Mapping Un-Explored Resistive Geo-Bodies Using 3D Csem Technology: A Case Study of CSEM Geo-Body Characterization from Rapak-Ganal Area in Kutai Basin, Makassar Strait, Indonesia
Year: 2016
Proceedings Title : Proc. Indon. Petrol. Assoc., 40th Ann. Conv., 2016
The Kutai basin is a prolific hydrocarbon producing basin. One of the challenges in these kind of basins is to quantify the size of the prize before drilling a costly well. A 3D CSEM survey in such scenario can serve dual purpose. Provided that the reservoir is sufficiently thick and sufficiently saturated with hydrocarbon, it will be imaged in inverted CSEM data. This will not only increase ‘Chance of Success’ (COS) but also allow accurate estimate of areal extent of the resistive geobody and a better handle on size.
On various occasions previously it was stated that ‘CSEM is only successful in places like Barents sea where the resistivity is high and the contrast between background and target is sufficient enough. In areas such as South-East Asia with low resistive sediments, this technology fails’. Critics have argued there was no solid example where a survey was done over a discovered field and hence could have served as a calibration point.
In 2015 a multi-client 3D CSEM campaign was initiated in the Makassar-Strait which included a survey over the newly announced Oti and East-Kendilo block as well as the Rapak-Ganal block operated by ‘Chevron-Indonesia’ which covers the Gehem discovery. One of the reasons behind this survey was to see if the anomaly pertaining to the Gehem field can be imaged as a resistive geobody, which would be a very good calibration point for the entire survey. The unconstrained 3D CSEM inversion was successful in reproducing a resistive anomaly matching well with the Gehem field outline. This observation increased our confidence with regards to additional resistors inverted in the area being hydrocarbon related.
Gehem calibration is good example of calibrated CSEM inversion results to a proven discovery in South East Asia. This example is a proof that CSEM is not dependent on geography but on the physical parameters of the subsurface. Basins like Kutai are very conducive to CSEM and given the cost of a deep water well, an early adoption of this technology in the value chain can save millions of dollars on dry holes.
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