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Fracture and Carbonate Reservoir Characterization Using Sequential Hybrid Seismic Rock Physics, Statistic and Artificial
- Publisher: European Association of Geoscientists & Engineers
- Source: Conference Proceedings, 76th EAGE Conference and Exhibition 2014, Jun 2014, Volume 2014, p.1 - 5
Abstract
Tiaka field is located in the Senoro-Toili block at the eastern arm of Sulawesi, Indonesia. The main hydrocarbon bearing reservoir is a lower Miocene carbonate sequences which posses a dual porosity system both matrix and fracture. This carbonate complexity is required special treatment to precisely characterize the reservoir.
In this paper, the latest technology for carbonate complex reservoir characterization using hybrid seismic rock physics, statistic and artificial neural network will be presented. This methodology enable in integrating a huge size of various data set to produce “coherence correlation” among input data and their target. The data set consist of core, electric logs, multi-attribute either pre-stack or post-stack of a 2 D seismic lines and seismic rock physics. The whole input data was trained using workflow and combined with statistic and artificial neural network to predict reservoir parameters.
This method is applied to predict the lateral lithofacies, fracture, porosity, fluid or hydrocarbon distribution. By using these approach, its can produce high accuracy on the reservoir parameter prediction. The accuracy of testing process show that predicted parameter reservoir on the average 90 percent matched reservoir parameter in the existing wells.