Use of autoconvolution to suppress first‐order, long‐period multiples

Geophysics ◽  
1985 ◽  
Vol 50 (9) ◽  
pp. 1410-1425 ◽  
Author(s):  
C. J. Tsai
Keyword(s):  
Single Channel ◽  
Primary Energy ◽  
Low Frequencies ◽  
First Order ◽  
Seismic Wavelet ◽  
Common Depth Point ◽  
Band Limited ◽  
Marine Seismic ◽  
Prediction Problems ◽  
Water Bottom

A common problem in interpreting marine seismic data is the interference of water‐bottom multiples with primary reflections containing the structural or stratigraphic information. In deep ‐water areas, where considerable primary energy arrives before the first simple water‐bottom multiple, weak and deep crustal reflections are often obscured by the first‐order water‐bottom multiples. In order to obtain a more interpretable section, a technique involving a two‐step process was developed to suppress the first‐order water‐bottom multiples. First, the relation between the zero‐order, water‐bottom primary and its first‐order, simple water‐bottom multiple is used to derive statistically an inverse of the seismic wavelet in order to remove its effect, i.e., to wavelet‐shape the data. This wavelet processing provides a band‐limited estimate of the subsurface impulse response. The second step consists of using the autoconvolution of the wavelet‐shaped primary energy to estimate deterministically and subtract the actual first‐order, water‐bottom multiples, The method was applied to field data from the deep Gulf of Mexico. Different incidence angles for the input primaries and multiples, as well as dipping reflecting interfaces, introduce uncompensated traveltime errors. These errors reduce the ability to suppress multiples, thus restricting the validity of the method to low frequencies where common‐depth‐point stacking is less effective. On the other hand, curved interfaces may also cause amplitude prediction problems. In spite of this, the first‐order, water‐bottom multiple energy is significantly reduced (by up to 18 dB) on dip‐filtered, single‐channel data.

Stochastic sparse-spike deconvolution

Geophysics ◽  
2008 ◽  
Vol 73 (1) ◽  
pp. R1-R9 ◽  
Author(s):  
Danilo R. Velis
Keyword(s):  
Synthetic Data ◽  
Noisy Data ◽  
Simulated Data ◽  
Time Lags ◽  
Low Frequencies ◽  
Seismic Wavelet ◽  
3D Data ◽  
Highly Nonlinear ◽  
Very Fast Simulated Annealing ◽  
Band Limited

Sparse-spike deconvolution can be viewed as an inverse problem where the locations and amplitudes of a number of spikes (reflectivity) are estimated from noisy data (seismic traces). The main objective is to find the least number of spikes that, when convolved with the available band-limited seismic wavelet estimate, fit the data within a given tolerance error (misfit). The detection of the spikes’ time lags is a highly nonlinear optimization problem that can be solved using very fast simulated annealing (SA). Amplitudes are easily estimated using linear least squares at each SA iteration. At this stage, quadratic regularization is used to stabilize the solution, to reduce its nonuniqueness, and to provide meaningful reflectivity sequences, thus avoiding the need to constrain the spikes’ time lags and/or amplitudes to force valid solutions. Impedance constraints also can be included at this stage, providing the low frequencies required to recover the acoustic impedance. One advantage of the proposed method over other sparse-spike deconvolution techniques is that the uncertainty of the obtained solutions can be estimated stochastically. Further, errors in the phase of the wavelet estimate are tolerated, for an optimum constant-phase shift is obtained to calibrate the effective wavelet that is present in the data. Results using synthetic data (including simulated data for the Marmousi2 model) and field 3D data show that physically meaningful high-resolution sparse-spike sections can be derived from band-limited noisy data, even when the available wavelet estimate is inaccurate.

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.

scholarly journals Frequency Response Stabilization and Comparative Studies of MET Hydrophone at Marine Seismic Exploration Systems

Sensors ◽  
2020 ◽  
Vol 20 (7) ◽  
pp. 1944 ◽  
Author(s):  
Egor Egorov ◽  
Anna Shabalina ◽  
Dmitry Zaitsev ◽  
Sergey Kurkov ◽  
Nikolay Gueorguiev
Keyword(s):  
Frequency Response ◽  
Field Tests ◽  
High Sensitivity ◽  
Seismic Exploration ◽  
Joint Stock Company ◽  
Experimental Sample ◽  
Frequency Range ◽  
Stock Company ◽  
Low Frequencies ◽  
Marine Seismic

