... the processing workflows on the waterfront, fluid movement, change in water saturation and seismic history matching over Volve field. upstream oil & gas american association signature history matching seismic history matching quantitative interpretation international refine saturation...

... is a potential candidate for large-scale offshore CO 2 storage in the North Sea. The numerical results demonstrate that DAS data is capable of monitoring CO 2 plume movement and thus can be considered as an efficient geophysical tool in CCS. upstream oil & gas production logging history matching...

... Geophysicists First International Meeting for Applied Geoscience & Energy 10.1190/segam2021-3582926.1 Page 2161 REFERENCES Baker, R. O., S. Chugh, C. Mcburney, and R. McKishnie, 2006, History matching standards; quality control and risk analysis for simulation: Paper Presented at the Canadian International...

... with synthetic seismic data. machine learning history matching posterior distribution reservoir simulation proposal distribution water saturation seismic inversion artificial intelligence seismic data inverse problem iteration algorithm porosity inversion mcmc method geophysics markov chain...

... Presentation Type: Poster reservoir simulation discrepancy artificial intelligence upstream oil & gas machine learning history matching posterior distribution stein discrepancy kernel stein discrepancy exploration geophysicist 10 measuring langevin mcmc sample quality international...

... Time: 1:50 PM Presentation Time: 3:55 PM Location: Poster Station 4 Presentation Type: Poster artificial intelligence upstream oil & gas reservoir simulation rosemary knight department machine learning structural geology aem method reservoir characterization history matching...

... ABSTRACT Seismic history matching is typically a high-dimensional and severely non-linear inverse problem, which is extremely time-consuming especially for ensemble-based methods. In this work, we propose a deep convolutional auto-encoder (DCAE) to sparsely represent the seismic data...

.... posterior sample oware reservoir simulation seg international exposition coefficient realization annual meeting algorithm artificial intelligence constraint basis vector machine learning water resource research imaging history matching inversion estimation reconstruction reduction...

... ABSTRACT In this work, we propose an ensemble-based seismic history matching approach to predict reservoir properties, i.e. porosity and permeability, with uncertainty quantification, using both production and time lapse seismic data. To avoid the common underestimation of uncertainty...

... data acquisition hamiltonian monte carlo inverse problem hamiltonian dynamic monte carlo method hmc reservoir simulation posterior distribution inversion canonical distribution lwd upstream oil & gas history matching log analysis well logging model parameter annual meeting...

... ABSTRACT In this work, we propose an ensemble based 4D seismic history matching framework for reservoir characterization. Here, we use amplitude versus angle (AVA) attributes as seismic data, apply multilevel discrete wavelet transforms (DWT) to the attributes, and estimate noise level...

... algorithm inverse problem estimation seismic parameter estimation proposal reservoir characterization forward simulation posterior distribution mcmc algorithm algorithm interface gmsfem inversion simulation seg denver 2014 reservoir simulation bayesian inference basis function history...

... reservoir simulation Artificial Intelligence Upstream Oil & Gas Reservoir Characterization history matching Bayesian Inference Scarborough gas field rj-mcmc inversion noise correlated error marine csem data hierarchical bayesian inversion horizontal line probability correlation seg...

... evolution of the flow. velocity field geophysical imaging initial state regularization flow field upstream oil & gas history matching experiment reservoir characterization tomography experiment reservoir simulation saturation lar ruthotto initial saturation artificial intelligence...

... and applicability of the proposed method and sensitivity of different parameters is explored using synthetic seismic data. adaptive spatial history matching mp ple mmo od machine learning mp pli upstream oil & gas da ata reservoir property artificial intelligence ost ter rio modeling markov...

... sediments. history matching bayesian inversion horizontal resistivity inversion kerry key posterior distribution upstream oil & gas interface resistivity reservoir simulation bayesian inference layered structure parameterization reservoir characterization artificial intelligence...

... Background Summary Model updating in history matching is a difficult and non-unique process. Normally, the model update depends on the insight of reservoir engineers. The updating of the model is done so that the historical production data can be reproduced. 3D seismic data in general...

... of the production history matching process, and show how the use of seismic monitoring can improve reservoir prediction. seismic data history matching stanford university reservoir characterization time-lapse seismic data reservoir simulation seg houston 2009 artificial intelligence coefficient...

... corporation university interface depth seg houston 2009 history matching annual international meeting velocity log algorithm international exposition seismogram artificial intelligence machine learning quantification backus averaging reservoir simulation mcmc algorithm velocity model log data...

... machine learning seismic parameter estimation realization parameter estimation fine scale information different scale algorithm mcmc algorithm bayesian inference history matching new mcmc algorithm posterior estimation reservoir characterization marginal ppd genetic algorithm...