Predictive modeling of coagulant dosing in drilling wastewater treatment using artificial neural networks.

ABSTRACT: Due to water resource limitations and the environmental challenges associated with wastewater generated during oil and gas well drilling processes, the treatment and reuse of drilling wastewater have become essential. In Iran, most drilling wastewater treatment is conducted chemically using coagulant and flocculant agents, typically managed by on-site jar testing, which requires high technical expertise and can be time-consuming and prone to human error. Replacing this conventional approach with artificial intelligence techniques can significantly accelerate the process and reduce operational inaccuracies. In this study, data from 200 drilling waste management reports across various wells in the West Karun oilfields were collected, including input wastewater characteristics, dosages of pol

SUBMITTER: Kalhormohammadi M 

PROVIDER: S-EPMC12357918 | biostudies-literature | 2025 Aug

REPOSITORIES: biostudies-literature