Comparison of particle swarm optimization and simulated annealing for locating additional boreholes considering combined variance minimization

Soltani-Mohammadi, Saeed; Safa, Mohammad; Mokhtari, Hadi

doi:10.1016/j.cageo.2016.07.020

Cited by 29 publications

(7 citation statements)

References 39 publications

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“…It has been extensively used in the last years, particularly in the field of geosciences (e.g. Berné and Baselga, 2004;Santé-Riveira et al, 2008;Baselga, 2011;Sharma, 2012;Chimi-Chiadjeu et al, 2013;and Soltani-Mohammadi et al, 2016).…”

Section: Optimization Methodsmentioning

confidence: 99%

Fibonacci lattices for the evaluation and optimization of map projections

Baselga

2018

Computers & Geosciences

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Latitude-longitude grids are frequently used in geosciences for global numerical modelling although they are remarkably inhomogeneous due to meridian convergence. In contrast, Fibonacci lattices are highly isotropic and homogeneous so that the area represented by each lattice point is virtually the same. In the present paper we show the higher performance of Fibonacci versus latitude-longitude lattices for evaluating distortion coefficients of map projections. In particular, we obtain first a typical distortion for the Lambert Conformal Conic projection with their currently defined parameters and geographic boundaries for Europe that has been adopted as standard by the INSPIRE directive. Further, we optimize the defining parameters of this projection, lower and upper standard parallel latitudes, so that the typical distortion for Europe is reduced a 10% when they are set to 36º and 61.5º, respectively. We also apply the optimization procedure to the determination of the best standard parallels for using this projection in Spain, whose values remained unspecified by the National decree that commanded its official adoption, and obtain optimum values of 37º and 42º and a resulting typical distortion of 828 ppm.

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Section: Optimization Methodsmentioning

confidence: 99%

Fibonacci lattices for the evaluation and optimization of map projections

Baselga

2018

Computers & Geosciences

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“…In this paper, we use a distance-based generalized sensitivity analysis (DGSA) method (Fenwick et al, 2014;Park et al, 2016) to perform sensitivity analysis. Compared to the other global sensitivity analyses, such as variance-based methods (e.g., Sobol, 2001Sobol, , 1993, regionalized methods (e.g., Pappenberger et al, 2008;Spear and Hornberger, 1980), or treebased method (e.g., Wei et al, 2015), DGSA has its specific advantages for high-dimensional problems while requiring no functional form between model responses and model parameters. It can efficiently compute global sensitivity, which makes it preferred for our geological UQ problem where the models are large and computationally intensive.…”

Section: Reviewmentioning

confidence: 99%

Automated Monte Carlo-based quantification and updating of geological uncertainty with borehole data (AutoBEL v1.0)

2020

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Abstract. Geological uncertainty quantification is critical to subsurface modeling and prediction, such as groundwater, oil or gas, and geothermal resources, and needs to be continuously updated with new data. We provide an automated method for uncertainty quantification and the updating of geological models using borehole data for subsurface developments within a Bayesian framework. Our methodologies are developed with the Bayesian evidential learning protocol for uncertainty quantification. Under such a framework, newly acquired borehole data directly and jointly update geological models (structure, lithology, petrophysics, and fluids), globally and spatially, without time-consuming model rebuilding. To address the above matters, an ensemble of prior geological models is first constructed by Monte Carlo simulation from prior distribution. Once the prior model is tested by means of a falsification process, a sequential direct forecasting is designed to perform the joint uncertainty quantification. The direct forecasting is a statistical learning method that learns from a series of bijective operations to establish “Bayes–linear-Gauss” statistical relationships between model and data variables. Such statistical relationships, once conditioned to actual borehole measurements, allow for fast-computation posterior geological models. The proposed framework is completely automated in an open-source project. We demonstrate its application by applying it to a generic gas reservoir dataset. The posterior results show significant uncertainty reduction in both spatial geological model and gas volume prediction and cannot be falsified by new borehole observations. Furthermore, our automated framework completes the entire uncertainty quantification process efficiently for such large models.

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“…All of them perform well in seeking the optimised solution, but SA and GA generally cost more computation times, especially for the cases with the complicated objective function. On the contrary, the PSO algorithm is faster in convergence and more convenient in digital implementation [32,33,34].…”

Section: Introductionmentioning

confidence: 99%

Model updating for rotor-discs system and its application in dynamic coefficients identification of journal bearings

et al. 2021

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An accurate finite element (FE) model of the rotor-discs system is essential on the field identification of dynamic coefficients for journal bearings. This paper proposes a novel model updating method using the measured modal parameters. In this method, system mass and stiffness matrices were firstly updated by the particle swarm optimization (PSO) algorithm, in which the sensitivity analysis was used to select the appropriate variables to be optimized. Based on the updated results, the damping matrix defined as an improved Rayleigh Damping was then determined according to the experimental modal frequencies and damping ratios. To evaluate the effectiveness of this method, the FE model of a dual rotor-discs system was updated. The frequencies responses predicted by the updated model perform a good agreement with that from measured. Moreover, to validate the reliability of the updated model, the identifications of the dynamic coefficients were conducted on the flexible rotor test rig experimentally. The results demonstrated that the updated model has higher accuracy in field identification of dynamic coefficients than the original model, especially the system under critical speed.This study provides a feasibility strategy for updating the rotor-discs system and thereby establishes a foundation for further parameters identification and dynamic analysis.

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Comparison of particle swarm optimization and simulated annealing for locating additional boreholes considering combined variance minimization

Cited by 29 publications

References 39 publications

Fibonacci lattices for the evaluation and optimization of map projections

Fibonacci lattices for the evaluation and optimization of map projections

Automated Monte Carlo-based quantification and updating of geological uncertainty with borehole data (AutoBEL v1.0)

Model updating for rotor-discs system and its application in dynamic coefficients identification of journal bearings

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