A Multi-Point Geostatistical Seismic Inversion Method Based on Local Probability Updating of Lithofacies

Zhihong Wang, Tiansheng Chen, Xun Hu, Lixin Wang and Yanshu Yin
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Zhihong Wang: Research Institute of Petroleum Exploration & Development, PetroChina, P.O. Box 910,20#, Xueyuan Road, Beijing 100083, China
Tiansheng Chen: SINOPEC Petroleum Exploration and Production Research Institute, 31 Xueyuan Road, Haidian District, Beijing 100083, China
Xun Hu: College of Geosciences, China University of Petroleum (Beijing), 18 Fuxue Road, Changping, Beijing 102249, China
Lixin Wang: Key Laboratory of Oil and Gas Resources and Exploration Technology, Ministry of Education, Yangtze University, Wuhan 430100, China
Yanshu Yin: Key Laboratory of Oil and Gas Resources and Exploration Technology, Ministry of Education, Yangtze University, Wuhan 430100, China

Energies, 2022, vol. 15, issue 1, 1-20

Abstract: In order to solve the problem that elastic parameter constraints are not taken into account in local lithofacies updating in multi-point geostatistical inversion, a new multi-point geostatistical inversion method with local facies updating under seismic elastic constraints is proposed. The main improvement of the method is that the probability of multi-point facies modeling is combined with the facies probability reflected by the optimal elastic parameters retained from the previous inversion to predict and update the current lithofacies model. Constrained by the current lithofacies model, the elastic parameters were obtained via direct sampling based on the statistical relationship between the lithofacies and the elastic parameters. Forward simulation records were generated via convolution and were compared with the actual seismic records to obtain the optimal lithofacies and elastic parameters. The inversion method adopts the internal and external double cycle iteration mechanism, and the internal cycle updates and inverts the local lithofacies. The outer cycle determines whether the correlation between the entire seismic record and the actual seismic record meets the given conditions, and the cycle iterates until the given conditions are met in order to achieve seismic inversion prediction. The theoretical model of the Stanford Center for Reservoir Forecasting and the practical model of the Xinchang gas field in western China were used to test the new method. The results show that the correlation between the synthetic seismic records and the actual seismic records is the best, and the lithofacies matching degree of the inversion is the highest. The results of the conventional multi-point geostatistical inversion are the next best, and the results of the two-point geostatistical inversion are the worst. The results show that the reservoir parameters obtained using the local probability updating of lithofacies method are closer to the actual reservoir parameters. This method is worth popularizing in practical exploration and development.

Keywords: local updating; permanent updating ratio of probability; multi-point geostatistical inversion; cyclic iteration; correlation coefficient; Xinchang gas field (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
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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