Modeling of Reservoir Temperature Transients, and Parameter Estimation Constrained to a Reservoir Temperature Model


Obinna Duru







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Permanent downhole gauges (PDGs) provide a continuous source of downhole pressure, temperature and sometimes rate data. Until recently, the measured temperature data have been largely ignored. However, a close observation of the temperature measurements reveals that the temperature responds to changes in flow rate and pressure, which implies that the temperature data may be a source of reservoir information.

In this work, the Alternating Conditional Expectations (ACE) technique was applied to temperature and flow rate signals from PDGs to establish the existence of a functional relationship between them. Then, performing energy, mass and mo- mentum balances, reservoir temperature transient models were developed for single- and multiphase uids, as functions of formation parameters, uid properties, and changes in rate and pressure. The pressure field in oil and gas bearing formations are usually nonstationary. This gives rise to pressure-temperature effects appearing as temperature changes in the porous medium when the pressure field is nonstationary. The magnitudes of these effects depend on the properties of the formation,fl ow geometry, time and other factors and result in a reservoir temperature distribution that is changing in both space and time. Therefore, in this study, reservoir ther- mometric effects were modeled as convective, conductive and transient phenomena with consideration for time and space dependencies. This mechanistic model included the Joule-Thomson effects due to fluid compressibility, and viscous dissipation in the reservoir during fluid flow in accounting for the reservoir temperature dependence on changing pressure/flowrate fields.

Numerical solution schemes as well as the semianalytical scheme - Operator Splitting and Time Stepping (OSATS) were used to solve the models, and the solutions closely reproduced the temperature profiles seen in real measured data. By matching the models to different temperature transient histories obtained from PDGs, reservoir parameters namely porosity and saturation and fluid Joule-Thomson coefficient could be estimated. The significant contributions of this work include a method which:

* Utilizes temperature data measured by PDGs.
* Provides a way to estimate porosity and potentially saturation.
* May provide a less expensive substitute for downhole flow rate measurement.

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