How to Attenuate Diffracted Noise: (DSCAN) A New Methodology

Similar documents
Seismic interference noise attenuation based on sparse inversion Zhigang Zhang* and Ping Wang (CGG)

Radial trace filtering revisited: current practice and enhancements

Th-P08-11 Deblending of Single Source Vibroseis Land Data in Egypt with V1 Noise Attenuation Algorithm

Effect of Frequency and Migration Aperture on Seismic Diffraction Imaging

Interferometric Approach to Complete Refraction Statics Solution

Seismic processing workflow for supressing coherent noise while retaining low-frequency signal

Strong Noise Removal and Replacement on Seismic Data

Th ELI1 07 How to Teach a Neural Network to Identify Seismic Interference

Enhanced low frequency signal processing for sub-basalt imaging N. Woodburn*, A. Hardwick and T. Travis, TGS

Enhanced random noise removal by inversion

T17 Reliable Decon Operators for Noisy Land Data

Th B3 05 Advances in Seismic Interference Noise Attenuation

Amplitude balancing for AVO analysis

Application of complex-trace analysis to seismic data for random-noise suppression and temporal resolution improvement

Summary. Introduction

Stanford Exploration Project, Report 103, April 27, 2000, pages

Evaluation of a broadband marine source

High-dimensional resolution enhancement in the continuous wavelet transform domain

Polarization Filter by Eigenimages and Adaptive Subtraction to Attenuate Surface-Wave Noise

Seismic Reflection Method

Application of Coherent Noise Attenuation to 4-C Ocean Bottom Cable Seismic Data from the Niger Delta.

P and S wave separation at a liquid-solid interface

Latest field trial confirms potential of new seismic method based on continuous source and receiver wavefields

Ocean-bottom hydrophone and geophone coupling

Joint Time/Frequency Analysis, Q Quality factor and Dispersion computation using Gabor-Morlet wavelets or Gabor-Morlet transform

Downloaded 09/04/18 to Redistribution subject to SEG license or copyright; see Terms of Use at

Th N Broadband Processing of Variable-depth Streamer Data

Processing the Blackfoot broad-band 3-C seismic data

This presentation was prepared as part of Sensor Geophysical Ltd. s 2010 Technology Forum presented at the Telus Convention Center on April 15, 2010.

Tu SRS3 07 Ultra-low Frequency Phase Assessment for Broadband Data

Downloaded 11/02/15 to Redistribution subject to SEG license or copyright; see Terms of Use at

Attenuation of high energy marine towed-streamer noise Nick Moldoveanu, WesternGeco

Optimize Full Waveform Sonic Processing

Deblending workflow. Summary

Variable-depth streamer acquisition: broadband data for imaging and inversion

Processing the Teal South 4C-4D seismic survey

Air blast attenuation by combining microphone and geophone signals in the time-frequency domain

Application of Surface Consistent Amplitude Corrections as a Manual Editing Tool

Introduction. Figure 2: Source-Receiver location map (to the right) and geometry template (to the left).

A robust x-t domain deghosting method for various source/receiver configurations Yilmaz, O., and Baysal, E., Paradigm Geophysical

Vibration and air pressure monitoring of seismic sources

WS15-B02 4D Surface Wave Tomography Using Ambient Seismic Noise

Bandwidth Extension applied to 3D seismic data on Heather and Broom Fields, UK North Sea

Survey results obtained in a complex geological environment with Midwater Stationary Cable Luc Haumonté*, Kietta; Weizhong Wang, Geotomo

Multiple Attenuation - A Case Study

Investigating power variation in first breaks, reflections, and ground roll from different charge sizes

Broadband processing of West of Shetland data

Multi-survey matching of marine towed streamer data using a broadband workflow: a shallow water offshore Gabon case study. Summary

Multiple attenuation via predictive deconvolution in the radial domain

Spectral Detection of Attenuation and Lithology

Seismic reflection method

Anisotropic Frequency-Dependent Spreading of Seismic Waves from VSP Data Analysis

Air-noise reduction on geophone data using microphone records

ABSTRACT INTRODUCTION. different curvatures at different times (see figure 1a and 1b).

