title: Ð£ÑÐºÐ¾ÑÐµÐ½Ð¸Ðµ ÑÐ°ÑÑÐµÑÐ¾Ð² Ð¸Ð½ÑÐµÐ³ÑÐ¸ÑÐ¾Ð²Ð°Ð½Ð½Ð¾Ð¹ Ð¼Ð¾Ð´ÐµÐ»Ð¸ Ð¼ÐµÑÑÐ¾ÑÐ¾Ð¶Ð´ÐµÐ½Ð¸Ñ Ð¿ÑÐ¸ Ð¿Ð¾Ð¼Ð¾ÑÐ¸ Ð°Ð»Ð³Ð¾ÑÐ¸ÑÐ¼Ð¾Ð² Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ
title: Ð²ÑÐ¿ÑÑÐºÐ½Ð°Ñ ÐºÐ²Ð°Ð»Ð¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¾Ð½Ð½Ð°Ñ ÑÐ°Ð±Ð¾ÑÐ° Ð¼Ð°Ð³Ð¸ÑÑÑÐ°
titleType: Subtitle
title: Acceleration of calculations of integrated field models using machine learning methods
Creators: name: ÐÐµÑÐºÐ¾, ÐÐ¾Ð½ÑÑÐ°Ð½ÑÐ¸Ð½
Publisher: name: Ð¡Ð°Ð½ÐºÑ-ÐÐµÑÐµÑÐ±ÑÑÐ³ÑÐºÐ¸Ð¹ Ð¿Ð¾Ð»Ð¸ÑÐµÑÐ½Ð¸ÑÐµÑÐºÐ¸Ð¹ ÑÐ½Ð¸Ð²ÐµÑÑÐ¸ÑÐµÑ ÐÐµÑÑÐ° ÐÐµÐ»Ð¸ÐºÐ¾Ð³Ð¾
Year: 2022
Subjects: ÐÑÐºÑÑÑÑÐ²ÐµÐ½Ð½ÑÐ¹ Ð¸Ð½ÑÐµÐ»Ð»ÐµÐºÑ
ÐÐ¾Ð´ÐµÐ»Ð¸ÑÐ¾Ð²Ð°Ð½Ð¸Ðµ
ÐÐµÑÑÐ¾ÑÐ¾Ð¶Ð´ÐµÐ½Ð¸Ñ Ð¿Ð¾Ð»ÐµÐ·Ð½ÑÑ Ð¸ÑÐºÐ¾Ð¿Ð°ÐµÐ¼ÑÑ
Ð¸Ð½ÑÐµÐ³ÑÐ¸ÑÐ¾Ð²Ð°Ð½Ð½Ð¾Ðµ Ð¼Ð¾Ð´ÐµÐ»Ð¸ÑÐ¾Ð²Ð°Ð½Ð¸Ðµ
ÑÐµÑÐ°ÑÑÐ¸Ð¹ Ð»ÐµÑ
Ð³ÑÐ°Ð´Ð¸ÐµÐ½ÑÐ½ÑÐ¹ Ð±ÑÑÑÐ¸Ð½Ð³
integrate model
decision tree
gradient boosting

description: Ð¢ÐµÐ¼Ð° Ð²ÑÐ¿ÑÑÐºÐ½Ð¾Ð¹ ÐºÐ²Ð°Ð»Ð¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¾Ð½Ð½Ð¾Ð¹ ÑÐ°Ð±Ð¾ÑÑ: "Ð£ÑÐºÐ¾ÑÐµÐ½Ð¸Ðµ ÑÐ°ÑÑÐµÑÐ¾Ð² Ð¸Ð½ÑÐµÐ³ÑÐ¸ÑÐ¾Ð²Ð°Ð½Ð½ÑÑ Ð¼Ð¾Ð´ÐµÐ»ÐµÐ¹ Ð¼ÐµÑÑÐ¾ÑÐ¾Ð¶Ð´ÐµÐ½Ð¸Ñ Ð¼ÐµÑÐ¾Ð´Ð°Ð¼Ð¸ Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ". ÐÐ¾Ð´ÐµÐ»Ð¸ÑÐ¾Ð²Ð°Ð½Ð¸Ðµ ÑÐºÐ²Ð°Ð¶Ð¸Ð½, Ð² ÑÐ°ÑÑÐ½Ð¾ÑÑÐ¸ Ð¿ÑÐ¾Ð³Ð½Ð¾Ð·Ð¸ÑÐ¾Ð²Ð°Ð½Ð¸Ðµ Ð·Ð°Ð±Ð¾Ð¹Ð½Ð¾Ð³Ð¾ Ð´Ð°Ð²Ð»ÐµÐ½Ð¸Ñ, ÑÐ²Ð»ÑÐµÑÑÑ Ð²Ð°Ð¶Ð½Ð¾Ð¹ Ð·Ð°Ð´Ð°ÑÐµÐ¹, ÑÐ¸Ð¿Ð¸ÑÐ½Ð¾Ð¹ Ð¿ÑÐ¸ Ð¸Ð½ÑÐµÐ³ÑÐ¸ÑÐ¾Ð²Ð°Ð½Ð½Ð¾Ð¼ Ð¼Ð¾Ð´ÐµÐ»Ð¸ÑÐ¾Ð²Ð°Ð½Ð¸Ð¸ Ð°ÐºÑÐ¸Ð²Ð¾Ð² (ÐÐÐ). Ð¡ÐºÐ²Ð°Ð¶Ð¸Ð½Ð°, ÐºÐ°Ðº ÑÐ»ÐµÐ¼ÐµÐ½Ñ, ÑÐ²ÑÐ·ÑÐ²Ð°ÑÑÐ¸Ð¹ Ð¿Ð»Ð°ÑÑ Ñ Ð½Ð°Ð·ÐµÐ¼Ð½Ð¾Ð¹ ÑÐµÑÑÑ ÑÐ±Ð¾ÑÐ° Ð´Ð¾Ð»Ð¶Ð½Ð° Ð¾Ð¿Ð¸ÑÑÐ²Ð°ÑÑ Ð´Ð²Ð¸Ð¶ÐµÐ½Ð¸Ðµ Ð´Ð²ÑÑÑÐ°Ð·Ð½Ð¾Ð³Ð¾ ÑÐ»ÑÐ¸Ð´Ð° ÑÐµÑÐµÐ· Ð½ÐµÑ. ÐÐ»Ñ Ð²ÑÐ±Ð¾ÑÐ° ÑÐµÐ¶Ð¸Ð¼Ð° ÑÐ°Ð±Ð¾ÑÑ ÑÐºÐ²Ð°Ð¶Ð¸Ð½Ñ Ð½ÐµÐ¾Ð±ÑÐ¾Ð´Ð¸Ð¼Ð¾ Ð¾Ð¿Ð¸ÑÐ°ÑÑ Ð·Ð°Ð²Ð¸ÑÐ¸Ð¼Ð¾ÑÑÑ Ð·Ð°Ð±Ð¾Ð¹Ð½Ð¾Ð³Ð¾ Ð´Ð°Ð²Ð»ÐµÐ½Ð¸Ñ Ð¾Ñ Ð¿ÑÐ¾Ð¼ÑÑÐ»Ð¾Ð²ÑÑ Ð¿Ð°ÑÐ°Ð¼ÐµÑÑÐ¾Ð². ÐÐ»Ð°ÑÑÐ¸ÑÐµÑÐºÐ¸Ð¼ Ð¿Ð¾Ð´ÑÐ¾Ð´Ð¾Ð¼ ÑÐ²Ð»ÑÐµÑÑÑ Ð¿ÑÑÐ¼Ð¾Ð¹ ÑÐ°ÑÑÐµÑ Ð¿Ð¾ ÑÐ¼Ð¿Ð¸ÑÐ¸ÑÐµÑÐºÐ¸Ð¼ ÐºÐ¾ÑÑÐµÐ»ÑÑÐ¸ÑÐ¼ â ÑÐ¸Ð·Ð¸ÑÐµÑÐºÐ¸Ð¼ ÑÑÐ°Ð²Ð½ÐµÐ½Ð¸ÑÐ¼, Ð¿Ð¾ÑÑÑÐ¾ÐµÐ½Ð½ÑÑ Ð¿Ð¾ ÑÐºÑÐ¿ÐµÑÐ¸Ð¼ÐµÐ½ÑÐ°Ð»ÑÐ½ÑÐ¼ Ð´Ð°Ð½Ð½ÑÐ¼, Ð»Ð¸Ð±Ð¾ Ð¿Ð¾ Ð¼ÐµÑÐ°Ð½Ð¸ÑÑÐ¸ÑÐµÑÐºÐ¸Ð¼ Ð¼Ð¾Ð´ÐµÐ»ÑÐ¼, Ð¾ÑÐ½Ð¾Ð²Ð°Ð½Ð½ÑÑ Ð½Ð° ÑÐ¸Ð·Ð¸ÑÐµÑÐºÐ¸Ñ Ð·Ð°ÐºÐ¾Ð½Ð°Ñ. ÐÐ½Ð¸ ÑÑÐµÐ±ÑÐµÑ Ð±Ð¾Ð»ÑÑÐ¸Ñ Ð²ÑÑÐ¸ÑÐ»Ð¸ÑÐµÐ»ÑÐ½ÑÑ Ð¼Ð¾ÑÐ½Ð¾ÑÑÐµÐ¹, ÑÐºÑÐ¿ÐµÑÑÐ¸Ð·Ñ ÑÐ¿ÐµÑÐ¸Ð°Ð»Ð¸ÑÑÐ° Ð¿ÑÐ¸ Ð¿Ð¾ÑÑÑÐ¾ÐµÐ½Ð¸Ð¸ Ð¸ Ð°Ð´Ð°Ð¿ÑÐ°ÑÐ¸Ð¸ Ð¼Ð¾Ð´ÐµÐ»Ð¸ Ð¸, ÐºÐ°Ðº ÑÐ»ÐµÐ´ÑÑÐ²Ð¸Ðµ, Ð±Ð¾Ð»ÑÑÐ¸Ñ Ð²ÑÐµÐ¼ÐµÐ½Ð½ÑÑ ÑÐµÑÑÑÑÐ¾Ð².