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- 1. From Imaging to Inversion Ian F. Jones SEG 2012 Honorary Lecture
- 2. Acknowledgements Society of Exploration Geophysicists Shell Sponsorship ION GX Technology
- 3. SEG Membership SEG Digital Library - full text articles Technical Journals in Print and Online Networking Opportunities Receive Membership Discounts on: Continuing Education Courses Publications (35% off list price) Workshops and MeetingsSEG materials are available today!Join Online http://seg.org/join
- 4. Student Opportunities Student Chapters available Student Chapter Book Program SEG/Chevron Student Leadership Symposium Challenge Bowl Student Membership Resources Scholarships SEG/ExxonMobil Student Education Program Annual Meeting Travel Grants Student Expos the Anomaly newsletter More information please visit: http://seg.org/students
- 5. From Imaging to Inversion Ian F. Jones SEG 2012 Honorary Lecture
- 6. But before I start…
- 7. But before I start…A big thanks to Judy Wall at the SEG for her sterling work organizing my schedule !
- 8. Talk OutlineTo a large extent, this presentation isspeculative, in that I’m looking at what ‘mightcome next’ moving beyond the current industrialpractise of:- data pre-conditioning (multiple suppression),- velocity model building,- migrating data and then- analysing amplitude information….
- 9. Talk Outline• Hydrocarbon exploration• Subsurface Imaging• Waves versus rays• Velocity model building• Migration• Attribute estimation• Full waveform inversion
- 10. What is itthat hydrocarbon explorationgeoscientists set out to do …
- 11. Find oil and gas !
- 12. But how ?
- 13. Drill here ???
- 14. … or here ???
- 15. How do we decide where to drill?
- 16. How do we decide where to drill?… we use sound waves reflecting of the rocklayers to make pictures (similar to ultrasoundmedical imaging) and then analyse the amplitudebehaviour of the data to infer what types of rocksand fluids are present
- 17. The process currently involves several keystages:1) Removal of noise and undesired signal2) Velocity model building3) Migration4) Attribute estimation
- 18. The process currently involves several keystages:1) Removal of noise and undesired signal2) Velocity model building3) Migration4) Attribute estimation
- 19. Attribute estimationOnce we have estimated the speed of sound(velocity) in the different rock layers, and thenformed an image from the recorded data(‘migration’), we can analyse the amplitudes ofthe reflections to estimate rock properties(which helps us distinguish between oil, gas,water, etc)
- 20. The geophysical problem We need to relocate recordedV1(x,y,z) energy to its ‘true’ position using an appropriate approximate solution to the visco-elasticV2(x,y,z) two-way wave equationetc target location (and what is ‘appropriate’, depends on our objectives)
- 21. What do these images ofthe subsurface look like?
- 22. Southern North Sea exampleImage dimensions are typically several hundred squarekilometres in area, extending to several kilometres depthMigrated image Sea bed 30km chalk 30km 1600m/s 1800m/s 2000m/s 3000m/s 3500m/s 3.5 km anhydriteGas-bearing layers salt Sound speed in the rocks
- 23. Near-surface buried riverchannel, which distorts thedeeper image (unlesscorrectly dealt with)
- 24. How do we describe the way in which sound travels through the earth?
- 25. Waves versus Rays
- 26. Waves versus RaysThe theoretical description of wave phenomenafalls into two categories:Ray-basedandWave- (diffraction or scattering) based- Both migration and model update depend onone or other of these paradigms
- 27. A propagating wavefront…we can characterise its direction ofmotion, and speed, with a successionof normal vectors, constituting ‘rays’Time = t Time = t + 25ms
- 28. A propagating wavefront…we can characterise its direction ofmotion, and speed, with a successionof normal vectors, constituting ‘rays’Time = t Time = t + 25ms
- 29. A propagating wavefront…we can characterise its direction ofmotion, and speed, with a successionof normal vectors, constituting ‘rays’Time = t Time = t + 25ms
- 30. A propagating wavefront…we can characterise its direction ofmotion, and speed, with a successionof normal vectors, constituting ‘rays’Time = t Time = t + 25ms
- 31. A propagating wavefront…we can characterise its direction ofmotion, and speed, with a successionof normal vectors, constituting ‘rays’Time = t Time = t + 25ms
- 32. A propagating wavefront…we can characterise its direction ofmotion, and speed, with a successionof normal vectors, constituting ‘rays’Time = t Time = t + 25ms
- 33. Snell’s law at a flat interface θi Sinθi = Sinθr vi vi vr vr θr θr = Sin-1( vr Sinθi ) vi
- 34. The high frequency approximation Seismic wavelength much smaller than the anomaly we are trying to resolve Velocity anomaly The propagating wavefront can adequately be described by ray-pathsSnell’s law adequately describes the wave propagation… ray-based methods (Kirchhoff, beam, …) are OK
- 35. The high frequency approximation Seismic wavelength larger or similar to the anomaly we are trying to resolve Small scale-length velocity anomaly The velocity feature behaves more like a scatterer than a simple refracting surface element Trying to describe the propagation behaviour as ‘rays’ obeying Snell’s law, is no longer appropriateRay-based methods (Kirchhoff, beam, …) using the ‘highfrequency approximation’ begin to fail
- 36. A propagating wavefront…Time = t Time = t + 25ms Time = t + 50msThe elements of some velocity features behave more likepoint scatterers producing secondary wavefronts
- 37. Velocity Model Building
- 38. Common midpointsource receiver CMP v1 Vrms1 v2 Vrms2v3 Vrms3 v4 Vrms4
- 39. CMP Common midpoint gather CMP t1 t2 t3 t4 t5For a CMP gather, we have manyarrival time measurements for agiven subsurface reflectorelement
- 40. CMP Common midpoint gather CMP t1 t2 t3 t4 t5For a CMP gather, we have manyarrival time measurements for agiven subsurface reflectorelement This curvature is related to the velocity
- 41. To estimate velocity for flat layers….
