1-6 of 6
Keywords: factor analysis
Close
Follow your search
Access your saved searches in your account

Would you like to receive an alert when new items match your search?
Close Modal
Sort by
Proceedings Papers

Paper presented at the SPWLA 60th Annual Logging Symposium, June 15–19, 2019
Paper Number: SPWLA-2019-V
... the challenges mentioned above. The workflow builds on recent advancements to extract maximum information from minimal NMR data acquisition, such as factor analysis, a statistical method to determine various T2 cutoffs, and fluids substitution, a method to replace all hydrocarbons with water in T2 distribution...
Proceedings Papers

Paper presented at the SPWLA 57th Annual Logging Symposium, June 25–29, 2016
Paper Number: SPWLA-2016-UU
... on "Exploratory Factor Analysis" (Jain et al, 2013) was used to determine underlying poro-fluid structure. This helps address perennial questions such as: the number of poro-fluid components in the NMR T2 distribution, and their respective T2 cutoffs; characteristics, identification and volumes...
Proceedings Papers

Paper presented at the SPWLA 57th Annual Logging Symposium, June 25–29, 2016
Paper Number: SPWLA-2016-X
...-related complications. In these circumstances, fluid substitution is performed on the NMR logs in which the hydrocarbon response is replaced by water response. This paper details the workflow first proposed by Shell (Volokitin et al., 1999, 2001), enhanced by NMR factor analysis (Jain et al., 2013...
Proceedings Papers

Paper presented at the SPWLA 54th Annual Logging Symposium, June 22–26, 2013
Paper Number: SPWLA-2013-TT
... Abstract A novel technique, based on "exploratory factor analysis", for NMR logging measurements provides improved accuracy and efficiency in determining poro-fluid distributions and associated porosities in clastic and carbonate reservoirs. The technique addresses questions concerning 1) how...
Proceedings Papers

Paper presented at the SPWLA 44th Annual Logging Symposium, June 22–25, 2003
Paper Number: SPWLA-2003-O
... from logs becomes crucial because the quantitative analysis of logs for porosity, saturation, etc, depends on lithology, or mineral compositions. Q-mode and R-mode factor analysis are commonly used for sample and variable analysis respectively. The correspondence analysis (CA), combining R-mode and Q...

Product(s) added to cart

Close Modal