Early arrival waveform tomography on near-surface refraction data

Geophysics ◽  
2006 ◽  
Vol 71 (4) ◽  
pp. U47-U57 ◽  
Author(s):  
Jianming Sheng ◽  
Alan Leeds ◽  
Maike Buddensiek ◽  
Gerard T. Schuster
Keyword(s):  
Ground Truth ◽  
Velocity Model ◽  
Frequency Method ◽  
Near Surface ◽  
Good Convergence ◽  
Traveltime Tomography ◽  
Early Arrival ◽  
Synthetic Test ◽  
Waveform Tomography ◽  
Tomography Method

We develop a waveform-tomography method for estimating the velocity distribution that minimizes the waveform misfit between the predicted and observed early arrivals in space-time seismograms. By fitting the waveforms of early arrivals, early arrival waveform tomography (EWT) naturally takes into account more general wave-propagation effects compared to the high-frequency method of traveltime tomography, meaning that EWT can estimate a wider range of slowness wavenumbers. Another benefit of EWT is more reliable convergence compared to full-waveform tomography, because an early-arrival misfit function contains fewer local minima. Synthetic test results verify that the waveform tomogram is much more accurate than the traveltime tomogram and that this algorithm has good convergence properties. For marine data from the Gulf of Mexico, the statics problem caused by shallow, gassy muds was attacked by using EWT to obtain a more accurate velocity model. Using the waveform tomogram to correct for statics, the stacked section was significantly improved compared to using the normal move-out (NMO) velocity, and moderately improved compared to using the traveltime tomogram. Inverting high-resolution land data from Mapleton, Utah, showed an EWT velocity tomogram that was more consistent with the ground truth (trench log) than the traveltime tomogram. Our results suggest that EWT can provide supplemental, shorter-wavelength information compared to the traveltime tomogram for both shallow and moderately deep seismic data.

Target-oriented interferometric tomography for GPR data

Geophysics ◽  
2007 ◽  
Vol 72 (3) ◽  
pp. J1-J6 ◽  
Author(s):  
Sherif M. Hanafy ◽  
Gerard T. Schuster
Keyword(s):  
Velocity Model ◽  
Estimation Accuracy ◽  
Real Field ◽  
Near Surface ◽  
Interferometric Technique ◽  
Traveltime Tomography ◽  
Transit Times ◽  
The Difference ◽  
Tomography Method ◽  
Ground Penetrating

An interferometric form of Fermat’s principle and traveltime tomography is used to invert ground-penetrating radar (GPR) data for the subsurface velocity distribution. The input data consist of GPR traveltimes of reflections from two buried interfaces, [Formula: see text] (reference) and [Formula: see text] (target), where the data are excited and recorded by GPR antennas at the surface. Fermat’s interferometric principle is then used to redatum the surface transmitters and receivers to interface [Formula: see text] so the associated reflection traveltimes correspond to localized transit times between interfaces [Formula: see text] and [Formula: see text]. The overburden velocity model above interface [Formula: see text] is not required. The result after tomographic inversion is a high-resolution estimate of the velocity between interfaces [Formula: see text] and [Formula: see text] that does not depend on the velocity model above interface [Formula: see text]. A motivation for introducing interferometric traveltime tomography is that typical layer-stripping approaches will see the slowness error increase with depth as the layers are inverted. This suggests that near-surface statics errors are propagated and amplified with depth. In contrast, the interferometric traveltime tomography method largely eliminates statics errors by taking the difference between reflection events that emanate from neighboring layer interfaces. Slowness errors are not amplified with depth. However, the method is sensitive to the estimation accuracy for the geometry of the reference interface. Both synthetic and real field data are used successfully to validate the effectiveness of this interferometric technique.

