Current Volume 8
The oil and gas industry is a prominent contributor to the global energy value chain but has some significant environmental issues, particularly from its drilling operations. The application of Artificial Intelligence in minimizing drilling waste and avoiding formation damage, which are central issues in upstream oil and gas exploration, is the subject of this paper. Drilling waste in the form of cuttings and spent fluids is an environmental hazard and also an economic cost if not managed effectively. The paper outlines the state of the art of Artificial Intelligence approaches in drilling recognizing significant advances. It also highlights existing literature deficiencies. Of particular concern is that, real-time AI-based decision-making support for formation damage prevention is in its very early stages and needs additional field verification. The paper calls for the creation of adaptive, resilient, and scalable AI models for the improvement of sustainable drilling operations. By bridging these knowledge gaps, the research hopes to contribute to enhancing more efficient and sustainable operations in the oil and gas industry.
Artificial Intelligence, Drilling Waste, Formation Damage, Oil and Gas Industry, Sustainable Practices.
IRE Journals:
Ifeanyi Kingsley Egbuna , Joshua Babatunde Asere , Umar Ado , Abdussamad Idris Ali , Harrison Agboro; Chimezie Zereuwa
"The Role of Artificial Intelligence in Minimizing Drilling Waste and Formation Damage in the Oil and Gas Industry." Iconic Research And Engineering Journals Volume 8 Issue 11 2025 Page 52-66
IEEE:
Ifeanyi Kingsley Egbuna , Joshua Babatunde Asere , Umar Ado , Abdussamad Idris Ali , Harrison Agboro; Chimezie Zereuwa
"The Role of Artificial Intelligence in Minimizing Drilling Waste and Formation Damage in the Oil and Gas Industry." Iconic Research And Engineering Journals, 8(11)