Enormous efforts have been made to facilitate produced-gas analyses by in situ
combustion implication in heavy-oil recovery processes. Robust intelligencebased
approaches such as artificial neural network (ANN) and hybrid methods
were accomplished to monitor CO2/O2/CO. Implemented optimization approaches
like particle swarm optimization (PSO) and hybrid approach focused
on pinpointing accurate interconnection weights through the proposed ANN
model. Solutions acquired from the developed approaches were compared with
the pertinent experimental in situ combustion data samples. Implication of hybrid
genetic algorithm and PSO in gas analysis estimation can lead to more reliable
in situ combustion quality predictions, simulation design, and further plans
of heavy-oil recovery methods.
کلید واژگان :
Enhanced Oil Recovery, Evolutionary algorithm, Heavy oil, In situ combustion, Neural network
