Modeling asphaltene precipitation in Algerian oilfields with the CPA EoS

resumo

One of the major flow assurance problems afflicting the oil industry is the asphaltene precipitation during the production, transportation and storage of oil. The precipitation of these heavy compounds is responsible for changes in crude oil properties, increases in oil viscosity, and formation of deposits that reduce oil production and disable equipment leading to significant operational costs. In Algeria, the deposition of asphaltene in reservoirs and pipelines is a severe problem. During production the depressurization of reservoir fluid and the variations of thermodynamic conditions create the need to frequently pig the lines and, in some cases, to inject solvents and dispersants to maintain the production. The understanding of the asphaltene behavior and the prediction of its deposition in flow conditions is crucial to implement appropriate strategies for the prevention or remediation, especially in the wellbore region. In this work we used the CPA EoS to describe the asphaltene phase envelope and predict the PT regions of stability for five Algerian live oils. The model provides a very good description of the experimental behavior of live oils without and with gas injection. The sensitivity to SARA analysis data and its effect on the asphaltene phase boundaries were also analyzed.

palavras-chave

CUBIC-PLUS-ASSOCIATION; PC-SAFT CHARACTERIZATION; PHASE-BEHAVIOR; GAS INJECTION; CRUDE OILS; RESINS; PREDICTION; STABILITY

categoria

Energy & Fuels; Engineering

autores

Behnous, D; Palma, A; Zeraibi, N; Coutinho, JAP

nossos autores

agradecimentos

This work was developed within the scope of the project CICECO-Aveiro Institute of Materials, FCT Ref. UIDB/50011/2020 & UIDP/50011/2020 financed by national funds through the FCT/MEC and when appropriate co-financed by FEDER under the PT2020 Partnership Agreement. The authors acknowledge KBC Advanced Technologies Limited for providing Multiflash and Sonatrach for providing the experimental data used in this work.

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