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General Information
Editor-in-chief
Prof. Adrian Olaru
University Politehnica of Bucharest, Romania
I'm happy to take on the position of editor in chief of IJMO. It's a journal that shows promise of becoming a recognized journal in the area of modelling and optimization. I'll work together with the editors to help it progress.
IJMO 2019 Vol.9(6): 303-309 ISSN: 2010-3697
DOI: 10.7763/IJMO.2019.V9.727

Estimation of Mature Water Flooding Performance and Optimization by Using Capacitance Resistive Model and Fractional Flow Model by Layer

Francisco Castillo Gamarra, Néstor Ramos, and Ignacio Borsani

Abstract—Water flooding is the oldest and most extended method for enhance recovery from oil reservoirs in primary production with low natural energy, in the San Jorge Gulf Basin in Argentina. Water injection has proved an effective method to enhance recovery from oil reservoirs for project CM-123-A at Cañadón Minerales field, San Jorge Gulf Basin. Defining the optimized injection rates and injection patterns, that depends on the geological structure of the reservoir, is an essential operational and economical decision for reservoir management. In this paper, the Capacitance-Resistive Model(CRM), that takes into account implicitly the geological and reservoir parameters, is used to find inter-well connectivity by layer(independent reservoir), optimize injection rates and with the complement of net sand maps, petrophysical and production test data, check the consistency of the solutions with all the available data to support the decisions. The CRM model receives the injection rates variations as input signal, from the different reservoirs, while the producer responses determine the injector/producer pair connectivity quantitatively. The different runs of CRM can be used to detect how some abrupt changes in the artificial lift of the producers affect the connectivity and propose some improvements. Also, this model is used to predict gross production for individual reservoir, together with a multilayer FFM (Fractional Flow Model) can be estimated the oil production for each individual reservoir, identify the potential from different reservoirs and improvements in the injection rates to optimize the oil production. The results show that the CRM approach has the capability to match the production history and calibrate the dynamical effective parameters, and with this characterization optimize the injection rates of the different wells injectors and reservoirs, during the immiscible flooding, understand water injection movement, and as accessory the joint validation of the net sand maps. The CRM model was able to detect inter-well connectivity for producers connected not only at fist line, but at second line, with a clear response in field.

Index Terms—Reservoir engineer, mature waterflooding, multilayer CRM (capacitance resistive model), multilayer fractional flow model, nonlinear optimization, mathematical programming, AML, gams, conopt, octave, R.

Francisco Castillo Gamarra, Néstor Ramos, Ignacio Borsani are with Sinopec Argentina E&P, Manuela Saénz 323, CABA, Argentina (e-mail: francisco_castillo@sinopecarg.com.ar, nestor_ramos@sinopecarg.com.ar, ignacio_borsani@sinopecarg.com.ar).

[PDF]

Cite: Francisco Castillo Gamarra, Néstor Ramos, and Ignacio Borsani, "Estimation of Mature Water Flooding Performance and Optimization by Using Capacitance Resistive Model and Fractional Flow Model by Layer," International Journal of Modeling and Optimization vol. 9, no. 6, pp. 303-309, 2019.

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