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BEGIN:VEVENT
UID:news283@dmi.unibas.ch
DTSTAMP;TZID=Europe/Zurich:20180716T233556
DTSTART;TZID=Europe/Zurich:20121026T110000
SUMMARY:Seminar Numerical Analysis: Drosos Kourounis (Università della Svi
 zzera italiana)
DESCRIPTION:Adjoint-based gradients form an important ingredient of fast  o
 ptimization algorithms for computer-assisted history matching and  life-cy
 cle production optimization. Large-scale applications of  adjoint-based re
 servoir optimization reported so far concern relatively  simple physics\, 
 in particular two-phase (oil-water) or three-phase  (oil-gas-water) applic
 ations. In contrast\, compositional simulation has  the added complexity o
 f frequent flash calculations and high  compressibilities which potentiall
 y complicate both the adjoint  computation and gradient-based optimization
 \, especially in the presence  of complex constraints. These aspects are i
 nvestigated using a new  adjoint implementation in a research reservoir si
 mulator designed on top  of an automatic differentiation framework coupled
  to a standard  large-scale nonlinear optimization package.  Based on sev
 eral examples  of increasing complexity we conclude that the AD-based adjo
 int  implementation is capable of accurately and efficiently computing  gr
 adients for multi-component reservoir flow. However\, optimization of  str
 ongly compressible flow with constraints on well rates or pressures  leads
  to potentially poor performance in conjunction with an external  optimiza
 tion package. We present a pragmatic but effective strategy to  overcome t
 his issue.
X-ALT-DESC:Adjoint-based gradients form an important ingredient of fast  op
 timization algorithms for computer-assisted history matching and  life-cyc
 le production optimization. Large-scale applications of  adjoint-based res
 ervoir optimization reported so far concern relatively  simple physics\, i
 n particular two-phase (oil-water) or three-phase  (oil-gas-water) applica
 tions. In contrast\, compositional simulation has  the added complexity of
  frequent flash calculations and high  compressibilities which potentially
  complicate both the adjoint  computation and gradient-based optimization\
 , especially in the presence  of complex constraints. These aspects are in
 vestigated using a new  adjoint implementation in a research reservoir sim
 ulator designed on top  of an automatic differentiation framework coupled 
 to a standard  large-scale nonlinear optimization package.&nbsp\; Based on
  several examples  of increasing complexity we conclude that the AD-based 
 adjoint  implementation is capable of accurately and efficiently computing
   gradients for multi-component reservoir flow. However\, optimization of 
  strongly compressible flow with constraints on well rates or pressures  l
 eads to potentially poor performance in conjunction with an external  opti
 mization package. We present a pragmatic but effective strategy to  overco
 me this issue. 
DTEND;TZID=Europe/Zurich:20121026T120000
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