Abstract

Abstract Only one wildcat well had been drilled for deep formation hydrocarbon exploration (4400 m to 4800 m) and partially penetrated into Lower Paleogene Formation Wenchang (FM WC) without commercial oil discovery in the Enping 17 Sag, northern of the Pearl River Mouth Basin in the South China Sea. Although large thicknesses of grey lacustrine mudstone with abundant organic material are proven to be the regional source rock, lack of a good reservoir for hydrocarbon accumulation in FM WC is the failure reason for this well. Encountering a 9-m-thick sand layer at a depth of 4650 m indicates that braided fluvial delta and lowstand turbidite sandstone may develop in the FM WC, and the zones below upper section 1 of FM WC are proved to be overpressure. It protects pores in the deep reservoir from compaction. Condensate gas was observed by drill stem test (DST) in overpressure sand layer while no gas was measured in sand layers above the overpressure zone. Aiming at delineating effective reservoir in FM WC, an integrated workflow for 3D seismic reservoir characterization of offshore deep and thin layers was developed for this area without sufficient well data. The workflow includes seismic data reprocessing, well log-based rock physics analysis, seismic structure interpretation, 3D simultaneous amplitude variation with offset (AVO) inversion, 3D lithology prediction, and geological integrated analysis. We present four key solutions to address four specific challenges in this case study: 1) application of adaptive deghosting (AD) techniques to remove the source and streamer depth-related ghost notches in the seismic data spectrum and the bandwidth extension (BWXT) technique to improve the seismic data resolution; 2) a practical rock physics modeling approach to consider the formation overpressure for pseudo-shear sonic log prediction; 3) interactive and synchronized workflow between prestack 3D AVO inversion and seismic processing to predict a 9-m-thick layer in FM WC after 60+ rounds of cyclic tests; 4) cross validation between seismic qualitative attributes and quantitative inversion results to verify the lithology prediction result with limited well data.

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