Tomostatic Waveform Tomography on Near-surface Refraction Data

Summary. Volumetric Q tomography on offshore Brunei dataset

3-D tomographic Q inversion for compensating frequency dependent attenuation and dispersion. Kefeng Xin* and Barry Hung, CGGVeritas

Estimation of a time-varying sea-surface profile for receiver-side de-ghosting Rob Telling* and Sergio Grion Shearwater Geoservices, UK

The case for longer sweeps in vibrator acquisition Malcolm Lansley, Sercel, John Gibson, Forest Lin, Alexandre Egreteau and Julien Meunier, CGGVeritas

Tu A D Broadband Towed-Streamer Assessment, West Africa Deep Water Case Study

7. Consider the following common offset gather collected with GPR.

Attacking localized high amplitude noise in seismic data A method for AVO compliant noise attenuation

SAUCE: A new technique to remove cultural noise from HRAM data

ERTH3021 Note: Terminology of Seismic Records

Ground-roll attenuation based on SVD filtering Milton J. Porsani, CPGG, Michelngelo G. Silva, CPGG, Paulo E. M. Melo, CPGG and Bjorn Ursin, NTNU

Uses of wide-azimuth and variable-depth streamers for sub-basalt seismic imaging

Broad-bandwidth data processing of shallow marine conventional streamer data: A case study from Tapti Daman Area, Western Offshore Basin India

How to Check the Quality of your Seismic Data Conditioning in Hampson-Russell Software. HRS9 Houston, Texas 2011

FOCUS ARTICLE. BroadSeis: Enhancing interpretation and inversion with broadband marine seismic

25823 Mind the Gap Broadband Seismic Helps To Fill the Low Frequency Deficiency

SVD filtering applied to ground-roll attenuation

Design of an Optimal High Pass Filter in Frequency Wave Number (F-K) Space for Suppressing Dispersive Ground Roll Noise from Onshore Seismic Data

Time-Frequency Attenuation of Swell Noise on Seismic Data from Offshore Central Niger-Delta, Nigeria.

Resolution and location uncertainties in surface microseismic monitoring

Deterministic marine deghosting: tutorial and recent advances

Improvement of signal to noise ratio by Group Array Stack of single sensor data

A second-order fast marching eikonal solver a

Summary. Introduction

Extending the useable bandwidth of seismic data with tensor-guided, frequency-dependent filtering

2D field data applications

Downloaded 01/03/14 to Redistribution subject to SEG license or copyright; see Terms of Use at

Multicomponent seismic polarization analysis

Ground Penetrating Radar (day 1) EOSC Slide 1

Northing (km)

F-x linear prediction filtering of seismic images

Satinder Chopra 1 and Kurt J. Marfurt 2. Search and Discovery Article #41489 (2014) Posted November 17, General Statement

Th ELI1 08 Efficient Land Seismic Acquisition Sampling Using Rotational Data

There is growing interest in the oil and gas industry to

Noise Attenuation in Seismic Data Iterative Wavelet Packets vs Traditional Methods Lionel J. Woog, Igor Popovic, Anthony Vassiliou, GeoEnergy, Inc.

Adaptive f-xy Hankel matrix rank reduction filter to attenuate coherent noise Nirupama (Pam) Nagarajappa*, CGGVeritas

Hunting reflections in Papua New Guinea: early processing results

Summary. D Receiver. Borehole. Borehole. Borehole. tool. tool. tool

Random and coherent noise attenuation by empirical mode decomposition Maïza Bekara, PGS, and Mirko van der Baan, University of Leeds

=, (1) Summary. Theory. Introduction

Optimal Processing of Marine High-Resolution Seismic Reflection (Chirp) Data

Direct Imaging of Group Velocity Dispersion Curves in Shallow Water Christopher Liner*, University of Houston; Lee Bell and Richard Verm, Geokinetics

