Time vs Depth Migration Insensitive to v(z) model Sensitive to v(z) model Time migration uses best fit hyperbola Depth migration uses best guess moveout.

Slides:



Advertisements
Similar presentations
The Seismic Method Lecture 5 SLIDE 1
Advertisements

Lecture 5 3D Scalar Visualization Part One: Isosurfacing
The Topology of Graph Configuration Spaces David G.C. Handron Carnegie Mellon University
CS 253: Algorithms Chapter 22 Graphs Credit: Dr. George Bebis.
MCA 202: Discrete Mathematics Instructor Neelima Gupta
Making CMP’s From chapter 16 “Elements of 3D Seismology” by Chris Liner.
Warping for Trim Statics
Accommodation space, Coluvial wedge. Even in this image, throw is hard to interpret however, there is still geologic insight to be gained. Surface expression.
Multiple attenuation in the image space Paul Sava & Antoine Guitton Stanford University SEP.
Processing and Binning Overview From chapter 14 “Elements of 3D Seismology” by Chris Liner.
Processing: zero-offset gathers
Computational Challenges for Finding Big Oil by Seismic Inversion.
GG450 April 22, 2008 Seismic Processing.
I.1 Diffraction Stack Modeling I.1 Diffraction Stack Modeling 1. Forward modeling operator L 1. Forward modeling operator L d (x) = (x |x’) m(x’) dx’ ModelSpace.
Sensitivity kernels for finite-frequency signals: Applications in migration velocity updating and tomography Xiao-Bi Xie University of California at Santa.
Aerial View Eucalyi River, Peru Seismic View: 2 km Deep Meandering River.
CFP technology DELPHI consortium. slide 2 CFP technology Data t x z x TWT CFP method OWT z x Focusing Operator t x * CFP gather = t x z x OWT Stack.
First Arrival Traveltime and Waveform Inversion of Refraction Data Jianming Sheng and Gerard T. Schuster University of Utah October, 2002.
Wave-equation migration velocity analysis beyond the Born approximation Paul Sava* Stanford University Sergey Fomel UT Austin (UC.
Reverse Time Migration Reverse Time Migration. Outline Outline Finding a Rock Splash at Liberty Park Finding a Rock Splash at Liberty Park ZO Reverse.
1 Preliminary Test on a New Anti- aliasing Filter for Kirchhoff Migration Weiping Cao Sept. 18, 2009.
Advanced Seismic Imaging GG 6770 Variance Analysis of Seismic Refraction Tomography Data By Travis Crosby.
Wave-equation MVA by inversion of differential image perturbations Paul Sava & Biondo Biondi Stanford University SEP.
Wave-equation migration velocity analysis Paul Sava* Stanford University Biondo Biondi Stanford University Sergey Fomel UT Austin.
Loading of the data/conversion Demultiplexing Editing Geometry Amplitude correction Frequency filter Deconvolution Velocity analysis NMO/DMO-Correction.
Arbitrary Parameter Extraction, Stationary Phase Migration, and Tomographic Velocity Analysis Jing Chen University of Utah.
Analytical image perturbations for wave-equation migration velocity analysis Paul Sava & Biondo Biondi Stanford University.
G(m)=d mathematical model d data m model G operator d=G(m true )+  = d true +  Forward problem: find d given m Inverse problem (discrete parameter estimation):
Wave-equation migration velocity analysis Paul Sava* Stanford University Biondo Biondi Stanford University.
Multisource Least-squares Reverse Time Migration Wei Dai.
Body Waves and Ray Theory
Seeing the Invisible with Seismic Interferometry: Datuming and Migration Gerard T. Schuster, Jianhua Yu, Xiao Xiang and Jianming Sheng University of Utah.
Coherence-weighted Wavepath Migration for Teleseismic Data Coherence-weighted Wavepath Migration for Teleseismic Data J. Sheng, G. T. Schuster, K. L. Pankow,
Time vs Depth Migration Insensitive to v(z) model Sensitive to v(z) model Time migration uses best fit hyperbola Depth migration uses best guess moveout.
Migration In a Nutshell Migration In a Nutshell Migration In a Nutshell D.S. Macpherson.
Prestack Migration Intuitive Least Squares Migration Green’s Theorem.
EXPLORATION GEOPHYSICS. EARTH MODEL NORMAL-INCIDENCE REFLECTION AND TRANSMISSION COEFFICIENTS WHERE:  1 = DENSITY OF LAYER 1 V 1 = VELOCITY OF LAYER.
The Experimental Comparison of Conventional and Differential Semblance on several data sets Jintan Li Rice University.
Introduction to Seismology
Migration Velocity Analysis 01. Outline  Motivation Estimate a more accurate velocity model for migration Tomographic migration velocity analysis 02.
Wave-equation migration velocity analysis Biondo Biondi Stanford Exploration Project Stanford University Paul Sava.
T 2 = T X 2 /V 2. It is a hyperbola with apex at X = 0 and T 0 = 2H/V. – –V and H are the layer velocity and thickness. T 2 -X 2 plot is a straight.
Introduction to Seismic Reflection Imaging References: J.M. Reynolds, An Introduction to Applied and Environmental Geophysics, John Wiley & Sons,
Super-virtual Interferometric Diffractions as Guide Stars Wei Dai 1, Tong Fei 2, Yi Luo 2 and Gerard T. Schuster 1 1 KAUST 2 Saudi Aramco Feb 9, 2012.
Wave-Equation Waveform Inversion for Crosswell Data M. Zhou and Yue Wang Geology and Geophysics Department University of Utah.
Migration Velocity Analysis of Multi-source Data Xin Wang January 7,
Tutorial on Green’s Functions, Forward Modeling, Reciprocity Theorems, and Interferometry..
Geology 5660/6660 Applied Geophysics Last time: The Refraction Method Cont’d Multiple Horizontal Layers: Using Snell’s law, generalizes simply to: Dipping.
 = 0.5  j  r j (  kk’ (  m kk’ /  z) 2  m ii’ =  j  r j  r j /  m ii’ + (  kk’  m kk’ /  m ii’  m kk’ /  z) (1) m 11 m 12.
Geology 5660/6660 Applied Geophysics 12 Feb 2016
Lee M. Liberty Research Professor Boise State University.
Resolution. 0 km 7 km 0 km 3 km m = L d T r = [L L] m 0 km 7 km T.
Reverse Time Migration
LSM Theory: Overdetermined vs Underdetermined
Zero-Offset Data d = L o ò r ) ( g = d dr r ) ( g = d
R. G. Pratt1, L. Sirgue2, B. Hornby2, J. Wolfe3
Primary-Only Imaging Condition And Interferometric Migration
SEISMIC DATA GATHERING.
Vladimir Grechka Shell International E&P
Steepest Descent Optimization
Wave Equation Traveltime Inversion
Migration Intuitive Least Squares Migration Green’s Theorem.
Multiple attenuation in the image space
I.1 Diffraction Stack Modeling
Making CMP’s From chapter 16 “Elements of 3D Seismology” by Chris Liner.
I.1 Diffraction Stack Modeling
Processing and Binning Overview
EXPLORATION GEOPHYSICS
Inverse Crimes d=Lm m=L-1 d Red Sea Synthetics
Packing of uniform spheres
Presentation transcript:

