APPLICATION OF ARTIFICIAL INTELLIGENCE IN ESTIMATION AND OPTIMIZATION OF GEOTHERMAL RESERVOIR PRODUCTION
Reservoir is the main asset of geothermal exploitation business. The decline in reservoir performance affects the sustainability of geothermal fluid production. Reservoir has a heterogeneous nature with high degree of uncertainty, so the development and estimation of reservoir performance using a...
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| Format: | Theses |
| Language: | Indonesia |
| Online Access: | https://digilib.itb.ac.id/gdl/view/48341 |
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| Institution: | Institut Teknologi Bandung |
| Language: | Indonesia |
| Summary: | Reservoir is the main asset of geothermal exploitation business. The decline in
reservoir performance affects the sustainability of geothermal fluid production.
Reservoir has a heterogeneous nature with high degree of uncertainty, so the
development and estimation of reservoir performance using a numerical model will
require a relatively long time. This study aims to create alternative models for
optimization and estimation of geothermal production with artificial intelligence
(AI). The AI model was arranged, trained and validated using measurement data
of production parameters (wellhead pressure, wellhead temperature, trim valve
open, fluid mass flow) in the Patuha steam domination geothermal field, Indonesia
with variations scenario use of the data and implemented on a single well for
prediction, multi wells for prediction and optimization. The model created in the
study produced a mean absolute percentage error <9% with the scenario of using
80% data for the training process and validation using 100% (of the total data).
The AI model can be used as an alternative method for optimizing and forecasting
Patuha geothermal reservoir production with a relatively shorter time than the
current method.
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