Source signature determination by inversion

Geophysics ◽  
1992 ◽  
Vol 57 (12) ◽  
pp. 1633-1640 ◽  
Author(s):  
M. Landrø ◽  
R. Sollie
Keyword(s):  
Reflection Coefficient ◽  
Forward Modeling ◽  
Sea Surface ◽  
Inversion Algorithm ◽  
Air Bubble ◽  
Damping Coefficients ◽  
Air Gun ◽  
Marine Air ◽  
Source Array ◽  
Effective Source

A new method for estimating the pressure wavefield generated by a marine air‐gun array is presented. It is assumed that data is acquired at a ministreamer located below the source array. Effective source signatures for each air gun are estimated by an inversion algorithm. The forward modeling scheme used in the inversion algorithm is based upon a physical modeling of the air bubble generated by each air gun. This means that typical inversion parameters are: gun depths, empirical damping coefficients, and reflection coefficient of the sea surface. Variations in streamer depth are also taken into account by the inversion scheme. The algorithm has been successfully tested on examples with unknown streamer positions, gun parameters, reflection coefficient of sea surface, and ministreamer data contaminated with white noise.

Source signature determination from ministreamer data

Geophysics ◽  
1994 ◽  
Vol 59 (8) ◽  
pp. 1261-1269 ◽  
Author(s):  
Martin Landrø ◽  
Jan Langhammer ◽  
Roger Sollie ◽  
Losse Amundsen ◽  
Eivind Berg
Keyword(s):  
Point Sources ◽  
Inversion Method ◽  
Far Field ◽  
Nonlinear Inversion ◽  
Inversion Algorithm ◽  
Linear Inversion ◽  
Air Bubble ◽  
Air Gun ◽  
Error Energy ◽  
Effective Source

Two methods for estimating the pressure wavefield generated by a marine airp‐gun array are tested. Data have been acquired at a ministreamer located below the source array. Effective source signatures for each air gun are estimated. In the first method a nonlinear inversion algorithm is used, where the forward modeling scheme is based upon a physical modeling of the air bubble generated by each air gun. In the second method a linear inversion method is used, with the assumption that the physics in the problem can be described by the acoustic wave equation with explosive point sources as the driving term. From the estimated effective source signatures, far‐field signatures have been calculated for both methods and compared with measured far‐field signatures. The error energy between the measured and estimated far‐field signatures was approximately 8 percent for both methods.

scholarly journals Estimating source signatures from source-over-spread marine seismic data

Geophysics ◽  
2018 ◽  
Vol 83 (6) ◽  
pp. P39-P48
Author(s):  
Kristian Svarva Helgebostad ◽  
Martin Landrø ◽  
Vetle Vinje ◽  
Carl-Inge Nilsen
Keyword(s):  
Field Data ◽  
Forward Modeling ◽  
Inversion Algorithm ◽  
Surface Reflection ◽  
Air Gun ◽  
Recent Developments ◽  
Seismic Acquisition ◽  
The Difference ◽  
Marine Seismic ◽  
Bubble Oscillations

Recent developments in marine seismic acquisition include deploying a source vessel above a towed-streamer spread. We have developed an inversion algorithm to estimate source signatures for such acquisition configurations, by minimizing the difference between the recorded and a modeled direct wave. The forward modeling is based upon a physical modeling of the air bubble created by each air gun in the source array, and a damped Gauss-Newton approach is used for the optimization. Typical inversion parameters are empirical damping factors for the bubble oscillations and firing time delays for each air gun. Variations in streamer depth are taken into account, and a constant sea-surface reflection coefficient is also estimated as a by-product of the inversion. For data acquired in shallow waters, we have developed an extension of the forward modeling to include reflections from the water bottom to stabilize the inversion. The algorithm is tested on synthetic- and field-data examples, and the estimated source signature for the field-data example is used in a designature processing flow.