Time vs Depth Migration Insensitive to v(z) model Sensitive to v(z) model Time migration uses best fit hyperbola Depth migration uses best guess moveout curve Incoherent summation if guess is wrong Coherent summation Time Migration Depth Migration CMP Gather time time

Depth Migration -> Time Migration We know 2z/c=T so m(x,z) = g d (g, 4[(x-g)/c] + (2z/c) ) 22 z 2-way vertical traveltime d (g, 4[(x-g)/c] + T ) M(x,T) = g 22 Depth Migration: Maps data into function(x,z) Time Migration: Maps data into function(x,T) m(x,z(T)) = g d (g, 4[(x-g)/c] + T ) 22

Time Migration for c(T) d (g, 4[(x-g)/c(T)] + T ) M(x,T) = g 2 2 Time Migration: Maps data into function(x,T) v1 v2 v3 v4 v5 v6 Tc(T) More generally, c(T) is a function of T!

MATLAB ZO Depth Migration d (g, ) xgxgxgxg m(x,z) = g for ixtrace=1:ntrace; for ixtrace=1:ntrace; for ixs=istart:iend; for ixs=istart:iend; for izs=1:nz; for izs=1:nz; r = sqrt(4*(ixtrace*dx-ixs*dx )^2+(2*izs*dx)^2); r = sqrt(4*(ixtrace*dx-ixs*dx )^2+(2*izs*dx)^2); time = 1 + round( r/c/dt ); time = 1 + round( r/c/dt ); mig(ixs,izs) = mig(ixs,izs)/r + data(ixtrace,time); mig(ixs,izs) = mig(ixs,izs)/r + data(ixtrace,time); end; end; end; end; Traveltime Loop over x in model Loop over z in model

MATLAB ZO Time Migration for ixtrace=1:ntrace; for ixtrace=1:ntrace; for ixs=istart:iend; for ixs=istart:iend; for iT=1:nT; for iT=1:nT; time = sqrt(4*([ixtrace*dx-ixs*dx]/c(iT))^2+(iT*dt)^2); time = sqrt(4*([ixtrace*dx-ixs*dx]/c(iT))^2+(iT*dt)^2); time = 1 + round( time/dt ); time = 1 + round( time/dt ); mig(ixs,iT) = mig(ixs,iT)/r + data(ixtrace,time); mig(ixs,iT) = mig(ixs,iT)/r + data(ixtrace,time); end; end; end; end; Traveltime Loop over x in model Loop over iT in model M(x,T) = g 22 d (g, 4[(x-g)/c(T)] + T ) Note: c(iT) or c(ixtrace,iT)

Time Migration vs Depth Migration Insensitive to c(z) model Time migration uses best fit hyperbola d (g, 4[(x-g)/c] + T ) M(x,T) = 2 2

Time Migration vs Depth Migration Insensitive to v(z) model Time migration uses best fit hyperbola d (g, 4[(x-g)/c] + T ) M(x,T) = 2 2

Time Migration vs Depth Migration Insensitive to v(z) model Time migration uses best fit hyperbola d (g, 4[(x-g)/c] + T ) M(x,T) = 2 2

Time Migration vs Depth Migration Insensitive to v(z) model Time migration uses best fit hyperbola d (g, 4[(x-g)/c] + T ) M(x,T) = 2 2

Time Migration vs Depth Migration Insensitive to v(z) model Sensitive to v(z) model Time migration uses best fit hyperbola Depth migration uses best guess moveout curve d (g, 4[(x-g)/c] + T ) M(x,T) = 2 2 d (g, t ) M(x,z) = gxgxgxgx Incoherent summation if guess is wrong Coherent summation Cheap: no ray tracing Expensive: ray tracing Uniform wavelet thickness Stretched wavelet thickness =c/f1/f Best focusing if v(x,z) correct Best focusing if v(x,z) really wrong Good focusing if v(x,z) smooth

Depth Migration in Deep GOM is only Way to Go if V(x,y,z) Correct Therefore, spend time to get v(x,y,z) Correct: Tomography, MVA, Waveform Inversion

Velocity Analysis CMP Time x T c d (g, 4[(x-g)/c] + T ) M(x,T) = 2 2 C(T)