Sparse seismic wavefield sampling

Campman, Xander; Tang, Zijian; Jamali-Rad, Hadi; Kuvshinov, B. N.; Danilouchkine, Mikhail G.; Ji, Ying; Walk, Wim; Smit, Dirk

doi:10.1190/tle36080654.1

Cited by 17 publications

(2 citation statements)

References 23 publications

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“…can minimize the maximum mutual coherency of a dictionary matrix such that densely sampled data can be effectively recovered from sparsely sampled data. Campman et al (2017) also showed its applicability to design activation times of overlapped sources instead of the use of time dithering from a random realization. Additionally, Wu, Blacquière and Groenestijn (2015) introduced blended acquisition using shot repetition that activates multiple shots at the same location within a short time interval.…”

Section: Figure 14mentioning

confidence: 99%

Blended‐acquisition design of irregular geometries towards faster, cheaper, safer and better seismic surveying

Nakayama

Blacquière

Ishiyama

et al. 2018

Geophysical Prospecting

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The application of blended acquisition has drawn considerable attention owing to its ability to improve the operational efficiency as well as the data quality and health, safety and environment performance. Furthermore, the acquisition of less data contributes to the business aspect, while the desired data density is still realizable via subsequent data reconstruction. The use of fewer detectors and sources also minimizes operational risks in the field. Therefore, a combined implementation of these technologies potentially enhances the value of a seismic survey further. One way to encourage this is to minimize any imperfection in deblending and data reconstruction during processing. In addition, one may derive survey parameters that enable a further improvement in these processes as introduced in this study. The proposed survey design workflow iteratively performs the following steps to derive the survey parameters responsible for source blending as well as the spatial sampling of detectors and sources. The first step is the application of blending and sampling operators to unblended and well‐sampled data. We then apply closed‐loop deblending and data reconstruction. The residue for a given design from this step is evaluated and subsequently used by genetic algorithms to simultaneously update the survey parameters related to both blending and spatial sampling. The updated parameters are fed into the next iteration until they satisfy the given termination criteria. We also propose a repeated encoding sequence to form a parameter sequence in genetic algorithms, making the size of problem space manageable. The results of the proposed workflow are outlined using blended dispersed source array data incorporating different scenarios that represent acquisition in marine, transition zone and land environments. Clear differences attributed solely to the parameter design are easily recognizable. Additionally, a comparison among different optimization schemes illustrates the ability of genetic algorithms along with a repeated encoding sequence to find better solutions within a computationally affordable time. The optimized parameters yield a notable enhancement in the deblending and data reconstruction quality and consequently provide optimal acquisition scenarios.

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Section: Figure 14mentioning

confidence: 99%

Blended‐acquisition design of irregular geometries towards faster, cheaper, safer and better seismic surveying

Nakayama

Blacquière

Ishiyama

et al. 2018

Geophysical Prospecting

View full text Add to dashboard Cite

show abstract

“…Mueller et al (2016) describe a method for optimizing near-orthogonal source codes using a simulated annealing algorithm. Campman et al (2017) use the so-called Golomb Ruler to optimize the shot-firing time in an algebraic way such that the correlation property is maximized. In the case of shot repetition, we use a trial-and-error algorithm to optimize the orthogonal properties of the blending code, which means that we aim to obtain source code pairs with spiky autocorrelation and minimal crosscorrelation.…”

Section: Source-code Optimizationmentioning

confidence: 99%

Shot repetition: An alternative seismic blending code in marine acquisition

Blacquière

Groenestijn

2018

GEOPHYSICS

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In blended seismic acquisition, or simultaneous source seismic acquisition, source encoding is essential at the acquisition stage to allow for separation of the blended sources at the processing stage. In land seismic surveys, the vibroseis sources may be encoded with near-orthogonal sweeps for blending. In marine seismic surveys, the sweep type of source encoding is difficult because the main source type in marine seismic exploration is the air-gun array, which has an impulsive character. Another issue in marine streamer seismic data acquisition is that the spatial source sampling is generally coarse. This hinders the deblending performance of algorithms based on the random time delay blending code that inherently requires a dense source sampling because they exploit the signal coherency in the common-receiver domain. We have developed an alternative source code called shot repetition that exploits the impulsive character of the marine seismic source in blending. This source code consists of repeated spikes of ones and can be realized physically by activating a broadband impulsive source more than once at (nearly) the same location. Optimization of the shot-repetition type of blending code was done to improve the deblending performance. As a result of using shot repetition, the deblending process can be carried out in individual shot gathers. Therefore, our method has no need for a regular dense source sampling: It can cope with irregular sparse source sampling; it can help with real-time data quality control. In addition, the use of shot repetition is beneficial for reducing the background noise in the deblended data. We determine the feasibility of our method on numerical examples.

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