Abstract
In recent years, the oil industry has developed increasingly by creating continuous innovation system, whether identifying barriers, evaluating new possibilities, integrating systems, adding value to research and development to overcome commonly encountered challenges. In this respect, the operations concerning the treatment of produced water stand out. In dynamic environments, these Foresights must be constantly updated. The present work sought to identify factors that provide directions to understand future scenarios for the treatment process of produced water from the oil industry. The methodology used was initially based on the Delphi method, which was applied to direct and concatenate opinions obtained through a consensus among experts in the field. Additionally, the SAPEVO-M tool was implemented to assist decision-making based on the identified scenarios, evaluating, in advance, the risks, uncertainties, and possibilities involved in the treatment of produced water. The results obtained allowed us to infer potential technological scenarios, especially sustainable processes, which will be promising and challenging for the oil industry in the medium and long term, a period necessary for the maturation of the potential technologies used. In addition, a critical assessment of existing risks in each technology to minimize future uncertainties was considered.
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The authors acknowledge financial assistance from the Brazilian research funding agencies as CAPES (Coordination for the Improvement of Higher Education Personnel) under Finance Code 001, a Brazilian foundation within the Ministry of Education (MEC), CNPq (National Council for Scientific and Technological Development), a Brazilian foundation associated to the Ministry of Science, Technology and Innovations (MCTI), and FAPITEC/SE (the Foundation of Support to Research and Technological Innovation of the State of Sergipe).
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Macêdo-Júnior, R.O., Serpa, F.S., Santos, B.L.P. et al. Produced water treatment and its green future in the oil and gas industry: a multi-criteria decision-making study. Int. J. Environ. Sci. Technol. 20, 1369–1384 (2023). https://doi.org/10.1007/s13762-022-04057-3
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DOI: https://doi.org/10.1007/s13762-022-04057-3