Visible to the public Exploring Immersive Interfaces for Well Placement Optimization in Reservoir Models

TitleExploring Immersive Interfaces for Well Placement Optimization in Reservoir Models
Publication TypeConference Paper
Year of Publication2016
AuthorsRamos Mota, Roberta C., Cartwright, Stephen, Sharlin, Ehud, Hamdi, Hamidreza, Costa Sousa, Mario, Chen, Zhangxin
Conference NameProceedings of the 2016 Symposium on Spatial User Interaction
PublisherACM
Conference LocationNew York, NY, USA
ISBN Number978-1-4503-4068-7
Keywordscomposability, Human Behavior, immersion, immersive systems, pubcrawl, reservoir engineering, Resiliency, security, spatial user interaction, virtual reality
Abstract

As the oil and gas industry's ultimate goal is to uncover efficient and economic ways to produce oil and gas, well optimization studies are crucially important for reservoir engineers. Although this task has a major impact on reservoir productivity, it has been challenging for reservoir engineers to perform since it involves time-consuming flow simulations to search a large solution space for an optimal well plan. Our work aims to provide engineers a) an analytical method to perform static connectivity analysis as a proxy for flow simulation, b) an application to support well optimization using our method and c) an immersive experience that benefits engineers and supports their needs and preferences when performing the design and assessment of well trajectories. For the latter purpose, we explore our tool with three immersive environments: a CAVE with a tracked gamepad; a HMD with a tracked gamepad; and a HMD with a Leap Motion controller. This paper describes our application and its techniques in each of the different immersive environments. This paper also describes our findings from an exploratory evaluation conducted with six reservoir engineers, which provided insight into our application, and allowed us to discuss the potential benefits of immersion for the oil and gas domain.

URLhttp://doi.acm.org/10.1145/2983310.2985762
DOI10.1145/2983310.2985762
Citation Keyramos_mota_exploring_2016