Water velocity estimation using inversion methods

Geophysics ◽  
2010 ◽  
Vol 75 (1) ◽  
pp. U1-U8 ◽  
Author(s):  
Gerson Luis da Silva Ritter
Keyword(s):  
Sound Velocity ◽  
Propagation Velocity ◽  
Real Data ◽  
Velocity Model ◽  
Velocity Estimation ◽  
Seismic Survey ◽  
Sound Waves ◽  
Sea Bottom ◽  
Tomographic Method ◽  
Two Parameters

It is known that the propagation velocity of sound waves in water can vary over time. For a 3D seismic survey, if data are acquired in adjacent lines but at different dates, this implies the same reflection point will be recorded at different times. To take this effect into account in seismic processing, it is necessary to measure the sound velocity in water. I have developed a 3D tomographic method that directly estimates it. It assumes a constant sound velocity for a group of shots belonging to a single sail line. Using a picked water-bottom reflection and an initial depth and velocity model, results good for use in subsequent processing can be obtained by estimating only two parameters: the variation of the propagation velocity and a constant vertical shift of the reflector depth in relation to the initial model. The method was tested with both synthetic and real data. The real data results were validated using two methods. First, I analyzed the histogram of the residuals of the final updated model. Second, I used a specially modified Kirchhoff migration algorithm to migrate the sea bottom. The main advantages of this method are that it takes into account the sea-bottom dips to estimate the velocities and it can be applied to each sail line separately. Also, the inversion is not ill-conditioned provided that data with large enough offsets are used. As a result, the method is simple to apply.

MAZ depth-velocity modelling and imaging with azimuthal anisotropy

2010 ◽  
Vol 50 (2) ◽  
pp. 723
Author(s):  
Sergey Birdus ◽  
Erika Angerer ◽  
Iftikhar Abassi
Keyword(s):  
Seismic Data ◽  
Real Data ◽  
Azimuthal Velocity ◽  
Velocity Model ◽  
Azimuthal Anisotropy ◽  
Lessons Learned ◽  
Seismic Survey ◽  
Depth Migration ◽  
Velocity Anisotropy ◽  
Interval Velocity

Processing of multi and wide-azimuth seismic data faces some new challenges, and one of them is depth-velocity modelling and imaging with azimuthal velocity anisotropy. Analysis of multi-azimuth data very often reveals noticeable fluctuations in moveout between different acquisition directions. They can be caused by several factors: real azimuthal interval velocity anisotropy associated with quasi-vertical fractures or present day stress field within the sediments; short-wavelength velocity heterogeneities in the overburden; TTI (or VTI) anisotropy in the overburden; or, random distortions due to noise, multiples, irregularities in the acquisition geometry, etcetera. In order to build a velocity model for multi-azimuth pre-stack depth migration (MAZ PSDM) taking into account observed azimuthal anisotropy, we need to recognise, separate and estimate all the effects listed above during iterative depth-velocity modelling. Analysis of seismic data from a full azimuth 3D seismic land survey revealed the presence of strong spatially variable azimuthal velocity anisotropy that had to be taken into consideration. Using real data examples we discuss major steps in depth processing workflow that took such anisotropy into account: residual moveout estimation in azimuth sectors; separation of different effects causing apparent azimuthal anisotropy (see A–D above); iterative depth-velocity modelling with azimuthal anisotropy; and, subsequent MAZ anisotropic PSDM. The presented workflow solved problems with azimuthal anisotropy in our multi-azimuth dataset. Some of the lessons learned during this MAZ project are relevant to every standard narrow azimuth seismic survey recorded in complex geological settings.

Tomographic modeling of a cross‐borehole data set

Geophysics ◽  
1989 ◽  
Vol 54 (10) ◽  
pp. 1249-1257 ◽  
Author(s):  
Larry R. Lines ◽  
Edward D. LaFehr
Keyword(s):  
Wave Equation ◽  
Ray Tracing ◽  
Velocity Model ◽  
Velocity Estimation ◽  
P Wave ◽  
Seismic Survey ◽  
Equation Modeling ◽  
Data Set ◽  
True Solution ◽  
Velocity Models

In this paper we describe a methodology for estimating P‐wave velocities from a cross‐borehole seismic survey that uses straight‐ray tomography, ray tracing, and finite‐difference wave‐equation modeling to produce velocity models that fit the first‐break traveltimes. After a starting model is established by straight‐ray tomography, the velocity model is checked by ray tracing and wave‐equation modeling. Since the models for each procedure show consistent results and the modeled traveltimes closely match those traveltimes from the actual data, we felt our interpretation was confirmed. However, the fitting of cross‐well first break traveltimes is only a necessary validity check and is not sufficient to guarantee that the true solution has been found. Two wells were drilled through the areas that were anomalous on the derived tomogram and check‐shot velocity surveys were run. Due primarily to a lateral ambiguity in velocity estimation caused by too few near‐vertical raypaths, the check‐shot surveys did not agree with the tomogram velocities. However, subsequently the check‐shot traveltimes were used to place bounds on velocity in a constrained least‐squares procedure; the combined modeling of uphole and cross‐well rays produced an optimum velocity model which satisfies all available data.