A perturbed ghost model for estimating air-gun array signatures

2019 ◽  
Vol 38 (9) ◽  
pp. 692-696
Author(s):  
Rob Telling ◽  
Sergio Grion
Keyword(s):  
Field Data ◽  
Near Field ◽  
Sea Surface ◽  
Model Parameters ◽  
Full Data ◽  
Air Gun ◽  
Accurate Treatment ◽  
Improved Performance ◽  
Source Array ◽  
Made In

Source designature for seismic data acquired using an air-gun array aims to remove the effects of pulse asymmetry, bubble oscillation, array directivity, and ghosting at the sea surface. For the process to be successful, we require an accurate representation of the source signature in the far field over the full data bandwidth. The well-established approach to this problem is to derive signatures from hydrophone data recorded in the near field of the source array. We perform a least-squares inversion of the near-field data, using a representation of the physics of propagation within the vicinity of the array, according to the measured geometry and incorporating bubble motion and source ghost formation. While ghost formation is typically treated using a simple linear model of propagation and reflection at the sea surface, observations suggest that this may be too simplistic. For example, ghost amplitudes are often found to be lower than expected, and features indicative of acoustically induced cavitation are observed. Hence there is interest in developing approaches that allow us to solve for the ghost directly using additional measurements made in the near field. We present an approach that builds on the standard method of inverting for notional sources and that seeks to take account of nonlinear perturbations to the downgoing wavefield, including attenuation of the ghost. Perturbation of the ghost is described using a series of virtual notional sources situated in the water column between the guns and the sea surface. This is found to provide a more accurate treatment of the ghost and does not require optimization of model parameters as is often necessary in practice with the standard approach. It is also found that the inversion is more stable than an alternative parameter-free approach that solves directly for real and mirror virtual notional sources. The improved performance and stability are demonstrated with a field data example.

scholarly journals Reducing high-frequency ghost cavitation signals from marine air-gun arrays

Geophysics ◽  
2016 ◽  
Vol 81 (3) ◽  
pp. P33-P46 ◽  
Author(s):  
Martin Landrø ◽  
Yuan Ni ◽  
Lasse Amundsen
Keyword(s):  
High Frequency ◽  
Separation Distance ◽  
Signal Model ◽  
Frequency Signal ◽  
High Frequency Signal ◽  
Array Configuration ◽  
Air Gun ◽  
Marine Air ◽  
Potential Signal ◽  
Source Array

Ghost cavitation, which is a term describing that cavitation bubbles are generated acoustically, has been hypothesized to occur when the ghost reflected signals from many individual air guns beneath the sea surface produce a pressure that is close to zero in the water above the source array. Ghost cavitation is typically observed some milliseconds after the ghost reflection, and it may last for 5–15 ms, depending on the configuration of the source array. The cavitation process subsequently generates a weak high-frequency signal. To investigate this potential signal model and mechanism, we have performed a dedicated source experiment. We found that the distance between the source strings in a source array is a major factor that influences the amount and strength of the high-frequency signal. By increasing the separation distance from 6.5 to 8 m, we have observed a significant decrease in the high-frequency signal. Further, the amount of ghost cavitation can be reduced by increasing the distance between the guns. Also single sub-arrays may create ghost cavitation sound, of course weaker in signal strength compared with full arrays, in agreement with the model. Conventional air-gun modeling can be used to predict where ghost cavitation can occur. Therefore, in principle, a workflow could be developed to quantify grossly if and how much high-frequency signals could be generated by this mechanism, given the source array configuration, and further change the configuration to reduce to a very minimum the high-frequency signals, if deemed necessary. For an air-gun array consisting of two subarrays separated by 6 m and fired at 9 m depth, we found that the high-frequency signals emitted between 1 and 10 kHz were of similar strength to the noise from conventional cargo ships, depending on their size and the vessels’ speed.

