Study of Adaptability for Variation Function in Random Inversion

Shan Ze Zhang; Xing Dong Liu

doi:10.4028/www.scientific.net/AMR.347-353.699

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 347-353Study of Adaptability for Variation Function in...

Study of Adaptability for Variation Function in Random Inversion

Abstract:

Abstract. Variation function is an important tool that can characterize the spatial correlation of geological variable quantitatively in geo-statistics. In the random inversion process, for different types of blocks and oil fields, choosing the appropriate function type and the corresponding model parameters, to improve the accuracy of inversion results is particularly important. By taking Gu83 block of GuLong oil field as an example, this article analyses common variation functions such as Gaussian, Spherical, Expo and Gen-Expo method and the influence of random inversion results under different variable distance parameters. From the experimental results, the inversion prediction precision will be higher in this block under the following situations: Expo variation function, horizontal variable distance is 3000 meters and vertical variable distance is 3 meters.

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Periodical:

Advanced Materials Research (Volumes 347-353)

Pages:

699-702

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.347-353.699

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Online since:

October 2011

Authors:

Shan Ze Zhang, Xing Dong Liu

Keywords:

Prediction Precision, Random Inversion, Variable Distance, Variable Distance Parameter

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References

[1] Guoqiang Shen,Xianjun Meng, etc. Random seismic inversion methods and usage in Chengbei 35 wellblock[J]. Oil Geophysical Prospecting, 2004,39(1):75-81.

Google Scholar

[2] Yunxia Li. Characteristics of total variation function. Journal of Xiangtan Normal University (natural science edition), 2002, 24(4):1-4.

Google Scholar

[3] Shenghe wu, etc. Reservoir modeling [M]. Beijing: Oil industry publishing company, (1999)

Google Scholar

[4] Ligui xu, Lianghe zheng. Practical geophysical prospecting technique used in Difficult-to produce reserves development [M]. Beijing: Oil industry publishing company, 2005:267-274.

Google Scholar

[5] Hanjun li, etc. Oil mathematical geology, [M].Shandong, Dongying：China petroleum university publishing company.1998.

Google Scholar

[6] G Shanor et al.A geostatistical inversion to flow simula-tion workflow example:Makarem Field,Oman.EAGE Meeting,2001.

DOI: 10.3997/2214-4609-pdb.15.f-11

Google Scholar