Waveform tomography of field vibroseis data using an approximate 2D geometry leads to improved velocity models

Geophysics ◽  
2012 ◽  
Vol 77 (1) ◽  
pp. R33-R43 ◽  
Author(s):  
Brendan R. Smithyman ◽  
Ronald M. Clowes
Keyword(s):  
Waveform Inversion ◽  
Velocity Model ◽  
Surface Velocity ◽  
Time Shift ◽  
Full Waveform Inversion ◽  
Near Surface ◽  
Traveltime Tomography ◽  
Full Waveform ◽  
First Arrival ◽  
Waveform Tomography

Waveform tomography, a combination of traveltime tomography (or inversion) and waveform inversion, is applied to vibroseis first-arrival data to generate an interpretable model of P-wave velocity for a site in the Nechako Basin, south-central British Columbia, Canada. We use constrained 3D traveltime inversion followed by 2D full-waveform inversion to process long-offset (14.4 km) first-arrival refraction waveforms, resulting in a velocity model of significantly higher detail than a conventional refraction-statics model generated for a processing workflow. The crooked-line acquisition of the data set makes 2D full-waveform inversion difficult. Thus, a procedure that improves the tractability of waveform tomography processing of vibroseis data recorded on crooked roads is developed to generate a near-surface ([Formula: see text]) velocity model for the study area. The data waveforms are first static corrected using a time shift determined by 3D raytracing, which accounts for the crossline offsets produced by the crooked-line acquisition. The velocity model generated from waveform tomography exhibits substantial improvement when compared with a conventional refraction-statics model. It also shows improved resolution of sharp discontinuities and low-velocity regions when compared to the model from traveltime tomography alone, especially in regions where the geometry errors are moderate. Interpretation of the near-surface velocity model indicates possible subbasins in the Nechako Basin and delineates the Eocene volcanic rocks of the study area. This approach limits the ability of the full-waveform inversion to fit some propagation modes; however, the tractability of the inversion in the near-surface region is improved. This new development is especially useful in studies that do not warrant 3D seismic acquisition and processing.

Random objective waveform inversion of surface waves

Geophysics ◽  
2020 ◽  
Vol 85 (4) ◽  
pp. EN49-EN61
Author(s):  
Yudi Pan ◽  
Lingli Gao
Keyword(s):  
Objective Function ◽  
Surface Waves ◽  
Waveform Inversion ◽  
Velocity Model ◽  
Initial Model ◽  
S Wave ◽  
Data Set ◽  
Near Surface ◽  
Synthetic Test ◽  
Ground Penetrating

Full-waveform inversion (FWI) of surface waves is becoming increasingly popular among shallow-seismic methods. Due to a huge amount of data and the high nonlinearity of the objective function, FWI usually requires heavy computational costs and may converge toward a local minimum. To mitigate these problems, we have reformulated FWI under a multiobjective framework and adopted a random objective waveform inversion (ROWI) method for surface-wave characterization. Three different measure functions were used, whereas the combination of one measure function with one shot independently provided one of the [Formula: see text] objective functions ([Formula: see text] is the total number of shots). We have randomly chose and optimized one objective function at each iteration. We performed a synthetic test to compare the performance of the ROWI and conventional FWI approaches, which showed that the convergence of ROWI is faster and more robust compared with conventional FWI approaches. We also applied ROWI to a field data set acquired in Rheinstetten, Germany. ROWI successfully reconstructed the main geologic feature, a refilled trench, in the final result. The comparison between the ROWI result and a migrated ground-penetrating radar profile further proved the effectiveness of ROWI in reconstructing the near-surface S-wave velocity model. We also ran the same field example by using a poor initial model. In this case, conventional FWI failed whereas ROWI still reconstructed the subsurface model to a fairly good level, which highlighted the relatively low dependency of ROWI on the initial model.

Detecting near-surface objects with seismic waveform tomography

Geophysics ◽  
2009 ◽  
Vol 74 (6) ◽  
pp. WCC119-WCC127 ◽  
Author(s):  
Brendan Smithyman ◽  
R. Gerhard Pratt ◽  
John Hayles ◽  
Ralph Wittebolle
Keyword(s):  
Seismic Attenuation ◽  
Blind Test ◽  
Near Surface ◽  
Traveltime Tomography ◽  
Seismic Waveform ◽  
Long Offset ◽  
Velocity Images ◽  
Weight Drop ◽  
Waveform Tomography ◽  
Geophysical Imaging

Three shallow, high-velocity, rubble-filled targets are imaged using waveform tomography in an engineering-scale clay embankment at Seven Sisters Falls, Manitoba, Canada, to locate targets buried at approximately [Formula: see text] as a blind test of geophysical imaging methods. Previous studies use near-offset reflection methods to image the targets; however, this test uses waveform tomography of the long-offset, refracted arrivals to image P-velocity and seismic attenuation. The targets are invisible to standard traveltime tomography. Using weight-drop data, with frequencies of 20–150 Hz, the subwavelength targets are resolved in the velocity images and complementary images of seismic [Formula: see text] are produced. The interpreted target locations are consistent with limited survey information from the embankment construction. Multiple quality-control efforts, paired with a very good fit between model and observed data, indicate the reliability of the results.

