In order to address the issues of environmental pollution and operational efficiency during oilfield downhole operations, this paper proposes a downhole operation scheme based on the integration of clean and automated technologies. This scheme designs a three-level control architecture that includes digital acquisition, distributed control, and intelligent decision support. It also develops an environmentally friendly work fluid system and modular pollutant treatment devices. At the same time, an intelligent decision-making system based on knowledge graphs and machine learning is constructed to achieve dynamic optimization and predictive control of the operation process. The results of field applications show that this scheme increases the recovery rate of work fluids to 95%, reduces pollutant emissions by 85%, and improves operational efficiency by 35%.