Overview

The conventional way of conducting seismic data processing QC / QA through qualitative way is no longer effective to take a proper decision for moving from one step to another in the processing workflow. Looking visually on the processing step QC results before and after any processing step and the difference between the input and output, especially at noise and multiple reductions, cannot be enough to see if the parameters of the processing algorithm is optimum or not. Signal and primary leak during the noise and multiple eliminations is not always controlled through running qualitative type of QC in seismic data processing. Moreover, the signal to noise improvement is some sort of trade-off if it increased as it should be or decreased due to processing artefacts as such statics computation if is solving any statics sags or induced wrongly any false structure. Wavelet processing and deconvolution which is really crucial in the QCing and application and its effect on the seismic wavelet stability as an indicator of any seismic data credibility is always not an easy decision to take. Phase of low-frequency bandwidth in the seismic broad bandwidth is always negligible due to looking at the seismic data quaintly form regular way of QCing. Velocity analysis is the most important processing step in time and depth processing is also QCED visually without quantifying if its optimum velocity is being picked or not.

We propose an innovative way to implement QC for time and depth seismic processing QC depends on conducting quantitative QCQA workflow in all processing steps from geometry updates till migration and post-migration.

Who Should Attend

This course is aimed toward Geoscientists involved in seismic data processing and interpretation either the seismic service provider side or consultancy in QC QA of seismic processing and oil and gas company side.

Key Learning Objectives

Participants will gain an understanding of seismic data processing latest seismic industry in QC / QA of seismic data processing. The ability to conduct quantitative QC / QA tools to measure the seismic data quality improvement from processing step to another. The ability to stream and ease taking seismic data processing decisions. They will learn the role of machine learning new seismic industry trend in QCing seismic well logs and velocity analysis picking editing and using machine learning in QC / QA of noise reduction as well.

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