Efficient and Flexible Reservoir Field Management Gas-Lift Optimization Approach to Unlock the Production Potential & Economic Investment of Giant Carbonate Reservoir

2020 ◽  
Author(s):  
Ahmed Mohamed M. Ismail ◽  
Jawaher Mohamed R. Alnaqbi ◽  
Hussein Mustafa ◽  
Shi Su ◽  
Adelis Alfonzo
2015 ◽  
Author(s):  
A. AL-Hassan ◽  
E. Anthony ◽  
S. Abd El-Aziz ◽  
M. Abdel-Basset ◽  
A. Mokhtar ◽  
...  

2020 ◽  
Author(s):  
Boubaker Hammadi ◽  
Karim Agoudjil ◽  
Abdelhafid Fahem ◽  
Fateh Tadjine ◽  
Hamza Moussa Benabdellah ◽  
...  

2020 ◽  
Author(s):  
Boubaker Hammadi ◽  
Karim Agoudjil ◽  
Abdelhafid Fahem ◽  
Fateh Tadjine ◽  
Hamza Moussa Benabdellah ◽  
...  

2021 ◽  
Author(s):  
Magdy Farouk Fathalla ◽  
Mariam Ahmed Al Hosani ◽  
Ihab Nabil Mohamed ◽  
Ahmed Mohamed Al Bairaq ◽  
Aditya Ojha ◽  
...  

Abstract This paper examines risk and rewards of co-development of giant reservoir has gas cap concurrently produce with oil rim. The study focus mainly on the subsurface aspects of developing the oil rim with gas cap and impact recoveries on both the oil rim and gas cap. The primary objective of the project was to propose options to develop oil rims and gas cap reservoir aiming to maximize the recovery while ensuring that the gas and condensate production to the network are not jeopardized and the existing facility constraints are accounted. Below are the specific project objectives for each of the reservoirs: To evaluate the heterogeneities of the reservoir using available surveillance information data.To evaluate the reservoir physics and define the depleted oil rims current Gas oil contact and Water Oil Contact using the available surveillance information and plan mitigate reservoir management plan.To propose strategies in co-development plan with increase in oil rim recovery without impact on gas cap recovery.To propose the optimum Artificial methods to extended wells life by minimize the drawn down and reduce bottom head pressure.To propose methods to reduce the well head pressure to reduce back pressure on the wells. The methodology adopted in this study is based on the existing full field compositional reservoir simulation model for proposing different strategical co-development scenario: Auto gas lift Pilot implementation phase.Reactivate using Auto gas lift all the in-active wells.Propose the optimum wells drilling and completion design, like MRC, ERD and using ICV to control water and gas breakthrough.Proposing different field oil production plateauPropose different water injection scheme The study preliminary findings that extended reach drilling (ERD) wells were proposed, The ability to control gas and water breakthrough along the production section will be handled very well by deploying the advanced flow control valves, reactivation of existing Oil rim wells with Artificial lift increases Oil Rim recovery factor, and optimize offtake of gas cap and oil rim is crucial for increase the recovery factories of oil Rim and gas cap.


2017 ◽  
Author(s):  
A. Al-Hassan ◽  
M. Abdel-Basset ◽  
B. Al-Enizi ◽  
S. Al-Mosailkh ◽  
A. Al-Qenae ◽  
...  

2020 ◽  
Vol 54 (6) ◽  
pp. 1703-1722 ◽  
Author(s):  
Narges Soltani ◽  
Sebastián Lozano

In this paper, a new interactive multiobjective target setting approach based on lexicographic directional distance function (DDF) method is proposed. Lexicographic DDF computes efficient targets along a specified directional vector. The interactive multiobjective optimization approach consists in several iteration cycles in each of which the Decision Making Unit (DMU) is presented a fixed number of efficient targets computed corresponding to different directional vectors. If the DMU finds one of them promising, the directional vectors tried in the next iteration are generated close to the promising one, thus focusing the exploration of the efficient frontier on the promising area. In any iteration the DMU may choose to finish the exploration of the current region and restart the process to probe a new region. The interactive process ends when the DMU finds its most preferred solution (MPS).


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