Prestack 2D parsimonious Kirchhoff depth migration of elastic seismic data

Geophysics ◽  
2011 ◽  
Vol 76 (4) ◽  
pp. S157-S164 ◽  
Author(s):  
Robert Sun ◽  
George A. McMechan
Keyword(s):  
Seismic Data ◽  
Velocity Model ◽  
P Wave ◽  
P Value ◽  
Common Source ◽  
S Wave ◽  
P Values ◽  
Depth Migration ◽  
Reflector Surface ◽  
Kirchhoff Depth Migration

We have extended prestack parsimonious Kirchhoff depth migration for 2D, two-component, reflected elastic seismic data for a P-wave source recorded at the earth’s surface. First, we separated the P-to-P reflected (PP-) waves and P-to-S converted (PS-) waves in an elastic common-source gather into P-wave and S-wave seismograms. Next, we estimated source-ray parameters (source p values) and receiver-ray parameters (receiver p values) for the peaks and troughs above a threshold amplitude in separated P- and S-wavefields. For each PP and PS reflection, we traced (1) a source ray in the P-velocity model in the direction of the emitted ray angle (determined by the source p value) and (2) a receiver ray in the P- or S-velocity model back in the direction of the emergent PP- or PS-wave ray angle (determined by the PP- or PS-wave receiver p value), respectively. The image-point position was adjusted from the intersection of the source and receiver rays to the point where the sum of the source time and receiver-ray time equaled the two-way traveltime. The orientation of the reflector surface was determined to satisfy Snell’s law at the intersection point. The amplitude of a P-wave (or an S-wave) was distributed over the first Fresnel zone along the reflector surface in the P- (or S-) image. Stacking over all P-images of the PP-wave common-source gathers gave the stacked P-image, and stacking over all S-images of the PS-wave common-source gathers gave the stacked S-image. Synthetic examples showed acceptable migration quality; however, the images were less complete than those produced by scalar reverse-time migration (RTM). The computing time for the 2D examples used was about 1/30 of that for scalar RTM of the same data.

Imaging structures below dipping TI media

Geophysics ◽  
1999 ◽  
Vol 64 (4) ◽  
pp. 1239-1246 ◽  
Author(s):  
Robert W. Vestrum ◽  
Don C. Lawton ◽  
Ron Schmid
Keyword(s):  
Seismic Data ◽  
Seismic Anisotropy ◽  
Rocky Mountain ◽  
Transversely Isotropic ◽  
Velocity Model ◽  
P Wave ◽  
Depth Imaging ◽  
Depth Migration ◽  
Kirchhoff Depth Migration ◽  
Ti Media

Seismic anisotropy in dipping shales causes imaging and positioning problems for underlying structures. We developed an anisotropic depth‐migration approach for P-wave seismic data in transversely isotropic (TI) media with a tilted axis of symmetry normal to bedding. We added anisotropic and dip parameters to the depth‐imaging velocity model and used prestack depth‐migrated image gathers in a diagnostic manner to refine the anisotropic velocity model. The apparent position of structures below dipping anisotropic overburden changes considerably between isotropic and anisotropic migrations. The ray‐tracing algorithm used in a 2-D prestack Kirchhoff depth migration was modified to calculate traveltimes in the presence of TI media with a tilted symmetry axis. The resulting anisotropic depth‐migration algorithm was applied to physical‐model seismic data and field seismic data from the Canadian Rocky Mountain Thrust and Fold Belt. The anisotropic depth migrations offer significant improvements in positioning and reflector continuity over those obtained using isotropic algorithms.

Scalar reverse‐time depth migration of prestack elastic seismic data

Geophysics ◽  
2001 ◽  
Vol 66 (5) ◽  
pp. 1519-1527 ◽  
Author(s):  
Robert Sun ◽  
George A. McMechan
Keyword(s):  
Seismic Waves ◽  
Velocity Model ◽  
P Wave ◽  
Common Source ◽  
Reverse Time ◽  
S Wave ◽  
Wave Source ◽  
Reflected Waves ◽  
S Waves ◽  
Elastic Data

Reflected P‐to‐P and P‐to‐S converted seismic waves in a two‐component elastic common‐source gather generated with a P‐wave source in a two‐dimensional model can be imaged by two independent scalar reverse‐time depth migrations. The inputs to migration are pure P‐ and S‐waves that are extracted by divergence and curl calculations during (shallow) extrapolation of the elastic data recorded at the earth’s surface. For both P‐to‐P and P‐to‐S converted reflected waves, the imaging time at each point is the P‐wave traveltime from the source to that point. The extracted P‐wave is reverse‐time extrapolated and imaged with a P‐velocity model, using a finite difference solution of the scalar wave equation. The extracted S‐wave is reverse‐time extrapolated and imaged similarly, but with an S‐velocity model. Converted S‐wave data requires a polarity correction prior to migration to ensure constructive interference between data from adjacent sources. Synthetic examples show that the algorithm gives satisfactory results for laterally inhomogeneous models.

