This paper describes the utilization of Real-Time geochemical analysis to support geosteering of a smart multi-lateral well, located in one of the highest flow potential areas in Kuwait. The Burgan reservoir consists of vertically stacked channel sands along with a fault network connected to the aquifer and contains highly viscous reservoir fluid. This drastically enhances the water mobility, and results in severe premature water breakthrough. Hence, leaves zones of by-passed oil. For optimum reservoir characterization, it was essential to integrate all reservoir-related data from macro to micro scale. X-ray Fluorescence elemental data collected from offset cores were used to predict key rock attributes and calibrated with standard petrophysical logs.The scope was constructing predictive models for the following properties: 1) lithological variations which cannot be captured by other LWD tools 2) detailed mineralogy to determine the diagenetic overprint 3) depositional environment of different Burgan sand facies. XRF elemental analysis while drilling was used to improve borehole positioning, and identify faults in correlation with Image logs. Nature of the fractures/faults, contributing to porosity and communicating with the aquifer, was inferred from XRF-obtained elemental markers. The integrated approach has resulted in successful geosteering and placing the well with maximum reservoir contact. Moreover, XRF elemental markers have been utilized for isolation of faulted and lower reservoir quality zones, splitting up of horizontal sections and optimization nozzle sizes of the ICDs and hence an optimized Smart completion design. X-ray fluorescence analysis on cuttings in Real-Time provides lithological information otherwise not available while drilling. It gives proxies contributing to the identification of faults and reservoir intervals in an otherwise homogeneous sequence. It helps designing the completion string, isolating sections of low quality or potentially producing water.


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