Flow Behavior of Gas-Condensate Wells

Investigator: Chunmei Shi

Introduction

Gas-condensate reservoirs experience reductions in productivity by as much as a factor of 10 due to the dropout of liquid close to the wellbore. The liquid dropout blocks the flow of gas to thewell and lowers the overall energy output by a very substantial degree. As heavier components separate into the dropped-out liquid while the flowing gas phase becomes lighter in composition, the overall composition of the reservoir fluid changes due to the combined effect of the condensate phase behavior and the rock relative permeability. The compositional variation has been sparsely recognized in the literature, although there is clearevidence of it in field observations. The work studies the well deliverability issue associated with condensateblockage effect with an emphasis on flow behavior analysis and aims to develop a methodology to increase the productivity of gas/condensate from gas-condensate reservoirs. Specifically, this work will focus on the following aspects:

• Composition variation. Study how the compositions of the heavier components for a given gas-condensate system change with time around production wells during depletion, and how the rate of the composition variation influences the fluid thermodynamic properties, and hence defines the dynamic phase diagram of the fluid in the reservoir.
• Dynamic condensate saturation build-up. Investigate the dynamic process of the condensate blockage effect, and learn how the condensate build-up varies as a function of time, place and phase behavior.
• Producing schemes. Changing the well producing schemes can affect the composition of the liquid dropout, and can therefore change the degree of productivity loss. In this study, we will conduct parametric studies to identify the most influential reservoir and fluid characteristics in the establishment of optimum gas production and condensate recovery for the exploitation of gas-condensate reservoirs.

This study will make use of the experimental measurements of gas-condensate flow, as well as compositional numerical simulations, to verify the compositional change and to develop the optimum producing/injecting strategies for maximum gas production and condensate recovery.

Figure 1 shows the schematic diagram of the gas-condensate flow system. One of the unusual aspects of this experiment is the ability to measure the in-place composition, as well as the usual pressure and temperature data.

Primary results

Experimental observations:

Composition changes as pressure drops below dewpoint pressure.

Figure 2 shows that more C4 (theheavier component) dropped out into the core as the pressure decreased below the dewpoint pressure, and hence more C1 (the lighter component) appeared in the flowing phase. After the flowing pressure dropped to some point, the condensate drop-out trapped in the core started to vaporize, at this stage, more C4 was detected in the flowing phase.

The condensate drop-out will hinder the flow capability, due to effective permeability effects. The decrease in the nitrogen permeability measurements indicates the existence of the condensate liquid drop-out even beyond the expected revaporization point and shows the permanent hindrance effect of the trapped liquid on the flow.

Simulation observations:

Figure 3 shows the simulation results for a binary gas-condensate system. Note that:

• The compositions and condensate saturations change significantly as a function of producing sequence. The higher the BHP, the smaller amount of the heavier components was trapped in the reservoir.
• Gas productivity can be maximized with proper producing strategy. The total gas production can be improved by lowering the BHP for this particular case.

Work in progress

Experimental work:

• Remodel the experimental setup.
• Repeat the first experiment.
• Run core flooding experiment with different gas-condensate systems (by using different combinations of methane and butane).
• Run core flooding experiment with different producing schemes.

Simulation work:

• Run compositional simulations with dynamic relative permeabilities to account for the IFT and composition variation effects.
• Run compositional simulations with different permeability fields (homogeneous vs. heterogeneous; tight vs. loose).
• Run compositional simulations with different gas-condensate systems (lean vs. rich, binary vs. multi-component).
• Run compositional simulations with different producing schemes.
• Conduct parametric studies to identify the most influential reservoir and fluid characteristics in the establishment of an optimum gas production and condensate recovery scenario for the gas-condensate reservoir