Feasibility of Reservoir Monitoring Using 4D Seismic in the Ichthys Gas-Condensate Field, NW Australia: Velocity-Geology-Pressure Relationships Defined in Core
- Levi Knapp (Japan Oil, Gas and Metals National Corporation (JOGMEC)) | Tetsuzo Fukunari (Japan Oil, Gas and Metals National Corporation (JOGMEC)) | Keita Yoshimatsu (Japan Oil, Gas and Metals National Corporation (JOGMEC)) | Masayoshi Suzuki (Japan Oil, Gas and Metals National Corporation (JOGMEC)) | Tatsuya Hattori (Japan Oil, Gas and Metals National Corporation (JOGMEC)) | Keiichi Furuya (INPEX) | Ryoichi Matsui (INPEX)
- Document ID
- Society of Petrophysicists and Well-Log Analysts
- 23rd Formation Evaluation Symposium of Japan, 11-12 October, Chiba, Japan
- Publication Date
- Document Type
- Conference Paper
- 2017. Society of Petrophysicists and Well Log Analysts
- 2 in the last 30 days
- 30 since 2007
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JOGMEC and INPEX have collaborated to test the feasibility of using 4D seismic for reservoir monitoring in the Ichthys gas-condensate Field in the Browse Basin, offshore NW Australia. The effectiveness of 4D seismic monitoring will depend on the ability to detect changes in the reservoir as the effective pressure (Peff) and fluid saturation change through the production phase. In order to predict the response of seismic waves to pressure changes and geological properties, we began by testing and quantifying these relationships at the core scale.
Velocity measurements were performed on 55 Brewster Member sandstone plug samples, under confining pressures up to 11,000 psi. The same plugs were analyzed for porosity, permeability and density. Mineralogy was measured on thin sections using QEMSCAN. Quartz cement abundance and grain size distribution were estimated on 40 prioritized thin sections using cathodoluminescence analysis. X-ray CT imaging of plugs and petrographic examination of thin sections were used to observe the internal structure of the samples.
Porosity was found to be the strongest control on core velocity and scatter in the porosity-velocity relationship is attributed primarily to clays. Correlation strength was strongest when velocity was measured parallel to bedding due to minimized effect of clays and bedding fabrics. Functions for geology-velocity relationships were generated using multiple linear regression.
In order to understand how velocity will change with increasing Peff, geological parameters were correlated to a pressure-sensitivity factor, C. A function was generated to predict velocity at any Peff between 7,000 and 11,000 psi (~current and end-of-production Peff) using porosity, %Clay, and Peff as inputs.
The results of this study have subsequently been used to estimate reservoir rock velocity at current and future pressures and fluid saturations, as well as for 1D seismic forward modeling.
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