Uncertainty quantifying of the green field: integrating experimental design and field development strategy

UDK: 622.276.1/.4

Key words: uncertainty, design of experiments, risk, experimental design, probability, forecast

Authors: E.V. Bogdanov (Oil and Gas Production Department Surgutneft, RF, Surgut)

Qualitative and quantitative determination of the risks and uncertainties in oil and gas fields - one of the key problems in the industry at the moment. The main purpose of the article is to improve the accuracy in the determination of the initial geological reserves of hydrocarbons and probable recoverable reserves through the application of uncertainty and risk assessment methodologies for development strategy optimization of the oil field. The author proposes a solution to the problem of identifying and taking into account the static geological uncertainty (when calculating reserves) and dynamic reservoir uncertainty of the field development (for the calculation of the forecast cumulative production). Unconventional approach has been applied, including the use of the method of design of experiments, to significantly reduce the time spent on analysis and quantification of the uncertainty.

The method of design of experiments aimed, in particular, quick calculation of the dynamic reservoir uncertainty as the most time-consuming calculations to assess the risks. This method can significantly reduce the number of starts of hydrodynamic reservoir models for determination possible forecasts for the field, taking into account the uncertainty for the risk assessment. Method testing was carried out in the field, has not yet entered into an industrial development phase (green field), through geological and hydrodynamic reservoir modeling, taking into account uncertainties, including applying the various field development systems. Result is the identification and quantification of the static uncertainty of reserve estimates and dynamic uncertainty of the cumulative production forecast calculation. An alternative field development strategy and optimal well planning was proposed, better taking into account the geological structure of the field, including static and dynamic uncertainty. The final calculation of the cost-effectiveness (NPV increase) of alternative development strategy that takes into account the risks is given.
References
1. Thore P., Shtuka A., Lecour M. et al., Structural uncertainties: Determination,
management, and applications, Geophysics, 2002, V. 67 (3), pp. 840–852.
2. Oliver D. S., Reynolds A.C., Liu N., Inverse theory for petroleum reservoir characterization
and history matching, Cambridge University Press, 2008, 380 p.
3. Bhark E., Dehghani K., Matching Benchmarking: Design of-Experimentsbased
techniques, SPE 170690, 2014.
4. Kostenko A.V., Hyndman R.J., Forecasting without significance tests, Australia:
Monash University, 2008.
5. Nuzzo R., Statistical errors. P values, the ‘gold standard’ of statistical validity,
are not as reliable as many scientists assume, Nature, 2014, V. 506,
pp. 150–152.
6. Pyrcz M.J., Deutsch C.V., Geostatistical reservoir modeling, New York: Oxford
University Press, 2014, 376 p.
7. Ringrose P., Bentley M., Reservoir model design: A practitioners’s guide,
Springer Netherlands, 2015.