
TY  - JOUR
A1  - Cremasco, Dylan 
A1  - II, Yahya Villareal Basman 
A1  - Travers, Judith 
T1  - Spatial Mapping of Seismic Facies Variations to Mitigate Reservoir Risk in Coal Prone Fluvial-Deltaic Settings
JF  - ASEG Extended Abstracts
JO  - ASEG Extended Abstracts
Y1  - 2016
VL  - 2016
IS  - 1
SP  - 1
EP  - 5
KW  - 
UR  - https://doi.org/10.1071/ASEG2016AB306 
N2  - Seismic facies classification has been used to reduce risk in laterally heterogeneous reservoir prediction. Studies were focused on the Barrolka/Coolah/Durham Downs Trend in the south-west Queensland sector of the Cooper Basin. The primary reservoir targets are the fluvial channel sediments of the Toolachee Formation. Historically, well success rates across the area have been low, with highly variable reservoir development and connectivity identified as the limiting factors influencing well performance.Conventional seismic attribute analysis has typically yielded inconclusive results, often associated to the presence of thick coals that dominate the seismic response. However, recent drilling campaigns utilised seismic waveform classification mapping, which resulted in an increase in technical success rate of wells. This study aims to investigate the concepts behind the success of the waveform classification method and to determine alternate techniques to further delineate reservoir presence.Key outcomes from rock physics studies indicate subtle variances in the seismic wave shape could be attributed to changing reservoir thickness underlying coal formations. Cross correlation of the wave shape against well results confirmed the concept of dimming seismic amplitude response to be related to increased reservoir thickness. In an attempt to capture the lateral extent of these variances, three adjacent 3D seismic volumes, covering majority of the complex, were subject to a variety of attribute analysis methods. Unsupervised waveform classification was found to be the most efficient and effective method for capturing the dimming seismic reflector, and thus defining the channel trends. The strong correlation between waveform class and reservoir thickness measured in wells enabled the generation of risk-segment maps for the reservoir units.Observed changes in wave shape on full stack seismic data have been related to lithological variations based on rock physics studies. These learnings have been used to select attribute extraction techniques that can best highlight the wave shape variations. Using seismic facies mapping to enhance reservoir prediction capabilities has reduced reservoir risk and improved the technical success rate of drill targets. The output maps from this study have been used to locate future opportunities in the region. 
ER  -

