A transient semi-analytical wellbore/reservoir model for gas well pressure buildup tests

It has already been widely accepted that, during a pressure transient test, wellbore effects often change the pressure transient behavior and mask important reservoir information contained in early-time pressure response. This work considers wellbore effects on gas well pressure buildup tests with surface shut-in.; Wellbore effects can cause errors in the results of interpretation. The pressure data distorted by wellbore effects can be mistakenly interpreted as a reservoir response. Also the combination of wellbore effects usually make the pressure buildup data deviate from the traditional type curves. Being able to distinguish between wellbore effects and reservoir behavior in the pressure response is very important. A general and rigorous wellbore/reservoir model is desired to help solve the problems. This is the motivation of this research.; In this work we present a semi-analytical transient wellbore/reservoir model for gas well pressure buildup tests. The governing equations of the wellbore model are based on mass, momentum, and energy balances for single-phase gas in one-dimensional space. The gas PVT correlation is also used. Different flow regimes (laminar, transition, and turbulence) inside the wellbore are modeled for calculating the friction factor. As one boundary condition, a simple analytical reservoir model is connected to the wellbore model at the bottomhole location using Duhamel's principle. Heat loss effects account for forced-convection heat transfer inside the tubing, heat conduction between tubing and formation, natural convection and radiation heat transfer of annular fluid, and transient heat flow in the formation.; A simulator is developed from the model. Pressure, temperature, velocity, and gas properties inside the wellbore can be predicted at any depth during an entire pressure buildup test. Variable wellbore storage, momentum, and thermal effects can be simulated with the simulator. Detailed sensitivity studies show that different combinations of reservoir and wellbore parameters cause different wellbore effects. Forward modeling was performed and tested with field data. Examples are presented to demonstrate how the rate deconvolution method can be performed to remove the wellbore storage effects using the afterflow rate calculated from the simulator and the measured the pressure data.