- 42. Conventional velocity analysis….. 0 Km 53.8S4.7 Input CMP data
- 43. Conventional velocity analysis….. 0 Km 53.8 ΣS4.7 Input CMP data
- 44. Conventional velocity analysis….. 0 Km 5 Km 5 1.5 2.5 3.5 Km/s3.8S4.7 Input CMP data scan along pick corresponding trajectories velocity
- 45. To estimate velocity for dipping layers….
- 46. To estimate velocity for dipping layers…. The notion of the CMP no longer has any meaning, as the mid-points do not sit above the same subsurface location for all offsets
- 47. Dipping layers Common midpointsource receiver CMP v1 Vrms1 Vrms2 v2 Vrms3v3 Vrms4
- 48. To estimate velocity for dipping layers…. The notion of the CMP no longer has any meaning, as the mid-points do not sit above the same subsurface location for all offsets We have to assess the travel times for each offset separately
- 49. Tomographic velocity update…..Trace raypaths through the current version ofthe model and note arrival times
- 50. Tomographic velocity update…..Picks of reflection event arrival times synthesizedarrival times from the from ray tracing throughreal data the current velocity model
- 51. Tomographic velocity update….. Tomography iteratively modifies the velocity model so as to minimize the difference between observed arrival times on the real data, and ray-traced times through the current velocity model
- 52. Iterative update (1) PreSDM (2) Autopickersmooth initial model output migrated gathers Using continuous CRPs, calculate semblance, velocity & anisotropy (6) Interpretation (if required) error grids, & RMO stackPick constraint layer, insert ‘flood’ velocity, and migrate (3) TTI Tomography compute dip field demigrate picks & RMO stack update TTI velocity field remigrate picks & RMO stack (5) PreSDM with updated velocity No (4) Inversion QC (4) RMO & z Residual velocity error minimised? Yes (gathers flat) Depth error acceptable? acceptable?Final Volume
- 53. Iterative update (1) PreSDM (2) Autopickersmooth initial model output migrated gathers Using continuous CRPs, calculate semblance, velocity & anisotropy (6) Interpretation (if required) error grids, & RMO stackPick constraint layer, insert ‘flood’ velocity, and migrate This process (3) TTI Tomography usually involves demigrate picksdipRMO stack compute & field 6-8 iterations update TTI velocity field remigrate picks & RMO stack (5) PreSDM with updated velocity No (4) Inversion QC (4) RMO & z Residual velocity error minimised? Yes (gathers flat) Depth error acceptable? acceptable?Final Volume
- 54. Iteration 1, 3D preSDM0 Top Chalkkm2
- 55. Iteration 2, 3D preSDM0 Top Chalkkm2
- 56. Iteration 3, 3D preSDM0 Top Chalkkm2
- 57. Iteration 1 Velocities0km2
- 58. Iteration 2 Velocities0km2
- 59. Iteration 3 Velocities0km2
- 60. Migration:putting the recorded databack where it came from
- 61. Common midpointsource receiver CMP v1 Vrms1 v2 Vrms2v3 Vrms3 v4 Vrms4
- 62. Common midpointsource receiver CMP v1 Vrms1 v2 Vrms2v3 Vrms3 v4 Vrms4
- 63. Plot all the traces from various common midpoints toform a picture of the subsurface…
- 64. Common midpointSource Geophone CMP tA Reflector segment A B tA
- 65. Common midpointSource Geophone CMP tA Reflector segment A B tA ‘Migration’ moves the recorded data back to where it came from
- 66. Main migration algorithms in use today - Kirchhoff Ray - Beam - (GB, CRAM, CRS, CFP, ….) - Wavefield extrapolation (WEM)Wave - Reverse-Time (two-way)
- 67. Migration algorithms relocate recorded energy to its ‘true’ position using an appropriate approximate solution to the two-way visco-elastic wave equation (but what is ‘appropriate’, depends on our objectives)
- 68. Migration algorithms Primarily, the degree of approximation relates to how well the algorithm comprehends lateral velocity change
