Applicability Analysis of Pre-Stack Inversion in Carbonate Karst Reservoir

Rui Wang and Bo Liu
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Rui Wang: Institute of Exploration and Development, SINOPEC Shanghai Offshore Oil & Gas Company, No. 1225, Mall Road, Pudong New District, Shanghai 200120, China
Bo Liu: School of Earth Science and Engineering, Hebei University of Engineering, No. 19 Tai Chi Road, Economic and Technological Development Zone, Handan 056083, China

Energies, 2022, vol. 15, issue 15, 1-13

Abstract: Although pre-stack inversion has been carried out on reservoir prediction, few studies have focused on the application of pre-stack for seismic inversion in fractured-cavity carbonate reservoirs. In carbonate rock, complicated combinations and fluid predictions in karst caves are remain unclear. Post-stack methods are commonly used to predict the position, size, and fillings of caves, but pre-stack inversion is seldom applied in carbonate karst reservoirs. This paper proposes a pre-stack inversion method for forward modeling data and oil survey seismic data, using both points to indicate the application of pre-stack inversion in karst caves. Considering influence of cave size, depth, and filler on prediction, three sets of models (different caves volume; different fillings velocity of caves; complicated combination of caves) are employed and inverted by pre-stack inversion. We analyze the pre-stack results to depict Ordovician oil bearing and characterize caves. Geological model parameters came from actual data of the Tahe oilfield, and seismic data were synthesized from geological models based on full-wave equation forward simulation. Moreover, a case study of pre-stack inversion from the Tahe area was employed. The study shows that, from both the forward modeling and the oil seismic data points of view, pre-stack inversion is applicable to carbonate karst reservoirs.

Keywords: carbonate cavern reservoir application; pre-stack inversion; model (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
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