Syed Firasat Shah, Naeem Sardar, Waqar Ahmad, and Mubashar Zahoor Bhatti
Pakistan Petroleum Limited, PIDC House, Karachi
It is very common practice that any consideration to phase is limited to two stages of seismic data processing: 1) when vibroseis data is converted to minimum phase at the beginning of processing sequence, 2) at the end of the processing sequence when many companies would like to have their final deliverables to be on zero phase. However, what happens at various steps in the processing sequence effects the phase of seismic data and thereby affects the processing steps that follow, often resulting in a significant loss of quality and integrity of the seismic dataset. Based on some real data examples and application of certain processing steps, this paper describes how the phase of seismic data is effected by certain processing steps and how it can be handled properly.
We intend to demonstrate that proper handling of the phase of seismic data at certain processing steps is a key to preserving its integrity. Ensuring such care for the phase would result in improving the quality of the dataset and in prudent interpretation and attribute studies by means of the final products coming out of such processing sequence. We will use the seismic data examples from recently acquired Sui 3D and from the reprocessing project of Hala 3D, Zindan and Dhok Sultan 2D surveys to show some of the data processing steps, which effect the phase and how these processes can be handled properly to keep the integrity of the phase. We will demonstrate the benefits in maintaining phase integrity through the application of inverse Q filter and through the application of phase matching filters for data obtained through various types of sources at appropriate point in seismic data processing. We will also demonstrate the effectiveness of cascaded zero phase surface-consistent deconvolution as an alternative process for broadening the spectral bandwidth to achieve a balanced spectra without losing the integrity of phase. We will further discuss and demonstrate the value a unified probabilistic approach of combing stochastic process for modeling a non-white reflectivity series with reflectivity whitening filter to arrive at a near accurate estimate of auto-correlation filter for deconvolution.
AAPG Search and Discovery Article #90160©2012 PAPG/SPE Annual Technical Conference, 3-5 December 2012, Islamabad, Pakistan.