- 69. Migration algorithms Primarily, the degree of approximation relates to how well the algorithm comprehends lateral velocity change No Smooth Rapid lateral lateral lateral velocity velocity velocity change change change
- 70. Migration algorithms Primarily, the degree of approximation relates to how well the algorithm comprehends lateral velocity change No Smooth Rapid lateral lateral lateral velocity velocity velocity change change change Time Ray-based and RTM migration low-order FD (high-order FD) depth migration depth migration
- 71. Migration algorithms Primarily, the degree of approximation relates to how well the algorithm comprehends lateral velocity change No Smooth Rapid lateral lateral lateral velocity velocity velocity change change change Time Ray-based and RTM migration low-order FD (high-order FD) depth migration depth migration simple ray-paths complex ray-paths
- 72. 1km Velocity-depth model1490 m/s1600 m/s2000 m/s2200 m/s3500 m/s
- 73. Acoustic shot gather 3km 6km 1sEnergy travelling in thewater (the ‘direct’ wave)Reflection fromwater bottom 3sReflections from 4sdeeper rock layers 5s
- 74. 1km Velocity-depth model1490 m/s1600 m/s2000 m/s2200 m/s3500 m/s
- 75. 1km preSDM1500 m/s1600 m/s2000 m/s2200 m/s3500 m/s
- 76. 1km preSTM1500 m/s (converted to depth)1600 m/s2000 m/s2200 m/s3500 m/s
- 77. Migration Issues:Lateral velocity variation: Kirchhoff preSTM vs Kirchhoff preSDM vs RTM Norwegian Sea shallow water gas example
- 78. Interval velocity modelAutopicking @50*50m 1km Courtesy of ConocoPhillips NorwayTomo @250*250*50m
- 79. Kirchhoff preSTM (initial model) 1km Courtesy of ConocoPhillips Norway
- 80. Kirchhoff preSDMAutopicking @50*50m 1km Courtesy of ConocoPhillips NorwayTomo @250*250*50m
- 81. RTMAutopicking @50*50m 1km Courtesy of ConocoPhillips NorwayTomo @250*250*50m
- 82. Migration Issues:In addition to the degree oflateral velocity change, we alsohave the issue of ray-pathcomplexity to consider in themigration…
- 83. Migration Issues:Multi-pathing:
- 84. What is multi-pathing? There is more than one path from a surface location to a subsurface point saltA Kirchhoff scheme usually only computes travel times forone ray path… what happens to the energy from the restof the ray paths from input data?
- 85. Migration Issues:Multi-pathing: Kirchhoff vs WEM North Sea shallow water diapir example
- 86. 1km salt2km46 Vi(z)
- 87. 1km2km46 Anisotropic Kirchhoff 3D preSDM
- 88. 1km2km46 Anisotropic one-way SSFPI (WEM) 3D preSDM
- 89. Migration Issues:Two-way propagation:
- 90. What is two-way propagation?Conventional one-way propagation Two-way propagation: requires a moreas assumed by standard migration complete solution of the wave equationschemes to migrate such arrivals Nor from the reflection point back up to the surface The direction of propagation changes either on the way down from the surfaceNo change in propagation to the reflection point, or from thedirection on the way from reflection point back up to the surfacethe surface down to thereflection point
- 91. Migration Issues:Two way ray paths: WEM vs RTM North Sea shallow water diapir example
- 92. 1km2km46 Anisotropic one-way SSFPI (WEM) 3D preSDM
- 93. 1km2km46 Anisotropic two-way RTM 3D preSDM
- 94. 1km2km46 Anisotropic two-way RTM 3D preSDM
- 95. Migration Issues:Two way ray paths: WEM vs RTM West African deep water diapir example
- 96. WEM 1km 1km
- 97. RTM 1km 1km
- 98. RTM 1km 1km
- 99. RTM 1km 1km
- 100. RTM 1km 1km
- 101. Once we have estimated velocity, andmigrated the data to obtain gathers intheir correct spatial location, we can begin to analyse amplitude information
- 102. Extracting other rock attributes (as well as velocity): rock type, fluid type, density,saturation, pressure, attenuation, ….
