2007 Unconventional Resources

A Self-Teaching Expert System for the Analysis, Design and Prediction of Gas Production from Shales

Subcontractor: Lawrence Berkeley National Laboratory

Principal Investigator: George Moridis
Project Number Project Status
07122-23 Completed
RPSEA Project Manager: Charlotte Schroeder
Participants
Texas A&M University; University of Houston; University of California at Berkeley; Anadarko Petroleum Corporation; Southwestern Energy
Period of Performance
Start Date End Date
December 3, 2008 November 30, 2011
Total Project Cost RPSEA Share Cost Share
$3,817,975.00 $1,771,475.00 $2,046,500.00
Project Objectives

Develop a self-teaching expert system, available as a Web application/computer program, that is located on Lawrence Berkeley National Laboratory servers and is distributable through the web, enables both "public" and "private" databases, continuously updates the databases and refines the underlying decision-making metrics and process (baseline mode) , in prediction mode, it enables the design of appropriate production systems, the operation and management of unconventional (tight) gas resources (UGR), and estimates uncertainties, and in optimization mode, it allows history matching and parameter identification from the data.

RPSEA Project Fact Sheet: Download 592.1 KB
Reports
File Type Date
A Self-Teaching Expert System (SETES) for the Analysis, Design and Prediction of Gas Production from Unconventional Gas Resources ( 234.0 KB ) Feasibility Assessment Report 03/10
A Self-Teaching Expert System (SETES) for the Analysis, Design and Prediction of Gas Production from Unconventional Gas Resources ( 142.1 KB ) Technology Status Assessment 02/09
SeTES, a Self-Teaching Expert System for the Analysis, Design and Prediction of Gas Production from Unconventional Resources ( 2.0 MB ) Final Report 11/11
SeTES, a Self-Teaching Expert System for the Analysis, Design and Prediction of Gas Production from Unconventional Resources - Users Guide ( 138.7 KB ) Final Report 11/11
Presentations
Title: Poster Presentation - 01/10 ( 2.0 MB )
Title: Paper: A Paper Presented at the TOUGH Symposium at Lawrence Berkeley National Laboratory, Berkeley CA in 2009 - 09/09 ( 318.7 KB )