, North West Shelf Australia and covers 12 600 km2. One of the primary objectives of this survey was to produce a wide coverage of high quality imaging with advanced processing technology within an agreed turnaround time. The complexity of the overburden was one of the imaging challenges that impacted the structuration and image quality at the reservoir level. Unlike traditional full-waveform inversion (FWI) workflow, here, FWI was introduced early in the workflow in parallel with acquisition and preprocessing to produce a reliable near surface velocity model from a smooth starting model. FWI derived an accurate and detailed near surface model, which subsequently benefitted the common image point (CIP) tomography model updates through to the deeper intervals. The objective was to complete the FWI model update for the overburden concurrently with the demultiple stages hence reflection time CIP tomography could start with a reasonably good velocity model upon completion of the demultiple process.

Tackling cycle skipping in full-waveform inversion with intermediate data

Geophysics ◽  
2019 ◽  
Vol 84 (3) ◽  
pp. R411-R427 ◽  
Author(s):  
Gang Yao ◽  
Nuno V. da Silva ◽  
Michael Warner ◽  
Di Wu ◽  
Chenhao Yang
Keyword(s):  
Objective Function ◽  
Waveform Inversion ◽  
Synthetic Data ◽  
Velocity Model ◽  
Full Waveform Inversion ◽  
Data Set ◽  
Intermediate Data ◽  
Full Waveform ◽  
L2 Norm ◽  
Recorded Data

Full-waveform inversion (FWI) is a promising technique for recovering the earth models for exploration geophysics and global seismology. FWI is generally formulated as the minimization of an objective function, defined as the L2-norm of the data residuals. The nonconvex nature of this objective function is one of the main obstacles for the successful application of FWI. A key manifestation of this nonconvexity is cycle skipping, which happens if the predicted data are more than half a cycle away from the recorded data. We have developed the concept of intermediate data for tackling cycle skipping. This intermediate data set is created to sit between predicted and recorded data, and it is less than half a cycle away from the predicted data. Inverting the intermediate data rather than the cycle-skipped recorded data can then circumvent cycle skipping. We applied this concept to invert cycle-skipped first arrivals. First, we picked up the first breaks of the predicted data and the recorded data. Second, we linearly scaled down the time difference between the two first breaks of each shot into a series of time shifts, the maximum of which was less than half a cycle, for each trace in this shot. Third, we moved the predicted data with the corresponding time shifts to create the intermediate data. Finally, we inverted the intermediate data rather than the recorded data. Because the intermediate data are not cycle-skipped and contain the traveltime information of the recorded data, FWI with intermediate data updates the background velocity model in the correct direction. Thus, it produces a background velocity model accurate enough for carrying out conventional FWI to rebuild the intermediate- and short-wavelength components of the velocity model. Our numerical examples using synthetic data validate the intermediate-data concept for tackling cycle skipping and demonstrate its effectiveness for the application to first arrivals.

scholarly journals Crustal velocity structure of the Superior and Grenville provinces of the southeastern Canadian Shield

1997 ◽  
Vol 34 (8) ◽  
pp. 1167-1184 ◽  
Author(s):  
S. Winardhi ◽  
R. F. Mereu
Keyword(s):  
Greenstone Belt ◽  
Velocity Structure ◽  
Canadian Shield ◽  
Crustal Thickening ◽  
Surface Velocity ◽  
Data Set ◽  
Tectonic Zone ◽  
Near Surface ◽  
Abitibi Greenstone Belt ◽  
Sudbury Structure

The 1992 Lithoprobe Abitibi–Grenville Seismic Refraction Experiment was conducted using four profiles across the Grenville and Superior provinces of the southeastern Canadian Shield. Delay-time analysis and tomographic inversion of the data set demonstrate significant lateral and vertical variations in crustal velocities from one terrane to another, with the largest velocity values occurring underneath the Central Gneiss and the Central Metasedimentary belts south of the Grenville Front. The Grenville Front Tectonic Zone is imaged as a southeast-dipping region of anomalous velocity gradients extending to the Moho. The velocity-anomaly maps suggest an Archean crust may extend, horizontally, 140 km beneath the northern Grenville Province. Near-surface velocity anomalies correlate well with the known geology. The most prominent of these is the Sudbury Structure, which is well mapped as a low-velocity basinal structure. The tomography images also suggest underthrusting of the Pontiac and Quetico subprovinces beneath the Abitibi Greenstone Belt. Wide-angle PmP signals, indicate that the Moho varies from a sharp discontinuity south of the Grenville Front to a rather diffuse and flat boundary under the Abitibi Greenstone Belt north of the Grenville Front. A significant crustal thinning near the Grenville Front may indicate post-Grenvillian rebound and (or) the extensional structure of the Ottawa–Bonnechere graben. Crustal thickening resulting from continental collision may explain the tomographic images showing the Moho is 4–5 km deeper south of the Grenville Front.

Near-surface full-waveform inversion in a transmission surface-consistent scheme

Geophysics ◽  
2020 ◽  
pp. 1-57
Author(s):  
Daniele Colombo ◽  
Ernesto Sandoval ◽  
Diego Rovetta ◽  
Apostolos Kontakis
Keyword(s):  
High Resolution ◽  
Seismic Data ◽  
Waveform Inversion ◽  
Surface Velocity ◽  
Full Waveform Inversion ◽  
Velocity Mapping ◽  
Signal To Noise ◽  
Near Surface ◽  
Velocity Modeling ◽  
Full Waveform

Land seismic velocity modeling is a difficult task largely related to the description of the near surface complexities. Full waveform inversion is the method of choice for achieving high-resolution velocity mapping but its application to land seismic data faces difficulties related to complex physics, unknown and spatially varying source signatures, and low signal-to-noise ratio in the data. Large parameter variations occur in the near surface at various scales causing severe kinematic and dynamic distortions of the recorded wavefield. Some of the parameters can be incorporated in the inversion model while others, due to sub-resolution dimensions or unmodeled physics, need to be corrected through data preconditioning; a topic not well described for land data full waveform inversion applications. We have developed novel algorithms and workflows for surface-consistent data preconditioning utilizing the transmitted portion of the wavefield, signal-to-noise enhancement by generation of CMP-based virtual super shot gathers, and robust 1.5D Laplace-Fourier full waveform inversion. Our surface-consistent scheme solves residual kinematic corrections and amplitude anomalies via scalar compensation or deconvolution of the near surface response. Signal-to-noise enhancement is obtained through the statistical evaluation of volumetric prestack responses at the CMP position, or virtual super (shot) gathers. These are inverted via a novel 1.5D acoustic Laplace-Fourier full waveform inversion scheme using the Helmholtz wave equation and Hankel domain forward modeling. Inversion is performed with nonlinear conjugate gradients. The method is applied to a complex structure-controlled wadi area exhibiting faults, dissolution, collapse, and subsidence where the high resolution FWI velocity modeling helps clarifying the geological interpretation. The developed algorithms and automated workflows provide an effective solution for massive full waveform inversion of land seismic data that can be embedded in typical near surface velocity analysis procedures.

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