Forum - Youth and innovation in the oil and gas industry. According to Michael Kenison, technical solutions must have the proper blend of creativity and practicality and ideas should meet a legitimate need. Kenison is a project manager at Schlumberger and has six patents to his credit with six more in the pipeline. He received his first patent at the age of 29. He is just one of the many young achievers in the oil and gas industry. Physics, chemistry, and mathematics are overflowing with people who have exemplified the meaning of prodigy and their names are found in numerous high school and college textbooks. Wikipedia pays respect to these names. Units are named after them. Newborn elements derive their name from these people, not to mention bagel houses. But we rarely take a look in our own backyard. Given that products and services in the oil and gas industry are highly specialized and that young people are given little responsibility in their initial career years, crossing the rift can be tricky. Instead of being inspired by these examples, sometimes young people feel constrained by the long learning curve in the industry. But with the “easy oil” era over, this is a time for innovation and young professionals can be a source of refreshing insight, unique perspectives, and new ideas.

The Oilfield is a cash flow dependent business, making the speed of decision-making very important. Our industry collects an incredible amount of data, but the volume of this data, coupled with inefficient oilfield software, slows down analysis and decision making. Critical decisions are delayed, and decision quality is affected. Smart Assistants like Siri and Alexa have become extraordinarily popular lately due to their ability to perform routine tasks and make information readily accessible. Considering the oil industry's drive towards enhanced speed and efficiency, there is a considerable upside in applying the concept of a Smart Assistant to oil and gas applications. This Smart Assistant for Oil and Gas would consolidate massive amounts of data, derive knowledge from it, automate workflows, and provide faster and consistent insights. This paper will look closely at a specific application of this Smart Assistant: analyzing flowback data from newly drilled wells. Engineers at Equinor have recently leveraged learnings from this Smart Assistant to increase efficiency in day-to-day tasks and realize results.

Summary Holistic understanding of well operations can play a key role in optimization and maintenance of assets. The traditional process for understanding well operations mainly involves fitting a curve through all of the historical production data and extending the curve to forecast production without modeling the stochastic nature of production history, considering impact of any well interventions, or feeding any a priori information into curve-fitting workflows. This leads to unreliable production and reserves estimates which, in turn, impact the strategy and planning process for asset management. A novel workflow was developed learns the production characteristics of a well through a statistical framework using principles of signal processing and Bayesian inferences. Using this workflow, high-fidelity empirical production performance forecasts can be obtained for all the wells in the asset in an automated fashion. This novel workflow aims to significantly simplify interpretation of well operations, reduce the turnaround time for analyzing and modeling well performance, and improve the quality of reserves estimates.