Thin-interbedded reservoirs prediction based on seismic sedimentology
지진 퇴적학에 기초한 얇은 상호층 매장층 예측
Predicción del reservorio delgado basado en la sedimentología sísmica
Prédiction de réservoirs interlits minces basée sur la sédimentologie sismique
прогноз тонких межслойных коллекторов на основе сейсмических отложений
Changkuan NI 倪长宽 ¹ ², Mingjun SU 苏明军 ¹, Cheng YUAN 袁成 ¹, Huaqing LIU 刘化清 ¹, Xiangli CUI 崔向丽 ¹
¹ Research Institute of Petroleum Exploration and Development-Northwest (NWGI), PetroChina, Lanzhou 730020, China
中国 兰州 中国石油天然气股份有限公司 勘探开发研究院西北分院
² University of Electronic Science and Technology, Chengdu 611731, China
中国 成都 电子科技大学
Petroleum Exploration and Development, 20 June 2022
Interference of thin-interbedded layers in seismic reflections has great negative impact on thin-interbedded reservoirs prediction. To deal with this, two novel methods are proposed that can predict the thin-interbedded reservoirs distribution through strata slices by suppressing the interference of adjacent layer with the help of seismic sedimentology.
The plane distribution of single sand bodies in thin-interbedded reservoirs can be clarified. (1) The minimum interference frequency slicing method, uses the amplitude-frequency attribute estimated by wavelet transform to find a constant seismic frequency with the minimum influence on the stratal slice of target layer, and then an optimal slice corresponding the constant frequency mentioned above can be obtained. (2) The superimposed slicing method can calculate multiple interference coefficients of reservoir and adjacent layers of target geological body, and obtain superimposed slice by weighted stacking the multiple stratal slices of neighboring layers and target layer.
The two proposed methods were used to predict the distribution of the target oil layers of 6 m thick in three sets of thin-interbedded reservoirs of Triassic Kelamayi Formation in the Fengnan area of Junggar Basin, Northwestern China. A comparison with drilling data and conventional stratal slices shows that the two methods can predict the distribution of single sand bodies in thin-interbedded reservoirs more accurately.