An Integrated System for Drilling Real Time Data Analytics

Abstract

Abstract Drilling operations is one of the potential areas where data mining and advanced analytics technology can be used to improve the company's bottom line. With real time drilling technology, huge amounts of data can be generated and captured. Exploiting this data and transform it into knowledge will help oil and gas companies to increase revenue, lower costs, and reduce risks. Building a data mining and analytics engine that uses drilling real time data is a difficult challenge. Data transmission, retrieval, storage, data accuracy, format of the data and the timeliness of the analysis are major considerations for developing a data mining and analytics solution. Most of the current analytical engines require more than one tool to have a complete system. Several tools will be needed for data transmission, retrieval, storage, and data formatting. In addition, separate tools for building data models and visualization are required. Therefore, adopting an integrated system that combines all required tools will significantly help an organization to address the above challenges in a timely manner. In this paper, we propose an architecture of an integrated system that combines all required tools of building a data mining and analytics engine for drilling real time data. Our architecture uses a single system that retrieve and preprocess data, apply data analytics models, extract the knowledge and visualize it, and store the results for further analysis. The advantage of such a system is the speed of the delivery of the analysis, which is crucial in drilling operations. The proof of concept experiments show that our proposed architecture can address and overcome the challenges of building a data mining and analytics engine for drilling real time data.