Midyear Overview of Year 2001 UTAM Results T. Crosby, Y. Liu, G. Schuster, D. Sheley, J. Sheng, H. Sun, J. Yu and M. Zhou J. Yu and M. Zhou

2001 Sponsors AramcoAramco Amerada HessAmerada Hess BP-AMOCOBP-AMOCO ChevronChevron ConocoConoco Japan Nat. Oil Co.Japan Nat. Oil Co. Inst. Mex. Pet.Inst. Mex. Pet. INCOINCO MarathonMarathon PhillipsPhillips SisimageSisimage TexacoTexaco VeritasVeritas

Salient 2001 Research Achievements 1. Wave-Beam Migration

Expense Accuracy Full-Wave Ray-BeamKirchhoff Phase-Shift Migration Accuracy vs $$$ Wave-Beam No Approx. MultiplesAnti-aliasing

SR ImagePoint Fresnel Zone Smear Reflection along Wavepath Slant Stack Smear Reflection along Wavepath

Standard FD Wavefront FD km km

Cost Ratio of Standard /Wavefront # Gridpts along side Cost Ratio

Prestack Migration Image Model km km km 1.5 km/s 2.2 km/s 1.8 km/s

Depth (kft) 0 3 Distance (kft) 0 5 Eikonal Traveltime Field Depth (kft) 0 3 Distance (kft) 0 5 Wave-Equation Traveltime Field

Depth (km) 0 3 Distance (km) 0 5 Kirchhoff Wave Equation Traveltimes Model Depth (kft) 5 11 Distance (km)

Wavefront Reverse Time Migration Open Questions Open Questions 1. More Storage 2. Resorting Overhead 3. Large scale tests? 1. Order Mag. Cheaper than 3-D RT 2. Fewer Artifacts 3. Optimal Accuracy

Salient 2001 Research Achievements 1. Wave-Beam Migration 2. Multiple Removal POIC

Multiple Removal by Multiple Removal by Primary-Only Imaging Condition Hongchuan Sun

Forward Modeling Distance Depth S R PrimaryMultipleSR Distance Depth S RR S

Migration with POIC Distance Depth S RSR P The rays intersect intersect at point P, and the traveltime  SP +  RP =  obs

Multiple Removal The rays never intersect; never intersect; or the traveltime  SP +  RP =  obs or the traveltime  SP +  RP =  obs Distance Depth S RR S P

Distance (kft) Depth (kft) Model KM Image POIC Image SEG/EAGE 2-D Salt Data

Depth (kft) 5 11 Distance (kft) 1551 KM ImagePOIC Image Model Depth (kft) 5 11 Distance (kft) Offsets Used: 0 ~ ft

Distance (kft) Depth (kft) Distance (kft) KM ImageModelPOIC Image Offsets Used: 0 ~ ft

Distance (kft) Depth (kft) Distance (kft) KM ImageModelPOIC Image Offsets Used: 1600 ~ ft

Conclusions POIC effectively remove surface POIC effectively remove surface related multiples related multiples POIC performs much better when POIC performs much better when near-offset data are not used near-offset data are not used POIC should be applicable to POIC should be applicable to interbed multiple removal interbed multiple removal

Salient 2001 Research Achievements 1. Wave-Beam Migration 2. Multiple Removal POIC 3. Sparse Fequency Migration

Fourier Finite Difference Migration with Sparse Frequencies Fourier Finite Difference Migration with Sparse Frequencies Jianhua Yu Department of Geology & Geophysics University of Utah

Objective Improve computational efficiency Improve computational efficiency of wave-equation extrapolation of wave-equation extrapolation Hi-quality Image Hi-quality Image

Frequency Domain Migration 70 Fourier Finite Difference Method 1/4 Sparser Frequency Domain Sampling o

Comparison of 3D Impulse Response X (km) 04 Depth (km) FD algorithm Main energy wider angle FFD Depth (km) 0 2.4

2D Impulse Response X (km) 04 Depth (km) Standard wider angle FFD X (km) 04 Main energy wider angle FFD (Velocity contrast, i.e., V/Vmin = 3.0)

Comparison of FFD and Main Energy FFD Migration X (km) 04 Depth (km) FFD algorithm Main energy FFD (computational time saving about 38 %) Depth (km) 0 2.4

3D SEG/EAGE Zero Offset Imaging Result X (km) 04 Depth (km) Y (km) X (km) Y (km)

