Neural networks techniques applied to reservoir engineering
Conference
·
OSTI ID:175655
- Gerencia de Proyectos Geotermoelectricos, Morelia (Mexico)
- RockoHill de Mexico, Indiana (Mexico)
Neural Networks are considered the greatest technological advance since the transistor. They are expected to be a common household item by the year 2000. An attempt to apply Neural Networks to an important geothermal problem has been made, predictions on the well production and well completion during drilling in a geothermal field. This was done in Los Humeros geothermal field, using two common types of Neural Network models, available in commercial software. Results show the learning capacity of the developed model, and its precision in the predictions that were made.
- OSTI ID:
- 175655
- Report Number(s):
- CONF-951037-; TRN: 95:008065-0067
- Resource Relation:
- Conference: Annual meeting of the Geothermal Resources Council, Reno, NV (United States), 8-11 Oct 1995; Other Information: PBD: 1995; Related Information: Is Part Of Accomplishments of the past and challenges of the future. Transactions, Volume 19; PB: 604 p.
- Country of Publication:
- United States
- Language:
- English
Similar Records
Recurrent neural networks for short-term and long-term prediction of geothermal reservoirs
Final Technical Report - Applications of Machine Learning Techniques to Geothermal Play Fairway Analysis in the Great Basin Region, Nevada
BIOMASSCOMP: artificial neural networks and neurocomputers. Final report, 18 August 1987-18 February 1988
Journal Article
·
Fri May 20 00:00:00 EDT 2022
· Geothermics
·
OSTI ID:175655
+2 more
Final Technical Report - Applications of Machine Learning Techniques to Geothermal Play Fairway Analysis in the Great Basin Region, Nevada
Technical Report
·
Sat Feb 10 00:00:00 EST 2024
·
OSTI ID:175655
+13 more
BIOMASSCOMP: artificial neural networks and neurocomputers. Final report, 18 August 1987-18 February 1988
Technical Report
·
Thu Sep 01 00:00:00 EDT 1988
·
OSTI ID:175655