Blended acquisition with temporally signatured/modulated and spatially dispersed source array: Relationship between acquisition productivity and processing performance

Machine learning (ML) has proven its value in the seismic industry with successful implementations in areas of seismic interpretation such as fault and salt dome detection and velocity picking. The field of seismic processing research also is shifting toward ML applications in areas such as tomography, demultiple, and interpolation. Here, a supervised ML deblending algorithm is illustrated on a dispersed source array (DSA) data example in which both high- and low-frequency vibrators were deployed simultaneously. Training data pairs of blended and corresponding unblended data were constructed from conventional (unblended) data from another survey. From this training data, the method can automatically learn a deblending operator that is used to deblend for both the low- and the high-frequency vibrators of the DSA data. The results obtained on the DSA data are encouraging and show that the ML deblending method can offer a good performing, less user-intensive alternative to existing deblending methods.

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Mie Resonance Based Quantum Optical Circuits Integrated with on-chip Single Photon Source Array for Quantum Information Processing

10.1109/rapid51799.2021.9521418 ◽

2021 ◽

Author(s):

Swarnabha Chattaraj ◽

Jiefei Zhang ◽

Siyuan Lu ◽

Anupam Madhukar

Keyword(s):

Quantum Information ◽

Quantum Information Processing ◽

Single Photon ◽

Single Photon Source ◽

Mie Resonance ◽

On Chip ◽

Quantum Optical ◽

Optical Circuits ◽

Source Array ◽

Photon Source

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Blended acquisition with dispersed source arrays

Geophysics ◽

10.1190/geo2011-0480.1 ◽

2012 ◽

Vol 77 (4) ◽

pp. A19-A23 ◽

Cited By ~ 46

Author(s):

A. J. Berkhout

Keyword(s):

High Frequency ◽

Spatial Sampling ◽

Acquisition Process ◽

Air Gun ◽

Seismic Acquisition ◽

Sampling Intervals ◽

Source Array

Blended source arrays are historically configured with equal source units, such as broadband vibrators (land) and broadband air-gun arrays (marine). I refer to this concept as homogeneous blending. I have proposed to extend the blending concept to inhomogeneous blending, meaning that a blended source array consists of different source units. More specifically, I proposed to replace in blended acquisition the traditional broadband sources by narrowband versions — imagine coded single air guns with different volumes or coded single narrowband vibrators with different central frequencies — together representing a dispersed source array (DSA). Similar to what we see in today’s audio systems, the DSA concept allows the design of dedicated narrowband source elements that do not suffer from the low versus high frequency compromise. In addition, the DSA concept opens the possibility to use source depths and spatial sampling intervals that are optimum for the low-, mid-, and high-frequency sources (multiscale shooting grids). DSAs are considered to be an important step in robotizing the seismic acquisition process.

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