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>

Using 2D long-streamer seismic waveform tomography to decipher sedimentary processes surrounding a forearc fault offshore Alaska

2021 ◽  
Author(s):  
Amin Kahrizi ◽  
Matthias Delescluse ◽  
Mathieu Rodriguez ◽  
Pierre-Henri Roche ◽  
Anne Bécel ◽  
...  
Keyword(s):  
Mass Transport ◽  
Hanging Wall ◽  
Plate Boundary ◽  
Normal Fault ◽  
P Wave ◽  
Fault System ◽  
Fault Activity ◽  
Seismic Waveform ◽  
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. Modern multichannel seismic (MCS) reflection data acquisition now  have long offsets which, in some cases, enable constraining FWI-derived 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 R/V Marcus G. Langseth during the 2011 ALEUT cruise 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 and forms the ~6-km deep Sanak basin. However, the record of the recent fault activity remains unclear as 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 result in a complex sedimentary record that make it challenging to evaluate the fault activity using conventional MCS imaging alone. The long streamers used facilitated recording of refraction arrivals in the targeted continental slope area, which permitted running streamer traveltime tomography followed by FWI to produce coincident detailed velocity profiles to complement the reflection sections. We performed FWI imaging on two 40-km-long sections of the ALEUT lines crossing the Sanak basin. The images reveal low velocities of mass transport deposits as well as velocity inversions that may indicate mechanically weak layers linking some faults to gravity sliding on a décollement. One section also shows a velocity inversion in continuity to a bottom simulating reflector (BSR) only partially visible in the reflection image. The BSR velocity anomaly abruptly disappears across the main normal fault suggesting either an impermeable barrier or a lack of trapped fluids/gas in the hanging wall.</p>

Iterative P-wave velocity inversion using Markov chain Monte Carlo method

2020 ◽  
Author(s):  
Hyunggu Jun ◽  
Hyeong-Tae Jou ◽  
Han-Joon Kim ◽  
Sang Hoon Lee
Keyword(s):  
Wave Velocity ◽  
Seismic Data ◽  
Velocity Structure ◽  
Low Frequency ◽  
P Wave ◽  
Velocity Analysis ◽  
Seismic Section ◽  
Traveltime Tomography ◽  
P Wave Velocity ◽  
Frequency Components

<p>Imaging the subsurface structure through seismic data needs various information and one of the most important information is the subsurface P-wave velocity. The P-wave velocity structure mainly influences on the location of the reflectors during the subsurface imaging, thus many algorithms has been developed to invert the accurate P-wave velocity such as conventional velocity analysis, traveltime tomography, migration velocity analysis (MVA) and full waveform inversion (FWI). Among those methods, conventional velocity analysis and MVA can be widely applied to the seismic data but generate the velocity with low resolution. On the other hands, the traveltime tomography and FWI can invert relatively accurate velocity structure, but they essentially need long offset seismic data containing sufficiently low frequency components. Recently, the stochastic method such as Markov chain Monte Carlo (McMC) inversion was applied to invert the accurate P-wave velocity with the seismic data without long offset or low frequency components. This method uses global optimization instead of local optimization and poststack seismic data instead of prestack seismic data. Therefore, it can avoid the problem of the local minima and limitation of the offset. However, the accuracy of the poststack seismic section directly affects the McMC inversion result. In this study, we tried to overcome the dependency of the McMC inversion on the poststack seismic section and iterative workflow was applied to the McMC inversion to invert the accurate P-wave velocity from the simple background velocity and inaccurate poststack seismic section. The numerical test showed that the suggested method could successfully invert the subsurface P-wave velocity.</p>

scholarly journals Seismic P  Wave Velocity Model From 3‐D Surface and Borehole Seismic Data at the Alpine Fault DFDP‐2 Drill Site (Whataroa, New Zealand)

2021 ◽  
Author(s):  
V Lay ◽  
S Buske ◽  
SB Bodenburg ◽  
John Townend ◽  
R Kellett ◽  
...  
Keyword(s):  
New Zealand ◽  
Wave Velocity ◽  
Seismic Data ◽  
Velocity Model ◽  
P Wave ◽  
Alpine Fault ◽  
P Wave Velocity ◽  
Drill Site ◽  
Borehole Seismic

