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Article citations


Chen, X.G., Xie, R.J. and Zhang, X. (2012) Fine Strata Classification and Correlation for Sanjianfang Formation (2s) in Hongtai Oil and Gas Field. Tuha Oil and Gas, 17, 25-27. (In Chinese)

has been cited by the following article:

  • TITLE: Application of Multi-Attribute Crossplots to Tight Gas in X Area, Western China

    AUTHORS: Lifang Cheng, Yanchun Wang, Zhiguo Li, Fei Li, Fuxiu Gong

    KEYWORDS: Multi-Attribute Crossplots, Mathematical Statistics, Tight Sandstone Gas, Fluid Identification

    JOURNAL NAME: Open Journal of Geology, Vol.6 No.4, April 19, 2016

    ABSTRACT: The gas-bearing reservoir in X area is mainly the tight sandstone reservoir characterized by low porosity and permeability, frequently lateral variation and poor connectivity of single sand. The previous research results reveal that the general seismic attributes analysis cannot meet the requirement of fluid identification. This is because the relationship between seismic attributes and their implication is uncertain and ambiguous, which decreases the precision of both reservoir prediction and fluid identification. To overcome the problem, multi-attribute crossplot technology is proposed from the mathematical statistical point of view rather than the correspondence between the seismic attributes and their geological implication. In this method, the wells which have the same statistical law are classified firstly, and then all the interest wells are retained while the wells beyond the statistical law are eliminated, and the seismic attributes sensitive to the same types of eliminated wells are optimized and used to generate crossplots. The nonzero area of their crossplots results just predicts the potential distribution. The discontinuity of subsurface geological conditions results in the non-continuous shape and the seismic bin lead to the mosaic form. The optimization of sensitive attributes relative to the same types of wells is independent from each other, and thus the order of attributes in crossplots does not affect the final prediction results. This method is based on the statistical theory and suitable for the areas such as the study area abundant of lots of well data. Application to X area proves the effectiveness of this method and predicts plane distribution about different types of gas production. Due to the effect of faults and other geological factors, the partition prediction results using multi-attribute crossplots reach 95% of coincidence which is obviously and far higher than the results of the whole area. The final prediction results show that the potential areas with medium and high gas production are mainly concentrated in the northern part of the study area, where lots of development research will be strengthened.