Prestack migration velocity estimation using nonlinear methods

Geophysics ◽  
1996 ◽  
Vol 61 (1) ◽  
pp. 138-150 ◽  
Author(s):  
Michael Jervis ◽  
Mrinal K. Sen ◽  
Paul L. Stoffa
Keyword(s):  
Objective Function ◽  
Real Data ◽  
Velocity Model ◽  
Optimization Methods ◽  
Velocity Estimation ◽  
Model Parameters ◽  
Waveform Data ◽  
Nonlinear Methods ◽  
Depth Migration ◽  
Computationally Intensive

We describe here methods of estimating interval velocities based on two nonlinear optimization methods; very fast simulated annealing (VFSA) and a genetic algorithm (GA). The objective function is defined using prestack seismic data after depth migration. This inverse problem involves optimizing the lateral consistency of reflectors between adjacent migrated shot records. In effect, the normal moveout correction in velocity analysis is replaced by prestack depth migration. When the least‐squared difference between each pair of migrated shots is at a minimum, the true velocity model has been found. Our model is parameterized using cubic‐B splines distributed on a rectangular grid. The main advantages of using migrated data are that they do not require traveltime picking, knowledge of the source wavelet, and expensive computation of synthetic waveform data to assess the degree of data‐model fit. Nonlinear methods allow automated determination of the global minimum without relying on estimates of the gradient of the objective function, the starting model, or making assumptions about the nature of the objective function itself. For the velocity estimation problem, the VFSA converges 4 to 5 times faster than the GA for both a 2-D synthetic example and a structurally complex real data example from the Gulf of Mexico. Though computationally intensive, this problem requires few model parameters, and use of a fast traveltime code for Kirchhoff migration makes the algorithm tractable for real earth problems.

scholarly journals A New Extension of Thinning-Based Integer-Valued Autoregressive Models for Count Data

Entropy ◽  
2020 ◽  
Vol 23 (1) ◽  
pp. 62
Author(s):  
Zhengwei Liu ◽  
Fukang Zhu
Keyword(s):  
Likelihood Estimation ◽  
Real Data ◽  
Autoregressive Models ◽  
Superior Performance ◽  
Data Sets ◽  
Binomial Thinning ◽  
Free Case ◽  
Two Parameters ◽  
Conditional Maximum ◽  
Thinning Operator

The thinning operators play an important role in the analysis of integer-valued autoregressive models, and the most widely used is the binomial thinning. Inspired by the theory about extended Pascal triangles, a new thinning operator named extended binomial is introduced, which is a general case of the binomial thinning. Compared to the binomial thinning operator, the extended binomial thinning operator has two parameters and is more flexible in modeling. Based on the proposed operator, a new integer-valued autoregressive model is introduced, which can accurately and flexibly capture the dispersed features of counting time series. Two-step conditional least squares (CLS) estimation is investigated for the innovation-free case and the conditional maximum likelihood estimation is also discussed. We have also obtained the asymptotic property of the two-step CLS estimator. Finally, three overdispersed or underdispersed real data sets are considered to illustrate a superior performance of the proposed model.

scholarly journals Velocity Analysis Using Separated Diffractions for Lunar Penetrating Radar Obtained by Yutu-2 Rover

2021 ◽  
Vol 13 (7) ◽  
pp. 1387
Author(s):  
Chao Li ◽  
Jinhai Zhang
Keyword(s):  
Dielectric Permittivity ◽  
Lunar Regolith ◽  
Velocity Model ◽  
Velocity Estimation ◽  
Quality Data ◽  
High Quality Data ◽  
Shallow Subsurface ◽  
Subsurface Structures ◽  
Ground Penetrating ◽  
Permittivity Model

The high-frequency channel of lunar penetrating radar (LPR) onboard Yutu-2 rover successfully collected high quality data on the far side of the Moon, which provide a chance for us to detect the shallow subsurface structures and thickness of lunar regolith. However, traditional methods cannot obtain reliable dielectric permittivity model, especially in the presence of high mix between diffractions and reflections, which is essential for understanding and interpreting the composition of lunar subsurface materials. In this paper, we introduce an effective method to construct a reliable velocity model by separating diffractions from reflections and perform focusing analysis using separated diffractions. We first used the plane-wave destruction method to extract weak-energy diffractions interfered by strong reflections, and the LPR data are separated into two parts: diffractions and reflections. Then, we construct a macro-velocity model of lunar subsurface by focusing analysis on separated diffractions. Both the synthetic ground penetrating radar (GPR) and LPR data shows that the migration results of separated reflections have much clearer subsurface structures, compared with the migration results of un-separated data. Our results produce accurate velocity estimation, which is vital for high-precision migration; additionally, the accurate velocity estimation directly provides solid constraints on the dielectric permittivity at different depth.

