Fluids discrimination by ray-path elastic impedance inversion: A successful case from Sulige tight gas field

Existing seismic prediction methods struggle to effectively discriminate between fluids in tight gas reservoirs, such as those in the Sulige gas field in the Ordos Basin, where porosity and permeability are extremely low and the relationship between gas and water is complicated. In this paper, we ha...

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Bibliographic Details
Published in:Applied geophysics 2019-06, Vol.16 (2), p.218-232
Main Authors: Wang, Da-Xing, Wang, Hao-Fan, Ma, Jin-Feng, Wang, Yong-Gang, Zhang, Na, Li, Lin
Format: Article
Language:English
Subjects:
Basins
Computational fluid dynamics
Earth and Environmental Science
Earth Sciences
Fluids
Geophysics
Geophysics/Geodesy
Geotechnical Engineering & Applied Earth Sciences
Impedance
Inversion
Mathematical models
Oil and gas fields
Parameter identification
Parameters
Permeability
Porosity
Reservoir Geophysics
Reservoirs
Saturation
Seismic data
Seismological data
Substitutes
Well logging
Wood
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Summary:Existing seismic prediction methods struggle to effectively discriminate between fluids in tight gas reservoirs, such as those in the Sulige gas field in the Ordos Basin, where porosity and permeability are extremely low and the relationship between gas and water is complicated. In this paper, we have proposed a comprehensive seismic fluid identification method that combines ray-path elastic impedance (REI) inversion with fluid substitution for tight reservoirs. This approach is grounded in geophysical theory, forward modeling, and real data applications. We used geophysics experiments in tight gas reservoirs to determine that Brie’s model is better suited to calculate the elastic parameters of mixed fluids than the conventional Wood’s model. This yielded a more reasonable and accurate fluid substitution model for tight gas reservoirs. We developed a forward model and carried out inversion of REI, which reduced the non-uniqueness problem that has plagued elastic impedance inversion in the angle domain. Our well logging forward model in the ray-path domain with different fluid saturations based on a fluid substitution model proved that REI identifies fluids more accurately when the ray parameters are large. The distribution of gas saturation can be distinguished from the crossplot of REI ( p = 0.10) and porosity. The inverted ray-path elastic impedance profile was further used to predict the porosity and gas saturation profile. Our new method achieved good results in the application of 2D seismic data in the western Sulige gas field.
ISSN:1672-7975
1993-0658
DOI:10.1007/s11770-019-0758-1