Intelligent well completions are increasingly being used in horizontal, multilateral, and
multi-branching wells. Such completions are equipped with permanent sensors to
measure temperature and pressure profiles, which must then be interpreted to determine
the inflow profiles of the various phases produced that are needed to characterize the
well??s performance. Distributed temperature measurements, using fiber optics in
particular, are becoming increasingly more often applied.
The value of an intelligent completion hinges on our capability to extract such inflow
profiles or, at a minimum, to locate the entry locations of undesirable water or gas
entries.
In this research, a model of temperature behavior in multilateral wells was developed.
The model predicts the temperature profiles in the build sections connecting the laterals
to one another or to a main wellbore, thus accounting for the changing well angle
relative to the temperature profile in the earth. In addition, energy balance equations
applied at each junction predict the effects of mixing on the temperature above each
junction.
The multilateral wellbore temperature model was applied to a wide range of cases, in
order to determine the conditions for which intelligent completions would be most
useful. Parameters that were varied for this experiment included fluid thermal properties,
absolute values of temperature and pressure, geothermal gradients, flow rates from each lateral, and the trajectories of each build section. From this parametric study, guidelines
for an optimal application of intelligent well completion are represented.
Identifer | oai:union.ndltd.org:tamu.edu/oai:repository.tamu.edu:1969.1/2614 |
Date | 01 November 2005 |
Creators | Romero Lugo, Analis Alejandra |
Contributors | Hill, Dan |
Publisher | Texas A&M University |
Source Sets | Texas A and M University |
Language | en_US |
Detected Language | English |
Type | Book, Thesis, Electronic Thesis, text |
Format | 593709 bytes, electronic, application/pdf, born digital |
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