深度学习及其在深层天然气储层预测中的应用实验

摘要

介绍深度学习的基本理论方法及基于地震数据深度学习的深层天然气储层预测.指出了深层油气储层的“三弱”特点和预测所涉及的问题与面临的困难;提出了深度学习的深网络构建与训练方法,基于地震数据深度学习的深层天然气储层预测进行实验.认为深度学习(Deeplearning)揭示对象内秉特征的能力,有助于发现使用现有方法难以发现的油气储层地震响应的内禀特征.同时探讨了基于地震数据深度学习的油气储层预测所涉及的关键性科学技术问题.%This paper introduces deep learning (DL) and deep gas reservoirs prediction based on the deep learning of seismic data.The paper introduces the "three weak" characteristics of deep oil and gas reservoirs and the key problems have to be dealt with in the reservoir recognition.The paper introduces the construction and training methods of deep network in deep learning,and an experimental result of deep gas reservoirs prediction based on the deep learning of seismic data.The experimental result shows that deep learning is of ability to reveal the intrinsic features of the seismic responses of hydrocarbon reservoirs.The paper also discusses the key scientific and technological issues involved in the prediction of deep oil and gas reservoirs using deep learning.