scholarly journals Anisotropy extraction using a deviated well in the Mahanadi Basin, East Coast of India

2019 ◽  
Vol 10 (3) ◽  
pp. 911-918
Author(s):  
Biplab Kumar Mukherjee ◽  
G. Karthikeyan ◽  
Karanpal Rawat ◽  
Hari Srivastava
Keyword(s):  
Seismic Data ◽  
East Coast ◽  
Velocity Model ◽  
P Wave ◽  
S Wave ◽  
Gardner Equation ◽  
East Coast Of India ◽  
Nonlinear Fitting ◽  
Sonic Log ◽  
Mahanadi Basin

Abstract Shale is the primary rock type in the shallow marine section of the Mahanadi Basin, East Coast of India. Shale, being intrinsically anisotropic, always affects the seismic data. Anisotropy derived from seismic and VSP has lower resolution and mostly based on P wave. The workflow discussed here uses Gardner equation to derive vertical velocity and uses a nonlinear fitting to extract the Thomsen’s parameters using both the P wave and S wave data. These parameters are used to correct the sonic log of a deviated well as well as anisotropic AVO response of the reservoir. The presence of negative delta was observed, which is believed to be affected by the presence of chloride and illite in the rock matrix. This correction can be used to update the velocity model for time–depth conversion and pore pressure modelling.

Robust and efficient upwind finite‐difference traveltime calculations in three dimensions

Geophysics ◽  
1995 ◽  
Vol 60 (4) ◽  
pp. 1108-1117 ◽  
Author(s):  
William A. Schneider
Keyword(s):  
Finite Difference ◽  
Seismic Data ◽  
Velocity Model ◽  
Radial Component ◽  
Three Dimensions ◽  
Spherical Coordinate ◽  
Depth Migration ◽  
Slowness Vector ◽  
Kirchhoff Depth Migration ◽  
Upwind Finite Difference

First‐arrival traveltimes in complicated 3-D geologic media may be computed robustly and efficiently using an upwind finite‐difference solution of the 3-D eikonal equation. An important application of this technique is computing traveltimes for imaging seismic data with 3-D prestack Kirchhoff depth migration. The method performs radial extrapolation of the three components of the slowness vector in spherical coordinates. Traveltimes are computed by numerically integrating the radial component of the slowness vector. The original finite‐difference equations are recast into unitless forms that are more stable to numerical errors. A stability condition adaptively determines the radial steps that are used to extrapolate. Computations are done in a rotated spherical coordinate system that places the small arc‐length regions of the spherical grid at the earth’s surface (z = 0 plane). This improves efficiency by placing large grid cells in the central regions of the grid where wavefields are complicated, thereby maximizing the radial steps. Adaptive gridding allows the angular grid spacings to vary with radius. The computation grid is also adaptively truncated so that it does not extend beyond the predefined Cartesian traveltime grid. This grid handling improves efficiency. The method cannot compute traveltimes corresponding to wavefronts that have “turned” so that they propagate in the negative radial direction. Such wavefronts usually represent headwaves and are not needed to image seismic data. An adaptive angular normalization prevents this turning, while allowing lower‐angle wavefront components to accurately propagate. This upwind finite‐difference method is optimal for vector‐parallel supercomputers, such as the CRAY Y-MP. A complicated velocity model that generates turned wavefronts is used to demonstrate the method’s accuracy by comparing with results that were generated by 3-D ray tracing and by an alternate traveltime calculation method. This upwind method has also proven successful in the 3-D prestack Kirchhoff depth migration of field data.

