... reservoir surveillance reservoir characterization production control reservoir simulation co 2 sparse representation applied geoscience application international ensemble coefficient correlation subsurface storage production monitoring inversion energy 10 figure 2 bhakta realization...

... Geostatistical sampling and stochastic inversion algorithms allow generating a large number of reservoir models conditioned by the available borehole and geophysical measurements. The spatial variability of these realizations represents the uncertainty in the reservoir model. However, in many...

.... upstream oil & gas machine learning porosity scenario reservoir characterization american association artificial intelligence interpretation realization international energy 10 society algorithm poisson ratio fairway handil oilfield modification reservoir simulation exploration...

...) medium that are based on normal moveout (NMO) travel- time calculations and detectability criterion. We provide mathematical derivations of stochastic relations of the properties of the anisotropy parameters and show how to model their realizations and uncertainties. We demonstrate the method using a 3D...

... perform a numerical study of focusing target events in the image domain using various realizations of the cluttered media velocity models. We also perform a feasibility study of statistical imaging with path summation and present a heuristic technique to obtain a subsurface image without specifying...

... structural geology viking graben reservoir characterization petroleum saturation realization kauerauf scenario exploration geophysicist american association simulation similarity applied geoscience upstream oil & gas multidimensional migration langfjellet discovery...

... is implemented. A Bayesian implementation of the network architecture is implemented to assess uncertainty if needed. To train the network, noisy training data are either generated by adding synthetic noise or by reprocessing image logs to produce multiple realizations of noisy images. Training is done using...

... upstream oil & gas facies exploration geophysicist 10 geology back reservoir characterization thickness geophysics realization inversion probability dpi shaley sand machine learning applied geoscience rock property direct probabilistic inversion southern alberta oil play avo inversion...

... reservoir characterization joint avo zoeppritz avo inversion target parameter artificial intelligence sensitivity coefficient ps-joint zoeppritz avo inversion zoeppritz equation inversion upstream oil & gas data quality exploration geophysicist 10 avo range realization pp ps...

... path and where the parameters of the prior model are computed using kriging with locally variable mean. The resulting McMC algorithm efficiently provides spatially correlated realizations of petrophysical properties that are used to estimate the posterior distribution of the model variables...

... coefficients. We also simulated different interpretation attributes from a plurality of input image volumes which styles by varying the stiffness constraints in the fault produces a statistically valuable population of fault attribute likelihood prediction: Style S (curved faults with small realizations. We...

... porosity model exploration geophysicist 10 gpr data artificial intelligence reflection data inversion upstream oil & gas source wavelet borehole location reservoir characterization porosity log seg international exposition realization standard deviation denote stochastic realization...

... uncertainty estimation neural network seismic data epistemic uncertainty prediction seg international exposition deep neural network exploration geophysicist 10 proceedings artificial intelligence approximation impedance inversion model parameter elastic property inference realization...

... Gaussian simulation to sample the posterior probability distribution for obtaining multiple realizations of the impedance. This method can provide high-resolution impedance inversion results which respect all prior information and can be used for the uncertainty evaluation. Our method is a contribution...

... pore porosity seg international exposition realization In this work, we investigate the applicability of an ensemble based petrophysical parameter inversion framework to decouple changes in porosity field from dynamic reservoir/petrophysical parameters such as changes in saturation, pressure...

... intelligence reservoir property utilizing seismic integrated modeling core facies elastic lithofacies seismic data velocity model seg international exposition lithofacies realization saudi aramco reservoir model Quantifying Uncertainties by Utilizing Geostatistical Seismic Integrated Modeling...

... dataset realization non-reservoir facies seismic data probability prediction seg international exposition cnn Seismic inversion for reservoir facies under geologically realistic prior uncertainty with 3D convolutional neural networks Anshuman Pradhan* and Tapan Mukerji, Stanford University...

... exploration geophysicist 10 shaly sand realization lithology reservoir characterization study area shale rock physics modeling case study Seismic reservoir characterization of Wara Formation using prestack geostatistical inversion integrated with rock physics modeling: a case study in Kuwait Taiwen...

... the generation of multiple realizations. In addition, it provides excellent flexibility and QC capabilities, to help the user optimize results. The process is very fast and therefore very attractive. Presentation Date: Wednesday, October 14, 2020 Session Start Time: 1:50 PM Presentation Time: 2:15 PM...

..., 2019 Session Start Time: 1:50 PM Presentation Start Time: 2:15 PM Location: 304A Presentation Type: Oral well pick point sample point fault realization upstream oil & gas ccsvir support vector regression artificial intelligence characterize uncertainty well path point machine...