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我国页岩气开发技术工程化实现的学习曲线研究 被引量:8

The Research on the Learning Curve of Technology Engineering Implementation for Shale Gas Development in China
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摘要 技术学习是实现页岩气开发技术工程化的重要途径,开发技术工程化是实现规模化商业开发的前提。页岩气开发极大地区别于常规油气,具有显著的技术学习效应。依据涪陵页岩气田实地调研数据,拟合不同开发阶段对应井别的钻井总成本学习曲线,并与传统的技术学习曲线进行了对比分析。研究发现,开发早期相对中后期,技术学习速率更高,钻井成本变动更剧烈;考虑规模效应时,钻井成本变动较为平缓,但技术学习的间接作用则更为明显。 Technological learning is the important road to realize shale gas development technology engineering,and technology engineering is the premise to realize large- scale commercial development. There are many differences in technology learning effect between conventional and unconventional oil and gas resources. Technology learning curve traditionally describes the relationship between marginal cost and the quantity of well drilled,which can not reflect changes in drilling costs caused by uncertainties coming from factors such as geology condition,technology and environment. Based on realization of technology engineering,the present paper identifies the effect approach of technology learning to drilling cost by two ways:direct technology scale effect and indirect effect caused by reducing possibility of uncertainties,rising success rate of well-drilling,and reducing sunk cost of well- drilling as well as mechanism and evolution process. Through so- site survey and expert interviews,this paper describes total cost learning curve corresponding to different functional wells. Compared with traditional technology learning curve,we find that at the early stage of shale gas development,there is a high technology learning rate with drilling cost fluctuation. When only taking scale effect of technology learning into account,there are little changes in drilling cost,and indirect effect of technology learning on drilling cost increases technology learning effect dramatically.
出处 《科技管理研究》 CSSCI 北大核心 2016年第3期118-122,共5页 Science and Technology Management Research
基金 国家自然科学基金资助项目"我国非常规油气开发技术工程化实现的投资激励策略研究"(71473193)
关键词 页岩气 开发成本 技术学习 技术能力 不确定性问题 shale gas extraction cost technology learning curve technical capacity uncertainty
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