Low frequency hydrophone with a frequency range of 1−300 Hz for marine seismic exploration systems has been developed. The operation principle of the hydrophone bases on the molecular electronic transfer that allows high sensitivity and low level self-noise at low frequencies (<10 Hz) to be achieved. The paper presents a stabilization method of the frequency response within the frequency range at a depth up to 30 m. Laboratory and marine tests confirmed the stated characteristics as well as the possibility of using this sensor in bottom marine seismic systems. An experimental sample of the hydrophone successfully passed a comparative marine test at Gelendzhik Bay (Black Sea) with the technical support of Joint-Stock Company (JSC) “Yuzhmorgeologiya”. One of the main results is the possibility of obtaining high-quality information in the field of low frequencies, which was demonstrated in the course of field tests.

Robust wavelet estimation and blind deconvolution of noisy surface seismics

Geophysics ◽  
2008 ◽  
Vol 73 (5) ◽  
pp. V37-V46 ◽  
Author(s):  
Mirko van der Baan ◽  
Dinh-Tuan Pham
Keyword(s):  
Blind Deconvolution ◽  
General Purpose ◽  
Sufficient Accuracy ◽  
Wiener Filtering ◽  
Challenging Problem ◽  
Limited Data ◽  
Wavelet Estimation ◽  
Seismic Wavelet ◽  
Principal Frequency ◽  
Band Limited

Robust blind deconvolution is a challenging problem, particularly if the bandwidth of the seismic wavelet is narrow to very narrow; that is, if the wavelet bandwidth is similar to its principal frequency. The main problem is to estimate the phase of the wavelet with sufficient accuracy. The mutual information rate is a general-purpose criterion to measure whiteness using statistics of all orders. We modified this criterion to measure robustly the amplitude and phase spectrum of the wavelet in the presence of noise. No minimum phase assumptions were made. After wavelet estimation, we obtained an optimal deconvolution output using Wiener filtering. The new procedure performs well, even for very band-limited data; and it produces frequency-dependent phase estimates.

scholarly journals Deep learning for low-frequency extrapolation from multioffset seismic data

Geophysics ◽  
2019 ◽  
Vol 84 (6) ◽  
pp. R989-R1001 ◽  
Author(s):  
Oleg Ovcharenko ◽  
Vladimir Kazei ◽  
Mahesh Kalita ◽  
Daniel Peter ◽  
Tariq Alkhalifah
Keyword(s):  
Deep Learning ◽  
Seismic Data ◽  
Signal To Noise Ratio ◽  
Waveform Inversion ◽  
Low Frequency ◽  
Low Frequencies ◽  
Seismic Surveys ◽  
Full Waveform ◽  
Frequency Components ◽  
Marine Seismic

Low-frequency seismic data are crucial for convergence of full-waveform inversion (FWI) to reliable subsurface properties. However, it is challenging to acquire field data with an appropriate signal-to-noise ratio in the low-frequency part of the spectrum. We have extrapolated low-frequency data from the respective higher frequency components of the seismic wavefield by using deep learning. Through wavenumber analysis, we find that extrapolation per shot gather has broader applicability than per-trace extrapolation. We numerically simulate marine seismic surveys for random subsurface models and train a deep convolutional neural network to derive a mapping between high and low frequencies. The trained network is then tested on sections from the BP and SEAM Phase I benchmark models. Our results indicate that we are able to recover 0.25 Hz data from the 2 to 4.5 Hz frequencies. We also determine that the extrapolated data are accurate enough for FWI application.

TOUR OF PETROLEUM GEOPHYSICS ACTIVITIES IN THE U.S.S.R.

Geophysics ◽  
1966 ◽  
Vol 31 (3) ◽  
pp. 630-637 ◽  
Author(s):  
George V. Keller ◽  
Richard L. Caldwell ◽  
Milton B. Dobrin ◽  
Otto G. Holekamp ◽  
James E. White ◽  
...  
Keyword(s):  
Single Channel ◽  
State University ◽  
Common Depth Point ◽  
Seismic Shear ◽  
Line Spacing ◽  
Early Fall ◽  
Electrical Prospecting ◽  
Set Up ◽  
Moscow State University ◽  
Geological Research

