Unlocking Value from Text: Visualizing Insights with Natural Language Processing in Unstructured Oil and Gas Reports

Abstract

Abstract In the ever-evolving oil and gas industry, engineers rely on effective risk identification, real-time operation monitoring, and accurate equipment assessment in their daily work. These crucial insights are captured as operator’s comments within reports such as the daily production report (DPR), daily drilling report (DDR), and well completion report (WCR), providing valuable information on field performance and well activities. However, the sheer volume and unstructured nature of these reports pose challenges, making it laborious and time consuming to manually extract and interpret key insights. This process often takes several days to complete, hindering timely well monitoring, limiting proactive event mitigation, and constraining performance improvement. As a result, valuable insights are missed, leading to revenue losses caused by delayed or uninformed decision making following reported issues. Furthermore, data visualization plays a vital role in transforming knowledge and complex information into actionable insights. However, a significant challenge lies in the visualization of these insights to facilitate informed decision making. Currently, there is a lack of robust systems that effectively transform unstructured textual data into visually accessible formats. Converting raw information into insights enables engineers to quickly derive meaningful interpretations. By employing appropriate data visualization techniques, pattern identification can be discovered, empowering decision makers to make well-informed and more accurate choices. Effective data visualization enhances well performance monitoring, expedites risk mitigation efforts, and facilitates proactive decision making. In this paper we emphasize the importance of transforming the knowledge available in oil and gas reports into actionable insights through proficient information extraction and visualization, highlighting its central role in driving operational success.