Here Bayes-Krijing estimation technique is studied to predict oil reservoir. The seismic data and the well data are combined in Bayes-Kerijing estimation to predict oil reservoir parameter.
本文提出贝叶斯-克里金估计技术可以将少量精度高的井点数据和大量精度低的地震数据有机结合，充分发挥各种数据的作用，完成对大范围的油藏参数的预测，提高预测精度。
参考来源 - 地下油藏的仿真与预测·2,447,543篇论文数据，部分数据来源于NoteExpress
Reservoir parameter of oil predict exactly is both one of the critical link of improving the effect of exploration and offering important basic data for the disposition and planning of development.
油藏储层参数的准确预测既是提高油田采收率的关键环节之一，又可为开发的部署与规划提供重要的基础数据。
Conclusion The method of parameter predict can provide a high quality oil pool geological model for reservoir fine evaluation.
结论基于神经网络模型的井间参数预测方法，可以为储层精细评价提供高质量的油藏地质模型。
Reservoir wettability is an important parameter for evaluating recoverable reserves and controlling fluid flow of a oil reservoir.
油藏润湿性是评估油藏可采储量，控制油藏流体流动行为的一个重要参数。
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