scholarly journals Attenuation of long period multiple using F-k filter and surface-related multiple elimination methods on 2D broadband seismic data from Morowali Waters, Sulawesi

2021 ◽  
Vol 944 (1) ◽  
pp. 012005
Author(s):  
G L Situmeang ◽  
H M Manik ◽  
T B Nainggolan ◽  
Susilohadi
Keyword(s):  
Seismic Data ◽  
Seismic Waves ◽  
Frequency Bandwidth ◽  
Long Period ◽  
Time Migration ◽  
Predictive Deconvolution ◽  
Short Period ◽  
Wide Range ◽  
Marine Seismic ◽  
Multiple Elimination

Abstract Wide range frequency bandwidth on seismic data is a necessity due to its close relation to resolution and depth of target. High-frequency seismic waves provide high-resolution imaging that defines thin bed layers in shallow sediment, while low-frequency seismic waves can penetrate into deeper target depth. As a result of broadband seismic technology, its wide range of frequency bandwidth is a suitable geophysical exploration method in the oil and gas industry. A major obstacle that is frequently found in marine seismic data acquisition is the existence of multiples. Short period multiple and reverberation are commonly attenuated by the predictive deconvolution method on prestack data. Advanced methods are needed to suppress long period multiple in marine seismic data. The 2D broadband marine seismic data from deep Morowali Waters, Sulawesi, contains both short and long period multiples. The predictive deconvolution, which is applied to the processing sequences, successfully eliminates short period multiple on prestack data. The combination of F-k filter and Surface Related Multiple Elimination (SRME) methods are successful in attenuating long period multiple of the 2D broadband marine seismic data. The Prestack Time Migration section shows fine resolution of seismic images.

LONG-PERIOD SURFACE-RELATED MULTIPLE SUPPRESSION IN 2D MARINE SEISMIC DATA USING PREDICTIVE DECONVOLUTION AND COMBINATION OF SURFACE-RELATED MULTIPLE ELIMINATION AND PARABOLIC RADON FILTERING

2021 ◽  
Author(s):  
Pimpawee Sittipan ◽  
Pisanu Wongpornchai
Keyword(s):  
Seismic Data ◽  
Seismic Reflection ◽  
Petroleum Reservoirs ◽  
The United States ◽  
Multiple Reflections ◽  
Long Period ◽  
Predictive Deconvolution ◽  
Short Period ◽  
Marine Seismic ◽  
Multiple Elimination

Some of the important petroleum reservoirs accumulate beneath the seas and oceans. Marine seismic reflection method is the most efficient method and is widely used in the petroleum industry to map and interpret the potential of petroleum reservoirs. Multiple reflections are a particular problem in marine seismic reflection investigation, as they often obscure the target reflectors in seismic profiles. Multiple reflections can be categorized by considering the shallowest interface on which the bounces take place into two types: internal multiples and surface-related multiples. Besides, the multiples can be categorized on the interfaces where the bounces take place, a difference between long-period and short-period multiples can be considered. The long-period surface-related multiples on 2D marine seismic data of the East Coast of the United States-Southern Atlantic Margin were focused on this research. The seismic profile demonstrates the effectiveness of the results from predictive deconvolution and the combination of surface-related multiple eliminations (SRME) and parabolic Radon filtering. First, predictive deconvolution applied on conventional processing is the method of multiple suppression. The other, SRME is a model-based and data-driven surface-related multiple elimination method which does not need any assumptions. And the last, parabolic Radon filtering is a moveout-based method for residual multiple reflections based on velocity discrimination between primary and multiple reflections, thus velocity model and normal-moveout correction are required for this method. The predictive deconvolution is ineffective for long-period surface-related multiple removals. However, the combination of SRME and parabolic Radon filtering can attenuate almost long-period surface-related multiple reflections and provide a high-quality seismic images of marine seismic data.

scholarly journals Combined Multiple Attenuation Methods and Geological Interpretation : Seram Sea Case Study 2D Marine Seismic Data

2019 ◽  
Vol 34 (1) ◽  
Author(s):  
Tumpal Bernhard Nainggolan ◽  
Said Muhammad Rasidin ◽  
Imam Setiadi
Keyword(s):  
Satisfactory Result ◽  
Radon Transform ◽  
Seismic Data ◽  
Thrust Belt ◽  
Geological Interpretation ◽  
Structural Style ◽  
Predictive Deconvolution ◽  
Fold And Thrust Belt ◽  
Short Period ◽  
Marine Seismic

