Matches in SemOpenAlex for { <https://semopenalex.org/work/W2173301092> ?p ?o ?g. }
Showing items 1 to 78 of
78
with 100 items per page.
- W2173301092 abstract "Abstract Current techniques for production data integration into reservoir models can be broadly grouped into two categories: deterministic and Bayesian. The deterministic approach relies on imposing parameter smoothness constraints using spatial derivatives to ensure large-scale changes consistent with the low resolution of the production data. The Bayesian approach is based on prior estimates of model statistics such as parameter covariance and data errors and attempts to generate posterior models consistent with the static and dynamic data. Both approaches have been successful for field-scale applications although the computational costs associated with the two methods can vary widely. This is particularly the case for the Bayesian approach that utilizes a prior covariance matrix that can be large and full. To date, no systematic study has been carried out to examine the scaling properties and relative merits of the methods. The purpose of this paper is twofold. First, we systematically investigate the scaling of the computational costs for the deterministic and the Bayesian approaches for realistic field-scale applications. Our results indicate that the deterministic approach exhibits a linear increase in the CPU time with model size compared to a quadratic increase for the Bayesian approach. Second, we propose a fast and robust adaptation of the Bayesian formulation that preserves the statistical foundation of the Bayesian method and at the same time has a scaling property similar to that of the deterministic approach. This can lead to orders of magnitude savings in computation time for model sizes greater than 100,000 grid blocks. We demonstrate the power and utility of our proposed method using synthetic examples and a field example from the Goldsmith field, a carbonate reservoir in west Texas." @default.
- W2173301092 created "2016-06-24" @default.
- W2173301092 creator A5035529329 @default.
- W2173301092 creator A5056914640 @default.
- W2173301092 creator A5072724263 @default.
- W2173301092 date "2003-02-03" @default.
- W2173301092 modified "2023-10-18" @default.
- W2173301092 title "Scalability of the Deterministic and Bayesian Approaches to Production Data Integration into Field-Scale Reservoir Models" @default.
- W2173301092 cites W1509609288 @default.
- W2173301092 cites W1784770034 @default.
- W2173301092 cites W2038988652 @default.
- W2173301092 cites W2049598335 @default.
- W2173301092 cites W2054917359 @default.
- W2173301092 cites W2063104339 @default.
- W2173301092 cites W2065547182 @default.
- W2173301092 cites W2069328152 @default.
- W2173301092 cites W2074224247 @default.
- W2173301092 cites W2078517433 @default.
- W2173301092 cites W2103267705 @default.
- W2173301092 cites W2159537297 @default.
- W2173301092 doi "https://doi.org/10.2118/79666-ms" @default.
- W2173301092 hasPublicationYear "2003" @default.
- W2173301092 type Work @default.
- W2173301092 sameAs 2173301092 @default.
- W2173301092 citedByCount "13" @default.
- W2173301092 crossrefType "proceedings-article" @default.
- W2173301092 hasAuthorship W2173301092A5035529329 @default.
- W2173301092 hasAuthorship W2173301092A5056914640 @default.
- W2173301092 hasAuthorship W2173301092A5072724263 @default.
- W2173301092 hasConcept C105795698 @default.
- W2173301092 hasConcept C107673813 @default.
- W2173301092 hasConcept C11413529 @default.
- W2173301092 hasConcept C124101348 @default.
- W2173301092 hasConcept C126255220 @default.
- W2173301092 hasConcept C149569020 @default.
- W2173301092 hasConcept C154945302 @default.
- W2173301092 hasConcept C160234255 @default.
- W2173301092 hasConcept C178650346 @default.
- W2173301092 hasConcept C202444582 @default.
- W2173301092 hasConcept C33923547 @default.
- W2173301092 hasConcept C41008148 @default.
- W2173301092 hasConcept C48044578 @default.
- W2173301092 hasConcept C71983512 @default.
- W2173301092 hasConcept C77088390 @default.
- W2173301092 hasConcept C9652623 @default.
- W2173301092 hasConceptScore W2173301092C105795698 @default.
- W2173301092 hasConceptScore W2173301092C107673813 @default.
- W2173301092 hasConceptScore W2173301092C11413529 @default.
- W2173301092 hasConceptScore W2173301092C124101348 @default.
- W2173301092 hasConceptScore W2173301092C126255220 @default.
- W2173301092 hasConceptScore W2173301092C149569020 @default.
- W2173301092 hasConceptScore W2173301092C154945302 @default.
- W2173301092 hasConceptScore W2173301092C160234255 @default.
- W2173301092 hasConceptScore W2173301092C178650346 @default.
- W2173301092 hasConceptScore W2173301092C202444582 @default.
- W2173301092 hasConceptScore W2173301092C33923547 @default.
- W2173301092 hasConceptScore W2173301092C41008148 @default.
- W2173301092 hasConceptScore W2173301092C48044578 @default.
- W2173301092 hasConceptScore W2173301092C71983512 @default.
- W2173301092 hasConceptScore W2173301092C77088390 @default.
- W2173301092 hasConceptScore W2173301092C9652623 @default.
- W2173301092 hasLocation W21733010921 @default.
- W2173301092 hasOpenAccess W2173301092 @default.
- W2173301092 hasPrimaryLocation W21733010921 @default.
- W2173301092 hasRelatedWork W1635468856 @default.
- W2173301092 hasRelatedWork W1991109006 @default.
- W2173301092 hasRelatedWork W3214042144 @default.
- W2173301092 hasRelatedWork W4225603608 @default.
- W2173301092 hasRelatedWork W4235165088 @default.
- W2173301092 hasRelatedWork W4297026079 @default.
- W2173301092 hasRelatedWork W4328114192 @default.
- W2173301092 hasRelatedWork W561902361 @default.
- W2173301092 hasRelatedWork W786367546 @default.
- W2173301092 hasRelatedWork W1919985504 @default.
- W2173301092 isParatext "false" @default.
- W2173301092 isRetracted "false" @default.
- W2173301092 magId "2173301092" @default.
- W2173301092 workType "article" @default.