... in the overall geological environment. The hidden layer design is closely integrated with Bayesian inference. In the diagram, the hidden layers extract and map the input features, with Bayesian inference applied such that the hidden layer weights are modeled as probabilistic parameters rather than simple...

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... simulation runs than the traditional genetic or evolutionary algorithms. The geological realism of the model is retained for robust prediction and development planning. geology modeling & simulation reservoir simulation artificial intelligence history matching bayesian inference localization...

... provides useful practical experience to mitigate under-deposit SRB corrosion of high salinity and high acidity water injection systems. geologist riser corrosion well integrity geology bayesian inference enhanced recovery mineral materials and corrosion flowline corrosion corrosion inhibitor...

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... the sequential processes. machine learning reservoir characterization data quality artificial intelligence bayesian inference upstream oil & gas uncertainty map uncertainty estimation time uncertainty velocity uncertainty well control depth uncertainty drilling depth prognosis workflow...

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... operators to predict and manage remaining membrane performance in the field proactively thereby optimize the membrane replacement expenditure. Workplace Hazard Corrosion Inhibition machine learning data mining Artificial Intelligence oilfield chemistry Production Chemistry Bayesian Inference...

... to preconditioning to ensure improved CDP gather flatness and signal-to-noise ratio. Starting from geostatistical modeling, the inversion generated multiple detailed realizations of lithology and elastic properties based on Bayesian Inference and Markov-Chain Monte Carlo methods. Statistic of multiple resulting...

... of reservoir models, which is a vital component in the entire hydrocarbon maturation cycle. geologic modeling geological modeling machine learning Reservoir Characterization Artificial Intelligence Bayesian Inference reservoir simulation Upstream Oil & Gas correspond dynamic fingerprint...

... of the uncertain event of interest. We suspect that the reason lies in the issue discussed above. machine learning Artificial Intelligence risk management asset and portfolio management Bayesian Inference Upstream Oil & Gas preposterior posterior likelihood function information error function...

... a unified framework to compute the Value of Information, and this is one of the reasons why there is still a certain level of distrust among the practitioners when using such tools. machine learning Reservoir Characterization Artificial Intelligence asset and portfolio management Bayesian...

... system Bayesian Inference Upstream Oil & Gas displacement EOR selection Efficiency selection information alet al Bayesian network Screening database evaluation advisor system logic EOR method international petroleum technology conference reservoir displacement efficiency IPTC...

... and disciplines with different languages. Therefore, the overall value can be easily lost or diminished in translation. machine learning Reservoir Characterization Artificial Intelligence Bayesian Inference Upstream Oil & Gas uncertainty analysis translation quantification seismic data...

...). machine learning Artificial Intelligence Bayesian Inference Drillstem Testing Upstream Oil & Gas drillstem/well testing well head pressure category well head temperature prediction result prediction Bayesian network input data vector workflow production well water production...

... to well calibrated reservoir models, the reliability is often questionable. machine learning Artificial Intelligence Bayesian Inference flow in porous media reservoir simulation history matching Upstream Oil & Gas Fluid Dynamics analysis step water saturation porosity conventional...

... a probabilistic approach (Bayesian inference) making use of both real time measurements and pre-calculated concentration responses from unitary emissions (puffs) on sensors. This approach was validated successfully using a limited number of sensors and sources but with the complex structure and flow patterns...

... production forecasts, we will consider both the uncertainty of parameters that do not influence the match and also a representative sample of all possible matched models. machine learning Artificial Intelligence Bayesian Inference reservoir simulation history matching Upstream Oil & Gas...

... that one of these conjugate priors and its associated likelihood functions adequately describe the uncertainties, the probability updating part of the VOI analysis is trivial. machine learning Artificial Intelligence risk management Bayesian Inference Upstream Oil & Gas discretization...

... decision analysis optimal design valve probability risk management bayesian inference iptc 11294 monte carlo oil production information IPTC 11294 Probabilistic Field Development in Presence of Uncertainty Sara Passone, BP Exploration, and Gregory J. McRae, Chemical Engineering Department...