<--- Back to Details
First PageDocument Content
Geostatistics / Computing / Software engineering / Academia / Kriging / Reservoir modeling / Variogram / Fortran
Date: 2009-07-15 11:48:00
Geostatistics
Computing
Software engineering
Academia
Kriging
Reservoir modeling
Variogram
Fortran

Reservoir Modeling with GSLIB Introduction to GSLIB • •

Add to Reading List

Source URL: www.statios.com

Download Document from Source Website

File Size: 67,98 KB

Share Document on Facebook

Similar Documents

Spatial Gaussian Process (GP) models for Massive Geostatistical Datasets Spatial Gaussian Process (GP) models—subsume kriging—for point-referenced geospatial datasets provide a statistically valid framework for predi

Spatial Gaussian Process (GP) models for Massive Geostatistical Datasets Spatial Gaussian Process (GP) models—subsume kriging—for point-referenced geospatial datasets provide a statistically valid framework for predi

DocID: 1sJDW - View Document

Tenke-Fungurume  Dynamic unfolding-complex geology case study of Tenke-Fungurume deposits by Justin Cardwell and Alyson Cartwright

Tenke-Fungurume Dynamic unfolding-complex geology case study of Tenke-Fungurume deposits by Justin Cardwell and Alyson Cartwright

DocID: 1roOC - View Document

OPTIMAL PREDICTORS FOR THE DATA COMPRESSION OF DIGITAL  ELEVATION MODELS USING THE METHOD OF LAGRANGE MULTIPLIERS .

OPTIMAL PREDICTORS FOR THE DATA COMPRESSION OF DIGITAL ELEVATION MODELS USING THE METHOD OF LAGRANGE MULTIPLIERS .

DocID: 1rica - View Document

Reservoir Modeling with GSLIB  Introduction to GSLIB •  •

Reservoir Modeling with GSLIB Introduction to GSLIB • •

DocID: 1rgx6 - View Document

CSIRO PUBLISHING  www.publish.csiro.au/journals/ajsr Australian Journal of Soil Research, 2003, 41, 1403–1422

CSIRO PUBLISHING www.publish.csiro.au/journals/ajsr Australian Journal of Soil Research, 2003, 41, 1403–1422

DocID: 1rftp - View Document