- 103. Rock physics basics:(for isotropic materials)Stress (pressure) = force/area = F/AStrain = fractional change in volume = dV/VBulk modulus = pressure/strain = B = - (F/A)/(dV/V)Compressibility = 1/B B = λ + 2/3 μ
- 104. Common midpoint gather CMP t1 t2 t3 t4 t5For a CMP gather, we have manyarrival time measurements for agiven subsurface reflectorelement
- 105. Common image gather CIG or CRP t1 t2 t3 t4 t5 offsetAfter depth migration with anacceptable velocity model, allevents in the gather shouldline-up ‘flat gathers’ Migrated depth
- 106. Having obtained estimates of velocity:we can then estimate other parameters fromamplitude behaviour
- 107. Gathers output from preSDM - not exactly flat
- 108. After final residual event alignment and noise suppression These data are now suitable for analyzing variations in amplitude:
- 109. After final residual event alignment and noise suppression These data are now suitable for analyzing variations in amplitude: vertically from reflector-to- reflector: (ρ2v2 – ρ1v1)/(ρ2v2 + ρ1v1)
- 110. After final residual event alignment and noise suppression These data are now suitable for analyzing variations in amplitude: vertically from reflector-to- reflector and laterally versus incidence angle at the reflectors
- 111. Incident P wave Transmitted P wave Reflected P wave textThe Knott-Zoeppritz equations relate theamplitude change as a function of incidentangle, to Vp, Vs, and density
- 112. Rock physics basics:(for isotropic materials) θ Vp Vp+δVp
- 113. 3D preSDM Showing AVO Anomalies Over Producing Fields Near stack Far stack AVO angle stack synthetics
- 114. 3D preSDM Showing AVO Anomalies Over Producing FieldsNear stack (0º-25º) Far stack (25º-50º) Average absolute amplitude Top Balder +50 - +200
- 115. MacCulloch 15/24b-6 Far-angle stack EI InversionN S W E 15/24b-6 15/24b-6 Top Balder Low EI Oil 650 Sand 600 550 500 450
- 116. N 15/25b-3 S Top Balder Brenda Field 650 600 Possible low EI Oil Sand on flank? 550 500 15/25b-3 Far-stack Inversion (inline) 450
- 117. Unconventional (tight) reservoir - China PS seismic line (PS time) through main producing wells Productive Interval Zone of interest11
- 118. Unconventional (tight) reservoir - China Characterizing Lithological Variations shale sandRecord P-wave onlyImpute shear-wave measurementusing simultaneous inversion (AVO)Attempt to infer sand-shale variations Record shear-waves directly More accurate depiction of sand-shale variations11
- 119. Unconventional (tight) reservoir - China Full-wave explains well productivity – fracture characterization Same lithology Note presence of No fractures fractures in No production producing zone New well location11
- 120. What we’ve reviewed so far, hasbeen the ‘state of the art’: 1) velocity model building 2) migration 3) attribute estimation
- 121. What next?Can we do all this in one step?= full elastic waveform inversion
- 122. To accomplish this task, we must accuratelymodel the behaviour of the recorded data:
- 123. To accomplish this task, we must accuratelymodel the behaviour of the recorded data:- we start with initial estimates of the rock physicsparameters (P-wave velocity, S-wave velocity,density, anisotropy, absorption, ..)
