Mass Transport Deposits in Reflection Seismic Data Offshore Oregon, USA

2021 ◽  
Author(s):  
Brandi L. Lenz ◽  
Derek E. Sawyer
Keyword(s):  
Mass Transport ◽  
Seismic Data ◽  
Reflection Seismic ◽  
Mass Transport Deposits

Shear margin moraine, mass transport deposits and soft beds revealed by high-resolution P-Cable three-dimensional seismic data in the Hoop area, Barents Sea

2018 ◽  
Vol 477 (1) ◽  
pp. 537-548 ◽  
Author(s):  
Benjamin Bellwald ◽  
Sverre Planke
Keyword(s):  
High Resolution ◽  
Mass Transport ◽  
Seismic Data ◽  
Slope Failure ◽  
Barents Sea ◽  
3D Seismic ◽  
Seismic Reflection Data ◽  
Shallow Subsurface ◽  
Mass Transport Deposits ◽  
Amplitude Reflection

AbstractHigh-resolution seismic data are powerful tools that can help the offshore industries to better understand the nature of the shallow subsurface and plan the development of vulnerable infrastructure. Submarine mass movements and shallow gas are among the most significant geohazards in petroleum prospecting areas. A variety of high-resolution geophysical datasets collected in the Barents Sea have significantly improved our knowledge of the shallow subsurface in recent decades. Here we use a c. 200 km2 high-resolution P-Cable 3D seismic cube from the Hoop area, SW Barents Sea, to study a 20–65 m thick glacial package between the seabed and the Upper Regional Unconformity (URU) horizons. Intra-glacial reflections, not visible in conventional seismic reflection data, are well imaged. These reflections have been mapped in detail to better understand the glacial deposits and to assess their impact on seabed installations. A shear margin moraine, mass transport deposits and thin soft beds are examples of distinct units only resolvable in the P-Cable 3D seismic data. The top of the shear margin moraine is characterized by a positive amplitude reflection incised by glacial ploughmarks. Sedimentary slide wedges and shear bands are characteristic sedimentary features of the moraine. A soft reflection locally draping the URU is interpreted as a coarser grained turbidite bed related to slope failure along the moraine. The bed is possibly filled with gas. Alternatively, this negative amplitude reflection represents a thin, soft bed above the URU. This study shows that P-Cable 3D data can be used successfully to identify and map the external and internal structures of ice stream shear margin moraines and that this knowledge is useful for site-survey investigations.

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 Diffraction imaging of sedimentary basins: An example from the Porcupine Basin 

2021 ◽  
Author(s):  
Brydon Lowney ◽  
Lewis Whiting ◽  
Ivan Lokmer ◽  
Gareth O'Brien ◽  
Christopher Bean
Keyword(s):  
Mass Transport ◽  
Seismic Data ◽  
Sedimentary Basins ◽  
Fracture Network ◽  
Generative Adversarial Network ◽  
Adversarial Network ◽  
Porcupine Basin ◽  
Diffraction Imaging ◽  
Flow Pathways ◽  
Mass Transport Deposits

<p>Diffraction imaging is the technique of separating diffraction energy from the source wavefield and processing it independently. As diffractions are formed from objects and discontinuities, or diffractors, which are small in comparison to the wavelength, if the diffraction energy is imaged, so too are the diffractors. These diffractors take many forms such as faults, fractures, and pinch-out points, and are therefore geologically significant. Diffraction imaging has been applied here to the Porcupine Basin; a hyperextended basin located 200km to the southwest of Ireland with a rich geological history. The basin has seen interest both academically and industrially as a study on hyperextension and a potential source of hydrocarbons. The data is characterised by two distinct, basin-wide, fractured carbonates nestled between faulted sandstones and mudstones. Additionally, there are both mass-transport deposits and fans present throughout the data, which pose a further challenge for diffraction imaging. Here, we propose the usage of diffraction imaging to better image structures both within the carbonate, such as fractures, and below.</p><p>To perform diffraction imaging, we have utilised a trained Generative Adversarial Network (GAN) which automatically locates and separates the diffraction energy on pre-migrated seismic data. The data has then been migrated to create a diffraction image. This image is used in conjunction with the conventional image as an attribute, akin to coherency or semblance, to identify diffractors which may be geologically significant. Using this technique, we highlight the fracture network of a large Cretaceous chalk body present in the Porcupine, the internal structure of mass-transport deposits, potential fan edges, and additional faults within the data which may affect fluid flow pathways.</p>

Genesis and evolution of the mass transport deposits in the middle segment of the Pearl River canyon, South China Sea: Insights from 3D seismic data

2017 ◽  
Vol 88 ◽  
pp. 555-574 ◽  
Author(s):  
Xingxing Wang ◽  
Yingmin Wang ◽  
Min He ◽  
Weitao Chen ◽  
Haiteng Zhuo ◽  
...  
Keyword(s):  
South China Sea ◽  
Mass Transport ◽  
South China ◽  
Seismic Data ◽  
Pearl River ◽  
3D Seismic ◽  
Middle Segment ◽  
The Pearl River ◽  
Mass Transport Deposits ◽  
3D Seismic Data

scholarly journals Slumping and mass transport deposition in the Nankai fore arc: Evidence from IODP drilling and 3-D reflection seismic data

2011 ◽  
Vol 12 (5) ◽  
pp. n/a-n/a ◽  
Author(s):  
Michael Strasser ◽  
Gregory F. Moore ◽  
Gaku Kimura ◽  
Achim J. Kopf ◽  
Michael B. Underwood ◽  
...  
Keyword(s):  
Mass Transport ◽  
Seismic Data ◽  
Reflection Seismic

scholarly journals A machine learning tool for interpretation of Mass Transport Deposits from seismic data

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Priyadarshi Chinmoy Kumar ◽  
Kalachand Sain
Keyword(s):  
Machine Learning ◽  
Mass Transport ◽  
Seismic Data ◽  
Learning Tool ◽  
Mass Transport Deposits ◽  
Machine Learning Tool

Mass-transport Deposits of the Upper Cretaceous Qingshankou Formation, Songliao Terrestrial Basin, Northeast China: Depositional Characteristics, Recognition Criteria and External Geometry

2014 ◽  
Vol 88 (1) ◽  
pp. 62-77 ◽  
Author(s):  
Shuxin PAN ◽  
Pingsheng WEI ◽  
Tianqi WANG ◽  
Caiyan LIU ◽  
Bintao CHEN ◽  
...  
Keyword(s):  
Mass Transport ◽  
Northeast China ◽  
Upper Cretaceous ◽  
Mass Transport Deposits

Shelf-derived mass-transport deposits: origin and significance in the stratigraphic development of trench-slope basins

2021 ◽  
pp. 1-36
Author(s):  
Barbara Claussmann ◽  
Julien Bailleul ◽  
Frank Chanier ◽  
Geoffroy Mahieux ◽  
Vincent Caron ◽  
...  
Keyword(s):  
Mass Transport ◽  
Mass Transport Deposits ◽  
Trench Slope
Sign in / Sign up

Export Citation Format

Share Document