enforceRankCorrelation: Rank Correlation

In madorning/energySim0.1.0: Spatial Energy Simulation: Linking Subsurface to Surface Resources

Description

Implements rank correlation method proposed by Iman & Conover (1982).

Usage

enforceRankCorrelation(auMC, auAreaDrainage, auEURss, auEURns = NULL, year)

Arguments

auMC	number of MC iterations to perform
auAreaDrainage	Uncertainty about average drainage area of wells: c(min,mode,max) [acres]
auEURss	Uncertainty about sweet spot average EUR (MMBO for oil; BCFG for gas): c(min,med,max) [MMBO or BCFG]
auEURns	Uncertainty about non-sweet spot average EUR (MMBO for oil; BCFG for gas): c(min,med,max) [MMBO or BCFG]
year	Year [XXXX] of factsheet publication of assessment numbers.

Details

Assumes correlation matrix C required by USGS Continuous Assessment methodology between mean drainage area, sweet spot EUR, and non-sweet spot EUR C = rbind(c(1,.5,.5),c(0.5,1,0),c(0.5,0,1)). As of July 2016, the standard 'z-score' for the EUR distribution is implemented as 2.326 (99%). Assigning year <= 1 will assume zscore of 3.09 (99.9%) as used in conventionalAssessment EUR distributions since approximately 2013.

Value

Matrix of correlated variables in each row. Individual columns are DrainageArea, EURsweetSpot,EURnonSweetSpot.

Note

Edited by CDMartinez 08 Dec 15

Author(s)

Created by CDMartinez 10 Nov 15

References

Iman, Ronald L, and W J Conover, 1982, A Distribution-free approach to inducing rank correlation among input variables. Communications in statistics - Simulation and Computation 11(3), 311-34.

Examples

enforceRankCorrelation(auMC = 50000,
auAreaDrainage = c(10,20,40),
auEURss=c(0.15,0.4,0.65),year=2016)

madorning/energySim0.1.0 documentation built on May 22, 2019, 2:23 p.m.