... by applying RPM. Then, RPM prediction errors are added to the data so generated to account for the uncertainty associated with the approximations of the constitutive equations linking petrophysical properties with geophysical responses. sedimentary rock clastic rock lwd bayesian inference well...

...) Jacobi 2 theta Analytical Holanda et al. (2018) Copyright © 2023 Society of Petroleum Engineers reserves evaluation shale gas upstream oil & gas production forecasting complex reservoir oil shale shale oil bayesian inference production control artificial intelligence...

... growth models, and two physics-based models: scaled slightly compressible single-phase and scaled two-phase (oil and gas) solutions of the diffusivity equation. First, we perform Bayesian inference to generate probabilistic production forecasts for each model using a Bayesian workflow in which we assess...

...-oriented ODE solvers and expressive function transformations. Chen et al. (2019) explored several applications of the neural ODE approach. Several Bayesian inference techniques appropriate for systems with high-dimensional parameters have emerged, such as stochastic gradient Markov chain Monte Carlo...

... posterior distribution markov chain spe reservoir evaluation cumulative production autocorrelation reservoir evaluation production monitoring bayesian inference reservoir simulation drillstem/well testing hindcast iteration spe reservoir evaluation & engineering pseudopressure convergence...

...-intensive approach and an ABC approach. reservoir characterization shale oil artificial intelligence production forecasting oil shale fluid dynamics computational time fracture half-length pressure transient analysis bayesian inference shale gas pressure transient testing credible...

... (Ward County) subplays. 31 8 2020 2 11 2020 27 10 2020 14 1 2021 11 8 2021 Copyright © 2021 Society of Petroleum Engineers machine learning production control production monitoring artificial intelligence complex reservoir bayesian inference reservoir...

... in the prediction. Bayesian inference is a statistically consistent approach that systematically quantifies the value of information, allowing knowledge about the model parameters ( m ) to be updated by considering the existing data ( D ). The Bayesian framework is based on Bayes rule (Kruschke 2014...

... suggest that the index correctly predicts open vs. sealed fractures with an accuracy in excess of 80%. The value added is calculated using Bayesian inference in which the accuracy of the index serves as the likelihood of the prior distribution of open fractures to assess the posterior probability...

... an inversion algorithm on the basis of Bayesian inference to predict permeability using only wireline data. We illustrate the application of the procedure with a carbonate reservoir having extensive conventional core data. The results show that the Bayesian‐based clustering and inversion technique delivers...

... the space of possible mineralogies, indicating that more samples should be added to the calibration set. Copyright © 2020 Society of Petroleum Engineers machine learning Upstream Oil & Gas Bayesian Inference constraint ith column reservoir simulation mineral mixture Artificial...

... the actual objective function. machine learning history matching Artificial Intelligence Upstream Oil & Gas objective function reservoir simulation parallelized ar algorithm Bayesian Inference rml sample conditional realization approximation map point uncertainty quantification gaussian...

... forecast Reservoir Characterization Artificial Intelligence cumulative production geologic modeling production control Bayesian Inference likelihood function machine learning Reservoir Surveillance Engineering production history cumulative production threshold unconventional reservoir...

... et al. 2017 ). machine learning Bayesian Inference complex reservoir well data confidence level strike tolerance predictive method Artificial Intelligence Upstream Oil & Gas contingency table Reservoir Characterization fracture characterization actual fracture corridor fuzzy...

... production control production forecasting oil-production rate SEM Upstream Oil & Gas model parameter cumulative oil production Bakken well forecast Artificial Intelligence Arp model decline-curve model SPE Reservoir Evaluation lgm confidence interval flow behavior Bayesian Inference...

... ) = { y i λ 1 − 1 λ 1 ,  if λ 1 ≠ 0 log ( y i ) ,   if λ 1 = 0 . machine learning shale gas Bayesian Inference Artificial Intelligence Engineering Upstream Oil & Gas Thickness Eagle Ford shale Gaussian distribution...

... Upstream Oil & Gas Engineering production history Arp SPE Reservoir Evaluation decline-curve analysis probabilistic calibration production monitoring Bayesian Inference constraint boundary-dominated flow production rate heuristic rule reservoir equation estimation unconventional...

... associated with DCA models. This methodology does not require the estimation of the likelihood, which simplifies the Bayesian inference greatly. In approximate Bayesian computation (ABC) with rejection sampling, the posterior distribution is approximated by substituting different values of the decline...

... strategic planning and management Energy Economics Bayesian Inference complex reservoir machine learning Upstream Oil & Gas appraisal phase cumulative production Montney formation development well appraisal program cumulative gas production reliability reservoir production period...

... − m p r ) ] . 25 4 2015 24 3 2016 17 5 2016 18 10 2016 Copyright 2016, Society of Petroleum Engineers machine learning Bayesian Inference Engineering flow in porous media oil production trial-and-error method relative permeability enhanced...