新疆石油地质 ›› 2022, Vol. 43 ›› Issue (zk(English)): 170-179.

• • 上一篇    

Seismic Prediction Method of Geological and Engineering Shale Oil Sweet Spots and Its Application in Fengcheng Formation of Mahu Sag

YU Jianglong, CHEN Gang, WU Junjun, LI Wei, YANG Sen, TANG Tingming   

  1. Research Institute of Exploration and Development, Xinjiang Oilfield Company, PetroChina, Karamay, Xinjiang 834000, China
  • 收稿日期:2022-08-16 修回日期:2022-09-23 出版日期:2023-01-01 发布日期:2023-07-28

Seismic Prediction Method of Geological and Engineering Shale Oil Sweet Spots and Its Application in Fengcheng Formation of Mahu Sag

YU Jianglong, CHEN Gang, WU Junjun, LI Wei, YANG Sen, TANG Tingming   

  1. Research Institute of Exploration and Development, Xinjiang Oilfield Company, PetroChina, Karamay, Xinjiang 834000, China
  • Received:2022-08-16 Revised:2022-09-23 Online:2023-01-01 Published:2023-07-28
  • About author:YU Jianglong, E-mail: wtyjl1991@163.com

摘要: In order to further accelerate the exploration and development of shale oil in the Lower Permian Fengcheng formation in the Mahu sag, Junggar basin, sweet spots of shale oil should be identified. Considering that lithology is the factor controlling geological sweet spots, and brittleness index and horizontal principal stress difference are the factors controlling engineering sweet spots, seismic methods of predicting geological and engineering sweet spots were established on the basis of prestack simultaneous inversion. In terms of geological sweet spots, by using core, experiment, drilling and logging data, the dominant lithology of shale oil sweet spots was identified to be dolomitic siltstone, the elastic parameters sensitive to the dominant lithology were selected, and the distribution of dolomitic siltstone was predicted by using prestack simultaneous inversion and lithofacies probability analysis. In terms of engineering sweet spots, using the Young's modulus and Poisson's ratio obtained from prestack simultaneous inversion, the brittleness index and in-situ stress in the study area were obtained through the Rickman brittleness index method and a combined spring model. The predicted results are consistent with the actual drilling results, demonstrating the accuracy of the prediction of geological and engineering sweet spots. The proposed methods can provide references for shale oil exploration and development in other areas.

关键词: Mahu sag, Fengcheng formation, shale oil, prestack simultaneous inversion, lithofacies probability analysis, brittleness index, combined spring model, in-situ stress

Abstract: In order to further accelerate the exploration and development of shale oil in the Lower Permian Fengcheng formation in the Mahu sag, Junggar basin, sweet spots of shale oil should be identified. Considering that lithology is the factor controlling geological sweet spots, and brittleness index and horizontal principal stress difference are the factors controlling engineering sweet spots, seismic methods of predicting geological and engineering sweet spots were established on the basis of prestack simultaneous inversion. In terms of geological sweet spots, by using core, experiment, drilling and logging data, the dominant lithology of shale oil sweet spots was identified to be dolomitic siltstone, the elastic parameters sensitive to the dominant lithology were selected, and the distribution of dolomitic siltstone was predicted by using prestack simultaneous inversion and lithofacies probability analysis. In terms of engineering sweet spots, using the Young's modulus and Poisson's ratio obtained from prestack simultaneous inversion, the brittleness index and in-situ stress in the study area were obtained through the Rickman brittleness index method and a combined spring model. The predicted results are consistent with the actual drilling results, demonstrating the accuracy of the prediction of geological and engineering sweet spots. The proposed methods can provide references for shale oil exploration and development in other areas.

Key words: Mahu sag, Fengcheng formation, shale oil, prestack simultaneous inversion, lithofacies probability analysis, brittleness index, combined spring model, in-situ stress