Operational Excellence and Product Reliability Enhancement Through Big Data Analytics

Abstract

Schlumberger, one of the world’s leading suppliers of oilfield technology, is a measurement and data-driven company that collects massive amounts of data in the course of its daily operations. These data, diverse in nature, are collected for use in various business and technical workflows. The data can be downhole, surface, post-analysis, and support functions from manufacturing, maintenance, asset management, and finance. Analysis of this Big Data has the potential to drive a step change in operational performance across multiple dimensions. However, accomplishing this step change is not easy to accomplish because often, the data are not well structured and are scattered across individual business systems that do not communicate well with each other. Most of the analysis of these scattered data occurs on a point basis, requiring the significant involvement of various experts and complex time-consuming manipulations. The results are short lived in that they cannot be tracked in real time and the effort expended is not applicable to other data sets or problems. Increasing data volumes, data diversity, and demand from engineers to record multiple new data attributes during the product or technology life cycle further limits the benefits of such a spot analytics process, with potentially severe impacts on the business due to inadequate decision support or missed opportunities. This paper presents a developmental model and change processes, challenges faced and resolution approaches leading to digital transformation, and finally, the resulting value creation through building data visualizations and comprehensible decision-making tools. Once the initial high-value data sets and visualizations are identified, automation opportunities can be exploited. These data sets become the foundation for predictive analysis and machine learning through artificial intelligence (AI) and Internet of things (IoT) to further influence product performance and development in support of customer needs.