Solving optimization problems of optimal control of operational parameters of oil reservoir

The paper proposes a method for solving optimal control operating parameters of oil stratum: the arrangement of injection and production wells; regulation works well in setting of the two-phase filtration. Depending on the optimization of the planning horizon on the basis of the proposed method gives the prediction of increasing production by 27 % in the long-term planning up to 60 % for short-term planning

Mini-Workshop: Numerical Upscaling for Flow Problems: Theory and Applications

The objective of this workshop was to bring together researchers working in multiscale simulations with emphasis on multigrid methods and multiscale finite element methods, aiming at chieving of better understanding and synergy between these methods. The goal of multiscale finite element methods, as upscaling methods, is to compute coarse scale solutions of the underlying equations as accurately as possible. On the other hand, multigrid methods attempt to solve fine-scale equations rapidly using a hierarchy of coarse spaces. Multigrid methods need “good” coarse scale spaces for their efficiency. The discussions of this workshop partly focused on approximation properties of coarse scale spaces and multigrid convergence. Some other presentations were on upscaling, domain decomposition methods and nonlinear multiscale methods. Some researchers discussed applications of these methods to reservoir simulations, as well as to simulations of filtration, insulating materials, and turbulence

Structure and pressure drop of real and virtual metal wire meshes

An efficient mathematical model to virtually generate woven metal wire meshes is presented. The accuracy of this model is verified by the comparison of virtual structures with three-dimensional images of real meshes, which are produced via computer tomography. Virtual structures are generated for three types of metal wire meshes using only easy to measure parameters. For these geometries the velocity-dependent pressure drop is simulated and compared with measurements performed by the GKD - Gebr. Kufferath AG. The simulation results lie within the tolerances of the measurements. The generation of the structures and the numerical simulations were done at GKD using the Fraunhofer GeoDict software

Iterative solution of the pressure problem for the multiphase filtration

Applied problems of oil and gas recovery are studied numerically using the mathematical models of multiphase fluid flows in porous media. The basic model includes the continuity equations and the Darcy laws for each phase, as well as the algebraic expression for the sum of saturations. Primary computational algorithms are implemented for such problems using the pressure equation. In this paper, we highlight the basic properties of the pressure problem and discuss the necessity of their fulfillment at the discrete level. The resulting elliptic problem for the pressure equation is characterized by a non-selfadjoint operator. Possibilities of approximate solving the elliptic problem are considered using the iterative methods. Special attention is given to the numerical algorithms for calculating the pressure on parallel computers

Can cancer cells inform us about the tumor microenvironment?

Characteristics of the tumor microenvironment (TME) such as the leaky intratumoral vascular network and the density and composition of the desmoplastic extracellular matrix (ECM) contain essential information that determine the possibly heterogeneous interstitial fluid (IF) velocity field and interstitial fluid pressure (IFP). This information plays an important role for how anticancer drug that is delivered through the blood vasculature will distribute and possibly affect the tumor. The main question we deal with in this work is: Can we lure the cancer cells to reveal such information to us? By means of an in silico tumor model we demonstrate that subject to the condition that the tumor progression behavior is dominated by a cancer cell phenotype which moves by fluid-sensitive migration mechanisms as reported from experimental works, such information about the TME can be acquired by measuring the change in the cancer cell volume fraction distribution between two times T0 and T1, e.g., based on MRI images. We demonstrate this principle by using a continuum based multiphase model for tumor progression combined with assimilation of observed data through an ensemble Kalman filter approach which has been extensively and successfully used for updating advanced multiphase flow models in the context of reservoir simulation. Our results based on a synthetic dataset demonstrate how the methodology can be used to extract valuable quantitative information (e.g., interstitial fluid velocity field and fluid pressure, tissue conductivity reflecting ECM status, and effective vasculature conductivity) for which direct measurements may not be possible or impractical.publishedVersio

A novel block non-symmetric preconditioner for mixed-hybrid finite-element-based flow simulations

In this work we propose a novel block preconditioner, labelled Explicit Decoupling Factor Approximation (EDFA), to accelerate the convergence of Krylov subspace solvers used to address the sequence of non-symmetric systems of linear equations originating from flow simulations in porous media. The flow model is discretized blending the Mixed Hybrid Finite Element (MHFE) method for Darcy's equation with the Finite Volume (FV) scheme for the mass conservation. The EDFA preconditioner is characterized by two features: the exploitation of the system matrix decoupling factors to recast the Schur complement and their inexact fully-parallel computation by means of restriction operators. We introduce two adaptive techniques aimed at building the restriction operators according to the properties of the system at hand. The proposed block preconditioner has been tested through an extensive experimentation on both synthetic and real-case applications, pointing out its robustness and computational efficiency