GaS_GeoT: A computer program for an effective use of newly improved gas geothermometers in predicting reliable geothermal reservoir temperatures
Por:
Acevedo-Anicasio, A., Santoyo, E., Perez-Zarate, D., Pandarinath, Kailasa, Guevara, M., Diaz-Gonzalez, L.
Publicada:
18 dic 2021
Resumen:
A geochemometric study based on a multi-criteria decision analysis was
applied, for the first time, for the optimal evaluation and selection of
artificial neural networks, and the prediction of geothermal reservoir
temperatures. Eight new gas geothermometers (GasG(1) to GasG(8)) were
derived from this study. For an effective and practical application of
these geothermometers, a new computer program GaS_GeoT was developed.
The prediction efficiency of the new geothermometers was compared with
temperature estimates inferred from twenty-five existing geothermometers
using gas-phase compositions of fluids from liquid- (LIQDR) and
vapour-dominated (VAPDR) reservoirs. After applying evaluation
statistical metrics (DIFF%, RMSE, MAE, MAPE, and the Theil's U test) to
the temperature estimates obtained by using all the geothermometers, the
following inferences were accomplished: (1) the new eight gas
geothermometers (GasG(1) to GasG(8)) provided reliable and systematic
temperature estimates with performance wise occupying the first eight
positions for LIQDR; (2) the GasG(3) and GasG(1) geothermometers
exhibited consistency as the best predictor models by occupying the
first two positions over all the geothermometers for VAPDR; (3) the
GasG(3) geothermometer exhibited a wider applicability, and a better
prediction efficiency over all geothermometers in terms of a large
number of samples used (up to 96% and 85% for LIQDR and VAPDR,
respectively), and showed the smallest differences between predicted and
measured temperatures in VAPDR and LIQDR; and lastly (4) for the VAPDR,
the existing geothermometers ND84c, A98c, and ND98b sometimes showed a
better prediction than some of the new gas geothermometers, except for
GasG(3) and GasG(1). These results indicate that the new gas
geothermometers may have the potential to become one of the most
preferred tools for the estimation of the reservoir temperatures in
geothermal systems.
Filiaciones:
Acevedo-Anicasio, A.:
Univ Autonoma Estado Morelos, Ciencias, Ctr Invest Ciencias IICBA, Ave Univ 1001, Col Chamilpa 62209, Morelos, Mexico
Santoyo, E.:
(Corresponding Author), Univ Nacl Autonoma Mexico, Inst Energias Renovables, Priv Xochicalco S-N, Temixco 62580, Morelos, Mexico
Univ Nacl Autonoma Mexico, Inst Energias Renovables, Priv Xochicalco S-N, Temixco 62580, Morelos, Mexico
Perez-Zarate, D.:
Univ Nacl Autonoma Mexico, CONACYT Inst Geofis, Circuito Interior S-N, Mexico City 04510, DF, Mexico
Pandarinath, Kailasa:
Univ Nacl Autonoma Mexico, Inst Energias Renovables, Priv Xochicalco S-N, Temixco 62580, Morelos, Mexico
Guevara, M.:
Univ Nacl Autonoma Mexico, Inst Energias Renovables, Priv Xochicalco S-N, Temixco 62580, Morelos, Mexico
Diaz-Gonzalez, L.:
Univ Autonoma Estado Morelos, Ctr Invest Ciencias IICBA, Ave Univ 1001, Col Chamilpa 62209, Morelos, Mexico
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