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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.

The attribute crossplots analysis is commonly used to predict the reservoir and identify the fluid by analyzing the sensitive seismic attributes anomaly caused by reservoir for fluid via forward modeling. The crossplots indicates the approximate distribution of potential area. Different researchers of different times study either more seismic attributes sensitive to reservoir and fluid or advanced methods for computing crossplots to improve the reliability of attribute crossplots analysis in reservoir prediction and fluid identification. Reinaldo J. Michelena (2011) [

Seismic attributes are the comprehensive response to the subsurface seismic and geological conditions. They have an uncertain relationship with their geological implication [

^{3}, while these two parameters of sandstone are 4400 m/s and 2530 kg/m^{3}. The seismic observation system is defined as the intermediate shot point where it is 100 m away from the left side of the model and bilateral receiver points whose distance between any two adjacent receivers is 5 m. The shot point has a zero offset. The exploded wavelet is zero-phase Ricker wavelet with its main frequency at 40 Hz. Keeping the top of sandstone layer unmoved, thickness non-isometrically varies from 5 m, 10 m, 15 m, 20 m to 30 m. The corresponding synthetic seismic records of shot point after muting the first arrivals are shown in

Above forward modeling study shows that just different thickness can lead to the changes of these attributes including main frequency, main frequency amplitude, bandwidth and attenuation gradient, etc. Therefore, we propose the statistical analysis on the large number of sample data based on the mathematical statistical theory and optimize lots of attributes sensitive to different type of wells. This ultimate way is on the basis of that the wells with same production features have same statistical laws. Under the guidance of the idea that is retention and elimination, the crossplots of seismic attributes sensitive to the same type of wells provide the distribution of tight gas even high production gas. This method does not require mathematical theory and artificial geological implication of seismic attributes. The idea of retention and elimination means that in the process of screening the range of one sensitive attribute, the interest wells are fully retained, while the non-interest wells are eliminated as much as possible. Each sensitive attribute contributes to eliminating one or more non-interest wells. Crossplots of variable sensitive attributes help to retain the entire interest wells and eliminate all the non-interest ones. Multi-attribute crossplots avoid the ambiguity caused by single attribute, and get unique abnormal distribution of interest tight gas, and identify different gas-bearing characteristics according to the variable classification of interest wells.

X area is located in the east of Taibei depression in Turpan-Hami Basin, western China (in

There are 44 wells in X area, production of all wells in the interest reservoir is classified to three types according

to

The top structures of J_{2}S_{2} member shown in

Values of prediction map in

class | low production | medium production | high production |
---|---|---|---|

daily gas (10^{4} m^{3}) | <1 | 1 - 2 | >2 |

by actual discontinuous geological conditions, even tight sandstone reservoir with frequent lateral variation and lots of isolated sand bodies, both of which make the dispersed form more obvious. The multi-attribute crossplots are used to identify fluid on the basis of seismic lines and traces. When a seismic bin of 3d data constituted by one line and one trace are discontinuous, the prediction results appears to mosaic. Because every sensitive attribute is independent in the process of selecting, crossplots of various attributes sensitive to the same kind of

wells are regardless of orders.

All wells of X area are used as sample wells to optimize the sensitive attributes. The multi-attribute crossplots provide the distribution of gas-bearing anomalies with different production. Merged prediction results are shown in

1) Seismic attributes of reservoir donâ€™t correspond with their geological implication. Multi-attribute crossplots based on the mathematical statistics overcome the ambiguity caused by above problems. This method classifies the distribution having same statistical laws as a class and considers them having the same production properties.

2) The promoted method is suitable for areas with large numbers of well data. More sample wells can bring statistical regularity much more closing actual situation and more reliable predict outcomes..

3) The prediction results of this method contain zero values and nonzero values indicating the development of interest fluid. Frequent lateral variation of subsurface geological settings leads to the discontinuity of the distribution map. Non-continuous distribution of seismic bins which is the smallest unit of crossplots results in the mosaic forms. Moreover, the orders of crossplots of seismic attributes are sensitive to the same class of wells.

4) Combined with the actual structural situations of X area, partition prediction improves the accuracy greatly compared with entire partition. Different areas do comparative analysis and adjustment according to their own situation.

The authors are very grateful to both of China University of Geosciences and Beijing Tech Art, Open Source S&T Company that provided the needed resources, which made this research successful. Many thanks to the sponsor from Key Geophysical Technology Research Program on the Unconventional Oil and Gas of China National Petroleum Corporation (2014A-3612). Also, much appreciation is extended to the editor and the anonymous reviewers highly acknowledged for their critical comments and suggestions which helped to improve the quality of the original manuscript.

Lifang Cheng,Yanchun Wang,Zhiguo Li,Fei Li,Fuxiu Gong, (2016) Application of Multi-Attribute Crossplots to Tight Gas in X Area, Western China. Open Journal of Geology,06,251-259. doi: 10.4236/ojg.2016.64022