Casing Damage Prediction Model Based on the Data-Driven Method
المؤلفون المشاركون
Yan, Wei
Tan, Chaodong
Tang, Qing
Wu, Hua
Bu, Hongguang
Kambi, Said Juma
Liu, Jiankang
المصدر
Mathematical Problems in Engineering
العدد
المجلد 2020، العدد 2020 (31 ديسمبر/كانون الأول 2020)، ص ص. 1-9، 9ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2020-08-26
دولة النشر
مصر
عدد الصفحات
9
التخصصات الرئيسية
الملخص EN
Casing damage caused by sand production in unconsolidated sandstone reservoirs often results in oil wells unable to produce normally.
However, due to the complex mechanism of sheath damage caused by sand production, there is no more mature technology for predicting the risk of casing damage in advance.
Data-driven method can better integrate various factors and use a large amount of historical data to solve complex classification prediction problems.
In this paper, XGBoost and LightGBM algorithms are used to establish casing damage prediction models, and 13 model application experiments are carried out to optimize the set of casing damage factors.
These two algorithms are used to calculate the feature importance of each factor and determine the final set of factors.
The evaluation results of five key metrics show that both prediction models show good performance, and the prediction accuracy is 0.99 for the XGBoost model and 0.94 for the LightGBM model.
Applying the established prediction model can determine reasonable range of the maximum daily liquid production of a single layer (Qlmax) to reduce the probability of casing damage.
In addition, at certain Qlmax, increasing the perforation density can significantly reduce the probability of casing damage.
Therefore, increasing the perforation density can achieve high production without causing casing damage.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Tan, Chaodong& Yan, Wei& Tang, Qing& Wu, Hua& Bu, Hongguang& Kambi, Said Juma…[et al.]. 2020. Casing Damage Prediction Model Based on the Data-Driven Method. Mathematical Problems in Engineering،Vol. 2020, no. 2020, pp.1-9.
https://search.emarefa.net/detail/BIM-1201031
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Tan, Chaodong…[et al.]. Casing Damage Prediction Model Based on the Data-Driven Method. Mathematical Problems in Engineering No. 2020 (2020), pp.1-9.
https://search.emarefa.net/detail/BIM-1201031
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Tan, Chaodong& Yan, Wei& Tang, Qing& Wu, Hua& Bu, Hongguang& Kambi, Said Juma…[et al.]. Casing Damage Prediction Model Based on the Data-Driven Method. Mathematical Problems in Engineering. 2020. Vol. 2020, no. 2020, pp.1-9.
https://search.emarefa.net/detail/BIM-1201031
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1201031
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر