學(xué)術(shù)報告
報告題目： Using Distributed Acoustic Sensor by Fiber Optic Sensing Technology for Fracture Diagnosis
報 告 人：Ding Zhu 教授，博士生導(dǎo)師，SPE杰出會員
時 間： 2019年4月3日（周三）上午8:30-10:00
地 點：國家重點實驗室A403學(xué)術(shù)報告廳
報告人單位：美國德州農(nóng)工大學(xué)石油工程系
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報告內(nèi)容：Downhole sensing technology today provide engineers continuous measurements for flow condition diagnosis. The measurements include temperature, pressure, acoustic, and strain, with distributed temperature sensors (DTS) and distributed acoustic sensors (DAS) being more commonly used compared with other measurements. Since the optical fiber technology introduced to the industry, it has advanced dramatically. Many field applications have been proven effective and beneficial. From downhole flow condition characterization, we can diagnose flow problems, monitor, control, and optimize producing and injecting well performance, monitor well stimulation, both matrix acidizing and hydraulic fracturing, and optimize treatment designs. There are rich field application examples to show the potential of the technology.
One of the keys of applying downhole sensing technology is to develop models and methodologies to interpret the senor measurements. This is challenging, because from data collection and processing, to model development, to invert the measured parameters to flow profiles, it is extremely mathematical and computationally intensive. In this lecture, we will review current status of downhole sensing technology, explain the available models and approaches for interpretation, and present field application examples including production profiling, horizontal well flow control, matrix acidizing optimization and multi-stage hydraulic fracture diagnosis. The lecture is based on publications by the author and other SPE publications. The lecture illustrates the power of DTS as a tool for production problem diagnosis and well performance optimization.
Initial DAS interpretation model of flow distribution was developed to compare with the DTS interpretation. The across-interpretation of DTS and DAS confirms that approach and decreases the uncertainty of interpretation.
報告人簡介:
Ding Zhu is a Professor the Harold Vance Department of Petroleum Engineering at Texas A&M University. She Holds a BS degree in mechanical engineering from the University of Science and Technology, Beijing, China, a MS and PhD degree in Petroleum Engineering, both from the University of Texas at Austin. Her research areas are production engineering, well stimulation, intelligent well modeling and complex well-performance optimization. Dr. Zhu is an author of more than 160 technical papers, a co-author of three text books, Petroleum Production Systems (2nd edition), SPE book Multilateral Wells, and Modern Completion Technology for Oil and Gas Wells. She has been a committee member and chairperson for many conferences and events with Society of Petroleum Engineers, and is currently an associate editor for SPE Production and Operation Journal. She is a Distinguished Member of SPE.
油氣藏地質(zhì)及開發(fā)工程國家重點實驗室
西南石油大學(xué)科研處
石油與天然氣工程學(xué)院
SPE成都分會
西南石油大學(xué)SPE學(xué)生分會
2019年3月26日
