Title: Stochastic production scheduling for water-oil displacement by reduced-order models generated using liquid production rates

Authors: Ehsan Roeinfard; Mehdi Assareh

Addresses: Faculty of Chemical, Petroleum and Gas Engineering, Iran University of Science and Technology (IUST), Tehran 16846-13114, Iran ' Faculty of Chemical, Petroleum and Gas Engineering, Iran University of Science and Technology (IUST), Tehran 16846-13114, Iran

Abstract: In this work, we show an effective approach for application of reduced order model (ROMs) constructed with proper orthogonal decomposition (POD) using liquid production rates for snapshot generation. These ROMs are used to maximise oil production while controlling associated water production. Using ROMs, we perform a parallel genetic algorithm (PGA) and consider liquid production rates as decision variables. The balanced rates are used for injection wells, based on open-flow potential and total amount of produced reservoir volume. The net present value (NPV) is selected as objective function to ensure project profitability and to penalise water production. The NPV by ROM optimisation is approached to within 98% of the NPV obtained by optimisation using the full-order model demonstrating acceptable accuracy. A synthetic model and a real field sector are used for evaluation. The optimisation runtime reduces by 55% in the synthetic model and 71% for optimisation with ROM in the sector case. [Received: April 4, 2022; Accepted: July 14, 2022]

Keywords: production scheduling; parallel genetic algorithm; PGA; reduced-order models; ROMs; waterflooding; proper orthogonal decomposition; POD.

DOI: 10.1504/IJOGCT.2023.128889

International Journal of Oil, Gas and Coal Technology, 2023 Vol.32 No.3, pp.205 - 227

Received: 03 Apr 2022
Accepted: 14 Jul 2022
Published online: 08 Feb 2023 *

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