Determining
petrophysical properties and gas content in the Barnett Shale using a
log
-based
neural network solution.
By
Lee Utley, Petroleum Consultant, Houston, Texas
The Barnett Shale in the Fort Worth Basin of Texas is an
organic-rich black shale capable of producing large amounts of natural gas and
natural gas liquids. Traditional log
analysis
methods have not yielded
acceptable results when attempting to determine standard petrophysical
properties. Therefore,
log
analysis
alone is an impractical method of predicting
production in the Barnett Shale. Production in the Barnett Shale is affected by
several factors, only some of which may be measured or calculated using
log
data, making gas content a poor predictor of
well
performance. However, a neural
network technique has been developed to successfully estimate reservoir
potential that relies on
log
derived qualitative and quantitative parameters.
Log
analysis
in the complex lithology of the Barnett Shale is
very difficult. The existence of several exotic minerals in the matrix along
with significant amounts of organic material makes a algorithm-based solution
virtually impossible. Using extensive core data, a neural network solution was
developed to calibrate the logs to the needed petrophysical properties, and thus
enable the foot-by-foot calculation of gas content of the Barnett Shale. Since
any evaluation technique requires proper verification, examples will be shown to
demonstrate the effectiveness of the calibration.
The logs required to perform the analysis
are readily available
on most wells in the Fort Worth Basin, making the solution a practical
exploration/exploitation tool. Outputs from the
analysis
include porosity, total
organic content, water saturation, lithology, and gas content, both in the
sorbed and free states.
Lee Utley is an independent petrophysical consultant
specializing in unconventional reservoirs. After spending 10 years with
Halliburton, he worked for 5 years as a petrophysical engineer with Mitchell
Energy in The Woodlands as the primary petrophysicist in the Barnett Shale and
the Fort Worth Basin. He is also the Houston representative for Petroleum
Software Technologies, providing technical support for their suite of
resistivity and SP modeling software as well
as neural network software. Lee has
a Bachelors degree in Petroleum Engineering from Texas Tech University and a
Masters degree in Business Administration from Southern Methodist University.
AAPG Search and Discovery Article #90010©2003 AAPG Southwest Section Meeting, Fort Worth, Texas, March 1-4, 2003