Optimization algorithm for number and wells placement

Abstract

Determination of the optimal number and placement of production wells is crucial for the effective depletion of the hydrocarbon reservoir. Due to the strongly non-linearity of the problem and the occurrence of multiple local minimums in the response function the non-gradient optimization methods in combination with reservoir simulations are most commonly used for its solution. However, it should be noted that most of the research works dedicated to this issue describe the process of placement optimization but not the number of drilling wells assuming that it was arbitrary set. This is partly due to the fact that known and used optimization methods operate on a fixed number of optimization parameters, therefore the number of production wells can not change during the optimization process. The paper is dedicated to the attempt to build an algorithm that allows simultaneous optimization of the number and position of production wells with respect to the discounted profit in a given period of operation. The basic optimization method in the presented algorithm is the Particle Swarm Optimization (PSO)-one of the most effective non-gradient optimization methods that belongs to the group of methods applying the swarm's intelligence. Taking into account the number of drilling wells in the optimization process means that the algorithm operates on a variable number of parameters. The objective algorithm starts optimization from an arbitrarily set number of producers, reducing it gradually. Efficiency tests conducted on the sample reservoir PUNQ-S3 indicated a satisfactory convergence of the proposed method. The computing program created implements the mechanisms of convergence enhancement by improving the boundary conditions for the optimization method. The minimum separation distance control between production wells was also introduced at the initial stage of optimization process. Although the algorithm is characterized by satisfactory convergence it would be advisable to improve it by using a hybrid method to increase its effectiveness in the local optimization phase and to introduce minimum well spacing during the entire optimization process.

Petrofizyczne aspekty poszukiwań naftowych na dużych głębokościach

“…Jeśli takie formuły powstaną, w sposób zdecydowany pozwoli to na skrócenie czasu potrzebnego do określenia parametrów petrofizycznych dla danego złoża, a tym samym do oszacowania liczby otworów i ilości węglowodorów możliwych do wydobycia (rys. 2) (Rushing et al, 2008;Łętkowski, 2019). Na każdym etapie należy weryfikować poprawność zastosowanych metod obliczeniowych.…”