Optimization and sensitivity analysis of seismic depth migrations from Hibernia Field

Geophysics ◽  
1998 ◽  
Vol 63 (6) ◽  
pp. 2054-2062 ◽  
Author(s):  
Irene Kelly ◽  
Larry R. Lines
Keyword(s):  
Sensitivity Analysis ◽  
Least Squares ◽  
Real Data ◽  
Optimization Method ◽  
Velocity Estimation ◽  
Inversion Method ◽  
Depth Migration ◽  
Velocity Models ◽  
Sensitivity Analysis Method ◽  
Seismic Reflectors

Accurate imaging of seismic reflectors with depth migration requires accurate velocity models. In frontier areas with few well constraints, velocity estimation generally involves the use of methods such as normal moveout analysis, seismic traveltime tomography, or iterative prestack depth migration. These techniques can be effective, but may also be expensive or time‐consuming. In situations where we have information on formation tops from a series of wells which intersect seismic reflectors, we use a least‐squares optimization method to estimate velocity models. This method produces velocity models that optimize depth migrations in terms of well constraints by using least‐squares inversion to match the depth migration images to formation tops. The well log information is used to optimize poststack migration, thereby eliminating some of the time and expense of velocity analysis. In addition to applying an inversion method which optimizes depth migration in terms of formation tops, we can use a sensitivity analysis method of “most‐squares inversion” to explore a range of velocity models which provide mathematically acceptable solutions. This sensitivity analysis quantifies the expected result that our velocity estimates are generally less reliable for thin beds than for thick beds. The proposed optimization method is shown to be successful on synthetic and real data cases from the Hibernia Field of offshore Newfoundland.

Time Integration Incorporated Sensitivity Analysis With Generalized-α Method for Multibody Dynamics Systems

2011 ◽  
Author(s):  
Guang Dong ◽  
Zheng-Dong Ma ◽  
Gregory Hulbert ◽  
Noboru Kikuchi
Keyword(s):  
Sensitivity Analysis ◽  
Topology Optimization ◽  
Dynamic Loading ◽  
Multibody Dynamics ◽  
Equations Of Motion ◽  
Time Integration ◽  
Optimization Method ◽  
Sensitivity Analysis Method ◽  
System Equations ◽  
Consecutive Time

The topology optimization method is extended for the optimization of geometrically nonlinear, time-dependent multibody dynamics systems undergoing nonlinear responses. In particular, this paper focuses on sensitivity analysis methods for topology optimization of general multibody dynamics systems, which include large displacements and rotations and dynamic loading. The generalized-α method is employed to solve the multibody dynamics system equations of motion. The developed time integration incorporated sensitivity analysis method is based on a linear approximation of two consecutive time steps, such that the generalized-α method is only applied once in the time integration of the equations of motion. This approach significantly reduces the computational costs associated with sensitivity analysis. To show the effectiveness of the developed procedures, topology optimization of a ground structure embedded in a planar multibody dynamics system under dynamic loading is presented.

scholarly journals Improved Land Evapotranspiration Simulation of the Community Land Model Using a Surrogate-Based Automatic Parameter Optimization Method

Water ◽  
2020 ◽  
Vol 12 (4) ◽  
pp. 943
Author(s):  
Chong Zhang ◽  
Zhenhua Di ◽  
Qingyun Duan ◽  
Zhenghui Xie ◽  
Wei Gong
Keyword(s):  
Sensitivity Analysis ◽  
Parameter Optimization ◽  
Land Surface ◽  
High Efficiency ◽  
Optimization Method ◽  
The Tibetan Plateau ◽  
Optimal Parameters ◽  
Community Land Model ◽  
Optimization Framework ◽  
Sensitivity Analysis Method

Land surface evapotranspiration (ET) is important in land-atmosphere interactions of water and energy cycles. However, regional ET simulation has a great uncertainty. In this study, a highly-efficient parameter optimization framework was applied to improve ET simulations of the Community Land Model version 4.0 (CLM4) in China. The CLM4 is a model at land scale, and therefore, the monthly ET observation was used to evaluate the simulation results. The optimization framework consisted of a parameter sensitivity analysis (also called parameter screening) by the multivariate adaptive regression spline (MARS) method and sensitivity parameter optimization by the adaptive surrogate modeling-based optimization (ASMO) method. The results show that seven sensitive parameters were screened from 38 adjustable parameters in CLM4 using the MARS sensitivity analysis method. Then, using only 133 model runs, the optimal values of the seven parameters were found by the ASMO method, demonstrating the high efficiency of the method. For the optimal parameters, the ET simulations of CLM4 were improved by 7.27%. The most significant improvement occurred in the Tibetan Plateau region. Additional ET simulations from the validation years were also improved by 5.34%, demonstrating the robustness of the optimal parameters. Overall, the ASMO method was found to be efficient for conducting parameter optimization for CLM4, and the optimal parameters effectively improved ET simulation of CLM4 in China.

