Data Management Framework for Risk Estimate of Electronic Boards in Drilling and Measurement Tools*

Abstract

With computer science and technology development in today's world, many traditional industries, such as the oil and gas industry, are beginning to transform to digitalization. In this transformation process, many data-driven models are often necessary; e.g., a data-driven model, based on existing data, is used to estimate the risk associated with drilling tools. Before building this model, the preliminary work needs to assess how much data are available at this stage, what is the quality of the data, whether the existing data are suitable for building the model, and if not, what measures can be taken to improve the data quality. To answer these questions, this paper presents a data management framework that includes data preparation, data quality assessment, and data-based knowledge acquisition. An actual case study result demonstrates that the framework can answer these questions.