3D seismic traveltime tomography imaging of the shallow subsurface at the C O2 SINK project site, Ketzin, Germany

Geophysics ◽  
2009 ◽  
Vol 74 (1) ◽  
pp. G1-G15 ◽  
Author(s):  
Sawasdee Yordkayhun ◽  
Ari Tryggvason ◽  
Ben Norden ◽  
Christopher Juhlin ◽  
Björn Bergman
Keyword(s):  
Velocity Structure ◽  
Velocity Model ◽  
Geological Structure ◽  
Seismic Survey ◽  
Storage Site ◽  
Near Surface ◽  
Shallow Subsurface ◽  
Traveltime Tomography ◽  
Reflection Seismic ◽  
Reflection Data

A 3D reflection seismic survey was performed in 2005 at the Ketzin carbon dioxide [Formula: see text] pilot geological-storage site (the [Formula: see text] project) near Berlin, Germany, to image the geological structure of the site to depths of about [Formula: see text]. Because of the acquisition geometry, frequency limitations of the source, and artefacts of the data processing, detailed structures shallower than about [Formula: see text] were unclear. To obtain structural images of the shallow subsurface, we applied 3D traveltime tomography to data near the top of the Ketzin anticline, where faulting is present. Understanding the shallow subsurface structure is important for long-term monitoring aspects of the project after [Formula: see text] has been injected into a saline aquifer at about [Formula: see text] depth. We used a 3D traveltime tomography algorithm based on a combination ofsolving for 3D velocity structure and static corrections in the inversion process to account for artefacts in the velocity structure because of smearing effects from the unconsolidated cover. The resulting velocity model shows low velocities of [Formula: see text] in the uppermost shallow subsurface of the study area. The velocity reaches about [Formula: see text] at a depth of [Formula: see text]. This coincides approximately with the boundary between Quaternary units, which contain the near-surface freshwater reservoir and the Tertiary clay aquitard. Correlation of tomographic images with a similarity attribute slice at [Formula: see text] (about [Formula: see text] depth) indicates that at least one east-west striking fault zone observed in the reflection data might extend into the Tertiary unit. The more detailed images of the shallow subsurface from this study provided valuable information on this potentially risky area.

Using 2D long-streamer seismic data waveform tomography to decipher sedimentary record of fault activity

2020 ◽  
Author(s):  
Amin Kahrizi ◽  
Matthias Delescluse ◽  
Mathieu Rodriguez ◽  
Pierre-Henri Roche ◽  
Anne Becel ◽  
...  
Keyword(s):  
Mass Transport ◽  
Seismic Data ◽  
Velocity Model ◽  
P Wave ◽  
Fault System ◽  
Fault Activity ◽  
Traveltime Tomography ◽  
P Wave Velocity ◽  
Waveform Tomography ◽  
Mass Transport Deposits