Practical aspects and applications of 2D stereotomography

Geophysics ◽  
2003 ◽  
Vol 68 (3) ◽  
pp. 1008-1021 ◽  
Author(s):  
Frederic Billette ◽  
Soazig Le Bégat ◽  
Pascal Podvin ◽  
Gilles Lambaré
Keyword(s):  
Estimation Method ◽  
Synthetic Data ◽  
Velocity Model ◽  
Velocity Estimation ◽  
Common Source ◽  
Depth Migration ◽  
Reflection Seismic ◽  
Velocity Models ◽  
Automatic Picking ◽  
Iterative Inversion

Stereotomography is a new velocity estimation method. This tomographic approach aims at retrieving subsurface velocities from prestack seismic data. In addition to traveltimes, the slope of locally coherent events are picked simultaneously in common offset, common source, common receiver, and common midpoint gathers. As the picking is realized on locally coherent events, they do not need to be interpreted in terms of reflection on given interfaces, but may represent diffractions or reflections from anywhere in the image. In the high‐frequency approximation, each one of these events corresponds to a ray trajectory in the subsurface. Stereotomography consists of picking and analyzing these events to update both the associated ray paths and velocity model. In this paper, we describe the implementation of two critical features needed to put stereotomography into practice: an automatic picking tool and a robust multiscale iterative inversion technique. Applications to 2D reflection seismic are presented on synthetic data and on a 2D line extracted from a 3D towed streamer survey shot in West Africa for TotalFinaElf. The examples demonstrate that the method requires only minor human intervention and rapidly converges to a geologically plausible velocity model in these two very different and complex velocity regimes. The quality of the velocity models is verified by prestack depth migration results.

scholarly journals A Novel Multiobjective Optimization Method Based on Sensitivity Analysis

2016 ◽  
Vol 2016 ◽  
pp. 1-12
Author(s):  
Tiane Li ◽  
Xiaoying Sun ◽  
Zhengzheng Lu ◽  
Yue Wu
Keyword(s):  
Sensitivity Analysis ◽  
Multiobjective Optimization ◽  
Optimization Problems ◽  
Mathematical Problem ◽  
Rank Correlation ◽  
Optimization Method ◽  
Computational Time ◽  
Truss Topology Optimization ◽  
Pareto Optimal Set ◽  
Sensitivity Analysis Method

For multiobjective optimization problems, different optimization variables have different influences on objectives, which implies that attention should be paid to the variables according to their sensitivity. However, previous optimization studies have not considered the variables sensitivity or conducted sensitivity analysis independent of optimization. In this paper, an integrated algorithm is proposed, which combines the optimization method SPEA (Strength Pareto Evolutionary Algorithm) with the sensitivity analysis method SRCC (Spearman Rank Correlation Coefficient). In the proposed algorithm, the optimization variables are worked as samples of sensitivity analysis, and the consequent sensitivity result is used to guide the optimization process by changing the evolutionary parameters. Three cases including a mathematical problem, an airship envelope optimization, and a truss topology optimization are used to demonstrate the computational efficiency of the integrated algorithm. The results showed that this algorithm is able to simultaneously achieve parameter sensitivity and a well-distributed Pareto optimal set, without increasing the computational time greatly in comparison with the SPEA method.

scholarly journals Structural Optimization of Variable Section Slender Manipulator Based on Sensitivity Analysis Method

2011 ◽  
Vol 2-3 ◽  
pp. 291-295
Author(s):  
Zhong Luo ◽  
Le Liang ◽  
Yan Yan Chen ◽  
Fei Wang
Keyword(s):  
Sensitivity Analysis ◽  
Structural Optimization ◽  
Optimization Method ◽  
Design Sensitivity ◽  
Design Sensitivity Analysis ◽  
Analysis Method ◽  
Design Variables ◽  
Variable Section ◽  
Sensitivity Analysis Method ◽  
In The Beginning

A parameter optimization method based on sensitivity analysis is presented for the structural optimization of variable section slender manipulator. Structure mechanism of a polishing robot is introduced firstly, and its stiffness model is established. Then, a design sensitivity analysis method and a sequential liner programming (SLP) strategy are proposed. In the beginning of the optimization, the design sensitivity analysis method can be used to select the sensitive design variables which can make the optimized results more efficient and accurate. And then, it can be used to improve the convergence during the process of the optimization. The design sensitivities are calculated using the finite difference method. The search for the final optimal structure is performed using the SLP method. Simulation results show that the structure optimization method is effective to enhance the stiffness of the manipulator, no matter when the manipulator suffers constant force or variable force. This work lays a theoretical foundation for the structural optimization for such manipulators.

