Rapid Development of Multi-Source Heterogeneous Drilling Data Service System
Abstract Digital oil and gas field is an overly complex integrated information system, and with the continuous expansion of business scale and needs, oil companies will constantly raise more new and higher requirements for digital transformation. In the previous system construction, we adopted multi-phase, multi-vendor, multi-technology and multi-method, resulting in the problem of data silos and fragmentation. The result of the data management problems is that decisions are often made using incomplete information. Even when the desired data is accessible, requirements for gathering and formatting it may limit the amount of analysis performed before a timely decision must be made. Therefore, through the use of advanced computer technologies such as big data, cloud computing and IOT (internet of things), it has become our current goal to build an integrated data integration platform and provide unified data services to improve the company's bottom line. As part of the digital oilfield, offshore drilling operations is one of the potential areas where data processing and advanced analytics technology can be used to increase revenue, lower costs, and reduce risks. Building a data mining and analytics engine that uses multiple drilling data is a difficult challenge. The workflow of data processing and the timeliness of the analysis are major considerations for developing a data service solution. Most of the current analytical engines require more than one tool to have a complete system. Therefore, adopting an integrated system that combines all required tools will significantly help an organization to address the above challenges in a timely manner. This paper serves to provide a technical overview of the offshore drilling data service system currently developed and deployed. The data service system consists of four subsystems. They are the static data management system including structured data (job report) and unstructured data (design documentation and research report), the real-time data management system, the third-party software data management system integrating major industry software databases, and the cloud-based data visual application system providing dynamic analysis results to achieve timely optimization of the operations. Through a unified logical data model, it can realize the quick access to the third-party software data and application support; These subsystems are fully integrated and interact with each other to function as microservices, providing a one-stop solution for real-time drilling optimization and monitoring. This data service system has become a powerful decision support tool for the drilling operations team. The learned lessons and gained experiences from the system services presented here provide valuable guidance for future demands E&P and the industrial revolution.