Image from Google Jackets

An automation system for gas-lifted oil wells Model indentification, control, and optimization

By: Publication details: feb. 2010Description: 11 p. ; 157-167 In: Journal of Petroleum Science & Engineering 70Summary: Transcripción del resumen del autor. Smart fields technology advocates the use of a suite of skills, workflows, and technologies to drive efficiency gains while maximizing oil recovery from reservoirs. This paper contributes to smart fields technology by developing an automation system for integrated operation of gas-lift platforms, thereby bridging the gap between downhole devices (sensors, valves, and controllers) and surface facilities (operating policies, constraints, and faults). The components of the system are: (1) a module for identification of well-performance curves from downhole pressure measurements; (2) a control strategy for the pressure of the gas-lift manifold and a software sensor to indirectly measure the gas-mass flow-rate available for artificial lifting; and (3) an algorithm for optimal allocation of limited resources, such as the lift-gas rate, fluid handling capacities, and water-treatment processing capacity. The paper reports results from simulations performed with a prototype platform as a proof of concept.
Item type: Artículo de Revista
Holdings
Current library Status Barcode
Biblioteca Alejandro Angel Bulgheroni Not for loan 200046008

Transcripción del resumen del autor. Smart fields technology advocates the use of a suite of skills, workflows, and technologies to drive efficiency gains while maximizing oil recovery from reservoirs. This paper contributes to smart fields technology by developing an automation system for integrated operation of gas-lift platforms, thereby bridging the gap between downhole devices (sensors, valves, and controllers) and surface facilities (operating policies, constraints, and faults). The components of the system are: (1) a module for identification of well-performance curves from downhole pressure measurements; (2) a control strategy for the pressure of the gas-lift manifold and a software sensor to indirectly measure the gas-mass flow-rate available for artificial lifting; and (3) an algorithm for optimal allocation of limited resources, such as the lift-gas rate, fluid handling capacities, and water-treatment processing capacity. The paper reports results from simulations performed with a prototype platform as a proof of concept.

3-4



Instituto Argentino del Petróleo y del Gas
Maipú 639 (C1006ACG) – Buenos Aires – Argentina
Tel: (54 11) 5277 IAPG (4274)
Lu - Vie 11 a 17 hs
Mail: biblio@iapg.org.ar


Copyright © 2026, Instituto Argentino del Petróleo y del Gas, todos los derechos reservados.

Protección de datos personales