A Methodology To Evaluate And Reduce Reservoir Uncertainties Using Multivariate Distribution

dc.creatorBertolini A.C.
dc.creatorMaschio C.
dc.creatorSchiozer D.J.
dc.date2015
dc.date2015-06-25T12:51:59Z
dc.date2015-11-26T14:43:41Z
dc.date2015-06-25T12:51:59Z
dc.date2015-11-26T14:43:41Z
dc.date.accessioned2018-03-28T21:51:59Z
dc.date.available2018-03-28T21:51:59Z
dc.identifier
dc.identifierJournal Of Petroleum Science And Engineering. Elsevier, v. 128, n. , p. 1 - 14, 2015.
dc.identifier9204105
dc.identifier10.1016/j.petrol.2015.02.003
dc.identifierhttp://www.scopus.com/inward/record.url?eid=2-s2.0-84924173367&partnerID=40&md5=a06cb1ab7bc6b1eb3caeefc69e771f0a
dc.identifierhttp://www.repositorio.unicamp.br/handle/REPOSIP/85318
dc.identifierhttp://repositorio.unicamp.br/jspui/handle/REPOSIP/85318
dc.identifier2-s2.0-84924173367
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/1251793
dc.descriptionHistory matching is a challenging and time-consuming task related to reservoir simulation. Probabilistic approaches using dynamic data are often used to reduce reservoir uncertainties and improve matching. This work presents a new process to evaluate and reduce reservoir uncertainties using multivariate analysis incorporating the interaction between reservoir properties.The proposed uncertainty reduction workflow provides a multivariate approach without the use of proxy models, allowing understanding of the reservoir response through the R2 matrix as well as more reliable reservoir predictions. The methodology offers a quantitative analysis and a new tool to evaluate and reduce uncertainties. The process uses a Latin Hypercube (LHC) to sample the reservoir attribute range and a smoothed mismatch data set from the LHC selected objective functions. The attribute interval, which minimizes the mismatch, is identified through polynomial fitting. The main objective is to reduce uncertainties considering the reservoir attributes range and a multivariate sensitivity matrix.The methodology was firstly applied to a simple synthetic reservoir simulation model with 20 uncertainty attributes and we drew the following conclusions: (1) R2 sensitivity matrix clearly showed the key physical features of the reservoir model; (2) all reservoir attributes ranges were reduced, providing a set of simulation models with improved history matching. We successfully applied to the UNISIM-I-H reservoir model based on Namorado field, Campos basin, Brazil.
dc.description128
dc.description
dc.description1
dc.description14
dc.descriptionAchelis, S.B., (1995) Technical Analysis From A to Z. Second Printing, pp. 184-192. , McGraw-Hill
dc.descriptionAvansi, G.D., Schiozer, D.J., A New Approach to History Matching Using Reservoir Characterization and Reservoir Simulation Integrated Studies, , OTC, 4-5 Maio, Houston, Estados Unidos, 2015
dc.descriptionBennett, F., Graf, T., Use of geostatistical modeling and automatic history matching to estimate production forecast uncertainty - a case study (2002) Proceedings of SPE 74389, International Petroleum Conference and Exhibition, , Mexico, 10-12 February
dc.descriptionBertolini, A., Schiozer, D., Influence of the objective function in the history matching process (2011) J. Pet. Sci. Eng., 78 (1), pp. 32-41
dc.descriptionBissel, R.C., Combining geostatistical modeling with gradient information for history matching: the Pilot Point Method (1997) Proceedings of SPE 38730 Annual Technical Conference and Exhibition, , San Antonio, Texas, USA, 5-8 October
dc.descriptionDeutsch, C., Calculating effective absolute permeability in sandstone/shale sequences SPE (1989) Form. Eval., 4 (3), pp. 343-348
dc.descriptionEmerick, A.A., Reynolds, A.C., Combining the ensemble Kalman filter with Markov Chain Monte Carlo for improved history matching and uncertainty characterization (2012) Proceedings of SPE 141336-PA, SPE Reservoir Simulation Symposium Held in The Woodlands, , Texas, USA
dc.descriptionFerreira, C., Vernon, I., Schiozer, D.J., Goldstein, M., Use of emulator methodology for uncertainty reduction quantification (2014) Proceedings of SPE 169405-MS, Latin American and Caribbean Petroleum Engineering Conference Held in Maracaibo, , Venezuela, 21-23 May
dc.descriptionGu, Y., Oliver, D.S., History matching of the PUNQ-S3 reservoir model using the ensemble Kalman filter (2004) Proceedings of SPE 89942, Annual Technical Conference and Exhibition, , Houston, Texas, USA, 26-29 September
dc.descriptionGuardado, L.R., Gamboa, L.A.P., Lucchesi, C.F., Petroleum geology of the Campos Basin, Brazil, a model for a producing Atlantic Type Basin: Part 2 (1989) AAPG Spec. Vol., A132, p. 42
dc.descriptionGuardado, L.R., Spadini, A.R., Brandao, J.S.L., Mello, M.R., Petroleum system of the Campos Basin, Brazil (2000) Proceedings of M.R.M.a Petroleum Systems if the South Atlantic Margins: AAPG Memoir, 73, pp. 317-324
dc.descriptionLiu, C., McVay, D.A., (2010) Continuous Reservoir-Simulation-Model Updating and Forecasting Improves Uncertainty Quantification, , SPE 119197
dc.descriptionGuardado, L.R., Gamboa, L.A.P., Lucchesi, C.F., Petroleum geology of the Campos Basin, Brazil, a model for a producing Atlantic type Basin: Part 1 (1989) AAPG Spec. Vol., A132, p. 33
dc.descriptionManceau, E., Mezghani, I., Zabalza-Mezghani, I., Roggero, F., Combination of experimental design and joint modeling methods for quantifying the risk associated with deterministic and stochastic uncertainties - an integrated test study (2001) Proceedings of SPE 71620 Annual Technical Conference and Exhibition held in New Orleans, , Louisiana, 30 September-3 October
dc.descriptionMaschio, C., Schiozer, D., A new upscaling technique based on Dykstra-Parsons coefficient: evaluation with streamline reservoir simulation (2003) J. Pet. Sci. Eng., 40, pp. 27-36
dc.descriptionMaschio, C., Schiozer, D., A new procedure to reduce uncertainties in reservoir models using statistical inference and observed data (2013) J. Pet. Sci. Eng., 110, pp. 7-21
dc.descriptionMeneses, S., Adams, T., (1990) Ocorrências de resistividades anÔmalas no Campo de Namorado, Bacia de Campos., , Rio de Janeiro, Brasil
dc.descriptionMaschio, C., Schiozer, D., Moura Filho, M.A.B., Methodology to quantify the impact of uncertainties in the history matching process and in the production forecast (2005) Proceedings of SPE 96613 Prepared for Presentation at the SPE Annual Technical Conference and Exhibition, , Dallas, Texas, USA
dc.descriptionRisso, F.V.A., Risso, V.F., Schiozer, D.J., Risk analysis of petroleum fields using Latin hypercube, Monte Carol and derivative tree techniques (2011) J. Pet. Gas Explor. Res., 1 (1), pp. 14-21
dc.languageen
dc.publisherElsevier
dc.relationJournal of Petroleum Science and Engineering
dc.rightsfechado
dc.sourceScopus
dc.titleA Methodology To Evaluate And Reduce Reservoir Uncertainties Using Multivariate Distribution
dc.typeArtículos de revistas


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