Understanding Seismic Amplitudes

SUMMARY INTRODUCTION GROUP VELOCITY

CDP noise attenuation using local linear models

Residual converted wave statics

Transcription:

How to Attenuate Diffracted Noise: (DSCAN) A New Methodology Ali Karagul* CGG Canada Service Ltd., Calgary, Alberta, Canada akaragul@cgg.com Todd Mojesky and XinXiang Li CGG Canada Service Ltd., Calgary, Alberta, Canada and Necati Gulunay CGG Americas Inc. Abstract Summary Marine surveys in shallow water can suffer heavily from shot-generated scattered noise. In particular, the icy conditions of Beaufort Sea data can produce noise that can completely overshadow the expected recorded signal. This diffracted noise originates from heterogeneities near shallow sea beds. We present a method of attenuating diffracted noise in marine seismic surveys by locating the position of such obstructions using semblance scan analysis, and then by extracting the noise from the traces at the calculated travel times for each diffraction trajectory. Applications to different 3D and D data show the efficiency of this method. Introduction Marine seismic surveys, D and 3D, sometimes suffer severely from scattering of source energy from sharp discontinuities at or near the sea bottom. Such scattered noise travels only in water and is much stronger than the reflection signals from deep strata. This diffracted noise interferes with many essential prestack processes, such as deconvolution, multiple prediction and migration. Its detection and suppression has been a difficult issue in research and practice of marine data processing. One industry solution to this problem has been the execution of the following sequence (Fookes et al., 003): (a) determine the position of one diffractor from picked travel times, (b) flatten the diffracted noise on all contaminated records, c) filter the flattened events using conventional techniques such as f-k or Radon filtering, and finally d) restore the original travel times for all the records. Typically there are many significant diffractors and sequences (a) to (d) have to be repeated for each, making the process rather inefficient. Our motivation starts with detecting and attenuating most of the diffracted energy without picking any travel times. Our approach uses a semblance scan method called DSCAN. Landa et al (1987) is probably the first to use semblance scan to determine the location of buried diffractors in land surveys. Gulunay et al. (005) proposed a method of automatic detection, modeling and removal of shallow water diffractors in marine surveys. This method resembles the so called migration What s Next? Where is Our Industry Heading? 59

filtering technique (Nemeth et al, 000) in terms of the utilization of the double-square-root travel time equations. In this paper, we summarize the method and show its successful application to 3D and D marine surveys. Diffractor position scan (DSCAN) method The diffracted noise comes from the scattering of the source energy at the sharp discontinuities near the water bottom. The diffracted energy arrives at the receivers at a time which is the sum of the time from the source to the diffractor plus the time from the diffractor to the receiver: 1 V T = ( xs xd ) + ( ys yd ) + zd + ( xr xd ) + ( yr yd ) + 1 V z d where V is the velocity of propagation. Given a diffractor point D=(x d,y d,z d ), in an area (x and y range), the amplitudes of data at time T calculated as above for all traces ( i.e. source S=( x s, y s ) and receiver R=(x r,, y r ) pairs ) can be used to compute the coherency of the diffraction generated by that diffractor location. Stack amplitudes, or stack power, could be used to estimate how strong this diffractor is. Semblance is used as the coherency measure, and one could use other measures as well. We use the best estimate of the water velocity for V and generally assume z d =0 for shallow water cases. Note that given the finite record length (typically from 5 to 14 seconds) and for a given shot record there is a finite area that one needs to scan to find the diffractor locations that are affecting that shot. Once semblance scans in the x and y range are completed, the most coherent points (diffractors) can be automatically selected, and for each such point the travel times to a receiver-shot pair (trace) can be calculated. A short wavelet around this time can be extracted from that trace to obtain the contribution of this diffractor which will later be subtracted from the input record to obtain the noise attenuated record. Field data examples We have tested this method on a number of marine surveys. Here we would like to present two of them: the first one is a sailline from a 3D survey with 3 streamers per shot, the second one a D survey with one cable. A typical noisy shot from the 3D survey is shown in Figure 1a. Close inspection of the shot record suggests that there are a few diffractors but it is not easy to predict how many or which event belongs to which diffractor. The semblance scan of this shot and another one next to it, using a scan area of 11km by 1 km are shown in Figure. We used V=1538 m/s in the scans. The red colour indicates semblance values above 0.08. The highest semblance value found in the search was 0.53. There are holes in the middle of the semblance distributions shown in Figure. They are due to the fact that the first second of the data was not included in the diffractor scans. The missing parts from the semblance scan on the broadside are due to the fact that cyclic (low frequency) reflectors may look like broadside diffractors, especially when the number of cables per shot is small. Such points may need to be excluded from the analysis to protect reflection energy. Note the consistency of diffractors between two shots. Diffractor selection can be made using local maxima criteria with thresholding. How to Attenuate Diffracted Noise: (DSCAN) A New Methodology 593