Blended acquisition with dispersed source arrays

Geophysics ◽  
2012 ◽  
Vol 77 (4) ◽  
pp. A19-A23 ◽  
Author(s):  
A. J. Berkhout
Keyword(s):  
High Frequency ◽  
Spatial Sampling ◽  
Acquisition Process ◽  
Air Gun ◽  
Seismic Acquisition ◽  
Sampling Intervals ◽  
Source Array

Blended source arrays are historically configured with equal source units, such as broadband vibrators (land) and broadband air-gun arrays (marine). I refer to this concept as homogeneous blending. I have proposed to extend the blending concept to inhomogeneous blending, meaning that a blended source array consists of different source units. More specifically, I proposed to replace in blended acquisition the traditional broadband sources by narrowband versions — imagine coded single air guns with different volumes or coded single narrowband vibrators with different central frequencies — together representing a dispersed source array (DSA). Similar to what we see in today’s audio systems, the DSA concept allows the design of dedicated narrowband source elements that do not suffer from the low versus high frequency compromise. In addition, the DSA concept opens the possibility to use source depths and spatial sampling intervals that are optimum for the low-, mid-, and high-frequency sources (multiscale shooting grids). DSAs are considered to be an important step in robotizing the seismic acquisition process.

Time-Lapse Monitoring of Daily Velocity Changes in Binchuan, Southwestern China, Using Large-Volume Air-Gun Source Array Data

2022 ◽  
Author(s):  
Yi Luan ◽  
Hongfeng Yang ◽  
Baoshan Wang ◽  
Wei Yang ◽  
Weitao Wang ◽  
...  
Keyword(s):  
Large Volume ◽  
Seismic Data ◽  
Temporal Changes ◽  
Air Pressure ◽  
Southwestern China ◽  
Long Period ◽  
Air Gun ◽  
Velocity Variations ◽  
Velocity Changes ◽  
Source Array

Abstract Temporal changes of seismic velocities in the Earth’s crust can be induced by stress perturbations or material damage from reasons such as strong ground motion, volcanic activities, and atmospheric effects. However, monitoring the temporal changes remains challenging, because most of them generally exist in small travel-time differences of seismic data. Here, we present an excellent case of daily variations of the subsurface structure detected using a large-volume air-gun source array of one-month experiment in Binchuan, Yunnan, southwestern China. The seismic data were recorded by 12 stations within ∼10 km away from the source and used to detect velocity change in the crust using the deconvolution method and sliding window cross-correlation method, which can eliminate the “intercept” error when cutting the air-gun signals and get the real subsurface variations. Furthermore, the multichannel singular spectral analysis method is used to separate the daily change (∼1 cycle per day) from the “long-period” change (<1 cycle per day) or noise. The result suggests that the daily velocity changes at the two nearest stations, 53277 (offset ∼700 m) and 53278 (offset ∼2.3 km), are well correlated with air temperature variation with a time lag of 5.0 ± 1.5 hr, which reflects that the velocity variations at the subsurface are likely attributed to thermoelastic strain. In contrast, both daily and long-period velocity changes at distant stations correlate better with the varying air pressure than the temperature, indicating that the velocity variations at deeper depth are dominated by the elastic loading of air pressure. Our results demonstrate that the air-gun source is a powerful tool to detect the velocity variation of the shallow crust media.

Effects of the Rough Sea Surface on the Signature of a Single Air Gun

2019 ◽  
Vol 44 (3) ◽  
pp. 575-581 ◽  
Author(s):  
Huseyin Ozkan Sertlek ◽  
Gerrit Blacquiere
Keyword(s):  
Sea Surface ◽  
Air Gun ◽  
Rough Sea Surface ◽  
Rough Sea

Fast 3D magnetic inversion of a surface relief in the space domain

Geophysics ◽  
2019 ◽  
Vol 84 (5) ◽  
pp. J57-J67 ◽  
Author(s):  
Marlon C. Hidalgo-Gato ◽  
Valéria C. F. Barbosa
Keyword(s):  
Hessian Matrix ◽  
Computational Cost ◽  
Magnetization Vector ◽  
Forward Modeling ◽  
Magnetic Data ◽  
Total Field ◽  
Inversion Algorithm ◽  
Sensitivity Matrix ◽  
Magnetic Inversion ◽  
Magnetic Basement

