Model predictive control and estimation of managed pressure drilling using a real-time high fidelity flow model.

When drilling an oil or gas well, well pressures may be controlled using a technology called managed pressure drilling. This technology often relies on model predictive control schemes; however, practical limitations have generally led to the use of simplified controller models that do not optimally handle certain perturbations in the physical system. The present work reports on the first implementation of a highly accurate system model that has been adapted for real-time use in a controller. This real-time high-fidelity model approximates the results of offline high-fidelity models without requiring operation by model experts. The effectiveness of the model is demonstrated through simulation studies of controller behavior under various drilling conditions, including an evaluation of the impact of sparse downhole feedback measurements.

Achieving Tiered Model Quality in 3D Structure from Motion Models Using a Multi-Scale View-Planning Algorithm for Automated Targeted Inspection.

This study presents a novel multi-scale view-planning algorithm for automated targeted inspection using unmanned aircraft systems (UAS). In industrial inspection, it is important to collect the most relevant data to keep processing demands, both human and computational, to a minimum. This study investigates the viability of automated targeted multi-scale image acquisition for Structure from Motion (SfM)-based infrastructure modeling. A traditional view-planning approach for SfM is extended to a multi-scale approach, planning for targeted regions of high, medium, and low priority. The unmanned aerial vehicle (UAV) can traverse the entire aerial space and facilitates collection of an optimized set of views, both close to and far away from areas of interest. The test case for field validation is the Tibble Fork Dam in Utah. Using the targeted multi-scale flight planning, a UAV automatically flies a tiered inspection using less than 25% of the number of photos needed to model the entire dam at high-priority level. This results in approximately 75% reduced flight time and model processing load, while still maintaining high model accuracy where needed. Models display stepped improvement in visual clarity and SfM reconstruction integrity by priority level, with the higher priority regions more accurately modeling smaller and finer features. A resolution map of the final tiered model is included. While this study focuses on multi-scale view planning for optical sensors, the methods potentially extend to other remote sensors, such as aerial LiDAR.