Study on the Geocad-Based Stochastic Model for the Reservoir Controlled by the Facies of the Fuyang Oil Layer in Gaotaizi Area, Songliao Basin

Abstract:

In Fuyang oil layer, the later-period structure is complex; the reservoir is mostly composed by river-way sand; the oil and gas reservoir is significantly concealed, so it is greatly difficult to identify. To accurately describe the reservoir, facies controlled reservoir is simulated stochastically using Geocad software in the study area: Lithofacies is first established using Gauss truncation algorithm to construct a facies model of mudstone, dry sandstone, poor sandstone, and sandstone, and its fitting rate is 0.814, and then a porosity model is established using sequential Gauss method under the constraint of the lithofacies model and its fitting rate is 0.814, and its correlation coefficients are as follows: 0.845 is for sandstone; 0.893 is for poor sandstone; 0.915 is for dry stone; a permeability model is established using cloud transformation method under the constraint of the porosity model and its fitting rate is 0.732, and its correlation coefficients are as follows: 0.695 is for sandstone; 0.734 is for poor sandstone; 0.824 is for dry sandstone. These prove that the facies controlled reservoir modeling based on Geocad plays a significant role in the areas where the later-period structure is complex and sand is thin and changed intricately. Thus, the needs of the oil field exploration and development can be fulfilled by the model to a certain extent.

• Periodical: Applied Mechanics and Materials (Volumes 416-417)
• Pages: 1935-1941
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.416-417.1935
• Online since: September 2013
• Authors: Xin Rong Zhang, Shi Fang, Jin Ping Liu, Mao Xin Yang
• Keywords: Facies Control, Fuyang Oil Layer, Reservoir Stochastic Modeling, Songliao Basin

References

[1] Jianying Wan, Shibo Wang, Qiufeng Zhao, et al. Reservoir Characteristics of Fuyang Oil Layer in Q3 and Q4 Member in Daqing Placanticline and Area to Its West [J]. Petroleum Geology & Oilfield Development in Daqing, 2007 (05).

[2] Jianying Wan, Shibo Wang. Shallow Water Lake Delta Sedimentary Characteristics of Fuyang Oil Layer in Q3 and Q4 Member in Daqing Placanticline and Area to Its West [J]. Inner Mongulia Petrochemical Industry, 2011 (10).

[3] Erhua ZHANG, Yongzhong SONG, Shummin CHEN, Guoping JIN, Ying QIU. Seismic Recognition Method of Channel Sand Body of Fuyang Pay Zone in Songliao Basin [J]. Petroleum Geology & Oilfield Development in Daqing, 2004 (05).

DOI: 10.1190/1.3603806

[4] Junshu LI, Yanlou Gao, Zhenhai TANG, Qingsheng JI. Sand Comprehensive Prediction Technology of Fuyang Reservoir [J]. Petroleum Geology & Oilfield Development in Daqing, 2002 (04).

[5] Changpin ZHANG, Shaohua LI, Yanshu YI, et al. Reservoir Stochastic Modeling Series Technology [J]. Oil Forum, 2007 (03).

[6] Yanshu YI, Shenghe WU, Changmin ZHANG, et al. Integrative Prediction of Micro-fancies with Multiple Stochastic Modeling Methods [J]. ACTA PETROLEI SINICA, 2007 (03).

[7] Wanyou DENG. Phased Parameter Stochastic Modeling Method and Its Application [J]. Journal of Northeast Petroleum, 2007 (06).

[8] Yujun LI, Hongwen DENG, Zhengui SHI, et al. Application of Seismic Data in Probabilistic Modeling of Sedimentary Micro-facies [J]. SPECIAL OIL & GAS RESERVOIRS, 2007 (05).

[9] Chengxue ZHANG, Rongge XIAO, Yongmin SHI. A Study of Stochastical Reservoir Modeling Methods based on Log Interpretation and Single Sandbody [J]. XINJIANG OIL & GAS, 2007 (03).

[10] Wangqing ZHANG, Yangping LIU, Chao CHEN, et al. Stochastic Modeling Controlled by Reservoir Micro-facies [J]. Fault-Block Oil and Gas Field, 2008 (05).

[11] Yong YANG, Lei WU, Henian LIU, et al. Study on the Acquirement of Robust Variogram in Stochastic Modeling [J]. Fault-Block Oil and Gas Field, 2005 (06).