Assisted History Matching of Channelized Models Using Pluri-Principal Component Analysis

2015 ◽  
Author(s):  
C. Chen ◽  
G. Gao ◽  
B.A. Ramirez ◽  
J.C. Vink ◽  
A.M. Girardi
Keyword(s):  
Principal Component Analysis ◽  
History Matching ◽  
Principal Component ◽  
Component Analysis ◽  
Assisted History Matching

Assisted History Matching of Channelized Models by Use of Pluri-Principal-Component Analysis

SPE Journal ◽  
2016 ◽  
Vol 21 (05) ◽  
pp. 1793-1812 ◽  
Author(s):  
C.. Chen ◽  
G.. Gao ◽  
B. A. Ramirez ◽  
J. C. Vink ◽  
A. M. Girardi
Keyword(s):  
Principal Component Analysis ◽  
History Matching ◽  
Large Scale ◽  
Gaussian Model ◽  
Principal Component ◽  
Component Analysis ◽  
Work Flow ◽  
Real Field ◽  
Assisted History Matching ◽  
Facies Types

Summary Assisted history matching (AHM) of a channelized reservoir is still a very-challenging task because it is very difficult to gradually deform the discrete facies in an automated fashion, while preserving geological realism. In this paper, a pluri-principal-component-analysis (PCA) method, which supports PCA with a pluri-Gaussian model, is proposed to reconstruct geological and reservoir models with multiple facies. PCA extracts the major geological features from a large collection of training channelized models and generates gridblock-based properties and real-valued (i.e., noninteger-valued) facies. The real-valued facies are mapped to discrete facies indicators according to rock-type rules (RTRs) that determine the fraction of each facies and neighboring connections between different facies. Pluri-PCA preserves the main (or principal) features of both geological and geostatistical characteristics of the prior models. A new method is also proposed to automatically build the RTRs with an ensemble of training realizations. An AHM work flow is developed by integrating pluri-PCA with a derivative-free optimization algorithm. This work flow is validated on a synthetic model with four facies types and a real-field channelized model with three facies types, and it is applied to update both the facies model and the reservoir model by conditioning to production data and/or hard data. The models generated by pluri-PCA preserve the major geological/geostatistical descriptions of the original training models. This has great potential for practical applications in large-scale history matching and uncertainty quantification.

A German version of the Intermittent Claudication Questionnaire (ICQ): cultural adaptation and validation

VASA ◽  
2012 ◽  
Vol 41 (5) ◽  
pp. 333-342 ◽  
Author(s):  
Kirchberger ◽  
Finger ◽  
Müller-Bühl
Keyword(s):  
Principal Component Analysis ◽  
Intermittent Claudication ◽  
Completion Time ◽  
Short Form ◽  
Principal Component ◽  
Component Analysis ◽  
German Version ◽  
Average Completion Time ◽  
Sf 36 ◽  
Related Quality

Background: The Intermittent Claudication Questionnaire (ICQ) is a short questionnaire for the assessment of health-related quality of life (HRQOL) in patients with intermittent claudication (IC). The objective of this study was to translate the ICQ into German and to investigate the psychometric properties of the German ICQ version in patients with IC. Patients and methods: The original English version was translated using a forward-backward method. The resulting German version was reviewed by the author of the original version and an experienced clinician. Finally, it was tested for clarity with 5 German patients with IC. A sample of 81 patients were administered the German ICQ. The sample consisted of 58.0 % male patients with a median age of 71 years and a median IC duration of 36 months. Test of feasibility included completeness of questionnaires, completion time, and ratings of clarity, length and relevance. Reliability was assessed through a retest in 13 patients at 14 days, and analysis of Cronbach’s alpha for internal consistency. Construct validity was investigated using principal component analysis. Concurrent validity was assessed by correlating the ICQ scores with the Short Form 36 Health Survey (SF-36) as well as clinical measures. Results: The ICQ was completely filled in by 73 subjects (90.1 %) with an average completion time of 6.3 minutes. Cronbach’s alpha coefficient reached 0.75. Intra-class correlation for test-retest reliability was r = 0.88. Principal component analysis resulted in a 3 factor solution. The first factor explained 51.5 of the total variation and all items had loadings of at least 0.65 on it. The ICQ was significantly associated with the SF-36 and treadmill-walking distances whereas no association was found for resting ABPI. Conclusions: The German version of the ICQ demonstrated good feasibility, satisfactory reliability and good validity. Responsiveness should be investigated in further validation studies.

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