Drilling Rate Optimization by Automatic Lithology Prediction Using Hybrid Machine Learning
- سال انتشار: 1398
- محل انتشار: مجله علوم و فن آوری نفت، دوره: 9، شماره: 4
- کد COI اختصاصی: JR_JPSTR-9-4_006
- زبان مقاله: انگلیسی
- تعداد مشاهده: 66
نویسندگان
Department of petroleum engineering, Amirkabir University, Tehran, Iran
Department of Petroleum Engineering, Amirkabir University of Technology
چکیده
It is essential to obtain valuable information during drilling from the formation that is being drilled for rate optimization. In the drilling operation, the process of lithology and formation determination is extremely obscurant and it seems machine learning, as a novel prediction method that can model complicated situations having a high degree of uncertainty, could be beneficial. In this work, the real-time drilling data was applied to predict the formation type and lithology while drilling that formation using a genetic algorithm and Taguchi design of experiment optimized artificial neural network. Drilling data of twelve wells in one of Iranian gas fields were applied for this work. ۴۷۵۰۰ sets of data were selected, and after data control, ۳۱۲۰۰ data sets were selected as valid data and imported to artificial neural networks. For performing this research, by changing the network features and optimizing the structure of the network using the Taguchi method and optimizing the weight and biases of the network using the genetic algorithm, a unique artificial neural network was designed. The results show that the developed hybrid machine learning method can predict formation and lithology with a high degree of accuracy.کلیدواژه ها
Real-Time Drilling Data, Formation Lithology, Virtual Intelligence, Genetic Algorithm, design of experimentاطلاعات بیشتر در مورد COI
COI مخفف عبارت CIVILICA Object Identifier به معنی شناسه سیویلیکا برای اسناد است. COI کدی است که مطابق محل انتشار، به مقالات کنفرانسها و ژورنالهای داخل کشور به هنگام نمایه سازی بر روی پایگاه استنادی سیویلیکا اختصاص می یابد.
کد COI به مفهوم کد ملی اسناد نمایه شده در سیویلیکا است و کدی یکتا و ثابت است و به همین دلیل همواره قابلیت استناد و پیگیری دارد.