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Shale gas reservoir characterization and sweet spot prediction in ChinaNormal access

Authors: Gang Yu, Yusheng Zhang, Ximing Wang, Xing Liang, Wei Liu, Riu Guo, Uwe Strecker and Maggie Smith
Journal name: First Break
Issue: Vol 35, No 7, July 2017 pp. 59 - 63
Language: English
Info: Article, PDF ( 891.25Kb )
Price: € 30

An integrated study of the well Zhao-104 and surrounding wide-azimuth 3D seismic data volume within the shale gas reservoir in South China has been conducted with the objective of generating shale formation properties related to fracture orientation and intensity in the area and deriving such reservoir rock properties as data quality allows. Well data, structural seismic information and prestack inversion products were combined in an integrated interpretation. Seismic gather conditioning improved seismic data quality prior to pre-stack inversion by improving signal/noise ratio, removing NMO stretch and aligning reflection events. Velocities from residual moveout (RMO) analysis on individual sectors were used as input to detection of fracture orientation and anisotropy. Fracture strike and P-wave anisotropy were calculated using the RMO updated sector velocity fields in elliptical velocity inversion, while inversion for P and S impedance and derivative attributes produced volumes that relate to rock properties such as brittleness and rigidity that are likely to impact fracturing. Measured logging curves were edited and missing curves estimated for the entire wellbore for geophysical purposes. Porosity, mineralogy and saturation were also estimated and elastic attributes were examined in crossplot space to find discrimination in properties of interest. Matrix modelling and synthetic seismograms were studied in order to understand likely seismic signatures and AVA behaviour. A set of post-stack volumetric attributes that are indicative of the presence of faults and fractures were derived and fed into an unsupervised neural network to perform fracture facies classification. In addition, seismically resolvable faults and discontinuities were automatically generated from fault sensitive attributes. At the end, information from all parts of the project were combined to assess structural characteristics and identify areas of high fracturing and stress direction that are important for the placement of horizontal wells and likely high total organic content (TOC) zones, necessary as a source of hydrocarbons or ‘sweet spot’.

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