... obtained for the two field cases consist of the posterior ensemble of model parameters, estimated flow rates, investigated pore volume, productivity index, single-well deconvolved response, as well as interference responses for the multi-well case. geologist drillstem testing production monitoring...

... index estimate water saturation model parameter enhanced recovery rock sample core sample equation 5 berea sandstone water saturation wettability state interpretation wettability resistivity measurement gaussian distribution function Introduction Sedimentary rocks are often...

... displacements, i.e., a non-wetting phase displacing a viscous wetting phase. We modified a previously proposed effective-fingering model for imbibition processes. Laboratory unstable coreflood experiments were history matched. Power-law correlations were developed between history matched model parameters...

... network models, which are first used to perform global sensitivity analysis on all relevant model parameters so that the influence of each parameter on the dipole dispersion data can be well understood. A least-squares inversion scheme utilizing the trained model was developed and tested on synthetic...

.... In our Finite Element simulations of the shale creep phenomenon, we have used the time-hardening creep model, which assumes a non-linear relationship between creep strain and stress, temperature and time. The model parameters were obtained from a curve fit of laboratory experimental results conducted...

.... The inversion method that solves the model-maturation problem takes advantage of the adjoint-based computation of objective function gradients for a very large number of model parameters at the cost of a forward and a backward (adjoint) simulation. The inversion algorithm calibrates model parameters...

... to reduce and characterize the uncertainties in the model parameters by honoring various types of data including field dynamic data and measurements. We discuss the implementation of automated schemes for weighting of various types of data in the ensemble-based history matching algorithms. These schemes...

... quantify the spatial distribution of reservoir model parameters like permeability or porosity. As the reservoir parameters and flow response variables are often related by non-linear relationships, the solution to the inverse problem of history matching is often non-unique. This makes it a problem that can...

... to the change in model parameters. This gives an additional detailed information that improves the inversion performance. The outline of our paper is as follows: First, we introduce the Bayesian theory with its application on the VSP look-ahead prediction. Second, we present the application of the Gauss...

... phase behavior model parameter surfactant equation curvature equation Introduction Chemical enhanced oil recovery processes may be conducted by injecting surfactants, co-solvents and polymer in a carefully designed chemical slug optimized for a target reservoir ( Hirasaki, et al. , 2011...

... mole of CH 4 from CH 4 -saturated water. equation of state stability analysis model parameter Modeling & Simulation methane composition PVT measurement calculation solubility phase equilibria fluid modeling Upstream Oil & Gas co 2 aqueous phase prsv ws experimental data...

... cube model parameter elastic property model property well data deep-water reservoir heterogeneity procedure cube reservoir model facies proportion cube heterogeneity reservoir property seismic facies society of petroleum engineers Introduction It is generally accepted...

... function model parameter pressure transient analysis pressure transient testing GLM likelihood maximization machine learning Upstream Oil & Gas Gaussian distribution convergence dataset 18 estimation iteration outlier probability density function Horne histogram parameter estimation...

...-uniqueness resulting from long-term transient flow regimes. This non-uniqueness, an unavoidable fact when analyzing inverse problems, is worsened by the uncertainty surrounding input model parameters when attempting to describe reservoir systems with a great deal of complexity (e.g. very low permeability...

...-estimated when large numbers of data are used to constrain forecast uncertainty in an imperfect model with accurate data. This undesired effect comes out as the flip-side of the attractive property of Bayesian methods that model parameters can be inferred with increased accuracy if the number of data...

... The EnKF consists of two recursive steps: forecast and update. During the forecast step, all realizations of reservoir model parameters are integrated with time using a reservoir simulator. The reservoir simulator used for modeling reservoir fluid flow and reporting the simulated data is treated...

...Introduction Abstract Most decline curve methods have two main limitations; the model parameters as a rule are not functions of reservoir parameters and may yield unrealistic (nonphysical) values of expected ultimate recovery (EUR) because boundary-dominated flow may not develop...

... derivative, or the so called "qDb" plots, are utilized to minimize the non-uniqueness inherent in the history matching process by providing guidance in the selection of rate decline model parameters. Following the selection of model parameters, the normalized rate decline relations are superposed...

... simulation simulation model model parameter model construction parameter upstream oil & gas future performance reliability forecast history matching particular purpose ryder scott company reviewer Introduction Petroleum engineers are required to make many significant decisions...

... characteristics, data-match quality, and posterior model parameter distributions. Based on the knowledge developed on the ICFM problem, we isolate VFSA and PSO and further evaluate their performance on a field case involving an offshore West African deepwater turbidite reservoir undergoing waterflooding...