Temperature data is a remarkable source of reservoir and well information and complements the Dynamic Data Analysis (DDA) workflow. There are a wide range of applications for this data including, but not limited to, qualitative indications of flow, completion integrity, assessment of valve operation, quantitative production and injection profiling.
Temperature logging started in the 30’s with methods for temperature-based flow profiling developed shortly after. Latterly, temperature has been recorded as part of production log surveys. Although often considered as a secondary measurement used for PVT calculations and qualitative indications of flow when flowmeter measurements fail, temperature can, with some limitations, prove valuable for quantitative computing of the flow profile. More recently, Distributed Temperature Sensing (DTS) systems based on fibre optics have gained considerable traction as permanent installations as part of the completion, or temporary deployment as part of an intervention. DTS has provided massive, high resolution, data gathering of temperature versus depth at rates up to every 10 seconds.
Similar to permanent downhole pressure gauges (PDG), the ever growing volume of data generated has presented its own challenge. Typically, massive data is required for time stepped qualitative purposes, whilst quantitative interpretation requires relatively very few data points.
Two KAPPA Workstation modules are used in the analysis of temperature data. Emeraude, the PL interpretation industry standard, is used for loading large DTS datasets, cleaning the data and then qualitative time stepped scrutiny. Extracted traces may then be analysed using analytical methods. Forward modelling can be used for simulating leaks and steam injection. When the limits of the analytical models are reached, the Rubis multipurpose numerical simulator can handle situations such as non-geothermal fluid entry, found in fields with water injection and aquifers.
- DTS\ndata loading
- Production profiling
- Injection fall-off
- Rubis Thermal
- Temperature simulation
DTS data loading and display
DTS data is typically exported in .las or .csv format either in a merged file or a single file per trace.
The temperature traces maybe time stamped.
When loaded in Emeraude, this data is treated as an ‘array’ dataset and is automatically plotted in an array image, with the temperature shown by a colour map and the time on the x-axis.
An ‘Explore’ option allows the user to select traces at specific times for thermal modelling.
Once selected and exported, the array data can be saved as an image, thus minimising file size.
Temperature Production profiling
Emeraude incorporates an energy model to obtain production or injection profiles from temperature data only.
This model couples energy and mass transfer equations both in the reservoir and in the wellbore.
They are solved iteratively until convergence is achieved. As a result, the profile is simulated, together with the wellbore and sandface temperatures.
The model is robust, and relies on user inputs to solve for conduction, convection and radiation heat transfer.
A transient correction is also available.
The method computes the downhole pressure based on PVT data and frictional pressure drop correlations.
In the absence of external hold-up information, this method remains applicable for single phase situations.
Water injection fall-off
In general, the measured temperature during injection periods is of limited use as, due to the large water rates involved, combined with the limits of the sensor resolution, usually little, or no, response to the temperature of the different inflow zones is observed.
However, when the injector is shut-in and the temperature is recorded during the fall off, the temperature in front of the different perforations will return to the geothermal at a rate proportional to the volume of water they have taken during the injection period.
Emeraude incorporates an analytical solution of the Water injection fall-off method, where multiple temperature traces can be matched simultaneously, resulting in the well’s injection profile
Thermal Modeling in Rubis
The analytical solutions available in Emeraude for producing and injecting wells have limitations.
Cold injection water inflows in a producing well or other types of non-geothermal fluid entries cannot be handled analytically.
Needless to say that attempting to solve this type of inverse problem without a source of holdup (only with DTS data) will lead to an infinite number of solutions.
For these situations, a transient multiphase flow solution in a coupled wellbore-reservoir system is needed.
The Rubis, multipurpose full-field numerical model, incorporates a thermal option. In addition to the typical outputs of pressure and saturation, temperature can be output as a function of time at any depth in the wells, in the reservoir as temperature fields, or as Production Logs at a user specified time interval.
Rubis can perform quick ‘What ifs’ or proof of concept thermal simulations that will aid the understanding of temperature behaviour observed in complex cases.
Using PL simulation, Emeraude can generate PL tool, including temperature, response to user defined rates for different inflow zones.
Two other useful options are available under PL simulation:
The leak option simulates the thermal profile along the tubing and annulus in a tubing leak simulation.
This is especially useful as, depending on the rate, the leak may be characterized by either warming or cooling. This is most helpful to know before running a leak detection survey.
The Steam injection option simulates the thermal profile in the specific case of steam injection. A specific PVT option is used to determine flow properties as a function of pressure, temperature and steam quality.
The objective is for the steam to reach the perforations as vapor and not condensed water. Sensitivities may be run on the injection parameters and completion details and hence obtaining insight into steam quality i.e. the mass of vapor reaching the perforations over the mass of water injected.