The goal of this paper is demonstration of an approach to enhancing reliability of quantitative interpretation of well tests data. The new approach comprises joint interpretation of transient temperature, pressure and flow rate data taking into account flow rate history before the test. It provides additional information and near-wellbore zone, flow profiles and hydrodynamic properties of a multilayer reservoir.

The transient model for solving the coupled thermal-hydraulic problems in the reservoir, formation, and wellbore is described in the paper. It takes into account heat convection and conduction, Joule-Thomson, adiabatic effects, thermal effect caused by degrassing as well as mixing of fluids in the well, heat transfer between wellbore fluid and formation, frictional heat release and thermal effect of fluid compression of expansion. This model allows simulating flow behind casing, crossflows during shut-in and different properties of the near-wellbore zone.

Transient temperature and pressure fields, and temperature profiles along the wellbore are simulated for a given flow rate history. The model parameters are determined by solving the inverse problem based on a comparison of simulated temperature data with measurements in the wellbore.

Application of new approach to quantitative interpretation of well test data and developed transient numerical code are demonstrated on the example of the field data from the Bashneft - Polus oil well. The data from production logging during flow at different choke sizes and transient station measurements of temperature and pressure after change of regimes are available and simulated with the developed code.

Standard Pressure Transient Analysis (PTA) was used for pressure and flow rate data interpretation, while available temperature measurements were simulated with a numerical code developed for solving the coupled thermal-hydraulic multiphase problems by Bashkir State University and Schlumberger Moscow Research Center.

The paper demonstrates the results of quantitative interpretation of the field data and sensitivity study of the model parameters to uncertainties in measurements, flow rate history, thermal properties and other input data.