训练图像对多点地质统计反演效果的影响

The Influence of Training Images on the Effect of Multipoint Geostatistical Inversion

摘要: 油气储层建模已经由两点统计发展为多点统计建模。相应的，基于多点地质统计学的储层反演方法也得到了开发。由于训练图像对建模有重要影响。本文以多点地质统计反演中关键输入参数训练图像为对象，探讨其对反演结果的影响。通过设计三种不同类型的训练图像，即与实际储层一致的训练图像；与实际储层结构一致但储层分布位置存在差异的训练图像；将实际储层旋转90度的训练图像。开展多点反演并比较其反演效果。结果表明，训练图像越准确，多点地质统计反演结果收敛速度快，反演误差小；而训练图像越不符合实际，则模拟收敛慢，耗时长，模拟误差大。训练图像结构符合实际情况时，其分布位置差异对反演结果影响不大。

Abstract: The stochastic modeling is developed from two point geostatistics to multi-point geostatistics, and a seismic inversion method based on multi-point geostatistics is proposed. Since the training image is the key of multi-point geostatistical modeling, it directly determines the quality of the modeling results. An evaluation of training image in inversion is necessary. Three different training image is designed to reveal the influence on inversion result, that is, a training image same to the real reservoir, a training image reflecting the structure of the real reservoir, and a rotation of 90 degree which is different to the real reservoir. The results show that the training image has a great influence on the convergence speed of the multi-point geostatistical inversion, and the more ac-curate the training image is, the faster convergence speed of the multi-point geostatistical inversion is. The place of the lithofacies has little influence unless they have different structure.