The goal of the project is to develop a surfactant soak technique to improve oil recovery by increasing the water-wettability of less than water-wet formations.
Encore Acquisition Company
Fort Worth, TX
University of Wyoming
Gel Technologies Corp.
Texland Petroleum, Inc.
Fort Worth, TX
Range Resources Corporation
Ft. Worth, TX
Yates Petroleum, Inc.
The project is the outgrowth of laboratory and fieldwork done to stimulate oil production from the Phosphoria formation in Cottonwood Creek field. The low-volume oil wells produce from a fractured, oil-wet carbonate reservoir in Wyoming. Imbibition testing of reservoir cores and fluids in the laboratory suggested the technique would work in the field.
Technology developed for the Phosphoria formation in Wyoming is being adapted to the San Andres formation in the Permian Basin. Laboratory techniques developed during the course of an SBIR (Small Business Research Innovation) project that focused on the Phosphoria formation have also been extended to include the San Andres formation. Artificial intelligence (AI) correlations developed during the SBIR project were used to design surfactant soak treatments in the San Andres formation of the Fuhrman-Masho field near Andres, TX. AI techniques are being developed to establish baseline production trends in order to evaluate San Andres formation surfactant soak treatments in conjunction with the water-frac stimulation process.
Static imbibition tests with and without surfactant were completed with cores and fluids from the Cedar Creek anticline. The results indicate that a field test maybe warranted.
Low-cost surfactant soak stimulation treatments will prolong the life of marginally economic wells in oil-wet reservoirs. About 22% of the original-oil-in-place of the entire U.S. oil resource resides in shallow-shelf carbonate reservoirs. Most of such reservoirs are oil-wet, heterogeneous, and naturally fractured, and therefore ideal candidates for the surfactant soak process. An estimated 100,000 of the Nation's 500,000 domestic producing oil wells could benefit from surfactant soak technology.
The rate vs. cumulative chart suggests that the experimental treatments produced about 25,000 bbl of incremental oil at a cost of $168,000. Of course, not all treatments performed in an equal manner. The patterns observed in the gamma ray log and the quantity of surfactant used with the incremental oil produced were correlated using AI. Given the gamma ray log, the neural network correlation of the standard deviation in the gamma ray log will be used to design surfactant treatments for the San Andres formation.
The highlights of the project are as follows:
Surfactant soaks field experiments have been completed in the Fuhrman-Masho (San Andres) pool in west Texas. Laboratory tests do not support a test of the surfactant soak process in the Eagle Creek field. All the proposed research work on this project has been successfully completed.
$698,000 (47% of total)
NETL - Chandra Nautiyal (email@example.com or 918-699-2021)
Correlations - William Weiss (firstname.lastname@example.org or 505-838-3876)
Two papers were presented at a professional meeting and two peer-reviewed publications were accepted for publication in international journals.
Weiss, W.W., Xie, X., Weiss, J.W., Subramaniam, V., Taylor, A. and Edens, F., Artificial Intelligence Used to Evaluate 23 Single-Well Surfactant Soak Treatments, SPE 89457, presented at the 14th SPE/DOE Symposium on Improved Oil Recovery, Tulsa, OK, April 17-21, 2004.
Xie, X., Weiss, W.W., Tong, T., and Morrow, N.R., Improved Recovery from Carbonate Reservoirs by Chemical Stimulation, SPE 89424 presented at the 14th SPE/DOE Symposium on Improved Oil Recovery, Tulsa, OK, April 17-21, 2004.
Weiss, W.W., Weiss, J.W., Subramaniam, V., and Xie, X., AI Applied to Evaluate Waterflood Response, Gas Behind Pipe, and Imbibition Stimulation Treatments, Journal of Petroleum Science and Engineering, Vol. 49, Issues 3-4, December 15, 2005, Pages 110-121.
Weiss, W.W., Xie, X., Weiss, J.W., Subramanian, V., Taylor, A., and Edens, F., Artificial Intelligence Used to Evaluate 23 Single-Well Surfactant Soak Treatments, SPE Reservoir Evaluation & Engineering, June 2006 (in press).