Open AccessAutomatic Trend Tracking Model for Coalbed Methane Production Forecast
Author(s) -
Qingzhong Zhu,
Du Haiwei,
Qin Hu,
Bojiang Fan,
Jigang Wang,
Yu Jiasheng,
Hongli Wang
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1894/1/012105
Subject(s) - coalbed methane , production (economics) , tracking (education) , segmentation , econometrics , data mining , computer science , environmental science , petroleum engineering , artificial intelligence , engineering , mathematics , economics , coal , psychology , pedagogy , coal mining , macroeconomics , waste management
Nowadays, huge quantities of coalbed methane (CMB) well production data have been saved in the fields’ database, which declares that the industry of CBM enters the age of Big Data. The traditional gas production data analysis methods, such as the decline curve and type curve, are not effective for complex production conditions. So, we proposed an automatic segmentation trend tracking Model for the CBM production forecast, which is based on the production data and is more robust for the complex production condition.