Â Ð¦ÐµÐ»ÑÑ ÑÐ°Ð±Ð¾ÑÑ ÑÐ²Ð»ÑÐµÑÑÑ ÑÐ¾ÐºÑÐ°ÑÐµÐ½Ð¸Ðµ Ð¸ÑÐ¿Ð¾Ð»ÑÐ·Ð¾Ð²Ð°Ð½Ð¸Ñ Ð·Ð°ÑÑÐ±ÐµÐ¶Ð½ÑÑ Ð´Ð¾ÑÐ¾Ð³Ð¾ÑÑÐ¾ÑÑÐ¸Ñ Ð¿ÑÐ¾Ð³ÑÐ°Ð¼Ð¼Ð½ÑÑ Ð¿Ð°ÐºÐµÑÐ¾Ð² Ð¸ ÑÑÐºÐ¾ÑÐµÐ½Ð¸Ðµ ÑÐ¾Ð·Ð´Ð°Ð½Ð¸Ñ ÐÐÐ. Ð ÑÑÐ°ÑÑÐµ Ð¿ÑÐµÐ´Ð»Ð°Ð³Ð°ÐµÑÑÑ Ð½Ð¾Ð²ÑÐ¹ Ð¿Ð¾Ð´ÑÐ¾Ð´ Ð¼Ð¾Ð´ÐµÐ»Ð¸ÑÐ¾Ð²Ð°Ð½Ð¸Ñ ÑÐºÐ²Ð°Ð¶Ð¸Ð½Ñ Ð² ÑÐ°Ð¼ÐºÐ°Ñ ÐÐÐ. ÐÑÐ¸ Ð¿Ð¾Ð¼Ð¾ÑÐ¸ Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ Ð¾Ð¿Ð¸ÑÑÐ²Ð°ÑÑ ÑÐºÐ²Ð°Ð¶Ð¸Ð½Ñ ÐºÐ°Ðº Ð·Ð°Ð²Ð¸ÑÐ¸Ð¼Ð¾ÑÑÑ Ð·Ð°Ð±Ð¾Ð¹Ð½Ð¾Ð³Ð¾ Ð´Ð°Ð²Ð»ÐµÐ½Ð¸Ñ Ð¾Ñ Ð´ÐµÐ±Ð¸ÑÐ° Ð¶Ð¸Ð´ÐºÐ¾ÑÑÐ¸, Ð¾Ð±Ð²Ð¾Ð´Ð½ÐµÐ½Ð½Ð¾ÑÑÐ¸, Ð³Ð°Ð·Ð¾Ð²Ð¾Ð³Ð¾ ÑÐ°ÐºÑÐ¾ÑÐ° Ð¸ ÑÑÑÑÐµÐ²Ð¾Ð³Ð¾ Ð´Ð°Ð²Ð»ÐµÐ½Ð¸Ñ.Â Ð¡ÐºÐ²Ð°Ð¶Ð¸Ð½Ð° ÑÐ¸Ð¼ÑÐ»Ð¸ÑÑÐµÑÑÑ Ð¿ÑÐ¸ Ð¿Ð¾Ð¼Ð¾ÑÐ¸ Ð¼Ð¾Ð´ÐµÐ»Ð¸ Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ ÑÐ¸Ð¿Ð° Â«Ð¡Ð»ÑÑÐ°Ð¹Ð½ÑÐ¹ Ð»ÐµÑÂ», ÑÐ¾ÑÑÐ¾ÑÑÐµÐ¹ Ð¸Ð· Ð°ÑÑÐ°Ð¼Ð±Ð»ÐµÐ¸ Â«ÐÐµÑÐµÐ²ÑÐµÐ² ÑÐµÑÐµÐ½Ð¸Ð¹Â» Ñ Ð¿ÑÐ¸Ð¼ÐµÐ½ÐµÐ½Ð¸ÐµÐ¼ ÑÐµÑÐ½Ð¸ÐºÐ¸ Ð³ÑÐ°Ð´Ð¸ÐµÐ½ÑÐ½Ð¾Ð³Ð¾ Ð±ÑÑÑÐ¸Ð½Ð³Ð°. Ð ÐºÐ°ÑÐµÑÑÐ²Ðµ Ð¿ÑÐ¸Ð·Ð½Ð°ÐºÐ¾Ð² Ð¸ÑÐ¿Ð¾Ð»ÑÐ·ÑÑÑÑÑ ÑÐ¸ÑÐ»ÐµÐ½Ð½ÑÐµ Ð·Ð½Ð°ÑÐµÐ½Ð¸Ñ Ð´ÐµÐ±Ð¸ÑÐ° Ð¶Ð¸Ð´ÐºÐ¾ÑÑÐ¸, Ð¾Ð±Ð²Ð¾Ð´Ð½ÐµÐ½Ð½Ð¾ÑÑÐ¸, Ð³Ð°Ð·Ð¾Ð²Ð¾Ð³Ð¾ ÑÐ°ÐºÑÐ¾ÑÐ° Ð¸ ÑÑÑÑÐµÐ²Ð¾Ð³Ð¾ Ð´Ð°Ð²Ð»ÐµÐ½Ð¸Ñ, Ð° Ð² ÐºÐ°ÑÐµÑÑÐ²Ðµ ÑÐµÐ»ÐµÐ²Ð¾Ð¹ Ð¿ÐµÑÐµÐ¼ÐµÐ½Ð½Ð¾Ð¹ Ð·Ð°Ð±Ð¾Ð¹Ð½Ð¾Ðµ Ð´Ð°Ð²Ð»ÐµÐ½Ð¸Ðµ. ÐÑÐ¾Ð³ÑÐ°Ð¼Ð¼Ð½Ð°Ñ ÑÐ°ÑÑÑ ÑÐµÐ°Ð»Ð¸Ð·Ð¾Ð²Ð°Ð½Ð° ÑÑÐµÐ´ÑÑÐ²Ð°Ð¼Ð¸ ÑÐ·ÑÐºÐ° python Ð¿ÑÐ¸ Ð¿Ð¾Ð¼Ð¾ÑÐ¸ Ð±Ð¸Ð±Ð»Ð¸Ð¾ÑÐµÐºÐ¸. Ð Ð°Ð·ÑÐ°Ð±Ð¾ÑÐ°Ð½Ð½Ð°Ñ Ð¼Ð¾Ð´ÐµÐ»Ñ Ð±ÑÐ»Ð° Ð¿ÑÐ¾ÑÐµÑÑÐ¸ÑÐ¾Ð²Ð°Ð½Ð° Ð½Ð° ÑÐ¸Ð½ÑÐµÑÐ¸ÑÐµÑÐºÐ¸Ñ Ð¸ ÑÐµÐ°Ð»ÑÐ½ÑÑ Ð´Ð°Ð½Ð½ÑÑ ÑÐ°Ð·Ð»Ð¸ÑÐ½ÑÑ Ð¼ÐµÑÑÐ¾ÑÐ¾Ð¶Ð´ÐµÐ½Ð¸Ð¹. ÐÑÐµÐ´Ð»Ð°Ð³Ð°ÐµÐ¼ÑÐ¹ Ð¿Ð¾Ð´ÑÐ¾Ð´ Ð¿ÑÐµÐ²Ð¾ÑÑÐ¾Ð´Ð¸Ñ ÑÐµÐºÑÑÐ¸Ðµ ÑÐµÑÐµÐ½Ð¸Ñ Ð² ÑÐºÐ¾ÑÐ¾ÑÑÐ¸ ÑÐ°ÑÑÐµÑÐ° Ð¸ Ð¿ÑÐµÐ´ÑÐºÐ°Ð·Ð°ÑÐµÐ»ÑÐ½Ð¾Ð¹ ÑÐ¿Ð¾ÑÐ¾Ð±Ð½Ð¾ÑÑÐ¸, Ð° ÑÐ°ÐºÐ¶Ðµ Ð¿Ð¾Ð·Ð²Ð¾Ð»ÑÐµÑ Ð¸ÑÐ¿Ð¾Ð»ÑÐ·Ð¾Ð²Ð°ÑÑ Ð¼ÐµÐ½ÑÑÐµÐµ ÐºÐ¾Ð»Ð¸ÑÐµÑÑÐ²Ð¾ Ð´Ð¾ÑÐ¾Ð³Ð¾ÑÑÐ¾ÑÑÐ¸Ñ Ð»Ð¸ÑÐµÐ½Ð·Ð¸Ð¹ Ð¸ Ð² ÑÐ»ÑÑÐ°Ðµ Ð¸ÑÐ¿Ð¾Ð»ÑÐ·Ð¾Ð²Ð°Ð½Ð¸Ñ ÑÐµÐ°Ð»ÑÐ½ÑÑ Ð´Ð°Ð½Ð½ÑÑ Ð¿Ð¾Ð·Ð²Ð¾Ð»ÑÐµÑ Ð½Ðµ ÑÐ¾Ð·Ð´Ð°Ð²Ð°ÑÑ Ð¼Ð¾Ð´ÐµÐ»Ð¸ ÑÐºÐ²Ð°Ð¶Ð¸Ð½ Ð² ÑÐ¸Ð¼ÑÐ»ÑÑÐ¾ÑÐ°Ñ.ÐÐ»Ð°Ð³Ð¾Ð´Ð°ÑÑ Ð²ÑÑÐ¾ÐºÐ¾Ð¹ Ð¿ÑÐµÐ´ÑÐºÐ°Ð·Ð°ÑÐµÐ»ÑÐ½Ð¾Ð¹ ÑÐ¿Ð¾ÑÐ¾Ð±Ð½Ð¾ÑÑÐ¸ Ð¿ÑÐµÐ´Ð»Ð°Ð³Ð°ÐµÐ¼ÑÐ¹ Ð°Ð»Ð³Ð¾ÑÐ¸ÑÐ¼ Ð±ÑÐ´ÐµÑ Ð²Ð½ÐµÐ´ÑÐµÐ½ Ð² Ð¿ÑÐ¾Ð¸Ð·Ð²Ð¾Ð´ÑÑÐ²ÐµÐ½Ð½ÑÐµ Ð¿ÑÐ¾ÑÐµÑÑÑ Ð² ÐºÐ°ÑÐµÑÑÐ²Ðµ Ð¼Ð¾Ð´ÐµÐ»Ð¸ ÑÐºÐ²Ð°Ð¶Ð¸Ð½Ñ Ð¿ÑÐ¸ ÑÐ¾Ð·Ð´Ð°Ð½Ð¸Ð¸ Ð¸Ð½ÑÐµÐ³ÑÐ¸ÑÐ¾Ð²Ð°Ð½Ð½Ð¾Ð¹ Ð¼Ð¾Ð´ÐµÐ»Ð¸ Ð¼ÐµÑÑÐ¾ÑÐ¾Ð¶Ð´ÐµÐ½Ð¸Ñ.
description: The subject of the graduate qualification work is "Acceleration of calculations of integrated field models using machine learning methods". Bottom hole pressure prediction is crucial issue in integrated field modeling. The well is connection element between surface network and reservoir. It must describe the movement of a two-phase fluid in the wellbore. To control the well production, it is necessary to describe the dependence of the bottom hole pressure on the fluid and well parameters. The classical approach is direct calculation by empirical correlation - physical equation constructed from experimental data. It requires large computing power, expert opinion and as a result large time resources.Â This article proposes a new approach to well modeling. Using machine learning describe the well as the dependence of bottomhole pressure on fluid flow rate, water cut, GOR and wellhead pressure.Â Materials and methods. The well model was implemented using the Â«Random ForestÂ» assembly of Â«Decision TreesÂ» using the gradient boosting technique. The model was tested on synthetic and real data from various fields.Â The developed model was tested on synthetic and real field data. The proposed approach outperforms current solutions in terms of speed and prediction score. It also allows to reduce usage of expensive licenses. In case of enough data the need to create models in simulator is lost. Due to its high predictive ability, the proposed algorithm will be introduced into production processes as a well model for the needs of integrated asset modeling.