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Navigating and Imaging in Complex Geology with Azimuthal Propagation Resistivity while Drilling
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Citations
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References
2006
Year
Azimuthal Propagation ResistivityApplied GeophysicsEngineeringComplex GeologyGeological ModelingEarth ScienceReservoir EngineeringDrillingGeophysicsGeotechnical EngineeringAbstract Reservoir NavigationDrilling EngineeringSeismic ImagingGeologyFractured Reservoir EngineeringEngineering GeologyReservoir ModelingStructural GeologySeismologyLwd ResistivityReservoir NavigationCivil EngineeringGeomechanicsFormation EvaluationReservoir Geology
Abstract Reservoir navigation with LWD resistivity has traditionally relied on matching real time measurements with ideal logs. Reservoir navigation engineers initially build one or more resistivity models including all expected resistivity boundaries such as oil-water contact, reservoir to cap rock interface, faults and unconformities. Then, during drilling, they direct the well and update the earth model by matching actual measurements with forward response model data. Because common LWD resistivity sensors cannot differentiate between an oil-water contact approaching from below and a shale lens approaching from above or from the side, the reservoir navigation engineer fills in the missing information through expertise and local knowledge. In case of complex geology however, such as reservoirs with tilted or rotated fault blocks, multiple fluid contact levels, cross-stratification and shale intrusions, navigation becomes much more challenging and the risk of getting geologically lost is high. In recent years imaging LWD tools were introduced to help reduce the azimuthal uncertainty but they were limited to a few inches in lateral investigation. A new azimuthally sensitive propagation resistivity tool was recently tested for reservoir navigation and formation imaging in some of the more complex reservoirs of the North Sea. In cases where standard omni directional tool responses would lead to ambiguous interpretations, the azimuthally sensitive tool provided the basis for clear geosteering advice. A new imaging algorithm helped visualize approaching beds much like modern imaging devices, but with a depth of investigation reaching several feet into the formation. At fault crossings, the azimuthally sensitive signal helped recognize the relative movement of the formations on either side of the fault. In other instances where the well was run immediately below the cap rock, deep looking azimuthal propagation anticipated the intersection by several hundred feet. Also, analysis of the detailed deep electrical images brought a more complete understanding of the subsurface.
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