@inbook{affaa6abe7ea4c8091b10e915f87d4ff,
title = "Probabilistic Integration of Geomechanical and Geostatistical Inferences for Mapping Natural Fracture Networks",
abstract = "Estimation of a reservoir{\textquoteright}s production potential, well placement and field development depends largely on accurate modeling of the existing fracture networks. However, there is always significant uncertainty associated with the prediction of spatial location and connectivity of fracture networks due to lack of sufficient data to model them. Therefore, stochastic characterization of these fractured reservoirs becomes necessary.",
author = "Akshat Chandna and Sanjay Srinivasan",
note = "Funding Information: Acknowledgements The authors would like to acknowledge the support and funding from Penn State Initiative for Geostatistics and Geo-Modeling Applications (PSIGGMA) and the member companies. Publisher Copyright: {\textcopyright} 2023, The Author(s).",
year = "2023",
doi = "10.1007/978-3-031-19845-8_11",
language = "English (US)",
series = "Springer Proceedings in Earth and Environmental Sciences",
publisher = "Springer Nature",
pages = "133--139",
booktitle = "Springer Proceedings in Earth and Environmental Sciences",
address = "United States",
}