Optimal Sequential Drilling for Hydrocarbon Field Development Planning
Abstract
We present a novel approach for planning the development of hydrocarbon fields, taking into account the sequential nature of well drilling decisions and the possibility to react to future information. In a dynamic fashion, we want to optimally decide where to drill each well conditional on every possible piece of information that could be obtained from previous wells. We formulate this sequential drilling optimization problem as a POMDP, and propose an algorithm to search for an optimal drilling policy. We show that our new approach leads to better results compared to the current standard in the oil and gas (O&G) industry.
Cite
Text
Torrado et al. "Optimal Sequential Drilling for Hydrocarbon Field Development Planning." AAAI Conference on Artificial Intelligence, 2017. doi:10.1609/AAAI.V31I1.19103Markdown
[Torrado et al. "Optimal Sequential Drilling for Hydrocarbon Field Development Planning." AAAI Conference on Artificial Intelligence, 2017.](https://mlanthology.org/aaai/2017/torrado2017aaai-optimal/) doi:10.1609/AAAI.V31I1.19103BibTeX
@inproceedings{torrado2017aaai-optimal,
title = {{Optimal Sequential Drilling for Hydrocarbon Field Development Planning}},
author = {Torrado, Ruben Rodriguez and Rios, Jesus and Tesauro, Gerald},
booktitle = {AAAI Conference on Artificial Intelligence},
year = {2017},
pages = {4734-4739},
doi = {10.1609/AAAI.V31I1.19103},
url = {https://mlanthology.org/aaai/2017/torrado2017aaai-optimal/}
}