--> Abstract: Integrated Reservoir Geological Modeling and Quantitative Uncertainty Appraisement of Models, by Li Gu, Chunliang Huo, Chunming Zhao, Guangyi Hu, Song Liu, and Qinghong Yang; #90082 (2008)
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Integrated Reservoir Geological Previous HitModelingNext Hit and Quantitative Uncertainty Appraisement of Models

Li Gu1, Chunliang Huo2, Chunming Zhao2, Guangyi Hu1, Song Liu2, and Qinghong Yang2
1Research center, CNOOC, Beijing, China
2Tianjin Branch, CNOOC, Tianjin, China

Taking Lower Minghuazhen Formation, Neocene, B Oilfield in Bohaiwan Basin as an example, the paper discusses a method of reservoir Previous HitmodelingNext Hit incorporating geological data, logs and Previous HitseismicNext Hit data and a method of quantitative uncertainty appraisement of models.

The reservoir of B Oilfield belongs to a distal delta system and is featured by distributary channels in delta front. The complicated distribution of channel sand requires facies-constrained Previous HitmodelingNext Hit method. Reasonable division of Previous HitmodelingNext Hit units, geological knowledge base and the corporation of Previous HitseismicNext Hit data are the key of geological Previous HitmodelingNext Hit. Division of Previous HitmodelingNext Hit units emphasizes the reasonable vertical division and horizontal correlation of reservoir. The corporation of 3D-seismic data with well data yields geological knowledge base, including quantitative description of microfiches, flow lines of channels, probability function of facies, and connection probability of sand bodies in each unit. Object-based simulation method is applied in facies Previous HitmodelingNext Hit.

To appraise uncertainty and optimum seeking of models is important after geological Previous HitmodelingNext Hit. Uncertainty mainly lies in the geological knowledge and in the parameters of reserves calculation. Thus, experiment designing was used to single out a set of 9 geological scenarios to describe all likelihoods. OOIP and drained OOIP, respectively reflecting the scale and the connectivity of the reservoir, were used as the quantitative indexes. Based on the 9 realizations of the 9 Previous HitmodelingNext Hit scenarios, the multinomial response surfaces of the main uncertainty factors with OOIP and drained OOIP were built up respectively, which were used as the substitute for Previous HitmodelingTop. Then the 3P probabilistic reserves were calculated by Monte Carlo method. A set of realizations was selected out by optimum seeking for numerical reservoir simulation, which covered the risks of the reservoir.

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