- 124. To accomplish this task, we must accuratelymodel the behaviour of the recorded data:- we start with initial estimates of the rock physicsparameters (P-wave velocity, S-wave velocity,density, anisotropy, absorption, ..)- make synthetic data and compare it to the realdata
- 125. To accomplish this task, we must accuratelymodel the behaviour of the recorded data:- we start with initial estimates of the rock physicsparameters (P-wave velocity, S-wave velocity,density, anisotropy, absorption, ...)- make synthetic data and compare it to the realdata- iteratively adjust the parameters until modelledand real data match
- 126. Real shot Modelled shot - = residual
- 127. Recall the conventional approach:(Tomographic velocity update)….. Tomography iteratively modifies the velocity model so as to minimize the difference between observed arrival times on the real data, and ray-traced times through the current velocity model
- 128. Waveform inversion update….. Waveform inversion iteratively modifies the parameter model so as to minimize the difference between observed amplitudes on the real data, and modelled amplitudes created using the current parameter model
- 129. What’s involved in getting the amplitude right? -Visco elastic wave propagation (incorporates attenuation and shear modes) -Elastic wave propagation (shear modes) -Acoustic wave propagation (P-wave only, thus ignoring density) -Anisotropy -Source wavelet (and are ghosts present?) -Source wavelet time delay -Cycle skipping (offset and frequency dependent)
- 130. Ignoring density Reflection strength (amplitude) is related to impedance contrast: (ρ2v2 – ρ1v1)/(ρ2v2 + ρ1v1) By ignoring density, we are saying that impedance is only a function of P velocity: Thus, if we invert using reflection events, we will have an amplitude error So, to avoid this error perhaps use only refractions (diving, turning waves)
- 131. Where are the refractions? Perform some forward modelling to assess how deeply the diving waves penetrate The region of validity of the model update will be related to this depth of penetration
- 132. Raytracing to show turning-ray paths- expected maximum depth of WFI update 10km cable H2OObserved depth ofupdate Insert Velocity Model Here with Rays for Cable we are using Maximum expected depth of WFI update Ray tracing performed in tomography derived sediment flood model
- 133. Wave modelling to show turning-ray pathsSnapshot (t=33ms)
- 134. Wave modelling to show turning-ray pathsSnapshot (t=1407ms)
- 135. Wave modelling to show turning-ray pathsSnapshot (t=1865ms)
- 136. Wave modelling to show turning-ray pathsSnapshot (t=2454ms)
- 137. Wave modelling to show turning-ray pathsSnapshot (t=3272ms) Max Depth of Turning Rays ~3400m for cable length
- 138. Do we obtain a better earth-model parameters? One way to confirm if FWI has produced better earth- model parameters is to use the FWI velocity to perform a new migration
- 139. Gathers migrated with ray-tomography velocities Courtesy of Chow Wang, GXT
- 140. Gathers migrated with waveform inversion velocities Courtesy of Chow Wang, GXT
- 141. Shallow Section Before WFI Courtesy of Chow Wang, GXT
- 142. Shallow Section After WFI Courtesy of Chow Wang, GXT
- 143. BP in-house project: Valhall(courtesy of Jan Kommedal & Laurent Sirgue) Courtesy of BP Norway
- 144. BP ValhallRay tomography velocity modelWaveform inversion velocity model Courtesy of BP Norway
- 145. BP Valhall: ray-based tomography Courtesy of BP Norway
- 146. BP Valhall: waveform tomography Courtesy of BP Norway
- 147. BP Valhall: waveform tomography Courtesy of BP Norway
- 148. 175m depth slice of preSDM amplitudes Courtesy of BP Norway
- 149. 175m depth slice of FWI velocity Courtesy of BP Norway
- 150. BP Valhall: 150m velocity slice Courtesy of BP Norway
- 151. BP Valhall: 150m velocity slice Courtesy of BP Norway
- 152. BP Valhall: 1050m velocity slice Courtesy of BP Norway
- 153. BP Valhall: 1050m velocity slice Courtesy of BP Norway
- 154. The ultimate goal of full waveform inversion…. At present, the limiting assumptions we make in waveform inversion limit what we can achieve: we can currently forward model with a priori parameters for: density, attenuation, anisotropy (and perhaps Vs) but invert only for P-wave velocity
- 155. The ultimate goal of full waveform inversion…. IFF we can move beyond the present limiting assumptions, then we may be able to invert so as to update all these parameters thereby recovering density, Vp, Vs, Q, and other parameters. Interpretation would then be performed on these parameter fields directly, rather than on inversions of migrated data obtained using the velocity parameter
- 156. The ultimate goal of full waveform inversion…. Vp Vs ρ ε δ model Inversion result Courtesy of Olga Podgornova
- 157. The ultimate goal of full waveform inversion…. Courtesy of Joachim Mispel & Ina Wenske
- 158. The ultimate goal of full waveform inversion…. Vp Vs/10 Vs Courtesy of Satish Singh
- 159. In other words ….
- 160. Move from thislengthy disjointedprocess……
- 161. Extensive data pre-processing (remove multiples) Move from this lengthy disjointed process……
- 162. Extensive data pre-processing (remove multiples) Move from this lengthy disjointed process……+ Iterative velocity model update and migration
- 163. Extensive data pre-processing (remove multiples) Move from this lengthy disjointed process……+ Iterative velocity model update and migration + elastic parameter inversion
- 164. Extensive data pre-processing (remove multiples) Move from this lengthy disjointed process……+ Iterative velocity model update and migration + elastic parameter inversion + rock property estimation
- 165. To this ……
- 166. CLEAN INPUT DATA(including multiples) To this …… FWI rock properties
- 167. But perhaps we shouldn’t ‘hold our breath’ just yet !
- 168. Thank you !

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