A Comprehensive Statistically-Based Method to Interpret Real-Time Flowing Measurements Page: 3 of 190
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Abstract
With the recent development of temperature measurement systems, continuous
temperature profiles can be obtained with high precision. Small temperature changes
can be detected by modern temperature measuring instruments such as fiber optic
distributed temperature sensor (DTS) in intelligent completions and will potentially aid
the diagnosis of downhole flow conditions. In vertical wells, since elevational
geothermal changes make the wellbore temperature sensitive to the amount and the type
of fluids produced, temperature logs can be used successfully to diagnose the downhole
flow conditions. However, geothermal temperature changes along the wellbore being
small for horizontal wells, interpretations of a temperature log become difficult. The
primary temperature differences for each phase (oil, water, and gas) are caused by
frictional effects. Therefore, in developing a thermal model for horizontal wellbore,
subtle temperature changes must be accounted for.
In this project, we have rigorously derived governing equations for a producing
horizontal wellbore and developed a prediction model of the temperature and pressure by
coupling the wellbore and reservoir equations. Also, we applied Ramey's model (1962)
to the build section and used an energy balance to infer the temperature profile at the
junction. The multilateral wellbore temperature model was applied to a wide range of
cases at varying fluid thermal properties, absolute values of temperature and pressure,
geothermal gradients, flow rates from each lateral, and the trajectories of each build
section.
With the prediction models developed, we present inversion studies of synthetic
and field examples. These results are essential to identify water or gas entry, to guide
flow control devices in intelligent completions, and to decide if reservoir stimulation is
needed in particular horizontal sections. This study will complete and validate these
inversion studies.iii
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Yoshioka, Keita; Dawkrajai, Pinan; Romero, Analis A.; Zhu, Ding; Hill, A. D. & Lake, Larry W. A Comprehensive Statistically-Based Method to Interpret Real-Time Flowing Measurements, report, January 15, 2007; Austin, Texas. (https://digital.library.unt.edu/ark:/67531/metadc882843/m1/3/: accessed April 25, 2024), University of North Texas Libraries, UNT Digital Library, https://digital.library.unt.edu; crediting UNT Libraries Government Documents Department.