Strengths: Efficient forward extrapolation Wider angle FFD operator Less numerical anisotropy in 3D by applying high order implicit FD algorithm Weaknesses: Coding Complexity Fewer Frequencies Reduced Quality

Salient 2001 Research Achievements 1. Wave-Beam Migration 2. Multiple Removal POIC 3. Sparse Fequency Migration 4. AVO Migration Decon

Prestack Migration Decon for AVO Analysis Jianhua Yu Department of Geology & Geophysics University of Utah

Solution: Deconvolve the point scatterer response from the migrated image T r = ( L L ) m Reflectivity Migrated Section Section Reason: m = L d TMigratedSectionData but d = L r L rL rL rL r Migration Section = Blured Image of r

Objective of PMD AVO Suppress unwanted interference Suppress unwanted interference Increase estimation accuracy of AVO Increase estimation accuracy of AVO parameters parameters Enhance resolution of AVO sections Enhance resolution of AVO sections

Zoom View of AVO parameter Section Before and After PMD X(km) Time (s) Before PMD Time (s) After PMD X(km)1.02.0

Migration CRG Before and After PMD Trace Trace Time (s) Before PMD After PMD

Comparison of Amplitude & Angle Estimation Before and After PMD 2rd layer Amplitude 1 0 1st layer 3rd layer +: Before PMD *: After PMD Solid line: Theoretical value Angle

Summary & Future MD reduces artifactsMD reduces artifacts MD improves resolution & AVOMD improves resolution & AVO MD field data case by Feb.MD field data case by Feb.

Salient 2001 Research Achievements 1. Wave-Beam Migration 2. Multiple Removal POIC 3. Sparse Fequency Migration 4. AVO Migration Decon 5. Joint Autocorrelation Imaging

Joint Imaging Using Both Primary and Multiple for IVSP Data Jianhua Yu Department of Geology & Geophysics University of Utah

Problems for Deviated and Horizontal well No Source Wavelet & Initiation Time No Source Wavelet & Initiation Time Not Easy to Get Pilot Signal in Not Easy to Get Pilot Signal in Hard to Separate Primary and Ghost Hard to Separate Primary and Ghost Static Shift at Source and Receiver Static Shift at Source and Receiver

Auto. Imaging using Primary and Ghost

Geological Model 0 Depth (m) 3 40 X (m) V1 V2 V4 V3 V5 V6

Shot Gather and Autocorrelogram Time (s) Time (s) Traces

Time (s) X (km) Standard Migration X (km) Joint Migration Eliminate Interferences using Joint Imaging in Time Domain

Eliminate Interferences using Joint Imaging in Depth Domain Depth (km) X (km) Conventional Imaging X (km) Joint Imaging

Kirchhoff and Auto. Migration with Statics Error at Source and Receiver Depth (km) X (km) Kirchhoff joint migrationg X (km) Auto. joint migrationg

SUMMARY Works for deviated and horizontal well Eliminating static shift errors Avoiding separating primary and ghost waves for horizontal well data Joint Migration method: Don’t require pilot signal & wavelet initial time

Salient 2001 Research Achievements 1. Wave-Beam Migration 2. Multiple Removal POIC 3. Sparse Fequency Migration 4. AVO Migration Decon 5. Joint Autocorrelation Imaging 6. Xwell Statics & Tomography

INCO Project Report M. Zhou Geology and Geophysics Department University of Utah

Objective Invert velocity & geometry jointly

Normalized Traveltime Residuals vs. Velocity & Geometry Changes 500 m V=5.0km/sec Velocity (km/sec) Horizontal shift (m) Vertical Shift (m) Rotation (degree)

Problems 1) Geometry is coupled with velocity 2) Joint inversion is ill-posed

a) Synthetic Model b) Standard Inversion with 10 m shot shift c) Joint Inversion for the shot shift ( all shots have the same shift ) d) Joint Inversion + a priori information for individual shot locations Depth (m) Offset (m) Km/s Km/s Geometry Error: synthetic example I

a) Synthetic Model c) Standard Inversion with +10 m shot shifts Depth (m) Offset (m) Geometry Error: synthetic example II Km/s Km/s b) Standard Inversion without shot shift d) Joint Inversion for the shot shift

a) Synthetic Model c) Joint Inversion + a priori information for the shot shift d) Joint Inversion + a priori information for individual shot locations Depth (m) Offset (m) Geometry Error: synthetic example II Km/s Km/s b) Standard Inversion without shot shift

Conclusions works for simple model works for simple model needs additional information needs additional information Joint inversion