Multiple often and always appear in marine seismic data due to very high acoustic impedance contrasts. These events have undergone more than one reflection. This causes the signal to arrive back at the receiver at an erroneous time, which, in turn, causes false results and can result in data misinterpretation. Several types of multiple suppression have been studied in literature. Methods that attenuate multiples can be classified into three broad categories: deconvolution methods; filtering methods and wavefield prediction subtraction methods. The study area is situated on Seram Sea in between 131°15’E – 132°45’E and 3°0’S – 4°0’S, Seram Trough which is located beneath Seram Sea at northern part of the Banda-Arc – Australian collision zone and currently the site of contraction between Bird’s Head and Seram. This research uses predictive deconvolution and FK-filter to attenuate short period multiple from their move out, then continued by SRME method to predict multiple that cannot be attenuated from previous method, then followed by Radon transform to attenuate multiple that still left and cannot be attenuated by SRME method. The result of each method then compared to each other to see how well multiple attenuated. Predictive deconvolution and F-K filter could not give satisfactory result especially complex area where multiple in dipping event is not periodic, SRME method successfully attenuate multiple especially in near offset multiple without need subsurface information, while SRME method fails to attenuate long offset multiple, combination of SRME method and Radon transform can give satisfactory result with careful selection of the Radon transform parameters because it can obscure some primary reflectors. Based on geological interpretation, Seram Trough is built by dominant structural style of deposited fold and thrust belt. The deposited fold and thrust belt has a complexly fault geometry from western zone until eastern of seismic line.

scholarly journals The 22 December 2018 tsunami from flank collapse of Anak Krakatau volcano during eruption

2020 ◽  
Vol 6 (3) ◽  
pp. eaaz1377 ◽  
Author(s):  
Lingling Ye ◽  
Hiroo Kanamori ◽  
Luis Rivera ◽  
Thorne Lay ◽  
Yu Zhou ◽  
...  
Keyword(s):  
Seismic Data ◽  
Seismic Waves ◽  
Moment Tensor ◽  
Time Duration ◽  
Ground Shaking ◽  
Long Period ◽  
Short Period ◽  
Single Force ◽  
Krakatau Volcano ◽  
Tsunami Warnings

On 22 December 2018, a devastating tsunami struck Sunda Strait, Indonesia without warning, leaving 437 dead and thousands injured along the western Java and southern Sumatra coastlines. Synthetic aperture radar and broadband seismic observations demonstrate that a small, <~0.2 km3 landslide on the southwestern flank of the actively erupting volcano Anak Krakatau generated the tsunami. The landslide did not produce strong short-period seismic waves; thus, precursory ground shaking did not provide a tsunami warning. The source of long-period ground motions during the landslide can be represented as a 12° upward-dipping single-force directed northeastward, with peak magnitude of ~6.1 × 1011 N and quasi-sinusoidal time duration of ~70 s. Rapid quantification of a landslide source process by long-period seismic wave inversions for moment-tensor and single-force parameterizations using regional seismic data available within ~8 min can provide a basis for future fast tsunami warnings, as is also the case for tsunami earthquakes.

Seismic inversions of large, rapid landslides: what they can and cannot tell us about event dynamics

2021 ◽  
Author(s):  
Kate Allstadt ◽  
Andrew Mitchell ◽  
Liam Toney ◽  
David George ◽  
Scott McDougall
Keyword(s):  
Seismic Data ◽  
Seismic Waves ◽  
Numerical Models ◽  
Seismic Inversion ◽  
Two Phase ◽  
Flow Equations ◽  
Long Period ◽  
Wide Range ◽  
Regularization Techniques ◽  
Event Dynamics

