Well-Placement Optimization in a Novel Heavy Oil Recovery Process Using In-Situ Steam Generated by Thermochemicals

2018 ◽  
Author(s):  
Tamer Moussa ◽  
Shirish Patil ◽  
Mohamed Mahmoud ◽  
Salaheldin Elkatatny
Keyword(s):  
Oil Recovery ◽  
Heavy Oil ◽  
Recovery Process ◽  
Heavy Oil Recovery ◽  
Well Placement ◽  
Placement Optimization ◽  
Well Placement Optimization

Gas Analysis by In Situ Combustion in Heavy-Oil Recovery Process: Experimental and Modeling Studies

2014 ◽  
Vol 37 (3) ◽  
pp. 409-418 ◽  
Author(s):  
Mohammad-Ali Ahmadi ◽  
Mohammad Masumi ◽  
Riaz Kharrat ◽  
Amir H. Mohammadi
Keyword(s):  
Oil Recovery ◽  
Heavy Oil ◽  
Recovery Process ◽  
Gas Analysis ◽  
Heavy Oil Recovery ◽  
In Situ Combustion ◽  
Modeling Studies

scholarly journals Dynamic Simulation of the Toe-to-Heel Air Injection Heavy Oil Recovery Process

2017 ◽  
Vol 31 (2) ◽  
pp. 1276-1284 ◽  
Author(s):  
Muhammad Rabiu Ado ◽  
Malcolm Greaves ◽  
Sean P. Rigby
Keyword(s):  
Dynamic Simulation ◽  
Oil Recovery ◽  
Heavy Oil ◽  
Recovery Process ◽  
Air Injection ◽  
Heavy Oil Recovery

A novel streamline-based objective function for well placement optimization in waterfloods

2020 ◽  
pp. 1-23
Author(s):  
Forouzan Naderi ◽  
Majid Siavashi ◽  
Ali Nakhaee
Keyword(s):  
Objective Function ◽  
Oil Recovery ◽  
Reservoir Simulation ◽  
Target Function ◽  
Water Flooding ◽  
Local Optimum ◽  
Full Time ◽  
Well Placement ◽  
Placement Optimization ◽  
Well Placement Optimization

Abstract In reservoir development plans, well placement optimization is usually performed to better sweep oil and reduce the amount of trapped oil inside reservoirs. Long term optimization of well placement requires multiple times simulation of reservoirs which makes these problems cumbersome, especially when a large number of decision variables exist. Cumulative oil production (COP) or net present value (NPV) functions are commonly used as the objective function of optimal enhance oil recovery projects. Use of these functions requires a full-time reservoir simulation and their convergence could be difficult with the chance to be trapped in local optimum solutions. In this study, the novel proportionally distributed streamlines (PDSL) target function is proposed that can be minimized to reach the optimal well placement. PDSL can be estimated even without full time reservoir simulation. PDSL tries to direct the appropriate number of streamlines toward the regions with larger amount of oil in the shortest time and hence can improve oil recovery. Particle swarm optimization (PSO) method linked to an in-house streamline-based reservoir simulator is implemented to optimize well placement of water flooding problems in a 2D heterogeneous reservoir model.

Sign in / Sign up

Export Citation Format

Share Document