Parsimonious 2D prestack Kirchhoff depth migration

Geophysics ◽  
2003 ◽  
Vol 68 (3) ◽  
pp. 1043-1051 ◽  
Author(s):  
Biaolong Hua ◽  
George A. McMechan
Keyword(s):  
Fresnel Zone ◽  
Computation Time ◽  
Structural Features ◽  
Common Source ◽  
Depth Migration ◽  
Kirchhoff Migration ◽  
Migration Velocity Analysis ◽  
Reflector Surface ◽  
Kirchhoff Depth Migration ◽  
Ray Parameter

The efficiency of prestack Kirchhoff depth migration is much improved by using ray parameter information measured from prestack common‐source and common‐receiver gathers. Ray tracing is performed only back along the emitted and emergent wave directions, and so is much reduced. The position of the intersection of the source and receiver rays is adjusted to satisfy the image time condition. The imaged amplitudes are spread along the local reflector surface only within the first Fresnel zone. There is no need to build traveltime tables before migration because the traveltime calculation is embedded into the migration. To further reduce the computation time, the input data are decimated by applying an amplitude threshold before the estimation of ray parameters, and only peak and trough points on each trace are searched for ray parameters. Numerical results show that the proposed implementation is typically 50–80 times faster than traditional Kirchhoff migration for synthetic 2D prestack data. The migration speed improvement is obtained at the expense of some reduction in migration quality; the optimal compromise is implemented by the choice of migration parameters. The main uses of the algorithm will be to get a fast first look at the main structural features and for iterative migration velocity analysis.

Lithospheric architecture of the Ligurian Basin from seismic travel time tomography

2021 ◽  
Author(s):  
Anke Dannowski ◽  
Heidrun Kopp ◽  
Ingo Grevemeyer ◽  
Grazia Caielli ◽  
Roberto de Franco ◽  
...  
Keyword(s):  
Seismic Data ◽  
Velocity Model ◽  
P Wave ◽  
Central Basin ◽  
Uppermost Mantle ◽  
Mantle Boundary ◽  
Oceanic Spreading ◽  
Refraction Seismic ◽  
Back Arc ◽  
Ligurian Basin

<p>The Ligurian Basin is located north-west of Corsica at the transition from the western Alpine orogen to the Apennine system. The Back-arc basin was generated by the southeast retreat of the Apennines-Calabrian subduction zone. The opening took place from late Oligocene to Miocene. While the extension led to extreme continental thinning little is known about the style of back-arc rifting. Today, seismicity indicates the closure of this back-arc basin. In the basin, earthquake clusters occur in the lower crust and uppermost mantle and are related to re-activated, inverted, normal faults created during rifting.</p><p>To shed light on the present day crustal and lithospheric architecture of the Ligurian Basin, active seismic data have been recorded on short period ocean bottom seismometers in the framework of SPP2017 4D-MB, the German component of AlpArray. An amphibious refraction seismic profile was shot across the Ligurian Basin in an E-W direction from the Gulf of Lion to Corsica. The profile comprises 35 OBS and three land stations at Corsica to give a complete image of the continental thinning including the necking zone.</p><p>The majority of the refraction seismic data show mantle phases with offsets up to 70 km. The arrivals of seismic phases were picked and used to generate a 2-D P-wave velocity model. The results show a crust-mantle boundary in the central basin at ~12 km depth below sea surface. The P-wave velocities in the crust reach 6.6 km/s at the base. The uppermost mantle shows velocities >7.8 km/s. The crust-mantle boundary becomes shallower from ~18 km to ~12 km depth within 30 km from Corsica towards the basin centre. The velocity model does not reveal an axial valley as expected for oceanic spreading. Further, it is difficult to interpret the seismic data whether the continental lithosphere was thinned until the mantle was exposed to the seafloor. However, an extremely thinned continental crust indicates a long lasting rifting process that possibly did not initiate oceanic spreading before the opening of the Ligurian Basin stopped. The distribution of earthquakes and their fault plane solutions, projected along our seismic velocity model, is in-line with the counter-clockwise opening of the Ligurian Basin.</p>

Using Seismic Data to Predict Shale Pore Pressure and Overpressure Sweet Spots: A Case Study from the Lower Silurian Longmaxi Formation in Sichuan Basin, China

2021 ◽  
Author(s):  
Sheng Chen ◽  
Qingcai Zeng ◽  
Xiujiao Wang ◽  
Qing Yang ◽  
Chunmeng Dai ◽  
...  
Keyword(s):  
Prediction Model ◽  
Wave Velocity ◽  
Shale Gas ◽  
Seismic Data ◽  
P Wave ◽  
Formation Pressure ◽  
S Wave ◽  
P Wave Velocity ◽  
New Formation ◽  
Sweet Spots

