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

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.

2020 ◽  
Vol 5 (1) ◽  
pp. 04-06
Author(s):  
Bridget L. Lawrence ◽  
Etim D. Uko ◽  
Chibuogwu L. Eze ◽  
Chicozie Israel-Cookey ◽  
Iyeneomie Tamunobereton-ari ◽  
...  

Three-dimensional (3D) land seismic datasets were acquired from Central Depobelt in the Niger Delta region, Nigeria, with with the aim of attenuating ground roll noise from the dataset. The Omega (Schlumberger) software 2018 version was used along with frequency offset coherent noise suppression (FXCNS) and Anomalous Amplitude Attenuation (AAA) algorithms for ground roll attenuation. From the results obtained, Frequency Offset Coherent Noise Suppression (FXCNS) attenuates ground roll while AAA algorithm attenuates the residual high amplitude noise from the seismic data. Average frequency of the ground roll in the seismic data is 10.50Hz which falls within the actual range of ground roll frequency which is within the range of 3.00 – 18.00Hz. The average velocity of the ground roll in the seismic data is 477.36ms-1 while the velocity of ground roll ranges between 347.44 and 677.37ms-1. The wavelength of ground roll in the seismic data is 50.28m. The amplitude of the ground roll of -6.24dB is maximum at 4.2Hz. Frequency of signal ranges between 10.21 and 25.12Hz with an average of 17.67Hz. Signal amplitude of -8.32dB is maximum at 6.30Hz, while its wavelength is 57.12m. The results of this work can be used in the seismic source-receiver design for application in the area of study. Moreover, with ground roll noise attenuated, a better image of the subsurface geology is obtained hence reducing the risk of obtaining a wild cat drilling.


2001 ◽  
Vol 41 (1) ◽  
pp. 671
Author(s):  
T. Brice ◽  
L. Larsen ◽  
S. Morice ◽  
M. Svendsun

A new concept for acquiring calibrated towed streamer seismic data is introduced through a new acquisition and processing system called ‘Q-Marine’. The specification of the new system has been defined by rigorous analysis of the factors that limit the sensitivity of seismic data in 4D studies and imaging. New sensor and streamer technology, new source technology and advances in positioning techniques and data processing have addressed these limitations.Sensitivity analysis revealed that the most significant perturbations to the seismic signal are swell noise and sensor sensitivity variations. Conventional analog groups of hydrophones are designed to suppress swell noise however a new technique for data-adaptive coherent noise attenuation delivers even greater noise suppression for densely spatially sampled single-sensor data.Although modern source controllers provide accurate airgun firing control, the signature of an airgun array may vary from shot to shot. This can be due to factors such as changes in the array geometry, air pressure variations, depth variations and wave action. A method for estimating the far-field signature of a source array is the Notional Source Method (proprietary to Schlumberger) which has been steadily refined since its first disclosure. A recent development compensates for variation in source array geometry by monitoring the position and azimuth of each subarray using GPS receivers mounted on the floats.New calibrated positioning and streamer control systems are part of the new acquisition system. Active vertical and lateral streamer control is achieved using steerable birds and positioning uncertainty is reduced through an in-built fully braced acoustic ranging system.Calibrated marine seismic data are achieved through quantifying the source output, the sensor responses and positioning uncertainty. The consequential improvements in seismic fidelity result in better imaging and more reliable 4D analysis.


2021 ◽  
Author(s):  
Pimpawee Sittipan ◽  
Pisanu Wongpornchai

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.


2019 ◽  
Vol 34 (1) ◽  
Author(s):  
Tumpal Bernhard Nainggolan ◽  
Said Muhammad Rasidin ◽  
Imam Setiadi

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.


Geophysics ◽  
2019 ◽  
Vol 85 (1) ◽  
pp. V1-V10
Author(s):  
Julián L. Gómez ◽  
Danilo R. Velis ◽  
Juan I. Sabbione

We have developed an empirical-mode decomposition (EMD) algorithm for effective suppression of random and coherent noise in 2D and 3D seismic amplitude data. Unlike other EMD-based methods for seismic data processing, our approach does not involve the time direction in the computation of the signal envelopes needed for the iterative sifting process. Instead, we apply the sifting algorithm spatially in the inline-crossline plane. At each time slice, we calculate the upper and lower signal envelopes by means of a filter whose length is adapted dynamically at each sifting iteration according to the spatial distribution of the extrema. The denoising of a 3D volume is achieved by removing the most oscillating modes of each time slice from the noisy data. We determine the performance of the algorithm by using three public-domain poststack field data sets: one 2D line of the well-known Alaska 2D data set, available from the US Geological Survey; a subset of the Penobscot 3D volume acquired offshore by the Nova Scotia Department of Energy, Canada; and a subset of the Stratton 3D land data from South Texas, available from the Bureau of Economic Geology at the University of Texas at Austin. The results indicate that random and coherent noise, such as footprint signatures, can be mitigated satisfactorily, enhancing the reflectors with negligible signal leakage in most cases. Our method, called empirical-mode filtering (EMF), yields improved results compared to other 2D and 3D techniques, such as [Formula: see text] EMD filter, [Formula: see text] deconvolution, and [Formula: see text]-[Formula: see text]-[Formula: see text] adaptive prediction filtering. EMF exploits the flexibility of EMD on seismic data and is presented as an efficient and easy-to-apply alternative for denoising seismic data with mild to moderate structural complexity.


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