SURVEY DESIGN FOR 2D SEISMIC IMAGING EXERCISE

Year 2017, Volume: 28 Issue: 1-2, 71 - 92, 20.04.2018

Cemal Erdemir

Abstract

This paper introduces a methodology to do a two-dimensional (2D) seismic forward modeling in a computer environment,

process and image its synthetic data, and compare the final image to the input model to evaluate the imaging

results. Also it discusses the importance of the pre-survey modeling for seismic data acquisition.

After a geological model was constructed, a finite difference modeling was successfully performed on the model.

The obtained data was processed, and a final image was produced using a pre-stack depth migration. When the

input model is compared to the pre-stack depth imaged result, an excellent match is obtained between the two which

proved the accuracy of the methodology.

The maximum frequency of the data was 50 Hz. Final image was evaluated with respect to different maximum

migration frequency. When the migration maximum frequency was lower than the optimum frequency, the image

quality deteriorated, the image got fuzzier, the sections of the model with thin layers did not focus well. When

the maximum frequency was too high, the final image began losing its quality again, some numerical noise was

introduced, the background noise on the image was increased substantially creating artifacts on the image. These

imaging tests indicated that the image quality depends on the frequency content. Determining and selecting correct

imaging frequency is essential for accurate subsurface illumination.

The paper also shows that the synthetic data is useful to test different processing steps, algorithms and software(s).

It could also be used for training.

Two acquisition geometries were simulated on the model, a surface seismic profile (SSP) and a vertical seismic

profile (VSP). P-wave modes were generated only. Relationship between the surface seismic and the vertical seismic

was discussed, and also shown how to use both data sets to tie each other for interpreting the surface seismic

reflections. However only the surface seismic data was further processed and imaged and evaluated for seismic data

acquisition parameters. It should be mentioned and noted that the parameter selection gets a lot more important and

complicated for 3D seismic survey designs since the survey size is bigger and it gets more expensive to re-evaluate

and re-select the wrong parameters used in 3D surveys.

Keywords

Seismic Model Building, Modeling, Synthetic Data Generation, Seismic Data Processing, Migration, Imaging, Survey Optimization

References

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