Leveraging Online Analytical Processing Cubes in the World's Largest Offshore and Land Drilling Record System

The purpose of this paper is to demonstrate the power and business benefits of leveraging online analytical processing (OLAP) cubes in the utilization of high-level data analytics and data dashboards from an established drilling record system (DRS). The DRS contains over 1.4 million wells, including 75,000 offshore wells drilled worldwide since 1980 with nearly 5 million total bottomhole assembly (BHA) runs from over 100 countries. Since 2009, over 1.5 million BHA runs drilling 2.6 billion feet of formation have been captured. Being able to visualize and understand the drilling data allows for increased efficiencies, reducing the days on wells for operators from deepwater to inland barge and land drilling worldwide. The development of the OLAP cubes required a multidisciplinary team consisting of software developers, business managers, domain champions, field-based engineers, and data scientists. The OLAP cubes consist of multidimensional databases built from relational and algorithmic interpretations of DRS transaction data. These algorithms are generated and developed by an iterative cycle of continuous improvement, development, and utilization of the OLAP cubes in parallel to improve the functionality and business impact for performance analysis, sales, product development, product reliability, and marketing. The data can be analyzed and visualized in the Microsoft Office suite by directly querying the DRS OLAP cubes. This also allows for dashboards to be updated in real time as data are added to DRS. OLAP cubes have been developed to analyze the performance of drill bits, motors, reamers, rotary steerable tools, and many more downhole tools. The DRS cubes assist in identifying failure causes on bits to identify high-risk intervals to better target products and parameters to reduce costly nonproductive time. Fit-for-purpose OLAP cubes have been developed to understand drilling efficiencies and strategies in multibit versus single-bit sections using variable trip speeds and field performance. Traditional business reports were made more efficient and auto-updated and dashboards were built to identify major business trends to equip business managers. This OLAP cube development has allowed for increased usage of the world's largest drilling record database and has made it easier to access and analyze the data. Ultimately, the techniques and development described in this paper help answer business questions to make better business decisions through data-driven analytics.