Methods developed over the past four years allow for the use of quantitative rock characterization data to better define well log response for purposes of computation and interpretation. The rock data is derived primarily from thin section point count analysis. Additional information is derived from bulk and fine fraction X-ray diffraction and non-quantitative scanning electron microscopy. Rock lithology and mineral composition are employed to determine the well log response to various quantities of minerals in the reservoir rock. The use of the log data then allows a continuous solution for the occurrence of these minerals in the interval of interest. The result is a more accurate evaluation of reservoir properties from the well logs than would normally be attained without this additional rock data. An additional benefit from the use of the rock data is an understanding of the distribution of minerals, such as clay, in the reservoir rock. Examples of the use and integration of the rock data and log data are shown. The well log data includes the newer measurements such as natural gamma ray spectroscopy and electromagnetic propagation time. The examples are elastic rocks. They include a full range of conditions including high porosity shallow Gulf Coast formations; tight low porosity Travis Peak in east Texas and unconventional reservoir rock such as the Devonian shale in the Appalachian Basin.
Skip Nav Destination
Utilization Of Rock Characterization Data To Improve Well Log Interpretation
R.K. Vessell
R.K. Vessell
David K. Davies & Associates
Search for other works by this author on:
Paper presented at the SPWLA 27th Annual Logging Symposium, Houston, Texas, June 1986.
Paper Number:
SPWLA-1986-V
Published:
June 09 1986
Citation
Truman, R.B., Davies, D.K., Howard, W.E., and R.K. Vessell. "Utilization Of Rock Characterization Data To Improve Well Log Interpretation." Paper presented at the SPWLA 27th Annual Logging Symposium, Houston, Texas, June 1986.
Download citation file:
Sign in
Don't already have an account? Register
Personal Account
You could not be signed in. Please check your username and password and try again.
Could not validate captcha. Please try again.
Pay-Per-View Access
$10.00
Advertisement
5
Views
Advertisement
Suggested Reading
Advertisement