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Abstract

Adjusting the geological well plan trajectories with geophysical methods could be an effective way in assisting to prepare more precise and accurate plans for drilling new wells. The main objective of this study was to check the proposed well path through geophysical sections and position the well trajectory with respect to the target layers and reduce the drilling risks and also costs as much as possible. For this reason at first a pre-stack simultaneous seismic inversion was conducted to generate Acoustic impedance and Vp/Vs ratio cubes. Consequently elastic and petrophysical well log data were evaluated to determine different litho-fluid classes including Hydrocarbon Sand (HC Sst.), Wet Sand (Wet Sst.) and Shale classes. Bayesian-derived probability density functions (PDFs) for each litho-fluid class were calculated from well log computations of AI and Vp/Vs. Using the PDFs and pre-stack seismic inversion results, probability cubes for the individual litho-fluids in addition to final litho-fluid cube were calculated. Based on generated results, well plan trajectory was adjusted to pass through the well-defined HC Sst (the target reservoir layer). Results of this study illustrated the usefulness of the Litho-fluid cubes derived from 3D seismic data in reducing the drilling risks and costs.

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/content/papers/10.3997/2214-4609.201701668
2017-06-12
2024-03-29
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http://instance.metastore.ingenta.com/content/papers/10.3997/2214-4609.201701668
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