基于神经网络的油气钻井浅层气识别方法研究  

Research on the Identification Method of Shallow Gas in Oil and Gas Drilling Based on Neural Network

作　　者：张祯祥 Zhang Zhenxiang(Sinopec Research Institute of Petroleum Engineering Co.,Ltd.,Beijing 102206)

机构地区：[1]中石化石油工程技术研究院有限公司,北京102206

出　　处：《石化技术》2025年第3期251-253,共3页Petrochemical Industry Technology

基　　金：国家重点研发计划项目“极地钻井浅层地质灾害风险识别及防控技术”(项目编号:2022YFC2806401);中国石化科技攻关项目“莺琼盆地高温高压井钻探关键技术研究”(P23191)。

摘　　要：我国南海深水油气资源丰富,然而深水地质环境复杂,深水油气钻井作业时常遭遇浅层气地质灾害。常规浅层气识别技术依赖于地震振幅等单一属性,易导致结果存在不确定性及多解性。为提高深水油气钻井浅层气灾害识别精准度,以振幅、频率等多种地震属性作为输入特征参数,利用BP神经网络对深水钻井过程中可能遭遇的浅层气地质灾害进行识别。分析结果表明,基于BP神经网络的深水钻井浅层气灾害识别准确率可达90.2%,识别精度较常规方法提高10%~15%,充分说明BP神经网络对浅层气识别具有显著的适用性与可靠性,为深水油气安全钻井作业提供技术指导。Deepwater oil and gas resources are abundant in the South China Sea.However,the deepwater geological environment is complex,and shallow gas geological disasters are frequently encountered during deepwater oil and gas drilling operations.Conventional shallow gas identification techniques rely on single attributes such as seismic amplitude,which easily leads to uncertainties and multiple solutions in the results.In order to improve the accuracy of identifying shallow gas disasters in deepwater oil and gas drilling,multiple seismic attributes such as amplitude and frequency are used as input characteristic parameters,and the BP neural network is utilized to identify the shallow gas geological disasters that may be encountered during deepwater drilling.The analysis results show that the accuracy rate of identifying shallow gas disasters in deepwater drilling based on the BP neural network can reach 90.2%,and the identification accuracy is 10%~15%higher than that of conventional methods.This fully demonstrates that the BP neural network has significant applicability and reliability for shallow gas identification and provides technical guidance for safe deepwater drilling operations.

关 键 词：油气钻井 浅层气 BP神经网络 精准识别 

分 类 号：TE52[石油与天然气工程—油气田开发工程]