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• W2317967661 abstract "History-Matching Multiple Attributes With Streamlines and Statistics Herv'e Gross Herv'e Gross Stanford University Search for other works by this author on: This Site Google Scholar Paper presented at the SPE Annual Technical Conference and Exhibition, San Antonio, Texas, USA, September 2006. Paper Number: SPE-106520-STU https://doi.org/10.2118/106520-STU Published: September 24 2006 Cite View This Citation Add to Citation Manager Share Icon Share Twitter LinkedIn Get Permissions Search Site Citation Gross, Herv'e. History-Matching Multiple Attributes With Streamlines and Statistics. Paper presented at the SPE Annual Technical Conference and Exhibition, San Antonio, Texas, USA, September 2006. doi: https://doi.org/10.2118/106520-STU Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex Search Dropdown Menu nav search search input Search input auto suggest search filter All ContentAll ProceedingsSociety of Petroleum Engineers (SPE)SPE Annual Technical Conference and Exhibition Search Advanced Search This paper was presented as part of the student paper contest associated with the Annual Technical Conference and Exhibition.AbstractGeological consistency is often overlooked in history-matching problems, yielding matched models that do not respect geological considerations. In reservoir modeling, geological consistency takes two aspects: the first is consistency in space, the second is consistency between the different properties. Consistency in space has been addressed in previous work, and a solution was found in the usage of local, flow-based, corrections as secondary information to a geostatistical simulation algorithm. Consistency across properties is the need for parameters such facies type, permeability, porosity, or net-to-gross, amongst others, to obey certain rules of inter-dependence. Honoring the relations across properties when correcting one parameter based on flow considerations is the topic of this paper.Instead of using a simple analytical correlation for all collocated properties, we use a statistical treatment of field data gathered either through pore network modeling or through analog models. The central idea of this technique is to compute probabilities of occurrence of any given combination of properties, and once a correction is computed on one given property, other properties are updated according to the prior probabilities.IntroductionHistory-matching is a complex inverse problem, consisting in model calibration based on flow data. It is an ill-posed problem, because the effect of a local modification on a particular property is difficult to anticipate. Treating history matching as a pure mathematical optimization problem is possible, but rapidly becomes untractable when the reservoir grid is large (most real reservoirs currently have 105-107 grid blocks). Nevertheless, reservoir models are a representation of geological reality, and any correction made to enhance flow predictions should therefore preserve the geological consistency of the calibrated models.With the increasing size and complexity of models, algorithms have been designed to automate history-matching. To counter the heavy computational load of traditional and automated trial-and-error methods, efficient inversion techniques using streamlines have been developed using either geophysical analogy with seismic rays[1], or an analogy with flow in independent layers[2,3]. The use of streamlines makes it possible to target corrections only where needed. Despite the simplifications often brought to the physics by streamline simulators, streamlines have proven to be suited to address real field history-matching problems in several studies[4,5,6].Once streamline-based corrections have been computed locally, an additional important contribution is to add the structural consistency to corrections. This has been done in previous papers using geostatistical algorithms[7], such as Direct Sequential Simulation[6,8], or Probability Perturbation Methods [9]. Adding geostatistical algorithms in history-matching made it possible to honor the structural component of geological consistency.The other component of geological consistency was still missing: cross-property correlations. Propagating corrections on all model parameters consistently without having to use analytical corrections issues a technique presented in this paper. The first part of this paper presents some conceptual notions on geological consistency in history matching while giving a rigorous mathematical definition. The second part describes the history-matching algorithm itself. The third part, finally, shows some examples validating the approach. Keywords: geological modeling, optimization problem, vertical permeability, geologic modeling, flow in porous media, Fluid Dynamics, Reservoir Characterization, reservoir simulation, Artificial Intelligence, Upstream Oil & Gas Subjects: Reservoir Characterization, Reservoir Fluid Dynamics, Reservoir Simulation, Geologic modeling, Flow in porous media This content is only available via PDF. 2006. Society of Petroleum Engineers You can access this article if you purchase or spend a download." @default.
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• W2317967661 title "History-Matching Multiple Attributeswith Streamlinesand Statistics" @default.
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