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  • Automated Well Monitoring: From Data Pre-processing to Well Performance Profile

    Wednesday, April 10, 2024, 06:00 PM - 08:00 PM CET
    Presented by Anton Shchipanov (NORCE – Norwegian Research Centre, Stavanger, Norway) Abstract: Automated well operations is a rapidly growing area with recent progress in automated drilling extending now into automated well monitoring and control during production operations. In reservoir engineering, although the industry continues to guide decision making processes mainly based on physics-based models and simulations, the focus of further developments of the industrial workflows has shifted towards hybrid solutions incorporating machine learning and big data analytics. Development of such solutions requires new approaches to integrate the reservoir physics into the workflows suitable for machine learning and big data analytics. We present one of such hybrid solutions focused on well monitoring using pressure and rate measurements with permanent gauges and flowmeters. Data-driven methods employed for data preprocessing like automated pressure transient identification and recognition of patterns in time - lapse pressure responses are combined with physics-informed methods used to evaluate well performance. Application of this hybrid workflow is illustrated with well examples from the Norwegian Continental Shelf. Potential application areas of this automated workflow include analysis of big well datasets already accumulated in the industry, on-the-fly data interpretation with real-time alarming of performance issues as well as providing input data for full-field reservoir simulations. Biography: Dr. Anton Shchipanov is a chief scientist at NORCE (Norwegian Research Centre) in Stavanger, Norway. Anton has been participating and managing R&D and consultancy projects for 20+ years and is a co-author of 30+ papers published. His research interests include well and reservoir monitoring and simulation within oil and gas, geological carbon storage and geothermal energy.

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    Stavanger, Norway

  • Early Kick Detection: Sensors, Data Acquisition, and Analysis

    Wednesday, May 15, 2024, 06:00 PM - 08:00 PM CET
    Early Kick Detection: Sensors, Data Acquisition, and Analysis By Distinguished Lecturer Jaideva Goswami (NOV) Abstract: One key message from this lecture: Kicks can be catastrophic, but recent and future developments in sensor technology, data processing, and telemetry are enabling timely identification and mitigation plans. A kick or an influx may be defined as an unintended flow of formation fluid into the borehole. It occurs when the wellbore pressure falls below the formation pore pressure. Not all kicks are dangers; however, an uncontrolled kick can lead to catastrophic events. A reliable early kick detection and monitoring system is critical to maintaining wellbore stability. Typically, the gain in pit volume and change in flow rate serve as some of the primary kick indicators. Secondary indicators include borehole pressure, temperature, resistivity, mud properties, and cuttings. While the gain in pit volume can indicate the kick with higher reliability, the downhole measurements in conjunction with high-speed telemetry and advanced real-time processing algorithms can be an effective early warning system, enabling timely mitigation plans. This lecture begins with some basics of wellbore stability, kick indicators, and monitoring systems. Various downhole sensor measurements and their relevance to kick detection are discussed. Both experimental and field examples are presented to illustrate the methodology. Pressure data are analyzed to estimate change in density and correlate it with the type, location, and evolution of the influx along the wellbore. Some innovative ideas on sensor design and real-time data processing for event detection and uncertainty quantification are discussed. Biography: Jaideva Goswami received his Ph.D. in Electrical Engineering from Texas A&M University in 1995. He is a Chief Scientist at NOV Inc, Houston. Previously, he was an Engineering Advisor and a Global Métier Manager at Schlumberger. He was also a Professor at the Indian Institute of Technology (IIT), Kharagpur, and has held academic positions at the University of Illinois, Urbana-Champaign and IIT, Kanpur. He has many publications and patents in the areas of electromagnetics, signal processing, sensor design, inverse problems, nuclear magnetic resonance, geophysical measurements, and interpretation. Dr. Goswami is a Fellow of the Institute of Electrical and Electronics Engineers.

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    Stavanger, Norway