No description supplied

The structural architecture of the Whataroa Valley at the Alpine Fault (New Zealand) from first-arrival tomography and reflection imaging using an extended 3D VSP survey

2020 ◽  
Author(s):  
Vera Lay ◽  
Stefan Buske ◽  
Sascha Barbara Bodenburg ◽  
Franz Kleine ◽  
John Townend ◽  
...  
Keyword(s):  
New Zealand ◽  
Seismic Data ◽  
Average Velocity ◽  
Velocity Model ◽  
P Wave ◽  
3D Seismic ◽  
Data Set ◽  
Alpine Fault ◽  
P Wave Velocity ◽  
First Arrival

<p>The Alpine Fault along the West Coast of the South Island (New Zealand) is a major plate boundary that is expected to rupture in the next 50 years, likely as a magnitude 8 earthquake. The Deep Fault Drilling Project (DFDP) aims to deliver insight into the geological structure of this fault zone and its evolution by drilling and sampling the Alpine Fault at depth.  </p><p>Here we present results from a 3D seismic survey around the DFDP-2 drill site in the Whataroa Valley where the drillhole penetrated almost down to the fault surface. Within the glacial valley, we collected 3D seismic data to constrain valley structures that were obscured in previous 2D seismic data. The new data consist of a 3D extended vertical seismic profiling (VSP) survey using three-component receivers and a fibre optic cable in the DFDP-2B borehole as well as a variety of receivers at the surface.</p><p>The data set enables us to derive a reliable 3D P-wave velocity model by first-arrival travel time tomography. We identify a 100-460 m thick sediment layer (average velocity 2200±400 m/s) above the basement (average velocity 4200±500 m/s). Particularly on the western valley side, a region of high velocities steeply rises to the surface and mimics the topography. We interpret this to be the infilled flank of the glacial valley that has been eroded into the basement. In general, the 3D structures implied by the velocity model on the upthrown (Pacific Plate) side of the Alpine Fault correlate well with the surface topography and borehole findings.</p><p>A reliable velocity model is not only valuable by itself but it is also required as input for prestack depth migration (PSDM). We performed PSDM with a part of the 3D data set to derive a structural image of the subsurface within the Whataroa Valley. The top of the basement identified in the P-wave velocity model coincides well with reflectors in the migrated images so that we can analyse the geometry of the basement in detail.</p>

Dense 3D seismic traveltime tomography to understand complex deep landslide structures

2021 ◽  
Author(s):  
Myriam Lajaunie ◽  
Céleste Broucke ◽  
Jean-Philippe Malet ◽  
Clément Hibert ◽  
Guy Sénéchal ◽  
...  
Keyword(s):  
Wave Velocity ◽  
Velocity Model ◽  
Slope Instability ◽  
P Wave ◽  
Seismic Survey ◽  
Physical Parameters ◽  
3D Seismic ◽  
Traveltime Tomography ◽  
P Wave Velocity ◽  
Refraction Tomography

