Estimation of static formation temperatures in geothermal wells by using an artificial neural network approach

Computers and Geosciences

Volumn 36, Issue 9, 2010, Pages 1191-1199

  Bassam, A ^a   Santoyo, E ^a   Andaverde, J ^b   Hernandez J A ^b   Espinoza Ojeda, O M ^a  

^a INSTITUTO DE ENERGÍAS RENOVABLES   (Mexico)

^b UNIVERSIDAD AUTÓNOMA DEL ESTADO DE MORELOS   (Mexico)

Author keywords

Artificial intelligence; Borehole drilling; Bottom hole temperature; Geothermal energy; Horner method; Levenberg Marquardt algorithm; Shut in time

Indexed keywords

BOREHOLE DRILLING; BOTTOMHOLE; HORNER METHOD; LEVENBERG-MARQUARDT ALGORITHM; SHUT-IN TIME;

BOREHOLES; GEOTHERMAL WELLS; HYPERBOLIC FUNCTIONS; LEARNING ALGORITHMS; NETWORK ARCHITECTURE; NEURAL NETWORKS; RENEWABLE ENERGY RESOURCES; TRANSFER FUNCTIONS; WELL DRILLING; WELLS;

GEOTHERMAL LOGGING;

ACCURACY ASSESSMENT; ALGORITHM; ARTIFICIAL NEURAL NETWORK; BOREHOLE GEOPHYSICS; DATA SET; EFFICIENCY MEASUREMENT; ESTIMATION METHOD; GEOTHERMAL ENERGY; GEOTHERMAL SYSTEM; MODEL VALIDATION; OPTIMIZATION; TEMPERATURE GRADIENT; TEMPERATURE PROFILE; TRANSFER FUNCTION;

EID: 77955921953     PISSN: 00983004     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.cageo.2010.01.006     Document Type: Article

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