scholarly journals Topology Optimization for Minimizing the Resonant Response of Plates with Constrained Layer Damping Treatment

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Zhanpeng Fang ◽  
Ling Zheng
Keyword(s):  
Sensitivity Analysis ◽  
Topology Optimization ◽  
Damping Ratio ◽  
Optimization Method ◽  
Constrained Layer Damping ◽  
Resonant Response ◽  
Optimal Layout ◽  
Analysis Method ◽  
Topology Optimization Problem ◽  
Sensitivity Analysis Method

A topology optimization method is proposed to minimize the resonant response of plates with constrained layer damping (CLD) treatment under specified broadband harmonic excitations. The topology optimization problem is formulated and the square of displacement resonant response in frequency domain at the specified point is considered as the objective function. Two sensitivity analysis methods are investigated and discussed. The derivative of modal damp ratio is not considered in the conventional sensitivity analysis method. An improved sensitivity analysis method considering the derivative of modal damp ratio is developed to improve the computational accuracy of the sensitivity. The evolutionary structural optimization (ESO) method is used to search the optimal layout of CLD material on plates. Numerical examples and experimental results show that the optimal layout of CLD treatment on the plate from the proposed topology optimization using the conventional sensitivity analysis or the improved sensitivity analysis can reduce the displacement resonant response. However, the optimization method using the improved sensitivity analysis can produce a higher modal damping ratio than that using the conventional sensitivity analysis and develop a smaller displacement resonant response.

scholarly journals Structural Optimization of Slender Robot Arm Based on Sensitivity Analysis

2012 ◽  
Vol 2012 ◽  
pp. 1-17 ◽  
Author(s):  
Zhong Luo ◽  
Xueyan Zhao ◽  
Le Liang ◽  
Fei Wang
Keyword(s):  
Sensitivity Analysis ◽  
Structural Optimization ◽  
Optimization Method ◽  
Design Sensitivity ◽  
Robot Arm ◽  
Analysis Method ◽  
Design Variables ◽  
Stiffness Model ◽  
Variable Section ◽  
Sensitivity Analysis Method

An effective structural optimization method based on a sensitivity analysis is proposed to optimize the variable section of a slender robot arm. The structure mechanism and the operating principle of a polishing robot are introduced firstly, and its stiffness model is established. Then, a design of sensitivity analysis method and a sequential linear programming (SLP) strategy are developed. At the beginning of the optimization, the design sensitivity analysis method is applied to select the sensitive design variables which can make the optimized results more efficient and accurate. In addition, it can also be used to determine the scale of moving step which will improve the convergency during the optimization process. The design sensitivities are calculated using the finite difference method. The search for the final optimal structure is performed using the SLP method. Simulation results show that the proposed structure optimization method is effective in enhancing the stiffness of the robot arm regardless of the robot arm suffering either a constant force or variable forces.

Removing fault shadow distortions from seismic images using depth-velocity modelling and pre-stack depth migration

2012 ◽  
Vol 52 (2) ◽  
pp. 700
Author(s):  
Sergey Birdus ◽  
Alexey Artyomov
Keyword(s):  
Real Data ◽  
Velocity Model ◽  
Velocity Inversion ◽  
Depth Migration ◽  
Velocity Models ◽  
Depth Processing ◽  
Different Types ◽  
Successful Removal ◽  
Velocity Anomalies ◽  
Additional Image

In many areas, fault shadows manifest a serious challenge to seismic imaging. The major part of this problem is caused by different types of velocity variations caused by faults. Pre-stack depth migration with sufficiently accurate velocity model successfully resolves this problem and the high resolution tomographic depth-velocity modelling is the most important component of the solution. During depth processing on a number of real 3D seismic datasets with fault shadows from Australia and other regions, the following were noticed: The appearance of the image distortions below the faults and the convergence speed of the tomographic velocity inversion depend on the acquisition direction. Sometimes, tomographic modelling produces depth-velocity models that closely follow geology, but the models contain non-geological looking anomalies in other areas. In both cases, the depth migration delivers distortion-free images. If anisotropy is present in faulted areas, it creates additional image distortions and can require extra input data and processing efforts. To examine these effects and optimise depth-processing workflow, several 3D synthetic seismic datasets were created for different types of velocity anomalies associated with the faults in isotropic and anisotropic media and different acquisition directions. On synthetic and real data from Australia, different types of fault shadows are illustrated; how they can be solved depending on the acquisition direction are also shown. Some types of the fault shadows are shown to require multi-azimuth illumination to guarantee their successful removal.

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.

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