... government artificial intelligence automation algorithm evaluation decision-making real-time autonomous decision-making information epoch markov decision process upstream oil & gas drilling equipment machine learning transition probability effect spe-214465-ms reinforcement learning...

... 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...

.... log analysis constraint machine learning artificial intelligence well logging information cumulative production output variable data mining upstream oil & gas initial rate similarity information content case study production forecasting petroleum engineer choke size algorithm...

... virtual flow metering systems has become a focal point for many companies. This paper discusses the importance of flow modelling for virtual flow metering. In addition, main data-driven algorithms are introduced for the analysis of several dynamic production data sets. Artificial Neural Networks (ANN...

... and divided into training and test sets. Supervised classification algorithms including logistic regression, Gaussian, Bernoulli, and multinomial Naïve Bayes, linear discriminant analysis, support vector machine, K-nearest neighbors, and Decision Tree as well as ANN were applied to the data sets to determine...

....%) on a 12meter skid-mounted hydrate closed flow loop. From the data generated, the optimal dosages of inhibitor A, B and C were observed to be 0.02 wt.%, 0.06 wt.% and 0.1 wt.% respectively. The data associated with these optimal dosages were fed to a set of supervised machine learning algorithms (Extreme...

... prognostic health signal efficiency esp natural language upstream oil & gas operating condition operation algorithm workflow health monitoring identification petroleum engineer natural language processing sme replacement Introduction Electrical Submersible Pump (ESP) systems...

...-reduced temperature and pressure, pseudo-critical temperature and pressure, and non-hydrocarbon gas components (N 2 , CO 2 , and H 2 S). Part of the data (75%) was used to train the developed models using the algorithms while another part of the data (25%) was used to predict the viscosity of gas...

...-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...

..., 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...

... and usability of rig sensor data. Focus is on gains/kick events in particular. The calibration algorithm analyzes the quality of sensors in a mud circulation system and calibrates these sensors to yield meaningful data. This leads to a much higher accuracy in the sensed data, e.g. by mitigating flow sensor...

... for certain activities on the rig site. The first step is to analyze surface data to prepare an operational recognition system. To automatically recognize drilling activities, an algorithm was developed that uses therealtime surface parameters data to calculate the current operation state, this is based...

... operation decision tree learning accuracy regression predictor input parameter ROP algorithm application prediction Sandstone Formation machine learning Upstream Oil & Gas computational efficiency surface measurement random forest penetration validation society of petroleum engineers...

... analyzing- and flow measuring technology. This replacement ensured better process overview and allowed implementation of Integrated Operations (IO) philosophy. Advanced control algorithms for real-time CFU operation and optimization were developed based on implementation of this technology. The work has...

... in a manner that respects the field’s optimisation objectives at both a Well (short-term, Reactive control) and a Reservoir (long-term, Proactive control) level. Relatively simple, well-proven algorithms are available for Reactive (mainly well out-flow) control. By contrast, techniques for Proactive control...

... optimization. Artificial Intelligence progressing cavity pump intervention spe 167416 Upstream Oil & Gas pcp 6 2011 artificial lift system controller pcp 10 2011 process variable intake pressure optimization Implementation algorithm control system application Pressure Control Setup...