Visualization as a big data artefact for knowledge interpretation of digital petroleum ecosystems

Abstract

In the current upstream business environment, we examine the risk involved in the petroleum exploration and field development. Many sedimentary basins worldwide possess hundreds of petroleum systems with thousands of oil and gas fields, geographically scattered. A significant amount of unstructured heterogeneous and multidimensional data are locked up in many industrial applications and knowledge domains. Our objective is to bring the relevant data together, integrate and visualize for adding values to the existing interpretation. We simulate a Big Data guided digital petroleum ecosystem (DPE) approach, a digital oil field solution, a new direction in the analysis of a total petroleum system (TPS), in which multiple sedimentary basins may have been grouped, inheriting an interconnectivity between the systems. The DPE is articulated in a framework, organizing variety of data associated with the elements and processes of complex petroleum systems and integrating their data dimensions and attributes. We develop an ontology based data warehousing and mining artefacts. We present warehoused metadata, with slicing and dicing of data views for visualization of new prospects in the investigating area. We further investigate the risk of exploratory drilling campaigns and how the integrated framework, with visualization and interpretation artefacts can holistically support the delivery of high-quality products and services.