scholarly journals The Censored Beta-Skew Alpha-Power Distribution

Symmetry ◽  
2021 ◽  
Vol 13 (7) ◽  
pp. 1114
Author(s):  
Guillermo Martínez-Flórez ◽  
Roger Tovar-Falón ◽  
María Martínez-Guerra
Keyword(s):  
Power Distribution ◽  
Information Matrix ◽  
Real Data ◽  
Likelihood Method ◽  
Data Sets ◽  
Alpha Power ◽  
Score Functions ◽  
New Family ◽  
Two Parameters ◽  
Family Of Distributions

This paper introduces a new family of distributions for modelling censored multimodal data. The model extends the widely known tobit model by introducing two parameters that control the shape and the asymmetry of the distribution. Basic properties of this new family of distributions are studied in detail and a model for censored positive data is also studied. The problem of estimating parameters is addressed by considering the maximum likelihood method. The score functions and the elements of the observed information matrix are given. Finally, three applications to real data sets are reported to illustrate the developed methodology.

scholarly journals Sound Velocity Estimation of Seabed Sediment Based on Parametric Array Sonar

2020 ◽  
Vol 2020 ◽  
pp. 1-6
Author(s):  
Jingxin Ma ◽  
Haisen Li ◽  
Jianjun Zhu ◽  
Baowei Chen
Keyword(s):  
Parameter Estimation ◽  
Acoustic Parameter ◽  
Velocity Estimation ◽  
Parameters Estimation ◽  
Real Field ◽  
Sound Waves ◽  
Sediment Thickness ◽  
Seafloor Topography ◽  
Seabed Sediment ◽  
Seabed Sediments

Backscattered sound waves of seabed sediments are important information carriers in seafloor detection and acoustic characteristic parameters inversion. Most of the existing methods for estimating geoacoustic parameters are based on multiangle seabed backscattered signal processing and suitable for flat seafloor conditions with uniform sediment thickness. This usually deviates from the real field conditions and affects the accuracy of parameter estimation. In this paper, the sound ray propagation theory is studied and analysed under the condition of sloping seabed and uneven sediment thickness. Based on the phased parameter array sonar system, a method of acoustic parameters estimation of the sediment under inclined seabed conditions is proposed. The simulation results show that the new method shows good adaptability to different inclination angles of the seabed and solves the problem of accuracy of acoustic parameter estimation of the inclined seabed sediments. The model will greatly reduce the seafloor topography requirements in the sediment acoustic parameter inversion, such as velocity, layer thickness, and acoustic impedance.

Migration velocity analysis from locally coherent events in 2‐D laterally heterogeneous media, Part I: Theoretical aspects

Geophysics ◽  
2002 ◽  
Vol 67 (4) ◽  
pp. 1202-1212 ◽  
Author(s):  
Hervé Chauris ◽  
Mark S. Noble ◽  
Gilles Lambaré ◽  
Pascal Podvin
Keyword(s):  
Cost Function ◽  
Velocity Model ◽  
Migration Velocity ◽  
Velocity Estimation ◽  
Velocity Analysis ◽  
Seismic Reflection Data ◽  
Velocity Models ◽  
Migration Velocity Analysis ◽  
Paraxial Ray ◽  
The Cost

We present a new method based on migration velocity analysis (MVA) to estimate 2‐D velocity models from seismic reflection data with no assumption on reflector geometry or the background velocity field. Classical approaches using picking on common image gathers (CIGs) must consider continuous events over the whole panel. This interpretive step may be difficult—particularly for applications on real data sets. We propose to overcome the limiting factor by considering locally coherent events. A locally coherent event can be defined whenever the imaged reflectivity locally shows lateral coherency at some location in the image cube. In the prestack depth‐migrated volume obtained for an a priori velocity model, locally coherent events are picked automatically, without interpretation, and are characterized by their positions and slopes (tangent to the event). Even a single locally coherent event has information on the unknown velocity model, carried by the value of the slope measured in the CIG. The velocity is estimated by minimizing these slopes. We first introduce the cost function and explain its physical meaning. The theoretical developments lead to two equivalent expressions of the cost function: one formulated in the depth‐migrated domain on locally coherent events in CIGs and the other in the time domain. We thus establish direct links between different methods devoted to velocity estimation: migration velocity analysis using locally coherent events and slope tomography. We finally explain how to compute the gradient of the cost function using paraxial ray tracing to update the velocity model. Our method provides smooth, inverted velocity models consistent with Kirchhoff‐type migration schemes and requires neither the introduction of interfaces nor the interpretation of continuous events. As for most automatic velocity analysis methods, careful preprocessing must be applied to remove coherent noise such as multiples.

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