... the high-definition (HD-RMWD), and the three-dimensional (3D-RMWD) systems, which convert ultra-deep electromagnetic measurements into a map of the resistivity profile around the borehole. The HD-RMWD provides multilayer detection using a 1D deterministic parametric inversion engine that provides...

... Abstract Detection of early signs of stuck pipe incidents is crucial because of the enormous costs of recovering from the incidents. Previous studies have leaned significantly toward a physics-based or data-science approach. However, both approaches have challenges, such as the uncertainty...

... for underwater computer vision processing and edge computing. The goal is to build a time-efficient and cost-effective system for underwater pipeline inspection that can detect oil leakage at early stages and prevent disastrous results. In this paper, we introduced a bio-inspired autonomous underwater vehicle...

... Abstract The detection of asphaltene precipitation and gas hydrate formation is critical to preventing production losses and to optimize strategies for mitigation and remediation. Likewise, the evaluation of some flow properties (e.g., viscosity and yield stress) of the slurries formed...

... pipeline offshore pilot validation validate reliability detection vehicle performance altitude qualification matrix Introduction Early deepwater developments are now exceeding 20-year operational life and demands for enhancements to the data currently obtained from Inspection activities...

... Abstract Using AI-Based sound wave analysis of drilling equipment to assess its health condition and to predict equipment failure by detecting anomalous sound patterns in both time and frequency domains, and apply predictive maintenance. Machines can produce noise with frequencies higher than...

.... artificial intelligence background detection machine learning industrial facility variation application algorithm optimization problem accuracy productivity turnaround health & medicine dataset inspection monitoring safety milestone automation offshore technology conference scenario...

... conference flowline corrosion artificial intelligence upstream oil & gas inspector high-risk defect point cloud prioritization detection dataset linear transformation correction model computer fabric maintenance inspection inspection window measurement method height measurement blister...

... known Deep Learning algorithm, is used in the Tensorflow framework with Keras in the backend is used in the digital twin for corrosion inspection. CNN algorithm will first detect the corrosion and then the type of corrosion based on image classification. Corrosion is identified based on the corroded...

... c-roc algorithm leak detection system leak detection climate change subsea system flowline pressure choke air emission false alarm ald system installation subsea production equipment leak simulation drill center process simulator algorithm ald chemical spill detection...

... can be critical in managing key seal and trap properties of a reservoir, enabling the operator to make improved operational decisions, increasing field productivity and production efficiency. geomaterial sample red st artificial intelligence sandstone detection microcrack geomaterial...

... and offline reliability data, to support run-time analysis, such as fault prognosis, detection, isolation and diagnosis. These computationally efficient data and system analyses then enable faults to be translated into failure modes that can affect decision making during the mission. With respect...

..., and substantial economic losses. Many blowouts start with a "kick event", where the formation pore pressure becomes greater than the wellbore pressure, causing formation fluid to flow into the wellbore and combine with the drilling fluid (i.e., mud). Detecting a kick as early as possible is key to preventing...

... Abstract The ability to detect oil spills reliably, as well as to carry out fast and effective recovery operations, is the onus of any extraction company working in the field. Unfortunately, detecting and tracking oil spills is no easy task. By employing a combination of radar, optical...

... Abstract The development of oil spill detection technologies up until now have converged to the broad use of satellite-based SAR (Synthetic Aperture Radar). However, those systems present high amounts of false negatives results (oil spills that are not detected as such) and false positives (any...

..., making connections, and tripping—to provide early identification of fluid influxes and losses, thus helping ensure safe and efficient well delivery. The advanced mud logging system includes a kick-detection system, flowback monitoring, trip monitoring software, and mud accounting software based on a new...

.... Fundamental components and equipment were detected that matched the original schematics in terms of depths and diameters. The designed tool saves considerable time and effort while providing accuracy and repeatability. These results highlight some of the benefits of applying multidisciplinary ideas for data...

...OTC-29511-MS Mooring Line Failure Detection Using Machine Learning Vivek Jaiswal and Alex Ruskin, DNV GL Copyright 2019, Offshore Technology Conference This paper was prepared for presentation at the Offshore Technology Conference held in Houston, Texas, USA, 6 9 May 2019. This paper was selected...

... data mining detection sulphate ion scale remediation operator reservoir membrane surface cip sulphate reduction membrane enhanced recovery membrane element Abstract In an effort to maximize the value of the Enhanced Oil Recovery(EOR) process, a condition monitoring software program...

... Abstract In this paper, we demonstrate the potential of neural networks in the automation of shallow geohazard detection and identification on seismic images. We discuss technical considerations and method limitations. The method used in this paper trains a neural network prediction model...