... evolutionary algorithm enhanced recovery shale oil machine learning sagd gas injection method oil shale objective function reservoir pressure shale gas optimization problem reservoir simulation upstream oil & gas matbal calculation gas injection steam-assisted gravity drainage field...

... history matching upstream oil & gas objective function simulation model application optimum field development planning field development optimization and planning fluid dynamics workflow data mining modeling & simulation equation of state reservoir simulation drillstem/well testing...

... oil & gas namorado field history match lswi optimization problem objective function optimization permeability curve development plan scenario dependent study artificial intelligence waterflooding geological realization robust optimization recovery factor wettability alteration...

... of the numerical reservoir scenarios, ensemble variability, and match improvement during data assimilation iterations. reservoir characterization reservoir simulation risk management upstream oil & gas objective function modeling & simulation dissimilarity matrix phylogenetic tree variability...

... scenarios than the traditional deterministic approach. The approach is also applicable to all types of enhanced oil recovery (EOR) projects. Artificial Intelligence injector information producer well optimizer Scenario enhanced recovery Upstream Oil & Gas objective function NPV...

... in the following steps of the decision-making process to define the production strategies under uncertainties. rmfinder 2 Upstream Oil & Gas original set original rmfinder Artificial Intelligence objective function representative model individual probability production strategy Scenario...

... representation matrix connectivity estimate objective function machine learning reservoir simulation productivity index production history Crmip connectivity time constant equation Injection Rate case 1 society of petroleum engineers Introduction The ultimate goal of reservoir modeling...

... challenges are both formulated as optimization problems of adjusting injection rates in order to optimize a particular objective function (e.g. minimizing subcool error or maximizing NPV). To address these challenges, this paper presents a nonlinear model-based adaptive-predictive control approach...

... as presented in Eq. 6 . In this way, a check for constraint violation is made for every well against every other well in the reservoir. Clearly, the formulation of constraints in this manner will yield a number of constraints equal to N c as given in Eq. 7 . Objective Function: Net Present Value...

... the probability distribution of the prediction period. It was based on the quality and weight attributed to the matching of an objective function defined for the history period. Similar approaches in this research topic are presented by WILLIAMS et al. (2004) and MA et al. (2006). QUEIPO et al. (2002) present...

... In this equation the coefficient values ( a k ) are related to the effects of the variables. The bigger their value, the larger will be their influence in the objective function value. The effects' values used in the construction of the response surface, which approximates the reservoir...

... to be adjusted is equal to or smaller than 15, a proxy model is built around the point of interest to calculate de gradient of the objective function ( Barton, 2009 ). If more than 15 variables are adjusted, a simultaneous perturbation ( Spall, 1998 ) is used to estimate the direction of the gradient...

... in the objective function. Transmissibility multipliers associated to regions located between wells are among the most traditional simulation model parameters used for history matching purposes. Such procedure is very efficient in order to match water production data, but usually leads to transmissibility maps...

... application reservoir simulation modeling processing facility scenario approximation wellpad timestep constraint simulation model spe 138888 objective function hysy optimization INTRODUCTION Repsol is a major integrated private oil and gas company with upstream activities in more than 30...

... recovery original well artificial intelligence spe 139376 objective function abandonment saturation oil rate marlim field Use of Sidetracks. As emphasized by Vikane et al. 1998 , citing the Gullfaks field, as the field becomes mature, the net present value of new wells decreases, either...

... of reservoir simulation. Neural networks can map the response surface in multidimensional spaces of a reservoir model (i.e. water production, bottom hole pressure etc.) or of an objective function with few number of simulations. The mapped response is then used as a substitute of reservoir simulation runs...

... model" very rapidly. New data must be incorporated as soon as possible, and, sometimes, important changes have to be made. As a rule, this must be done quickly, and the reservoir engineer hardly keeps the model accurate. reservoir simulation objective function artificial neural network machine...

... & Gas Artificial Intelligence optimization problem pipeline diameter NPV pump inlet pressure injector investment efficiency intelligent well reservoir waterflooding case example 2 workflow decision variable objective function producer Saputelli Scenario case example 1 valve...

... for a petroleum field? (b) For how long do the exploratory efforts deserve investment before the beginning of the development stage? (c) What is the appropriate value of the reservoir recovery factor? The maximization of the NPV is represented by an objective function. The influence of the parameters...

... to broaden the scope of analysis of the reservoirs in a time efficient manner. artificial intelligence oil density map interpretation best-matched model structural interpretation objective function fault block match quality recovery tdrm permeability spe 94940 assurance transmissibility...