Издательство СО РАН

Издательство СО РАН

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Поиск по журналу

Геология и геофизика

Принятые к публикации статьи

STUDY OF GEOSTATISTICAL INVERSION IN THE LITHOLOGIC DISTRIBUTION AND VELOCITY MODELING OF THICK IGNEOUS ROCK IN THE FY AREA, NORTHERN TARIM BASIN, CHINA

Yongzhong Xua, Haijun Yangb, Gengxin Pengb, Xingliang Dengb, Qing Miaob, Yiming Maa, Juntao Liua
a School of Resources and Geosciences, China University of Mining and Technology, Xuzhou 221116, China
b Institute of China Petroleum Tarim Oilfield Company, Korla 841000, China
Ключевые слова: thick igneous rocks; Geostatistical inversion; Lithology distribution; Velocity modeling

Аннотация

In the northern Tarim Basin, a large number of thick igneous rocks are encountered in the drilling process in the Permian, and lithology and velocity of them are violently varying, which has great influence on migration imaging of the “beaded”. It is very important to conduct the fine lithology identification and high precision velocity modeling of the igneous rocks for the exploration and development of the reservoirs. A geostatistical inversion method to obtain igneous lithologic distribution pattern and velocity modeling in the FY area of northern Tarim Basin is introduced in this paper. The results show that the application of the geostatistical inversion method greatly improves the resolution of lithology identification, which helps us further understand the Permian igneous rocks distribution in FY area. By comparing the seismic facies classification maps of FY study area, it shows that the obtained velocity model can well reflect the lateral distribution of igneous rocks. At the same time, the velocity model can also reflect the variation of igneous velocity in details and has a high precision. The average velocity error of the wells participating in the inversion is less than 2%, and the minimum average velocity error is 0.23%. At last, the velocity model is applied to seismic data processing, the processing results indicate that it can help to improve seismic migration imaging. The study demonstrates that the geostatistical inversion method can provide a high- precision velocity model for formation pressure prediction, seismic data processing and interpretation, and guide the exploration and development of oil.

DOI: 10.15372/GiG2019168