... technology in combination with a cloud-based IoT platform. Artificial Intelligence SCADA system artificial lift system esp fleet process data machine learning platform remote operation center abnormal behavior Upstream Oil & Gas operation neural network architecture operator reservoir...

... Abstract In recent years, the oil and gas industry has gained greater operational efficiencies and productivity by deploying advanced technologies, such as smart sensors, data analytics, artificial intelligence and machine learning — all linked via Internet of Things connectivity...

... Intelligence Support Vector Machine statistics matrix machine learning gas production classification algorithm validation classification String Integrity Failure integrity failure data Science confusion matrix hyperplane principal component analysis society of petroleum engineers Introduction...

... selection and formulation drilling fluids and materials drilling fluid property machine learning Artificial Intelligence drilling fluid chemistry controllable rheological parameter Iraq alkinani hilgedick drilling fluid formulation equivalent circulation density ECD correlation coefficient...

.... Drillstem Testing Novel Approach vit modeling rock type Model Match permeability Artificial Intelligence drillstem/well testing neural network heterogeneity modeling Probe pressure transient response formation model machine learning Upstream Oil & Gas flow unit classification multi...

.... production control Reservoir Surveillance artificial lift system production monitoring Upstream Oil & Gas pump head ESP machine learning enhanced recovery mechanical wear Efficiency real time system chemical flooding methods Artificial Intelligence friction loss pressure drop hydraulic...

... for complex carbonate reservoir. machine learning Artificial Intelligence water zone evaluation reprint log analysis Reservoir Characterization exploration Upstream Oil & Gas formation evaluation China resistivity decision tree learning carbonate reservoir well logging water formation...

.... Reservoir Characterization Artificial Intelligence Upstream Oil & Gas Abu Roash machine learning well logging waterflooding thickness map log analysis subsurface uncertainty enhanced recovery Modeling & Simulation pressure data net sand map information fusion Egypt assessment ARG...

... the integrated approach in an accurate definition of fracture properties, in terms of length and orientation, for reservoir simulation and production forecasting in unconventional reservoirs. machine learning shale gas Artificial Intelligence Upstream Oil & Gas Reservoir Characterization complex...

... under low oil price. The paper carries out studies on economic design of SP flooding according to particular reservoir properties. It also provides effective guidance for future pilot tests and commercial applications in more complex heavy oilfields under low oil price. machine learning Upstream...

... is significantly useful for generation of locales/leads for exploration & exploitation strategy in development stages. machine learning seismic data facies neutron porosity Cambay Basin delineate reservoir facies Reservoir Characterization PNN NPHI reservoir property Upstream Oil & Gas...

.... Artificial Intelligence machine learning Upstream Oil & Gas oilfield coefficient waterflood direction Interwell Connectivity producer streamline simulation waterflood front Injection Rate enhanced recovery injector Waterflood Management workflow production rate injection waterflooding...

... rate new solution misfit iumda machine learning reservoir simulation spe 153750 participation ratio hybrid algorithm control parameter Introduction Mutation operator Randomly generate a population of N solutions. Select a set of P promising solutions from the population...

... reservoirs, large number of wells and more than 40 years of production history, and finally how traditional reservoir assessment techniques can complement reservoir modeling work. data mining upstream oil & gas artificial intelligence forecasting primary parameter machine learning reservoir...

..., for example, oil saturation map from simulation. Our proposed method consistently outperforms the traditional approaches. Subsequent field infill drilling in the field has validated our approach. optimization problem grid cell artificial intelligence injector machine learning reservoir simulation...

... selection and formulation drilling fluids and materials log analysis drilling fluid property upstream oil & gas well testing machine learning artificial intelligence drilling fluid formulation shale reservoir section spe 155320 gauge mud weight corrosion drilling fluid chemistry well...

... the proposed methodology. We believe that this methodology opens new opportunities for real-time drilling optimization that can be efficiently implemented within the scope of the existing drilling practice. drilling interval real time diagnosis drill bit condition frequency machine learning neural...

..., and these facies associations may prove useful in future reservoir modeling studies. structural geology shale facies facies assam shelf neural network variation facies association bedded sandstone cross bedded sandstone depositional environment eocene reservoir bhogpara field sand body machine...

... machine learning proceedings evolutionary algorithm dimension upstream oil & gas christie Introduction History matching optimisation in Bayesian framework is a fairly recent approach to quantify uncertainty in oil industry practices. Currently some innovative global optimisation...

... programming technique and the good accuracy and simplicity of the developed model in comparison to the tested commonly utilized models. empirical correlation spe 128878 terminal equation of state natural gas yarborough machine learning genetic programming technique accuracy artificial...