&lt;p&gt;Researchers are increasingly incorporating force histories derived from long-period seismic waves into multidisciplinary studies of large, rapid landslides. The force history can provide important information about what happened during failure &amp;#8212; information that complements data available from field investigations and remote sensing analyses. It can also provide additional constraints on the dynamics of landslide motion than can be used to validate and/or calibrate numerical landslide models. However, the inversions need to be of high quality and must be interpreted properly. Because this technique is relatively new, we are still discovering how to best conduct inversions to obtain robust results and how to appropriately interpret these results. In this study, we run numerical models of landslides with idealized source and path geometries using two different modeling packages, DAN3D and D-Claw, and we use the model outputs to generate synthetic long-period seismic data. Both models use depth-averaged flow equations over 3D topography, with DAN3D using semi-empirical material rheologies and D-Claw using a two-phase granular and fluid flow approach. To examine the influence of station azimuthal coverage and distance, we synthesize seismic data for a wide range of possible station configurations. We then use these synthetic seismic data to conduct seismic inversions using the recently released open-source Python-based software package, lsforce (https://code.usgs.gov/ghsc/lhp/lsforce). In doing these inversions, we add differing levels and types of noise, vary the inversion options (e.g., frequency range, regularization techniques) and then compare the results to the &amp;#8220;known&amp;#8221; dynamics of the modeled idealized landslides. We aim to understand common artefacts, limitations, and other potential pitfalls in interpretation, to guide the inversion process in future studies. We repeat this process for idealized landslides of increasing complexity, including multi-part failures, sinuous paths, and gradual versus sudden initiations, to simulate how these characteristics are reflected in the force history and to better understand what level of detail can be constrained from the seismic inversion. This work will help guide researchers to obtain more reliable information about landslide dynamics from seismic inversions in future landslide studies.&lt;/p&gt;

Coherent noise in marine seismic data

Geophysics ◽  
1983 ◽  
Vol 48 (7) ◽  
pp. 854-886 ◽  
Author(s):  
Ken Larner ◽  
Ron Chambers ◽  
Mai Yang ◽  
Walt Lynn ◽  
Willon Wai
Keyword(s):  
Seismic Data ◽  
Noise Suppression ◽  
Seismic Source ◽  
Coherent Noise ◽  
Critical Data ◽  
Predictive Deconvolution ◽  
Scattered Energy ◽  
Marine Seismic ◽  
The Many ◽  
Water Bottom

Despite significant advances in marine streamer design, seismic data are often plagued by coherent noise having approximately linear moveout across stacked sections. With an understanding of the characteristics that distinguish such noise from signal, we can decide which noise‐suppression techniques to use and at what stages to apply them in acquisition and processing. Three general mechanisms that might produce such noise patterns on stacked sections are examined: direct and trapped waves that propagate outward from the seismic source, cable motion caused by the tugging action of the boat and tail buoy, and scattered energy from irregularities in the water bottom and sub‐bottom. Depending upon the mechanism, entirely different noise patterns can be observed on shot profiles and common‐midpoint (CMP) gathers; these patterns can be diagnostic of the dominant mechanism in a given set of data. Field data from Canada and Alaska suggest that the dominant noise is from waves scattered within the shallow sub‐buttom. This type of noise, while not obvious on the shot records, is actually enhanced by CMP stacking. Moreover, this noise is not confined to marine data; it can be as strong as surface wave noise on stacked land seismic data as well. Of the many processing tools available, moveout filtering is best for suppressing the noise while preserving signal. Since the scattered noise does not exhibit a linear moveout pattern on CMP‐sorted gathers, moveout filtering must be applied either to traces within shot records and common‐receiver gathers or to stacked traces. Our data example demonstrates that although it is more costly, moveout filtering of the unstacked data is particularly effective because it conditions the data for the critical data‐dependent processing steps of predictive deconvolution and velocity analysis.

Observations on the turbulent fluctuations of a tidal current

1949 ◽  
Vol 199 (1058) ◽  
pp. 311-327 ◽  
Keyword(s):  
Time Scale ◽  
Tidal Current ◽  
Velocity Fluctuations ◽  
Turbulent Fluctuations ◽  
Long Period ◽  
Auto Correlation ◽  
Short Period ◽  
Wide Range ◽  
First Time ◽  
A Current

Records have been obtained of fluctuations in the speed of the tidal current in the Mersey estuary, using a current meter in a stand on the bottom, and compared with other records taken with the meter suspended freely at various depths. The fluctuations covered a wide range of periods but could be separated into two main types: ‘short period’, having periods of the order of a few seconds, and ‘long period’, with periods from 30 sec. to several minutes. The amplitudes, periods and auto-correlation of the short-period fluctuations have been examined in some detail, and it is concluded that the fluctuations observed near the bottom are evidence of the turbulence associated with bottom friction. It is believed to be the first time that the presence of turbulent velocity fluctuations of this time-scale in the sea has been established experimentally. The long-period fluctuations resemble those found in previous investigations and show features consistent with their being turbulent in origin also, although turbulence of the time-scale involved in their case would probably be mainly horizontal.

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