09122-01

Primary Performer
University of Tulsa

Additional Participants
Marathon
Chevron

Abstract
One of the most important challenges the operators of tight gas reservoirs face is maintaining sustained production from these wells. One of the characteristics of tight gas wells is the significant drop in production rate over a short period of time. Since most of these wells produce some water, without some type of artificial lift method, it is difficult to sustain production from these wells. One of the most common techniques used for lifting the water is foam lift; this involves injecting surfactant in the well so that in-situ foam between gas and water is created, and the foam is produced to the surface which includes water and gas. For deep gas wells with small amounts of water production, foam lift is the most economical method. Unfortunately, no correlation exists to calculate the pressure drop under foam flow. Therefore, operators are unable to correctly predict the performance of the well under foam flow conditions. In addition, since we cannot predict the time of abandonment, we cannot determine the reserves for the wells which are on foam lift.

This project addresses the issue of pressure drop calculation under foam flow condition. By using available data from vendors and field measurements, as well as collecting data from new experimental facility, a suitable correlations to calculate the pressure drop in vertical gas wells will be developed.

A combination of both experimental data and theoretical modeling will be used to develop this correlation. The University of Tulsa will produce and characterize the foam, determine bubble rise velocity, and collect pressure drop data in both 2” and 3” tubings, using different surfactants employed in the field. They will validate their correlation by comparing the results with the field data. Using the proposed approach, the following will be able to be addressed:

• Predict the pressure drop in tubing under foam flow conditions; and hence the rate at which the well can be produced and optimized
• Predict the future performance as well as the time of abandonment of the well as the reservoir is depleted

The project will involve The University of Tulsa (Lead), Marathon and Chevron. The principal investigator is Dr. Mohan Kelkar of The University of Tulsa. The cost share for the project will be provided by Marathon, Chevron and The University of Tulsa.

Principal Investigator: Mohan Kelkar, Ph.D.