Abstract Practices of marine shale gas exploration and development in south China have proved that formation overpressure is the main controlling factor of shale gas enrichment and an indicator of good preservation condition. Accurate prediction of formation pressure before drilling is necessary for drilling safety and important for sweet spots predicting and horizontal wells deploying. However, the existing prediction methods of formation pore pressures all have defects, the prediction accuracy unsatisfactory for shale gas development. By means of rock mechanics analysis and related formulas, we derived a formula for calculating formation pore pressures. Through regional rock physical analysis, we determined and optimized the relevant parameters in the formula, and established a new formation pressure prediction model considering P-wave velocity, S-wave velocity and density. Based on regional exploration wells and 3D seismic data, we carried out pre-stack seismic inversion to obtain high-precision P-wave velocity, S-wave velocity and density data volumes. We utilized the new formation pressure prediction model to predict the pressure and the spatial distribution of overpressure sweet spots. Then, we applied the measured pressure data of three new wells to verify the predicted formation pressure by seismic data. The result shows that the new method has a higher accuracy. This method is qualified for safe drilling and prediction of overpressure sweet spots for shale gas development, so it is worthy of promotion.

3-D elastic prestack, reverse‐time depth migration

Geophysics ◽  
1994 ◽  
Vol 59 (4) ◽  
pp. 597-609 ◽  
Author(s):  
Wen‐Fong Chang ◽  
George A. McMechan
Keyword(s):  
Finite Differences ◽  
Synthetic Data ◽  
P Wave ◽  
Common Source ◽  
Reverse Time ◽  
Depth Migration ◽  
Full Wave ◽  
Source Data ◽  
Recorded Data ◽  
Time Extrapolation

By combining and extending previous algorithms for 2-D prestack elastic migration and 3-D prestack acoustic migration, a full 3-D elastic prestack depth migration algorithm is developed. Reverse‐time extrapolation of the recorded data is by 3-D elastic finite differences; computation of the image time for each point in the 3-D volume is by 3-D acoustic finite differences. The algorithm operates on three‐component, vector‐wavefield common‐source data and produces three‐component vector reflectivity distributions. Converted P‐to‐S reflections are automatically imaged with the primary P‐wave reflections. There are no dip restrictions as the full wave equation is used. The algorithm is illustrated by application to synthetic data from three models; a flat reflector, a dipping truncated wedge overlying a flat reflector, and the classical French double dome and fault model.

Prestack Kirchhoff depth migration of shallow seismic data

Geophysics ◽  
1998 ◽  
Vol 63 (4) ◽  
pp. 1241-1247 ◽  
Author(s):  
Linus Pasasa ◽  
Friedemann Wenzel ◽  
Ping Zhao
Keyword(s):  
Waste Disposal ◽  
Seismic Data ◽  
Signal To Noise Ratio ◽  
Disposal Site ◽  
Model Estimation ◽  
Waste Disposal Site ◽  
Depth Migration ◽  
Prestack Migration ◽  
Shallow Seismic ◽  
Kirchhoff Depth Migration

Prestack Kirchhoff depth migration is applied successfully to shallow seismic data from a waste disposal site near Arnstadt in Thuringia, Germany. The motivation behind this study was to locate an underground building buried in a waste disposal. The processing sequence of the prestack migration is simplified significantly as compared to standard common (CMP) data processing. It includes only two parts: (1) velocity‐depth‐model estimation and (2) prestack depth migration. In contrast to conventional CMP stacking, prestack migration does not require a separation of reflections and refractions in the shot data. It still provides an appropriate image. Our data example shows that a superior image can be achieved that would contain not just subtle improvements but a qualitative step forward in resolution and signal‐to‐noise ratio.

Leading-order seismic imaging using curvelets

Geophysics ◽  
2007 ◽  
Vol 72 (6) ◽  
pp. S231-S248 ◽  
Author(s):  
Huub Douma ◽  
Maarten V. de Hoop
Keyword(s):  
Seismic Data ◽  
Order Approximation ◽  
Angular Frequency ◽  
Leading Order ◽  
Numerical Examples ◽  
Depth Migration ◽  
Map Migration ◽  
Kirchhoff Depth Migration ◽  
Homogeneous Media ◽  
Spatial Support

Curvelets are plausible candidates for simultaneous compression of seismic data, their images, and the imaging operator itself. We show that with curvelets, the leading-order approximation (in angular frequency, horizontal wavenumber, and migrated location) to common-offset (CO) Kirchhoff depth migration becomes a simple transformation of coordinates of curvelets in the data, combined with amplitude scaling. This transformation is calculated using map migration, which employs the local slopes from the curvelet decomposition of the data. Because the data can be compressed using curvelets, the transformation needs to be calculated for relatively few curvelets only. Numerical examples for homogeneous media show that using the leading-order approximation only provides a good approximation to CO migration for moderate propagation times. As the traveltime increases and rays diverge beyond the spatial support of a curvelet; however, the leading-order approximation is no longer accurate enough. This shows the need for correction beyond leading order, even for homogeneous media.

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