Predicting formation target depth ahead of the bit with high accuracy: a case study from the Arun Field for a deviated well
Year: 1996
Proceedings Title : Proc. Indon. Petrol. Assoc., 25th Ann. Conv., 1996
Mobil Oil Indonesia used the ",look ahead VSP", technology at the Arun Field in North Sumatra for the purpose of predicting the depth at which the Top Arun limestone reservoir would be encountered by drilling. The objective of this work was to be able to set casing as close as possible to the Top Arun limestone. Two things made this work unique relative to the normal look ahead VSP: 1) the well was deviated (approximately 45 degrees at the VSP collection point), and 2) a high level of accuracy was required in the depth prediction. Using an inversion method to analyze the VSP data, a prediction was made that was in error by less than one foot.The need for setting casing close to the reservoir interface was due to the fact that the overlying Baong shales are over pressured and the underlying reservoir, due to years of production, is at a low pressure. The drilling program called for drilling through the over pressured shales with heavy weight mud, setting casing and then drilling into the reservoir layer with a lower weight mud.Attemps to predict the depth of the Top Arun interface using seismic and well control resulted in two different answers. The structure based on well control suggested . a dipping interface, however, analysis of sparse 2-D seismic data in the vicinity of the well suggested the possibility of a relatively flat structure or possibly even a structural high where the well was planned to encounter the Top Arun interface.Based on the VSP results, the depth of the Top Arun interface was predicted to be 9530.0 feet at the point of interest. Drilling encountered the Top Arun limestone at a depth of 9529.6 feet. The prediction was in error by only 0.4 feet. This study suggests that very accurate preditions ahead of the bit are possible with the look ahead VSP method when the inversion method is used to perform the analysis. The level of accuracy possible with the inversion method, similar to other methods, is highly dependent upon the quality of the input data.
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