Downhole fluid profiling is generally achieved by means of standard Production Logging (PL) strings, including pressure, temperature, holdup and spinner probes. This is no longer a viable option in case of asphaltenes, waxes and/or solids depositions during production that prevent any reliable mechanical measurements. In this respect, Distributed Temperature Sensing (DTS) and pulsed neutron Oxygen Activation (OA) logging represent valid techniques to describing the dynamics of such complex cases. This paper details an integrated modeling of DTS and OA data aimed at multiphase production profiling, together with the associated uncertainty.

The proposed approach starts from stationary OA data acquisitions that can identify the water entry points and estimate the water velocity at selected depths. To compute the desired water rate, the unknown water holdup profile is needed and a full factorial data analysis is carried out by considering all the combination of water velocities and possible physically-sound holdups. The obtained water rate scenarios are used as hard inputs for the next temperature modeling, performed utilizing DTS data acquired in shut-in and flowing conditions. The thermal analysis, based on heat transfer and thermodynamic principles, also relies on parameters such as geothermal gradient, fluid properties, pressure drawdown and wellbore-dependent heat loss. Again, a multi-scenario is modeled including the estimated or known uncertainties of the different inputs. In the end, hydrocarbon and water rate profiles are generated for accurate downhole dynamic characterization.

The complete workflow is presented by means of a study performed on a naturally fractured carbonate reservoir, intercepted by dozens of nearly horizontal wells completed in open-hole and with slotted liners. In particular, the water shut-off intervention for Well X has been guided by the outcomes of this integrated DTS and OA data modeling, since the asphaltene-rich scenario prevented any reliable conventional PL survey. Both measurements have been conveyed via coiled tubing. The different generated equiprobable scenarios also allowed critical risk analysis for a thoughtful decision making.

The presented methodology leads to accurate multiphase flow profiling, overcoming the limitations of standard PL in challenging environments. Although the added value of DTS is well-known, the full factorial analysis of OA data, and its quantitative incorporation into thermal modeling, is a novel and key aspect for reliable dynamic characterizations. In fact, standalone temperature interpretations are highly uncertain/not reliable in case of multiphase flows. Finally, the value of uncertainty quantification also has a huge relevance to correctly drive production optimization and water shut-off strategies.

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