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Detailed quantitative description of fluvial reservoirs: A case study of L6-3 Layer of Sandgroup 6 in the second member of Shahejie Formation, Shengtuo Oilfield, China

Jingzhe Li, Ke Yan, Huaiqiang Ren, Zhifeng Sun

(Published: 2020-02-28)


Corresponding Author and Email:Zhifeng Sun, zhifengsun879@gmail.com; ORCID: https://orcid.org/0000-0001-6315-2894


Citation:Li, J., Yan, K., Ren, H., Sun, Z. Detailed quantitative description of fluvial reservoirs: A case study of L6-3 Layer of Sandgroup 6 in the second member of Shahejie Formation, Shengtuo Oilfield, China. Advances in Geo-Energy Research, 2020, 4(1): 43-53, doi: 10.26804/ager.2020.01.05.


Article Type:Original article


Abstract:

The steady development of the oil field is facing severe challenges due to the problems of small-layer division, unclear genesis period and unclear river channel distribution in the 4-6 sand formation in the second district of Shengtuo Oilfield. Based on the processing and optimization of logging data, this paper firstly divided the isochronous strata and established the high-resolution isochronous stratigraphic framework. Using the geo-statistics method in the stratigraphic framework, the sand bodies in each small layer were divided according to the principle of equal time of fluvial facies. On this basis, the distribution pattern of the sand bodies in each stage was simulated by the magnetic random walk model. The magnetic random walk model has obtained robust simulation results, which is consistent with the anatomy of reservoir architectures by experienced geologists. The results also show that the number of channels in each small-layer is different, while the overall distribution of NE direction is reflected. At present, the model can well simulate the position of the main channel line, but it cannot reflect the variation of the river width. The method of quantitative fine description based on logging data has great potential application in fluvial reservoir, especially the magnetic random walk model that can reveal the distribution of sand body in every stage. At the same time, the model can also reflect certain randomness and facilitate the uncertainty analysis of geological factors.


Keywords:Quantitative reservoir description, geo-statistics, magnetic random walk model, fluvial facies, reservoir characterization, reservoir modelling.


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