Dingding CHEN - Plano TX, US Syed HAMID - Dallas TX, US Michael C. DIX - Houston TX, US
Assignee:
HALLIBURTON ENERGY SERVICES, INC. - Houston TX
International Classification:
G06K 9/62 G01V 3/00
US Classification:
382156, 3408532
Abstract:
Dimensionality reduction systems and methods facilitate visualization, understanding, and interpretation of high-dimensionality data sets, so long as the essential information of the data set is preserved during the dimensionality reduction process. In some of the disclosed embodiments, dimensionality reduction is accomplished using clustering, evolutionary computation of low-dimensionality coordinates for cluster kernels, particle swarm optimization of kernel positions, and training of neural networks based on the kernel mapping. The fitness function chosen for the evolutionary computation and particle swarm optimization is designed to preserve kernel distances and any other information deemed useful to the current application of the disclosed techniques, such as linear correlation with a variable that is to be predicted from future measurements. Various error measures are suitable and can be used.
Dingding Chen - Plano TX, US Syed Hamid - Dallas TX, US Michael Charles Dix - Houston TX, US
Assignee:
HALLIBURTON ENERGY SERVICES, INC. - Houston TX
International Classification:
G06F 7/60
US Classification:
703 2
Abstract:
A model is disclosed that includes an intelligent ligent linear programming (“ILP”) member to produce a ILP result, a member selected from the group consisting of a feed-forward neural network (“FNN”) to produce a FNN result and a geochemical normative analysis (“GNA”) model to produce a GNA result. The model also includes a result generator to combine the ILP result with the result from the other member to produce the estimates of the mineral content of the sample.
Systems And Methods Employing Cooperative Optimization-Based Dimensionality Reduction
- Houston TX, US Syed HAMID - Dallas TX, US Michael C. DIX - Houston TX, US
Assignee:
Halliburton Energy Services, Inc. - Houston TX
International Classification:
E21B 47/12 G06N 3/08 E21B 49/08
Abstract:
Dimensionality reduction systems and methods facilitate visualization, understanding, and interpretation of high-dimensionality data sets, so long as the essential information of the data set is preserved during the dimensionality reduction process. In some of the disclosed embodiments, dimensionality reduction is accomplished using clustering, evolutionary computation of low-dimensionality coordinates for cluster kernels, particle swarm optimization of kernel positions, and training of neural networks based on the kernel mapping. The fitness function chosen for the evolutionary computation and particle swarm optimization is designed to preserve kernel distances and any other information deemed useful to the current application of the disclosed techniques, such as linear correlation with a variable that is to be predicted from future measurements. Various error measures are suitable and can be used.
Global Calibration Based Reservoir Quality Prediction From Real-Time Geochemical Data Measurements
- Houston TX, US Simon N. Hughes - Houston TX, US Christopher N. Smith - Houston TX, US Michael C. Dix - Houston TX, US
International Classification:
G01V 5/04 G01V 5/10
US Classification:
702 11
Abstract:
Real-time or near real-time estimates of reservoir quality properties, along with performance indicators for such estimates, can be provided through use of methods and systems for fully automating the estimation of reservoir quality properties based on geochemical data obtained at a well site.