Guest Editorial: Cognitive Computing: Augmenting Human Intelligence To Improve Oil and Gas Outcomes

Abstract

Guest editorial The severe downturn in oil prices over the past 3 years has made business transformation complicated for the upstream sector. Early in the downturn, companies were focused on cutting costs and restructuring for future growth. Many organizations are now taking advantage of gradually increasing oil prices to launch digital transformation efforts. According to the International Data Corporation (IDC) 2018 Oil & Gas Predictions Report, by 2020, 80% of large oil and gas companies will run their business with help from cognitive/artificial-intelligence (AI) agents. The report found that 62% of users say outcomes from cognitive initiatives exceed their expectations. Cognition quite simply refers to thinking—and cognitive systems such as IBM Watson can understand, reason, learn, and interact with us. Cognitive systems excel at understanding natural language, pattern identification, and knowledge location, and have endless capacity. This allows humans to focus on interpreting, analyzing, and adjusting designs, plans, and activities, and make decisions based on the data provided. For example, a company’s cognitive system can focus on finding geohazards before drilling offshore. The system does 6–8 weeks of manual research in seconds, identifying specific geohazards buried within tens of thousands of pages of drilling reports, and dynamically converts text into easy to understand tables and graphs highlighting areas of interest. The goal is not to eliminate humans but allow highly skilled geoscientists and drilling engineers to spend time doing what is most valuable—defining the safest, most cost-effective drilling plan. This is why IBM prefers to reference AI as augmented intelligence because it augments or improves upon the expertise, capability, and potential of the decision makers and teams. Cognitive systems differ from traditional programmed systems that provide predetermined outcomes based on specific rules. They consume all types of information from structured to unstructured and historical to real time. These technologies include but are not limited to: Natural language processing Predictive analytics Recommendation engines Robotic automation Machine learning systems Cognitive systems are adding value to oil and gas companies around the globe in multiple functions. Here are a few samples. Near-real-time analytics identifies underperforming wells. A global oil and gas company set out to improve its rate and phase calculations using analytics to optimize oil production and maximize revenue streams. With near-real-time data from well sensors, the analytics solution rapidly executed a set of fluid rate and phase calculations to detect subtle changes in pressure and temperature. An imbalance/out-of-tolerance triggered an automated alert to the operations center, allowing the company to make adjustments, as necessary, quickly. This led to $11 million uncovered in revenue opportunities, 99% faster execution of rate and phase calculations, and 97% accuracy in detecting underperforming wells, allowing the company to make adjustments.

Knowledge graph construction and application in geosciences: A review

“…Marr (2019) listed several latest works at Google, Oracle, Facebook, Netflix, Siemens, and described the trends of integrating KGs and machine learning in the field of financial services. For the field of oil and gas exploration, there has been solid progress of using KGs to boost big data processing and aid decision making (Kimbleton and Matson, J., 2018;Sumbal et al, 2017). Specific examples can be seen in the capabilities enabled by IBM.…”