Figure 1b shows the noise model built from the first strongest diffractors chosen from the scans like Figures. This model can later be subtracted from the record either by straight subtraction (Figure 1c) or by least squares subtraction, if desired. Figure 3a, 3b and 3c show, respectively, the stack of the raw record, the stack of the noise model generated by DSCAN in 35-375 Hz range, and the stack of the noise reduced records for the D shallow marine high resolution survey (Nyquist frequency=500hz). The diffractors on this line were mostly broadside diffractors and are therefore undesirable for a D survey. Depending on the azimuths, the diffracted noise can have almost any shape within shot gathers. These diffractions are so strong that they indeed leak into the stack as seen in Figure 3a. The stack of the noise attenuated records (Figure 3c) show that most of the diffracted energy is attenuated by our method. The remaining noise has lower frequency content (0-35Hz) and is due to its exclusion of this range for reflection protection during noise model building. Discussions and Conclusions We have presented an automated method for attenuating diffracted energy from shallow water inhomegeneities that are harmful to marine surveys. The method uses the double square root travel time equation and in essence is a migration/demigration type process except that it uses semblance instead of stacking amplitudes at constant depth (e.g. z d =0) and applies signal processing methods to build the noise model instead of a demigration process. Seismic recorded in the MacKenzie Delta suffers from this and another common near surface noise: ice fractures. These noise bursts travel in the locally nearly constant velocity permafrost. An adaptation of DSCAN to deterministically attenuate direct arrivals can automate the heavy task of noise removal in these areas. Acknowledgments We thank Noble Energy for providing the 3D data set, another client of ours, who wishes to remain anonymous, for providing the D data set; we also wish to thank our colleague, Ken Nixon for helping to obtain show rights on that line, finally, we thank CGG Canada Services Ltd. for allowing us to present this paper. References Fookes, G., Warner, C., and, Borselen, R. V., (003), Practical interference noise elimination in modern marine data processing, 73 rd Ann. Internat,. Mtg., Soc. Expl. Geophys., Expanded Abstracts Gulunay, N., Magesan, M., Connor, J.,(005) Diffracted noise attenuation in shallow water 3D marine surveys, 75 th Ann. Internat,. Mtg., Soc. Expl. Geophys., Expanded Abstracts. Landa, E., Shtivelman, V, and, Gelchinsky, B., 1987, A method for detection of diffracted waves on common-offset sections., Geophy. Pros., 35, 359-373. Nemeth, T., Sun, H., and, Schuster, G. T.,(000), Separation of signal and coherent noise by migration filtering, Geophysics, 65,, 574-583. What s Next? Where is Our Industry Heading? 594

(a) (b) (c) Figure 1. A shot gather with 3 cables a) input contaminated with diffracted noise b) diffraction model built, and c) after direct subtraction of noise model from the input. (a) (b) Figure. Diffractor semblance scans for two consecutive shots (a and b). Each scan covers an area of 11 km by 1 km. How to Attenuate Diffracted Noise: (DSCAN) A New Methodology 595

Figure 3. Stack of a D line; a) initial, b) diffracted noise c) noise reduced. What s Next? Where is Our Industry Heading? 596