- ISSN: 2202-0586
- E-ISSN:
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oa Predicting Structural Permeability in the Deep Coal Play, Tirrawarra-Gooranie fields, Cooper Basin
- Australian Society of Exploration Geophysicists
- Source: ASEG Extended Abstracts, Volume 2018, Issue 1st Australasian Exploration Geoscience Conference – Exploration Innovation Integration, Dec 2018, p. 1 - 9
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- 01 Dec 2018
Abstract
A 2D numerical stress modelling study was conducted for the Tirrawarra-Gooranie oil and gas field in the Cooper Basin, which produces from a mixture of conventional and non-conventional (deep coal) reservoirs. The aim of this study is to understand the current state of stress, both magnitudes and orientation, within the zones of interest. A high confidence 3D structural framework was used as a key input to the model, which sought to demonstrate how the in-situ stress is distributed or perturbed throughout the field. The understanding of the current stress state at borehole scale can assist with the prediction of natural fractures or structural permeability, fracture stimulation design and placement, and production performance.
Extensive sensitivity studies were conducted, with the most important inputs found to be boundary stress magnitudes and stress orientation with respect to the faults. The models were interrogated at both the primary coal target and the underlying sandstone horizons. They were found to have significantly different stress states. The output models were compared against production data, 1D mechanical earth models, fracture stimulation data, image logs and core data. The model predictions are in reasonable agreement with the mechanical earth models and the stress orientations determined from the image logs. Predicted stress rotations greater than 4° from the regional stress direction appear to be associated with poorer frac placement, higher bottom hole treating pressures and poor gas rate outcomes. There is a clear association of mineralised natural fractures with areas of low differential stress. The models provide an additional element of subsurface information which will inform future appraisal activities and may improve the understanding of variability in the deep coal fracture stimulation outcomes.
