Porosity Parameters Quantitatively Predicted of Ultra-Low Permeability Reservoir in Hejiaji Area

Wei Huang; Xiao Li Zhang; Xi Zheng; Gao Run Zhong

doi:10.4028/www.scientific.net/AMR.1092-1093.1440

Paper Titles

Movable Fluid Saturation of Low-Permeability and Tight Sandstone Oil Reservoir: Taking Chang 6 Reservoir in Banqiao-Heshui Area as an Example
p.1420

Nonlinear Equations of Gas Seepage in Coal Considering Adsorption Effect
p.1424

Oil Sands Forming Model of the Northwest Edge of the Junggar Basin, China
p.1430

Optimal Design of Proppant Supported Fracture Length in Tight Oil Volume Fracturing
p.1436

Porosity Parameters Quantitatively Predicted of Ultra-Low Permeability Reservoir in Hejiaji Area
p.1440

Reliability Analysis of Fully Mechanized Working Face Based on Appraisal and Distribution Method
p.1444

Research on the Height of Water-Flowing Fractured Zone under the Weak Roof Strata and Fully Mechanized Caving Condition
p.1448

Research on Thermodynamic Properties of Bioleaching Solution in Lean Nickel-Cobalt Ore by Pitzer - Meissner Model
p.1455

Siderite Beneficiation with Magnetic Separation-Flotation Combined Method
p.1460

HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 1092-1093Porosity Parameters Quantitatively Predicted of...

Porosity Parameters Quantitatively Predicted of Ultra-Low Permeability Reservoir in Hejiaji Area

Abstract:

Using the acoustictime logging data to establish reasonable and effective porosity parameter quantitative prediction model, can predict quality reservoir and favorable petroliferous province. Chang 6 formation in Hejiaji area is taken as an example to studing the reservoir physical properties and logging response characteristics, and the acoustictime logging and core analysis porosity are used to set up porosity logging interpretation model, then acculate porosity according to the model. The results show that after the core place treatment, the porosity quantitative prediction model established by acoustictime and layer point analysis porosity has high precision. To verify the porosity logging interpretation model of the calculated porosity and core analysis porosity, the application effect is good.

You might also be interested in these eBooks

Sustainable Energy and Environmental Engineering III

View Preview

Info:

Periodical:

Advanced Materials Research (Volumes 1092-1093)

Pages:

1440-1443

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.1092-1093.1440

Citation:

Cite this paper

Online since:

March 2015

Authors:

Wei Huang*, Xiao Li Zhang, Xi Zheng, Gao Run Zhong

Keywords:

Hejiaji Area, Logging Response Characteristics, Porosity Parameters, Quantitative Prediction Model, Ultra-Low Permeability Reservoir

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

* - Corresponding Author

References

[1] Zhen Liu, Yanhui Huang, Gaofeng Pan. Acta Geologica sinica, 2012, 86(11): 1815-1825. (In Chinese).

Google Scholar

[2] Yanqin Guo, Zhen Yuan, Keyong Li. Lithologic reservoirs, 2008, 20(4): 86-90. (In Chinese).

Google Scholar

[3] Xiugang Pu, Zhilong Huang, Jiansheng Zhou. Journal of Xi'an Shiyou University(Natural Science Edition), 2006, 21(2): 15-17. (In Chinese).

Google Scholar

[4] Yina Gu, Jianming Li, Shanghua Si. Complex Hydrocarbon Reservoir, 2010, 3(1): 28-31. (In Chinese).

Google Scholar

[5] Yuanlin Meng, Wenya Jiang, Delai Liu. Acta sedimentologica sinica, 2008, 26(5): 780-787. (In Chinese).

Google Scholar

[6] Xupeng Ma. Progress in Exploration Geophysics, 2010, 33(3): 216-219. (In Chinese).

Google Scholar

[7] Fengjie Li, Duoyun Wang, Xuhui Xu. Petroleum geology & experiment, 2005, 27(40): 365-370. (In Chinese).

Google Scholar

[8] Xiaoli Zhang, Qiao Feng, Pei Sun. Chinese Journal of Geophysics, 2010, 53(1): 205-213. (In Chinese).

Google Scholar

[9] Liangzhi Zou, Ranhong Xie. Journal of Oil and Gas Technology(J. JPI), 2011, 33(5): 99-102. (In Chinese).

Google Scholar