Six American geophysicists spent three weeks in the U.S.S.R. during the early fall of 1965 as members of an exchange delegation in petroleum geophysics set up under the terms of a treaty on technical exchanges between the U. S. and the U.S.S.R. The group visited eleven different activities located in four cities, Moscow, Oktyabr’skiy, Krasnodar, and Leningrad. These activities included a number of geophysical and geological research institutes, the Moscow State University, and the Gubkin Institute. The principal difference between exploration geophysics in the U.S.S.R. and in the Western countries is the great emphasis in Soviet oil exploration on regional studies as a preliminary to the more direct search for petroleum deposits. As a result of such emphasis, their exploration program involves much greater use than ours of long refraction lines, electrical prospecting, and aeromagnetic surveys with close line spacing. Reflection work follows conventional lines without such recent refinements as common depth point shooting, impact sources, or vibrators. A possible reason these newer field techniques are not used is that no processing equipment appears to be generally available for compositing signals from more than one tape on to a single channel. Seismic shear waves generated at the surface have given reflections from depths as great as 5,000 ft but they have thus far been used only on an experimental basis. A technique of recording “exchange” (PS) waves from earthquakes has been employed for mapping basement depths in regional investigations.

scholarly journals Frequency-dependent attenuation analysis of ground-penetrating radar data

Geophysics ◽  
2007 ◽  
Vol 72 (3) ◽  
pp. J7-J16 ◽  
Author(s):  
John H. Bradford
Keyword(s):  
Attenuation Coefficient ◽  
Ground Penetrating Radar ◽  
A Priori ◽  
Radar Data ◽  
Frequency Dependent ◽  
First Order ◽  
Reflection Data ◽  
Frequency Independent ◽  
Band Limited ◽  
Ground Penetrating

In the early 1990s, it was established empirically that, in many materials, ground-penetrating radar (GPR) attenuation is approximately linear with frequency over the bandwidth of a typical pulse. Further, a frequency-independent [Formula: see text] parameter characterizes the slope of the band-limited attenuation versus frequency curve. Here, I derive the band-limited [Formula: see text] function from a first-order Taylor expansion of the attenuation coefficient. This approach provides a basis for computing [Formula: see text] from any arbitrary dielectric permittivity model. For Cole-Cole relaxation, I find good correlation between the first-order [Formula: see text] approximation and [Formula: see text] computed from linear fits to the attenuation coefficient curve over two-octave bands. The correlation holds over the primary relaxation frequency. For some materials, this relaxation occurs between 10 and [Formula: see text], a typical frequency range for many GPR applications. Frequency-dependent losses caused by scattering and by the commonly overlooked problem of frequency-dependent reflection make it difficult or impossible to measure [Formula: see text] from reflection data without a priori understanding of the materials. Despite these complications, frequency-dependent attenuation analysis of reflection data can provide valuable subsurface information. At two field sites, I find well-defined frequency-dependent attenuation anomalies associated with nonaqueous-phase liquid contaminants.

Motion Prediction of a Single-Point Moored Tanker Subjected to Current, Wind and Waves

1990 ◽  
Vol 112 (1) ◽  
pp. 83-90 ◽  
Author(s):  
T. Jiang ◽  
T. E. Schellin
Keyword(s):  
Digital Simulation ◽  
Single Point ◽  
Wave Spectrum ◽  
Memory Effects ◽  
Wave Forces ◽  
Restoring Force ◽  
Low Frequencies ◽  
Frequency Wave ◽  
First Order ◽  
Drift Forces

Horizontal motions of a tanker attached to a single-point mooring (SPM) terminal were predicted using digital simulation in the time domain. Excitations from steady current, gusting wind, and irregular seaway were included. Hydrodynamic forces generated by the ship’s motion and the action of its propeller and rudder were calculated in accordance with a previously validated, nonlinear quasi-steady four-quadrant maneuvering model, extended to include linear memory effects due to waves generated by the moving ship. Memory effects were approximated by a vectorial recursive state space model corresponding to a set of higher order differential equations. A nonlinear relationship of the force in the mooring hawser was assumed to represent restoring force characteristics of the SPM system. Wave excitation forces comprised first-order forces at wave frequencies and second-order drift forces at low frequencies. First-order wave forces were obtained by superposition of force components corresponding to regular wave components comprising the wave spectrum. Based on the low-frequency wave envelope, drift forces were calculated using mean drift force coefficients in regular waves. Selected sample simulations are presented to illustrate the use of this digital simulation method.

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