... Intelligence applications. However, with limited data connectivity options, and restriction of hosting confidential data on cloud platforms, the traditional cloud based Industrial Internet of Things (IIoT) architectures are not feasible for many global operators. In this paper we will discuss the various...

... also requires petrophysical rock types (PRTs) and saturation-height function (SHF), which are parameters derived from mercury-injection-capillary-pressure (MICP) data. This study presents the application of data mining algorithms for deriving useful parameters to constrain static and dynamic models...

... hypothesis application classification experiment machine learning lithology rhob nphi validity threat log analysis canada government precision evaluation metric prediction accuracy automatic identification reservoir characterization dataset identification objective null hypothesis...

... & simulation forecast topology petroleum engineer machine learning reservoir behavior application novel high-speed ai-physics hybrid model trajectory scenario assessment ai-physic forecast Introduction Petroleum engineers and geologists are faced with complex, nonlinear, and dynamic problems...

... of models capable of giving predictions on flow rates, such as full-scale 3D reservoir models. However, the model simplicity, assumptions, and limitations does not allow wide application of a conventional CRM in complex field cases. A vast majority of studies on CRM are about overcoming its limitations...

... sequence artificial intelligence emission onepetro ai forecast thatcher accurate forecast upstream oil & gas accuracy asia government prediction consumption eldred characteristic optimization inventory management application drilling sequence operation Introduction...

... is connected directly into Subsurface application by proper authorization and access. The data naming conventions was collected from all the specific service provider, and it was than mapped with standard naming that is used in the organization. The data consists of several different type of mnemonics. Example...

... deep learning machine learning artificial intelligence production control flow metering production monitoring neural network accuracy vfm gryzlov scenario upstream oil & gas flow rate multiphase rate data-driven method machine learning methods information prediction application...

... Abstract This paper provides the field application of the bee colony optimization algorithm in assisting the history match of a real reservoir simulation model. Bee colony optimization algorithm is an optimization technique inspired by the natural optimization behavior shown by honeybees during...

... In addition to the increase in AI and ML publications, all professional meetings (conferences, workshops, and symposia) now have sub-themes to highlight AI applications, showcase AI and ML research outcomes, and present novel solutions based on AI and ML. Special sessions dedicated to AI and ML...

... learning reservoir simulation complex reservoir condensate reservoir accuracy application nam con son basin well ht-c upstream oil & gas dynamic model artificial intelligence history matching transmissibility multiplier lgr area decision tree classifier lgr need lgr classifier test...

... and the pressure within the natural gas flow line. All models had accuracies greater than 90%. This result show that the application Machine learning to solving flow assurance problems is viable. The results show that it is viable to apply machine learning algorithms to solve flow assurance problems, analyzing...

... they are published on the optimization engine. The control system then ingests these values and applies them to the autodriller. For ease of use, the window size, step size, and response tuning setting are integrated into the control system and published back to the optimization engine. From an application...

... elkatatny artificial neural network model development rock porosity drilling parameter gamal petroleum engineer accuracy porosity application Introduction The porosity of the drilled rock is a critical characteristic for the reservoir rock as it represents the void spaces in the bulk volume...

...-time applications. The paper demonstrates the potential benefits of the real-life application of Artificial Intelligence (AI) / Machine Learning (ML) in conjunction with traditional Petroleum Engineering concepts and algorithms to predict imminent and future failures, extend and monitor run life...

... application accuracy pressure gradient well rate estimation pressure drop wpc new approach multiphase flow well model bottom hole Introduction Production engineers struggle to estimate daily well rates, understand well potential performance and reconcile well production with actual rates...

... convenient and user-friendly experience. The Petroleum Engineering Toolbox is available online and as a mobile application for better use on mobile devices. Its online interface is entirely built on top of open source technology. Server side connection is done by Apache 2.4.9 Web Server and PHP Version 5.2.4...

... Abstract Oil and gas production systems are complex and usually consist of several production elements and corresponding models: (1) reservoirs modelled with reservoir simulators using geological and fluid data, (2) wells and surface production networks modelled with flow assurance applications...

... Abstract Smart Metering Solutions have been developed and implemented on TOTAL assets by combining digital technology and in house metering expertise to improve quality of data needed for reservoir monitoring, installation operation and fiscal applications. Deployment within TOTAL upstream...

..., will contribute to maximizing production and reserves; while also reducing costs by applying efficiencies, and connecting the field to the back office. data quality adoption data source algorithm Upstream Oil & Gas information application information management data management Efficiency big...