Actas de congresos
Risk Assessment Of Oil Fields Using Proxy Models: A Case Study
Registro en:
Journal Of Canadian Petroleum Technology. , v. 47, n. 8, p. 9 - 14, 2008.
219487
2-s2.0-49749135103
Autor
Risso F.V.A.
Risso V.F.
Schiozer D.J.
Institución
Resumen
Reservoir studies commonly consider many scenarios, cases and realizations. However, reservoir simulation can be expensive. Statistical design has been used in reservoir engineering applications, including performance prediction, uncertainty modelling, sensitivity studies, upscaling, history matching and development optimization. If reservoir simulation studies are conducted with a statistical design, response surface models can estimate how the variation of input factors affects reservoir behaviour with a relatively small number of reservoir simulation models. In petroleum exploration and production, a decision has to consider the risk involved in the process which can be obtained by quantifying the impact of uncertainties on the performance of the petroleum field in question. The process is even more critical because most of the investments are realized during the phase in which the uncertainties are greater. The statistical design is efficient to quantify the impact of the uncertainties of the reservoirs in the production forecast and to reduce the number of simulations to obtain the risk curve. The main objective of this work is the application of the statistical design: Box-Behnken and Central Composite Design using different attributes ranges. To compare the precision of the results, different techniques are used. These are the Derivative Tree Technique by simulation flow, the Monte Carlo Technique and the Response Surface Methodology. 47 8 9 14 CORRE, B., THORE, P., DE FERAUDY, V., VINCENT, G., Integrated Uncertainty Assessment for Project Evaluation and Risk Analysis (2000) SPE European Petroleum Conference, , paper SPE 65205 presented at the, Paris, France. 24-25 October VIRINE, L., RAPLEY, L., Decision and Risk Analysis Tools for the Oil and Gas Industry (2003) SPE Eastern Regional Meeting, , paper SPE 8482 presented at the, Pittsburgh, PA, 6-10 September WHITE, C.D., ROYER, S.A., Experimental Design as a Framework for Reservoir Studies (2003) SPE Reservoir Simulation Symposium, , paper SPE 79676 presented at the, Houston, TX, 3-5 February VENKATARAMAN, R., Application of the Method of Experimental Design to Quantify Uncertainty in Production Profiles (2000) SPE Asia Pacific Conference on Integrated Modelling for Asset Management, , paper SPE 59422 presented at the, Yokohama, Japan, 25-26 April HAALAND, P.D., Experimental Design in Biotechnology Marcel Dekker, New York, NY, 1989 PENG, C.Y., GUPTA, R., Experimental Design in Deterministic Modelling: Assessing Significant Uncertainties (2003) SPE Asia Pacific Oil and Gas Conference and Exhibition, Jakarta. Indonesia. 9-11, , paper SPE 80537 presented at the September MANCEAU, E., MEZGHANI, M., 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 paper SPE 71620 presented at the SPE Annual Technical Conference and Exhibition. New Orleans. LA, 30 September-3 October 2001 BOX, G.E.P., BEHNKEN, D.W., Some New Three Level Designs for the Study of Quantitative Variables (1960) Technometrics, 2 (4), pp. 455-475. , November BARROS NETO, B., SCARMlNIO, I.S., BRUNS, R.E., Planejamento e Otimização de Experimentos Unicamp, Campinas, Brazil, 1995 STEAGALL, D.E., SCHIOZER, D.J., Uncertainty Analysis in Reservoir Production Forecasts During Appraisal and Pilot Production Phases (2001) SPE Reservoir Simulation Symposium, , paper SPE 66399 presented at the, Houston. TX, 11-14 February SCHIOZER, 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, 44 (1-2), pp. 131-141 HAMMERSLEY, J.M., HANDSCOMB, D.C., Monte Carlo Methods Chapman and Hall, London, UK, 1964 SCHIOZER, D.J., LIGERO, E.L., MASCHIO, C., RISSO, F.V.A., Risk Assessment of Petroleum Fields-Use of Numerical Simulation and Proxy Models (2008) Petroleum Science and Technology, 26 (10-11), pp. 1247-1266. , July MONTGOMERY, D.C., (1996) Design and Analysis of Experiments, , 4th Edition. John Wiley & Sons. Inc, New York, NY JENSEN, J.L., LAKE, L.W., CORBETT, P.W.M., GOGGIN, D.J., (2000) Statistics for Petroleum Engineers and Geoscientists, , 2nd Edition. Elsevier, Amsterdam, Netherlands