<div> <p>Bedrock geometry, geological discontinuities, geotechnical units and shear surfaces/bands control the deformation patterns and the mechanisms of slope instabilities. Seismic P-wave refraction tomography is useful to detect these features because P-wave velocity significantly decreases in fractured and weathered rocks relative to consolidated ones, and because lateral changes of velocity can highlight alternation of dipping fracture zones and consolidated rocks. Acquiring this information at high spatial resolution is of paramount importance to model landslide behaviour. </p> </div><div> <p>The Viella slope instability (Hautes-Pyrénées, France) is a complex and deep-seated (> 80 m) landslide which has reactivated in Spring 2018 as a consequence of both a 100-yr return period flash flood (Bastan torrent) which affects the lower part of the slope, and a major rockslide (> 100.000 m<sup>3</sup>) modifying the stress conditions in the upper part. The landslide, which covers an area of ca. 650 000 m², is primarily composed of schists with different degrees of weathering, forming several kinematic units with surface velocities in the range [0.5 – 5] mm.month<sup>-1</sup>. Many buildings and infrastructures (roads, bridge) are progressively damaged (cracks, progressive tilting) and scarps and lobes develop at the surface delineating the kinematic units.  </p> </div><div> <p>In order to model the evolution of the landslide and design possible mitigation measures (drainage, slope reprofiling), a 3D seismic survey has been carried out in summer 2020. The survey was designed to provide a highly detailed velocity model untill 100 m depth, highlighting possible lithological and mechanical contrasts as well as water preferential flow paths. The acquisition was carried out using 71 3C miniaturized seismic sensors buried at ca. 30 cm in the ground and spaced with an average intertrace of 70 m in accordance with slope topography. IGU16HR-3C 5Hz SmartSolo geophones of the DENSAR service (EOST) were used. The seismic array was recording continuously from June, 22nd to July, 21st 2020 at a sampling rate of 500 Hz. 370 controlled seismic sources were triggered at 122 locations using blank 12-gauge shotgun cartridges, Seismic Impulse Source Systemshots, 90-kg Propelled Energy Generator shots and a Mechatronics Lightning source generating P and S-waves with mono-frequency and sweep signals between 5 and 60 Hz of maximum 80 s length.  </p> </div><div> <p>We present the results of this active P-wave traveltime tomography. We first discuss the quality of the recorded signals related to each different type of source, given the noise and attenuation conditions at Viella. Because the signals were challenging to detect a methodology based on manual picking was used, supported by automatic detection tools and considerations regarding the network geometry in an a priori velocity model.  </p> </div><div> <p>The P-wave model was obtained using the inversion library pyGIMLI, which permits an accurate description of the topography, and provides a spatial discretization adapted to the problem. To supplement and constrain the interpretation of the P-wave velocity model, borehole information as well as a 3D resistivity model of the zone are available. With regards to these data, the geometric features and physical parameters of the main geological structures of the landslide are discussed. </p> </div>

scholarly journals No mafic layer in 80 km thick Tibetan crust

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Gaochun Wang ◽  
Hans Thybo ◽  
Irina M. Artemieva
Keyword(s):  
Seismic Data ◽  
P Wave ◽  
Indian Plate ◽  
Low Velocity ◽  
Crustal Earthquakes ◽  
Tectonic Processes ◽  
P Wave Velocity ◽  
Juvenile Crust ◽  
Mafic Lower Crust ◽  
Thick Crust

AbstractAll models of the magmatic and plate tectonic processes that create continental crust predict the presence of a mafic lower crust. Earlier proposed crustal doubling in Tibet and the Himalayas by underthrusting of the Indian plate requires the presence of a mafic layer with high seismic P-wave velocity (Vp > 7.0 km/s) above the Moho. Our new seismic data demonstrates that some of the thickest crust on Earth in the middle Lhasa Terrane has exceptionally low velocity (Vp < 6.7 km/s) throughout the whole 80 km thick crust. Observed deep crustal earthquakes throughout the crustal column and thick lithosphere from seismic tomography imply low temperature crust. Therefore, the whole crust must consist of felsic rocks as any mafic layer would have high velocity unless the temperature of the crust were high. Our results form basis for alternative models for the formation of extremely thick juvenile crust with predominantly felsic composition in continental collision zones.

Lithospheric architecture of the Ligurian Basin from seismic travel time tomography

2021 ◽  
Author(s):  
Anke Dannowski ◽  
Heidrun Kopp ◽  
Ingo Grevemeyer ◽  
Grazia Caielli ◽  
Roberto de Franco ◽  
...  
Keyword(s):  
Seismic Data ◽  
Velocity Model ◽  
P Wave ◽  
Central Basin ◽  
Uppermost Mantle ◽  
Mantle Boundary ◽  
Oceanic Spreading ◽  
Refraction Seismic ◽  
Back Arc ◽  
Ligurian Basin

