Effect Of Grid Size In Risk Assessment Of Petroleum Fields

dc.creatorLigero E.L.
dc.creatorSchiozer D.J.
dc.creatorMaschio C.
dc.date2004
dc.date2015-06-26T14:25:29Z
dc.date2015-11-26T14:15:08Z
dc.date2015-06-26T14:25:29Z
dc.date2015-11-26T14:15:08Z
dc.date.accessioned2018-03-28T21:16:01Z
dc.date.available2018-03-28T21:16:01Z
dc.identifier
dc.identifierSpe International Petroleum Conference In Mexico - Proceedings. , v. , n. , p. 43 - 49, 2004.
dc.identifier
dc.identifier
dc.identifierhttp://www.scopus.com/inward/record.url?eid=2-s2.0-22344445540&partnerID=40&md5=5ef45c923c1b5fe687fd26185d026440
dc.identifierhttp://www.repositorio.unicamp.br/handle/REPOSIP/94770
dc.identifierhttp://repositorio.unicamp.br/jspui/handle/REPOSIP/94770
dc.identifier2-s2.0-22344445540
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/1242718
dc.descriptionIt was shown recently that it is important to evaluate risk through probabilistic methodologies that involve a high number of simulation models because of the number of uncertain attributes. Geological modeling yields reservoir models that are represented through fine grids with millions of blocks. A probabilistic risk evaluation based on such grids would require a very high computational effort. Therefore, an upscaling procedure is necessary to reduce the grid size but it is difficult to select a grid size that could represent an adequate balance between precision of risk assessment and computational effort. The methodology applied to quantify risk involves a sensitivity analysis in order to reduce the number of critical attributes and the simulation of reservoir models obtained through all possible combinations of these attributes. After the simulation of the models, a statistic treatment is used to evaluate the risk involved in the process. Several procedures can be used to speedup the process; however the number of simulation runs maybe very high. Upscaling of the simulation models can decrease significantly the computational effort and global time of the risk analysis process but it can also yield an inadequate risk assessment. In this paper the effect of the grid size on the process is evaluated. It was developed a methodology (1) to select an adequate grid size and (2) to speed up the risk analysis process. The choice of geological representative models from coarse grid risk evaluation can to be useful to represent the risk on fine model, avoiding the simulation of all fine models, yielding a significant speedup up of the process. Practical applications of upscaling in a probabilistic risk assessment, that use the concept of representative models selected to characterize geological uncertainties, are shown through calculations performed in a petroleum field represented by a fine grid simulation model with geological uncertainties. Copyright 2004, Society of Petroleum Engineers Inc.
dc.description
dc.description
dc.description43
dc.description49
dc.descriptionChristie, M.A., Blunt, M.J., Tenth SPE comparative solution project: A comparison of upscaling techniques (2001) SPE Reservoir Simulation Symposium, , SPE 66599, Texas, USA, February
dc.descriptionCosta, A.P.A., Schiozer, D.J., Treatment of geological attributes in risk analysis applied to the appraisal phase of petroleum fields (2003) Canadian International Petroleum Conference, , Calgary, Alberta, Canada, June
dc.descriptionDamsleth, E., Hage, A., Volden, R., Maximum information at minimum cost: A north sea field development study with an experimental design (1992) Journal of Petroleum Technology, , December
dc.descriptionDejean, J.P., Managing uncertainty on production prediction using integrated statistics (1999) Annual Technical Conference and Exhibition, , SPE 56696, Houston, USA, October
dc.descriptionGarb, F.A., Assessing risk in estimating hydrocarbon reserves and in evaluating hydrocarbon-producing properties (1988) Journal of Petroleum Technology, , June
dc.descriptionLigero, E.L., Costa, A.P.A., Schiozer, D.J., Improving the performance of risk analysis applied to petroleum field development (2003) Latin American and Caribbean Petroleum Engineering Conference, , SPE 81162, Trinidad, West Indies, April
dc.descriptionLigero, E.L., Maschio, C., Schiozer, D.J., Quantifying the impact of grid size, upscaling and streamline simulation in the risk analysis applied to petroleum field development (2003) 17th Reservoir Simulation Symposium, , SPE79677, Houston, USA, February
dc.descriptionLigero, E.L., Schiozer, D.J., Risk analysis applied to petroleum field development: Automated methodology and parallel computing to speedup the process (2002) Second Meeting on Reservoir Simulation, , Buenos Aires, Argentina, November
dc.descriptionLoschiavo, R., Steagal, D., Schiozer, D.J., Estudo do Impacto de Incertezas no Desempenho de Reservatórios de Petróleo (2000) 8th Brazilian Congress of Thermal Engineering and Sciences (ENCIT), , Porto Alegre, Brasil
dc.descriptionMaschio, C., Schiozer, D.J., A new upscaling technique based on dystra-parsons coefficient: Evaluation with streamline reservoir simulation (2003) Journal of Petroleum Science and Engineering, 40 (1-2). , October
dc.descriptionNewendorp, P., Schuyler, J., (2000) Decision Analysis for Petroleum Exploration, , Planning Press, Colorado, USA
dc.descriptionRose, P., Risk analysis and management of petroleum exploration ventures (2001) AAPG Methods in Exploration Series, (12). , Tulsa, Oklahoma, USA
dc.descriptionSalomão, M.C., Grell, A.P., Uncertainty in production profiles on the basis of geostatistic characterization and flow simulation (2001) Latin American and Caribbean Petroleum Engineering Conference, , SPE 69477, Argentina, March
dc.descriptionSubbey, S., Christie, M., A strategy for rapid quantification of uncertainty in reservoir performance prediction (2003) 17th Reservoir Simulation Symposium, , SPE79678, Houston, USA, February
dc.descriptionSantos, J.A.M., Schiozer, D.J., Quantifying production strategy impact in risk analysis of an E&P project using reservoir simulation (2003) 17th Reservoir Simulation Symposium, , SPE 79679, Houston, USA, February
dc.descriptionSteagall, D.E., Schiozer, D.J., Uncertainty analysis in reservoir production forecast during the appraisal and pilot production phases (2001) SPE Reservoir Simulation Symposium, , SPE 66399, Dallas, USA, February
dc.descriptionSchiozer, D.J., Ligero, E.L., Suslick, S.B., Costa, A.P.A., Santos, J.A.M., Use of representative models in the integration of risk analysis and production strategy definition (2004) Journal of Petroleum Science and Engineering, , to be published
dc.descriptionVenkataraman, R., Application of the method of experimental design to quantify uncertainty in production (2000) SPE Asia Pacific Conference on Integrated Modelling for Asset Management, , SPE 59422, Yokohama, Japan, April
dc.languageen
dc.publisher
dc.relationSPE International Petroleum Conference in Mexico - Proceedings
dc.rightsfechado
dc.sourceScopus
dc.titleEffect Of Grid Size In Risk Assessment Of Petroleum Fields
dc.typeActas de congresos


Este ítem pertenece a la siguiente institución