Abstract
As the world struggles through the COVID-19 crisis and our industry suffers from linked oversupply and demand reduction, we are all forced to refocus on what makes a difference to the bottom line.In the numerical reservoir simulation space, that is generally, "How do we answer a decision-related question in the least amount of time with an acceptable degree of confidence?" Simulation has always been a double-edged sword - a method that, when well-used in fit-for-purpose ways to answer specific questions, can deliver real value. Conversely, when it is used as a substitute for understanding, perhaps to justify a development decision or simply to convince ourselves that we understand a system far better than we really do, many staff years of effort can be quickly lost while not delivering very much. Fit-for-purpose approaches likely will be of ever-increasing focus going forward. If it is not adding value, it should not be done. But "fit for purpose" encompasses a wide range of possibilities - leveraging new approaches as well as learning from old approaches and improving current approaches. It is these three prongs that have guided my paper selections for this edition. While the rapid rise to prominence of methods that eschew conventional numerical modeling approaches in favor of data-driven proxy approaches provides us with some new tools to answer these questions, these tools are unlikely to be reliably predictive unless they incorporate governing physics. It is for this reason that one of the following papers spells out just such a solution, marrying fundamental material-balance governing equations with analytics-driven clustering techniques to deliver what appears to be a fit-for-purpose approach to a complex problem. Keeping in mind the quote attributed to George Santayana - "Those who cannot learn from history are doomed to repeat it" - the second paper is an interesting look back at different attempts to simulated unconventional plays, while the third paper is an interesting extension of a current approach to well deconvolution. I hope you enjoy reading this selection of papers and look forward to what the future may hold in the numerical simulation space.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.