- -

A Pilot Point Guided Pattern Matching Approach to Integrate Dynamic Data into Geological Modeling

RiuNet: Institutional repository of the Polithecnic University of Valencia

Share/Send to

Cited by

Statistics

A Pilot Point Guided Pattern Matching Approach to Integrate Dynamic Data into Geological Modeling

Show simple item record

Files in this item

dc.contributor.author Li, Liangping es_ES
dc.contributor.author Srinivasan, Sanjay es_ES
dc.contributor.author Zhou, Haiyan es_ES
dc.contributor.author Gómez-Hernández, J. Jaime es_ES
dc.date.accessioned 2014-09-17T15:40:44Z
dc.date.available 2014-09-17T15:40:44Z
dc.date.issued 2013-12
dc.identifier.issn 0309-1708
dc.identifier.uri http://hdl.handle.net/10251/39704
dc.description.abstract Methods based on multiple-point statistics (MPS) have been routinely used to characterize complex geological formations in the last decade. These methods use the available static data (for example, measured conductivities) for conditioning. Integrating dynamic data (for example, measured transient piezometric head data) into the same framework is challenging because of the complex non-linear relationship between the dynamic response and geology. The Ensemble PATtern (EnPAT) search method was recently developed as a promising technique to handle this problem. In this approach, a pattern is postulated to be composed of both parameter and state variables, and then, parameter values are sequentially (point-wise) simulated by directly sampling the matched pattern from an ensemble of training images of both geologic parameters and state variables. As a consequence, the updated ensemble of realizations of the geological parameters preserve curvilinear structures (i.e., non-multiGaussanity) as well as the complex relationship between static and dynamic data. Moreover, the uncertainty of flow and transport predictions can be assessed using the updated ensemble of geological models. In this work, we further modify the EnPAT method by introducing the pilot-point concept into the algorithm. More specifically, the parameter values at a set of randomly selected pilot point locations are simulated by the pattern searching procedure, and then a faster MPS method is used to complete the simulation by conditioning to the previously simulated pilot point values. This pilot point guided MPS implementation results in lower computational cost and more accurate inference of the parameter field. In addition, in some situations where there is sparsity of measured geologic static data, the EnPAT algorithm is extended to work only with the dynamic data. We employed a synthetic example to demonstrate the effectiveness of pilot points in the implementation of EnPAT, and also the capability of dynamic data to identify complex geologic structures when measured conductivity data are not available. es_ES
dc.description.sponsorship The first three authors gratefully acknowledge the financial support by DOE through project DE-FE0004962. The fourth author acknowledges the financial support by the Spanish Ministry of Science and Innovation through project CGL2011-23295. The authors also wish to thank Wolfgang Nowak as well as two anonymous reviewers for their comments, which helped improving the final version of the manuscript. en_EN
dc.language Inglés es_ES
dc.publisher Elsevier es_ES
dc.relation DOE DE-FE0004962 es_ES
dc.relation Spanish Ministry of Science and Innovation CGL2011-23295 es_ES
dc.relation.ispartof Advances in Water Resources es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject Multiple-point geostatistics es_ES
dc.subject Conditional simulation es_ES
dc.subject Inverse modeling es_ES
dc.subject Ensemble-based methods es_ES
dc.subject History matching es_ES
dc.subject.classification INGENIERIA HIDRAULICA es_ES
dc.title A Pilot Point Guided Pattern Matching Approach to Integrate Dynamic Data into Geological Modeling es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1016/j.advwatres.2013.10.008
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Ingeniería Hidráulica y Medio Ambiente - Departament d'Enginyeria Hidràulica i Medi Ambient es_ES
dc.contributor.affiliation Universitat Politècnica de València. Instituto Universitario de Ingeniería del Agua y del Medio Ambiente - Institut Universitari d'Enginyeria de l'Aigua i Medi Ambient es_ES
dc.description.bibliographicCitation Li, L.; Srinivasan, S.; Zhou, H.; Gómez-Hernández, JJ. (2013). A Pilot Point Guided Pattern Matching Approach to Integrate Dynamic Data into Geological Modeling. Advances in Water Resources. 62(Part A):125-138. doi:10.1016/j.advwatres.2013.10.008 es_ES
dc.description.accrualMethod Senia es_ES
dc.relation.publisherversion http://dx.doi.org/10.1016/j.advwatres.2013.10.008 es_ES
dc.description.upvformatpinicio 125 es_ES
dc.description.upvformatpfin 138 es_ES
dc.type.version info:eu repo/semantics/publishedVersion es_ES
dc.description.volume 62 es_ES
dc.description.issue Part A es_ES
dc.relation.senia 263357


This item appears in the following Collection(s)

Show simple item record