Abstract Distributed Temperature Sensor (DTS) technology has recently developed to determine the zonal flow rate in gas/oil producing wells using the measured continuous temperature profile along the wellbore. Comapred to convenetial production logging tool (PLT), DTS has many advantages that can provide real time temperature data without any intervention.
Temperature logging applications described in early researches included, location of gas entries, detection of casing leaks and fluid movement behind casing, location of lost - circulation zones, and evaluation of cement placement.
Temperature logs are still used for these applications and others, but the most common use now is quanitative identification of injection or production zones. Despite the many other logs that have been developed, the temperature log remains the workhorse of the production logging stable. This is primarily because of its reliability; no matter what the wellbore flow conditions, temperature can be measured accurately, also the temperature logs tends to reflect the long term behavior of well, not just the current conditions.
This paper presents a new methodology developed to allocate gas rate and associated water of each individual layer using (DTS) and the total surface production of gas and water, also the pressure along the wellbore. The physics behind this model is based on steady-state gas-water flow in the wellbore, friction loss and Joule-Thomson effect in the wellbore, contrast in the thermal and physical properties of gas and water, wellbore heat losses due to unsteady heat conduction in the earth, and the mixing of the fluid streams of contrasting temperature.
The methodology allows users to run in two modes: forward simulation and flow profiling. The forward simulation mode calculates the temperature inside the wellbore at all producing layers at any given production profile to calibrate the model inputs. The flow profiling is used to estimate the production rate based on the measured temperatures using inversion technique. The implementation of the developed production allocation model is shown, in details, by using the data of two actual cases studies form Egyption offshore gaswells.
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