We have developed a fast 3D regularized magnetic inversion algorithm for depth-to-basement estimation based on an efficient way to compute the total-field anomaly produced by an arbitrary interface separating nonmagnetic sediments from a magnetic basement. We approximate the basement layer by a grid of 3D vertical prisms juxtaposed in the horizontal directions, in which the prisms’ tops represent the depths to the magnetic basement. To compute the total-field anomaly produced by the basement relief, the 3D integral of the total-field anomaly of a prism is simplified by a 1D integral along the prism thickness, which in turn is multiplied by the horizontal area of the prism. The 1D integral is calculated numerically using the Gauss-Legendre quadrature produced by dipoles located along the vertical axis passing through the prism center. This new magnetic forward modeling overcomes one of the main drawbacks of the nonlinear inverse problem for estimating the basement depths from magnetic data: the intense computational cost to calculate the total-field anomaly of prisms. The new sensitivity matrix is simpler and computationally faster than the one using classic magnetic forward modeling based on the 3D integrals of a set of prisms that parameterize the earth’s subsurface. To speed up the inversion at each iteration, we used the Gauss-Newton approximation for the Hessian matrix keeping the main diagonal only and adding the first-order Tikhonov regularization function. The large sparseness of the Hessian matrix allows us to construct and solve a linear system iteratively that is faster and demands less memory than the classic nonlinear inversion with prism-based modeling using 3D integrals. We successfully inverted the total-field anomaly of a simulated smoothing basement relief with a constant magnetization vector. Tests on field data from a portion of the Pará-Maranhão Basin, Brazil, retrieved a first depth-to-basement estimate that was geologically plausible.

Frequency‐domain acoustic‐wave modeling and inversion of crosshole data: Part II—Inversion method, synthetic experiments and real‐data results

Geophysics ◽  
1995 ◽  
Vol 60 (3) ◽  
pp. 796-809 ◽  
Author(s):  
Zhong‐Min Song ◽  
Paul R. Williamson ◽  
R. Gerhard Pratt
Keyword(s):  
Frequency Domain ◽  
Real Data ◽  
Forward Modeling ◽  
Two Dimensions ◽  
Inversion Method ◽  
Inversion Algorithm ◽  
Data Set ◽  
Wave Inversion ◽  
Full Wave ◽  
And Inversion

In full‐wave inversion of seismic data in complex media it is desirable to use finite differences or finite elements for the forward modeling, but such methods are still prohibitively expensive when implemented in 3-D. Full‐wave 2-D inversion schemes are of limited utility even in 2-D media because they do not model 3-D dynamics correctly. Many seismic experiments effectively assume that the geology varies in two dimensions only but generate 3-D (point source) wavefields; that is, they are “two‐and‐one‐half‐dimensional” (2.5-D), and this configuration can be exploited to model 3-D propagation efficiently in such media. We propose a frequency domain full‐wave inversion algorithm which uses a 2.5-D finite difference forward modeling method. The calculated seismogram can be compared directly with real data, which allows the inversion to be iterated. We use a descents‐related method to minimize a least‐squares measure of the wavefield mismatch at the receivers. The acute nonlinearity caused by phase‐wrapping, which corresponds to time‐domain cycle‐skipping, is avoided by the strategy of either starting the inversion using a low frequency component of the data or constructing a starting model using traveltime tomography. The inversion proceeds by stages at successively higher frequencies across the observed bandwidth. The frequency domain is particularly efficient for crosshole configurations and also allows easy incorporation of attenuation, via complex velocities, in both forward modeling and inversion. This also requires the introduction of complex source amplitudes into the inversion as additional unknowns. Synthetic studies show that the iterative scheme enables us to achieve the theoretical maximum resolution for the velocity reconstruction and that strongly attenuative zones can be recovered with reasonable accuracy. Preliminary results from the application of the method to a real data set are also encouraging.

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