Approaches to selection of realizations in probabilistic modeling of geological model and analysis of influence on forecast production profile
https://doi.org/10.51890/2587-7399-2023-8-4-25-32
Abstract
Probabilistic modeling of the geological model is an integral part of the development concept. The choice of final geologic model realizations corresponding to the P10, P50, P90, probability percentiles in probabilistic modeling affects the predicted production profile, so it is very important when selecting a realization to assess how accurately it reflects reservoir properties and accounts for uncertainties in both static and dynamic characteristics.
A large number of faults, resulting in deposits with complex block structure, characterizes East Siberian fields. This factor should also be taken into account in the selection process to ensure compliance with the percentiles of the distribution of counting parameters for each block.
The aim of the work is to select representative geologic realizations P10, P50, P90, from the pool of calculated models.
Materials and methods. This paper presents results of multivariate modeling for probabilistic estimation of reserves of the Botuobinsky horizon in one of the fields of Eastern Siberia using the Geoscreening tool in the Petrel software. The main peculiarity of the realized approach was a complex estimation of static and dynamic uncertainty parameters at the stage of multivariate model calculations.
Results. When analyzing the results obtained, the range of acceptable deviations from the values corresponding to the percentile of probability P10, P50, P90 was determined and the realizations falling within this range were selected for each block by such parameters as total hydrocarbon saturated volume, associated pore volume, initial geological oil and gas reserves and basic calculation parameters. Stress tests on the hydrodynamic model were performed, confirming the hypothesis that dynamic characteristics should be taken into account at the stage of multivariate calculations for probabilistic evaluation.
Conclusion. The tested methodology using the Geoscreening module allowed to select cases that most accurately correspond to the given percentiles of distribution for all parameters and optimize the time and number of calculations on the hydrodynamic model.
About the Authors
S. A. AndronovRussian Federation
Sergey A. Andronov — Head of project programs
3–5 Pochtamtamtskaya str., 190000, Saint Petersburg
E. A. Gorenkova
Russian Federation
Ekaterina A. Gorenkova — Head of area
3–5 Pochtamtamtskaya str., 190000, Saint Petersburg
A. A. Gomonov
Russian Federation
Anton A. Gomonov — Head of area
3–5 Pochtamtamtskaya str., 190000, Saint Petersburg
I. A. Maksimenko
Russian Federation
Irina A. Maksimenko — Head of area
3–5 Pochtamtamtskaya str., 190000, Saint Petersburg
References
1. Guidelines for the creation of 3D geological models. 01.05.25-03 // Moscow: PJSC «Gazprom neft», 2017, 294 p.
2. Workflow basics and uncertainty analysis, selection of geological realization with Geoscreening module. Schlumberger, 2021, 67 p.
3. Belyakov E.O. Petrophysical modelling of oil reservoir properties in the concept of pore volume connectivity (on the example of traditional terrigenous reservoirs of Western Siberia). Moscow–Izhevsk: Institute of Computer Scince, 2021, 288 p.
Review
For citations:
Andronov S.A., Gorenkova E.A., Gomonov A.A., Maksimenko I.A. Approaches to selection of realizations in probabilistic modeling of geological model and analysis of influence on forecast production profile. PROneft. Professionally about Oil. 2023;8(4):25-32. (In Russ.) https://doi.org/10.51890/2587-7399-2023-8-4-25-32