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Keywords: objective function
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Journal Articles
Journal: SPE Journal
SPE J. (2021)
Paper Number: SPE-206755-PA
Published: 11 November 2021
... the geological uncertainty. To fully grasp the expected economical revenue and the development risk, the MOO strategy is applied, in which the expected value and standard deviation of the net present values (NPVs) are regarded as the objective functions; a Pareto-ranking scheme is adopted to search...
Journal Articles
Journal: SPE Journal
SPE J. 26 (04): 2002–2017.
Paper Number: SPE-205395-PA
Published: 11 August 2021
... algorithm while honoring field-scale constraints and using a combined surface and subsurface performance-indicator-driven objective function. Ramp-up pattern designs are optimized separately using a solely pattern-scale performance-driven objective function in this stage. A preliminary pattern-delay time...
Journal Articles
Journal: SPE Journal
SPE J. 26 (04): 1964–1979.
Paper Number: SPE-205366-PA
Published: 11 August 2021
... constraint waterflooding objective function enhanced recovery reservoir simulation triobjective optimization production control artificial intelligence upstream oil & gas average life-cycle npv state constraint npv realization optimal control objective lexicographic method biobjective...
Journal Articles
Journal: SPE Journal
SPE J. 26 (04): 1590–1613.
Paper Number: SPE-204236-PA
Published: 11 August 2021
... simulation used for reservoir management has sufficient adjoint capability to compute gradients of the objective function and all state constraints, we show that one can develop a significantly more computationally efficient procedure by replacing the adjoint-enhanced reservoir simulator by a proxy model...
Journal Articles
Journal: SPE Journal
SPE J. 26 (04): 1614–1635.
Paper Number: SPE-205013-PA
Published: 11 August 2021
... black-box objective function and the high-dimensional design variables. Many low-fidelity methods based on simplified physical models or data-driven models have been proposed to reduce evaluation costs. These methods can approximate the global fitness landscape to a certain extent, but it is difficult...
Journal Articles
Journal: SPE Journal
SPE J. (2021)
Paper Number: SPE-203960-PA
Published: 13 July 2021
... of nonsmooth functions for problems in which the structure of the objective functions either cannot be exploited or are nonexistent. Such situations typically arise when the functions are computed as the result of numerical modeling, such as reservoir-flow simulation within the context of field-development...
Journal Articles
Journal: SPE Journal
SPE J. (2021)
Paper Number: SPE-205498-PA
Published: 04 June 2021
... spe journal training process application interwell connectivity machine learning reservoir surveillance reservoir simulation objective function oil production producer connectivity connectivity pattern proxy model minimization connectivity map regularization Reservoir simulation...
Journal Articles
Journal: SPE Journal
SPE J. 25 (05): 2433–2449.
Paper Number: SPE-199086-PA
Published: 15 October 2020
... simulated by SKESIM, the petrophysical properties were mapped by Gaussian‐like distributions. Numerical simulations were used to fit the simulated permeability field to a reference case through an objective function. A commercial finite difference simulator was used to compare the reference data...
Journal Articles
Journal: SPE Journal
SPE J. 25 (05): 2450–2469.
Paper Number: SPE-201229-PA
Published: 15 October 2020
... expensive problems, design computationally inexpensive functions to approximate each objective function. On the basis of characterization, we have designed an efficient multiobjective evolutionary algorithm (MOEA) to effectively deal with computationally expensive simulation‐based optimization problems...
Journal Articles
Journal: SPE Journal
SPE J. 25 (04): 1557–1577.
Paper Number: SPE-180148-PA
Published: 13 August 2020
... of the well‐test derivative with respect to reservoir permeability are derived and incorporated into an objective function to perform model calibration. The key to formulating the sensitivity coefficients is to use the functional derivative of the Eikonal equation to derive the analytic sensitivity...
Journal Articles
Journal: SPE Journal
SPE J. 25 (04): 2119–2142.
Paper Number: SPE-201209-PA
Published: 13 August 2020
... that are suitable for emulation and that are highly informative to reduce the input‐parameter space and investigate different classes of outputs and objective functions. We use output emulators and implausibility analysis iteratively to perform uncertainty reduction in the input‐parameter space, and we discuss...
Journal Articles
Journal: SPE Journal
SPE J. 25 (01): 139–161.
Paper Number: SPE-191480-PA
Published: 17 February 2020
... in place (OOIP) and the estimated ultimate recovery (EUR), are field‐scale objective functions that depend on properties (e.g., porosity) over the entire field. On the other hand, many measurement data from wells [e.g., bottomhole pressure (BHP)] are mainly sensitive to the reservoir properties near...
Journal Articles
Journal: SPE Journal
SPE J. 25 (01): 056–080.
Paper Number: SPE-198913-PA
Published: 17 February 2020
.... Previously, an efficient, distributed, optimization algorithm—global linear‐regression (GLR) with distributed Gauss‐Newton (GLR‐DGN)—has been proposed in the literature to iteratively minimize multiple objective functions by performing Gauss-Newton (GN) optimizations concurrently while dynamically sharing...
Journal Articles
Journal: SPE Journal
SPE J. 25 (01): 037–055.
Paper Number: SPE-193916-PA
Published: 17 February 2020
... simulation objective function covariance matrix history-matching problem error function gmm approximation training data uncertain parameter Bayesian Inference gaussian component production control gmm fitting method gmm fitting formulation posterior PDF reservoir characterization actual...
Journal Articles
Journal: SPE Journal
SPE J. 24 (04): 1526–1551.
Paper Number: SPE-190139-PA
Published: 27 May 2019
... for the current stage decisions while accounting for the uncertainty in future development activities. For optimization, a sequential approach is adopted whereby well locations and controls are repeatedly optimized until improvements in the objective function fall below a threshold. Case studies are presented...
Journal Articles
Journal: SPE Journal
SPE J. 23 (06): 2428–2443.
Paper Number: SPE-187430-PA
Published: 22 October 2018
... of numerical noise. We also propose a cost-saving training procedure by replacing bad-training points, which correspond to relatively large values of the objective function, with those training-data points (simulation data) that have smaller values of the objective function and are generated at most-recent...
Journal Articles
Journal: SPE Journal
SPE J. 23 (05): 1496–1517.
Paper Number: SPE-182639-PA
Published: 11 May 2018
... an approximate posterior by minimizing a large ensemble of perturbed objective functions in which the observed data and prior mean values of uncertain model parameters have been perturbed with Gaussian noise. Rather than performing these minimizations in isolation using large sets of simulations to evaluate...
Journal Articles
Journal: SPE Journal
SPE J. 23 (02): 467–481.
Paper Number: SPE-189457-PA
Published: 06 February 2018
... optimization iteration Control step optimization problem objective function gradient-based method optimization variable optimization process Scenario production optimization algorithm correlation range base case From the perspective of reservoir engineering, a reservoir-production strategy...
Journal Articles
Journal: SPE Journal
SPE J. 23 (02): 428–448.
Paper Number: SPE-182609-PA
Published: 09 January 2018
.... In this paper, a method called ensemble-variance analysis (EVA) is proposed. Derived from a multivariate Gaussian assumption between the observation data and the objective function, the EVA method quantifies the expected uncertainty reduction from covariance information that is estimated from an ensemble...
Journal Articles
Journal: SPE Journal
SPE J. 22 (06): 1984–1998.
Paper Number: SPE-182598-PA
Published: 25 September 2017
... continuous problems that have thousands of variables. An adjoint method is used to efficiently compute the derivatives of objective functions with respect to decision variables, and a sequential quadratic-programming method is used for optimization search. MOGA is a population-based method, which combines...

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