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Algorithm for Optimal Well Placement in Geothermal Systems Based on TOUGH2 Models

Dagur HELGASON, Ágúst VALFELLS, Egill JÚLÍUSSON

Key words
resource management, well placement, algorithm, optimization, tough2, python, pytough, reservoir engineering
Conference
Stanford Geothermal Workshop
Year
2017
Session
Reservoir Engineering
Language
English
Paper number
Helgason

Full text

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Abstract

In a world of ever increasing use of renewables geothermal has lagged behind and has seen little growth compared to other renewables due in part to its high capital cost. Geothermal wells account for about a third of the capital cost and it is therefore important to ensure the highest possible success rate and value creation from these wells. In order to address this, an algorithm has been developed that utilizes a numerical TOUGH2 model of a geothermal system to evaluate the optimal well placement based on a net present value estimation. The algorithm does this by using forward simulation of production for multiple potential well locations and estimating the net present value of each potential location. The algorithm is capable of using both deliverability wells and wellbore files. The algorithm was tested using a hypothetical model and found the optimal wells to be in the hottest parts of the model at depth, when using the deliverability setup, and in the upper heat zone, directly above the heat source, when using the wellbore file setup. The algorithm shows promise but has some faults and limitations, especially in the deliverability setup.

Copyright 2017, Stanford Geothermal Program. Readers who download papers from this site should honour the copyright of the original authors, and may not copy or distribute the work further without the permission of the original publisher.

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