| With the ongoing advancement of deepwater technology in offshore oil and gas extraction, the worldwide requirement for offshore drilling and production operations is steadily on the rise. Consequently, equipment selection, retrieval, and other related tasks have become crucial and competitive strategies for marine production companies. However, the conventional retrieval process encounters challenges, including high equipment demands and intricate equipment inventories. These issues generate substantial labor expenses and the possibility of human errors. This study has effectively created a swift retrieval software for semi-submersible drilling equipment utilizing the
Python Django framework. Through an extensive analysis of the needs of personnel involved in device retrieval, this program was developed using Python programming, HTML tools, and SQLite database. It is designed to implement essential functions, including generating frontend interfaces, processing data, and resetting retrieval mechanisms based on the Python Django framework. The system allows users to generate front-end pages in accordance with the requirements outlined in the documents and perform device retrieval and filtering. The tool's emergence simplifies device retrieval work and improves information efficiency, providing robust support for enhancing work
efficiency in this particular field. |
