Facies-Controlled Geostatistical Inversion Method Based on Low-Frequency Model Optimization and Its Application

doi:10.7657/XJPG20230316

Abstract

Abstract:

The oil and gas reservoirs in the Qiketai formation of Middle Jurassic in the Pubei area of Taibei sag, Turpan-Hami basin, are controlled by lithology. Early exploration confirmed that there are thin oil-bearing sand layers with the thickness of 6-15 m at the bottom of the Qiketai formation. It is difficult for conventional inversion methods to predict these sand layers and these methods often yield large errors due to the limitations of the frequency band of seismic data. In order to improve inversion accuracy, a facies-controlled geostatistical inversion method based on low-frequency model optimization was proposed. Combined with the characteristics of large structural relief and greatly varying sedimentary facies in the study area, the low-frequency model was established by combining the compaction trend correction method and the seismic attribute constraint method to obtain the deterministic inversion results. On this basis, a facies-controlled model was established for facies-controlled geostatistical inversion, thus enabling the identification of thin sand layers in the study area. This method effectively complements the low-frequency information missed in seismic signals, and improves the longitudinal resolution of the inversion results. By using this method, a thin sand layer with the thickness of 7 m can be identified, and the inversion result is basically consistent with the actual thickness of sand body, which confirms the effectiveness of this method in predicting thin sand layers in Pubei area.

Key words: Turpan-Hami basin, Pubei area, Qiketai formation, low-frequency model, compaction trend, seismic attribute, facies-controlled model, geostatistical inversion

CLC Number:

P631.445

SHI Nan, LIU Yuan, LENG Yue, WEN Yihua, PAN Haifeng, SUN Bo, WANG Bing. Facies-Controlled Geostatistical Inversion Method Based on Low-Frequency Model Optimization and Its Application[J]. Xinjiang Petroleum Geology, 2023, 44(3): 375-382.

Figures/Tables 10

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