&lt;p&gt;The Ligurian Basin is located north-west of Corsica at the transition from the western Alpine orogen to the Apennine system. The Back-arc basin was generated by the southeast retreat of the Apennines-Calabrian subduction zone. The opening took place from late Oligocene to Miocene. While the extension led to extreme continental thinning little is known about the style of back-arc rifting. Today, seismicity indicates the closure of this back-arc basin. In the basin, earthquake clusters occur in the lower crust and uppermost mantle and are related to re-activated, inverted, normal faults created during rifting.&lt;/p&gt;&lt;p&gt;To shed light on the present day crustal and lithospheric architecture of the Ligurian Basin, active seismic data have been recorded on short period ocean bottom seismometers in the framework of SPP2017 4D-MB, the German component of AlpArray. An amphibious refraction seismic profile was shot across the Ligurian Basin in an E-W direction from the Gulf of Lion to Corsica. The profile comprises 35 OBS and three land stations at Corsica to give a complete image of the continental thinning including the necking zone.&lt;/p&gt;&lt;p&gt;The majority of the refraction seismic data show mantle phases with offsets up to 70 km. The arrivals of seismic phases were picked and used to generate a 2-D P-wave velocity model. The results show a crust-mantle boundary in the central basin at ~12 km depth below sea surface. The P-wave velocities in the crust reach 6.6 km/s at the base. The uppermost mantle shows velocities &gt;7.8 km/s. The crust-mantle boundary becomes shallower from ~18 km to ~12 km depth within 30 km from Corsica towards the basin centre. The velocity model does not reveal an axial valley as expected for oceanic spreading. Further, it is difficult to interpret the seismic data whether the continental lithosphere was thinned until the mantle was exposed to the seafloor. However, an extremely thinned continental crust indicates a long lasting rifting process that possibly did not initiate oceanic spreading before the opening of the Ligurian Basin stopped. The distribution of earthquakes and their fault plane solutions, projected along our seismic velocity model, is in-line with the counter-clockwise opening of the Ligurian Basin.&lt;/p&gt;

A reality check on full-wave inversion applied to land seismic data for near-surface modeling

2022 ◽  
Vol 41 (1) ◽  
pp. 40-46
Author(s):  
Öz Yilmaz ◽  
Kai Gao ◽  
Milos Delic ◽  
Jianghai Xia ◽  
Lianjie Huang ◽  
...  
Keyword(s):  
Wave Velocity ◽  
Seismic Data ◽  
Surface Modeling ◽  
P Wave ◽  
Borehole Data ◽  
Near Surface ◽  
Traveltime Tomography ◽  
Wave Inversion ◽  
Full Wave ◽  
Elastic Inversion

We evaluate the performance of traveltime tomography and full-wave inversion (FWI) for near-surface modeling using the data from a shallow seismic field experiment. Eight boreholes up to 20-m depth have been drilled along the seismic line traverse to verify the accuracy of the P-wave velocity-depth model estimated by seismic inversion. The velocity-depth model of the soil column estimated by traveltime tomography is in good agreement with the borehole data. We used the traveltime tomography model as an initial model and performed FWI. Full-wave acoustic and elastic inversions, however, have failed to converge to a velocity-depth model that desirably should be a high-resolution version of the model estimated by traveltime tomography. Moreover, there are significant discrepancies between the estimated models and the borehole data. It is understandable why full-wave acoustic inversion would fail — land seismic data inherently are elastic wavefields. The question is: Why does full-wave elastic inversion also fail? The strategy to prevent full-wave elastic inversion of vertical-component geophone data trapped in a local minimum that results in a physically implausible near-surface model may be cascaded inversion. Specifically, we perform traveltime tomography to estimate a P-wave velocity-depth model for the near-surface and Rayleigh-wave inversion to estimate an S-wave velocity-depth model for the near-surface, then use the resulting pairs of models as the initial models for the subsequent full-wave elastic inversion. Nonetheless, as demonstrated by the field data example here, the elastic-wave inversion yields a near-surface solution that still is not in agreement with the borehole data. Here, we investigate the limitations of FWI applied to land seismic data for near-surface modeling.

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