شماره ركورد كنفرانس
5193
عنوان مقاله
Prediction of Oil Well Plugging Depth Caused by Asphaltene Using Intelligent Methods
پديدآورندگان
Nasiri Mohammad Reza Master student of petroleum engineering, University of Tehran , Moeini Zahra zahramoeini@ut.ac.ir Master student of petroleum engineering, University of Tehran , Sedaee Behnam sedaee@ut.ac.ir Assistant Professor, University of Tehran
تعداد صفحه
9
كليدواژه
Formation damage , Asphaltene precipitation , Asphaltene deposition , Artificial Intelligence , Plugging depth
سال انتشار
1401
عنوان كنفرانس
همايش بين المللي هوش مصنوعي، علم داده و تحول ديجيتال در صنعت نفت و گاز
زبان مدرك
انگليسي
چكيده فارسي
Asphaltene precipitation accumulation in the oil industry is a controversial issue that has led to a lot of problems during production, transport and processing of the crude oil. The initial reservoir conditions, asphaltenes in crude oil is stable. By changing the thermodynamic conditions such as pressure, temperature, and composition of crude oil, asphaltenes start to separate from the oil phase, the phase separation and precipitation in different environments continue to accumulate in the upstream and downstream sectors along. In upstream sector, the quality of the reservoir rock lessens by two mechanisms include changing wettability and reducing porosity. At the facilities, asphaltene precipitation causes cramping in: casing, wellhead facilities, pipelines and heat exchangers as well as loss of function as catalysts. Due to the unpredictability of oil fluid properties and particularly the asphaltenes in reservoirs can be achieved using intelligent algorithms with reasonable accuracy the depth of Predicted Asphaltene precipitation. Asphaltene deposition problems will be reduced by predicting asphaltene deposition depth in wellbore. Actions will be done by knowing asphaltene depth in wellbore such as changing damaged tubing, decrease in oil or gas flow rate, using inhibitor to postpone asphaltene deposition.
كشور
ايران
لينک به اين مدرک