<p>Acoustic full-waveform inversion (FWI), or waveform tomography, involves use of both phase and amplitude of the recorded compressional waves to obtain a high-resolution P-wave velocity model of the propagation medium. Recent theoretical and computing advances now allow the application of this highly non-linear technique to field data. This led to common use of the FWI for industrial purposes related to reservoir imaging, physical properties of rocks, and fluid flow. Application of FWI in the academic domain has, so far, been limited, mostly because of the lack of adequate seismic data. While refraction seismic datasets include large source-receiver offsets that are useful to find a suitable starting velocity model through traveltime tomography, these acquisitions rarely reach the high density of receivers necessary for waveform tomography. On the other hand, multichannel seismic (MCS) reflection data acquisition has a dense receiver spacing but only modern long-streamer data have offsets that, in some cases, enable constraining subsurface velocities at a significant enough depth to be useful for structural or tectonic purposes.</p><p>In this study, we show how FWI can help decipher the record of a fault activity through time at the Shumagin Gap in Alaska. The MCS data were acquired on RV Marcus G. Langseth during the ALEUT cruise in the summer of 2011 using two 8-km-long seismic streamers and a 6600 cu. in. tuned airgun array. One of the most noticeable reflection features imaged on two profiles is a large, landward-dipping normal fault in the overriding plate; a structural configuration making the area prone to generating both transoceanic and local tsunamis, including from landslides. This fault dips ~40°- 45°, cuts the entire crust and connects to the plate boundary fault at ~35 km depth, near the intersection of the megathrust with the forearc mantle wedge. The fault system reaches the surface at the shelf edge 75 km from the trench, forming the Sanak basin where the record of the recent activity of the fault is not clear. Indeed, contouritic currents tend to be trapped by the topography created by faults, even after they are no longer active.  Erosion surfaces and onlaps from contouritic processes as well as gravity collapses and mass transport deposits results in complex structures that make it challenging to evaluate the fault activity. The long streamers used facilitated recording of refraction arrivals in the target continental slope area, which permitted running streamer traveltime tomography followed by FWI to produce coincident detailed velocity profiles to complement the reflection sections. FWI imaging of the Sanak basin reveals low velocities of mass transport deposits and velocity inversions indicate mechanically weak layers linking some faults to gravity sliding on a décollement. These details question previous interpretation of a present-day active fault. Our goal is to further analyze the behavior of the fault system using the P-wave velocity models from FWI to quantitatively detect fluids and constrain sediment properties.</p>

scholarly journals Ray-tracing traveltime tomography versus wave-equation traveltime inversion for near-surface seismic land data

2017 ◽  
Vol 5 (3) ◽  
pp. SO11-SO19
Author(s):  
Lei Fu ◽  
Sherif M. Hanafy
Keyword(s):  
Wave Equation ◽  
Ray Tracing ◽  
Water Table ◽  
Seismic Data ◽  
Velocity Model ◽  
Water Table Depth ◽  
Seismic Survey ◽  
Near Surface ◽  
Traveltime Tomography ◽  
Initial Starting

Full-waveform inversion of land seismic data tends to get stuck in a local minimum associated with the waveform misfit function. This problem can be partly mitigated by using an initial velocity model that is close to the true velocity model. This initial starting model can be obtained by inverting traveltimes with ray-tracing traveltime tomography (RT) or wave-equation traveltime (WT) inversion. We have found that WT can provide a more accurate tomogram than RT by inverting the first-arrival traveltimes, and empirical tests suggest that RT is more sensitive to the additive noise in the input data than WT. We present two examples of applying WT and RT to land seismic data acquired in western Saudi Arabia. One of the seismic experiments investigated the water-table depth, and the other one attempted to detect the location of a buried fault. The seismic land data were inverted by WT and RT to generate the P-velocity tomograms, from which we can clearly identify the water table depth along the seismic survey line in the first example and the fault location in the second example.

Waveform tomography at a groundwater contamination site: VSP-surface data set

Geophysics ◽  
2006 ◽  
Vol 71 (1) ◽  
pp. H1-H11 ◽  
Author(s):  
Fuchun Gao ◽  
Alan R. Levander ◽  
R. Gerhard Pratt ◽  
Colin A. Zelt ◽  
Gian Luigi Fradelizio
Keyword(s):  
Groundwater Contamination ◽  
Velocity Model ◽  
Target Area ◽  
Low Velocity ◽  
Data Set ◽  
Traveltime Tomography ◽  
Surface Data ◽  
Vertical Variations ◽  
Waveform Tomography ◽  
Air Force Base

Application of 2D frequency-domain waveform tomography to a data set from a high-resolution vertical seismic profiling (VSP) experiment at a groundwater contamination site in Hill Air Force Base (HAFB), Utah, reveals a surprisingly complicated shallow substructure with a resolution of approximately 1.5 m. Variance in the waveform misfit function is reduced 69.4% by using an initial velocity model from first-arrival traveltime tomography. The waveform tomography model suggests (1) a low-velocity layer at 1 to 4 m depth, (2) a high-vertical-velocity gradient of 80 m/s/m on average, and (3) severe lateral variations — velocity contrasts as large as about 200 m/s occur in a distance as short as 1.5 m. The model is well correlated with lithologic logs and is interpreted geologically. A Q-value of 20 is estimated for the target area. The extreme lateral and vertical variations of the subsurface compromise many standard seismic processing methods.

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