Parameter identification in large-scale models for oil and gas production

Doren, J. F. M. Van; Hof, Paul M.J. Van den; Bosgra, О.H.

doi:10.3182/20110828-6-it-1002.01823

Cited by 11 publications

(8 citation statements)

References 8 publications

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“…Next, by specifying a threshold, they eliminated the couplings where the interaction degree is below the threshold, which in turn resulted in a "manual" partitioning of the zones into a "non-predetermined" number of clusters where medium-to-high thermal interactions exist between members in each cluster. In [11], the concepts of graph theory-based structural and output identifiability [12], [13] together with the relevant metrics were used to decompose a multi-zone building into identifiable clusters satisfying both structural and output identifiability. Next, using decentralized uncertain models, a two-level hierarchical robust MPC scheme was developed for control of the whole building system.…”

Section: Introductionmentioning

confidence: 99%

Optimal partitioning of multi-thermal zone buildings for decentralized control

Atam¹,

Kerrigan²

2020

Preprint

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In this paper, we develop an optimization-based systematic approach for the challenging, less studied, and important problem of optimal partitioning of multi-thermal zone buildings for the decentralized control. The proposed method consists of (i) construction of a graph-based network to quantitatively characterize the thermal interaction level between neighbor zones, and (ii) the application of two different approaches for optimal clustering of the resulting network graph: stochastic optimization and robust optimization. The proposed method was tested on two case studies: a 5-zone building (a small-scale example) which allows one to consider all possible partitions to assess the success rate of the developed method; and a 20-zone building (a large-scale example) for which the developed method was used to predict the optimal partitioning of the thermal zones. Compared to the existing literature, our approach provides a systematic and potentially optimal solution for the considered problem.

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Section: Introductionmentioning

confidence: 99%

Optimal partitioning of multi-thermal zone buildings for decentralized control

Atam¹,

Kerrigan²

2020

Preprint

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“…Parameter estimation plays a crucial role in imaging whether in the medical field or in seismic exploration, and remains an active subject of research, with many applications such as tumor detection or stroke prevention in the case of medical imaging [39,37]. In geophysics, seismic imaging is used as a tool for exploring subsoil for oil, gas or other deposits [48,15]. From the mathematical point of view, parameter estimation can be written as a PDE-constrained optimization problem [45,26,29], which tries to minimize the misfit between the recorded data and the reconstruction obtained by an estimated parameter.…”

Section: Introductionmentioning

confidence: 99%

How to solve inverse scattering problems without knowing the source term: a three-step strategy

Graff¹,

Grote²,

Nataf³

et al. 2019

Inverse Problems

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The solution of inverse scattering problems always presupposed knowledge of the incident wavefield and require repeated computations of the forward problem, for which knowing the source term is crucial. Here we present a three-step strategy to solve inverse scattering problems when the time signature of the source is unknown. The proposed strategy combines three recent techniques: (i) wave splitting to retrieve the incident and the scattered wavefields, (ii) time-reversed absorbing conditions (TRAC) for redatuming the data inside the computational domain, (iii) adaptive eigenspace inversion (AEI) to solve the inverse problem. Numerical results illustrate step-by-step the feasibility of the proposed strategy. * Earlier known as Marie Kray.

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“…In the inverse medium problem, the scatterer is a penetrable, bounded inhomohogeneity inside the medium characterized by one or several varying physical parameters and the inverse problem consists in estimating these parameters from scattering data. Typical inverse medium problems include oil and gas exploration [35] in geophysics or breast tumor detection [23] in medical imaging. Numerical methods for the solution of inverse scattering problems essentially fall into either of two classes: qualitative and quantitative methods.…”

Section: Introductionmentioning

confidence: 99%

Adaptive eigenspace method for inverse scattering problems in the frequency domain

Grote

Nahum

2017

Inverse Problems

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A nonlinear optimization method is proposed for the solution of inverse scattering problems in the frequency domain, when the scattered field is governed by the Helmholtz equation. The time-harmonic inverse medium problem is formulated as a PDE-constrained optimization problem and solved by an inexact truncated Newtontype iteration. Instead of a grid-based discrete representation, the unknown wave speed is projected to a particular finite-dimensional basis of eigenfunctions, which is iteratively adapted during the optimization. Truncating the adaptive eigenspace (AE) basis at a (small and slowly increasing) finite number of eigenfunctions effectively introduces regularization into the inversion and thus avoids the need for standard Tikhonov-type regularization. Both analytical and numerical evidence underpins the accuracy of the AE representation. Numerical experiments demonstrate the efficiency and robustness to missing or noisy data of the resulting adaptive eigenspace inversion method.

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Parameter identification in large-scale models for oil and gas production

Cited by 11 publications

References 8 publications

Optimal partitioning of multi-thermal zone buildings for decentralized control

Optimal partitioning of multi-thermal zone buildings for decentralized control

How to solve inverse scattering problems without knowing the source term: a three-step strategy

Adaptive eigenspace method for inverse scattering problems in the frequency domain

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