Abstract
The seismic data quality can be improved by evaluating two aspects: seismic data acquisition and seismic imaging. In recent years, a number of innovative acquisition layouts and methods have been introduced that produced better subsurface images compare to previous dataset. However, the seismic technology in the industry has been largely on an ad-hoc basis without any qualitative analysis of the subsurface geology and complexity and its influence on data quality. In this chapter, the poor images beneath shallow gas cloud were analysed by using two types of illumination methods, namely wave propagation and ray interpolation techniques. Meanwhile the data enhancement methodology was conducted through optimization of receiver positions on surface level. This will address the issue of subsurface illumination below complex overburden and shallow anomaly that cause wave field distortion. The outcome from this work aims at developing the new technique of getting a good and reliable seismic data underneath the near surface anomaly by integrating the existing illumination techniques and optimizing the source and receiver positions. The proposed integrated method of illumination analysis, leads to a new attribute known as Illumination Factor (IF), was formulated based on information from two forward modelling methods; (i) Amplitude distribution in spatial domain and (ii) Ray hit count at the target subsurface. Evaluation of the proposed Illumination Factor will set a basis for improving seismic acquisition design, by enhancing seismic data through better illumination analysis while providing an insight for accurate reservoir characterization.
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Acknowledgements
The authors are grateful to all members of the Geoscience Department for their support and as well as the members of the above consultancy model’s team, which includes engineers, associate professors, lecturers, laboratory technologists, and students. Special thanks to the Universiti Teknologi PETRONAS, Malaysia for providing the permission and resources to carry out the laboratory demonstration. Without the kind cooperation this study would have been impossible.
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Abdul Latiff, A. (2022). Hybrid Illumination Analysis for Complex Overburden Geological Structure. In: Abdul Karim, S.A., Shafie, A. (eds) Towards Intelligent Systems Modeling and Simulation. Studies in Systems, Decision and Control, vol 383. Springer, Cham. https://doi.org/10.1007/978-3-030-79606-8_21
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DOI: https://doi.org/10.1007/978-3-030-79606-8_21
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