Phase-domain reservoir prediction technology: a case study of channel sand in Chengdao area, Shengli Oilfield
LUO Hongmei1, YANG Peijie1, WANG Yanguang2, MU Xing1, WANG Changjiang1
1. Exploration and Development Research Institute, SINOPEC Shengli Oilfield Company, Dong-ying, Shandong 257015, China; 2. SINOPEC Shengli Oilfield Company, Dong-ying, Shandong 257015, China
Abstract:Changes in lithology and physical properties alter the phase of the seismic signal. Therefore, effectively extracting and then analyzing phase information from seismic data are conducive to identifying special geological bodies and target reservoirs. For this reason, this paper proposes and implements a phase-domain reservoir prediction technology, the core of which is phase decomposition and reconstruction. Analyzing and determining the sensitive phase is the key to the success of phase-domain reservoir prediction, and it involves three steps. Step 1 is the phase decomposition and reconstruction of seismic traces, which produce phase-decomposed seismic data and phase gathers after phase reconstruction. Step 2 is sensitive phase analysis, whereby the phase most sensitive to reservoir changes can be obtained according to the seismic-geological characteristics of the study area. Step 3 is the analysis of phase-decomposed data bodies with the seismic attribute analysis technology, mainly involving profile analysis and slice analysis, to ultimately achieve reservoir prediction. The model analysis shows that synthetic seismic records fail to reflect the lateral differences in wave impedance in thin layers, whereas phase-decomposed data of synthetic seismic records amplify the subtle lateral impedance differences in thin layers so that they are easy to identify. The practical application reveals that the seismic attribu-tes of the data body in the sensitive phase depict the channel more clearly and offer higher resolution.
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LUO Hongmei, YANG Peijie, WANG Yanguang, MU Xing, WANG Changjiang. Phase-domain reservoir prediction technology: a case study of channel sand in Chengdao area, Shengli Oilfield. Oil Geophysical Prospecting, 2022, 57(5): 1129-1137.
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